remove keys (#225)

* new fetch_calendar_data function

* new class Calendar

* Revert common/model.py to the state before the last commit

* dataframe transformation is making Timestamp objects in open and close columns naive before converting to dictionary.

* typing for function arguments added. Function returns list of Calendar objects that have properties defined like strings.

* else condition fixed

* else condition returns directly an  empty without declaring a list name

CODEOWNERS

@@ -0,0 +1 @@
+*       @drew2323

README.md

@@ -0,0 +1,128 @@
+# V2TRADING - Advanced Algorithmic Trading Platform
+
+## Overview
+Custom-built algorithmic trading platform for research, backtesting and live trading. Trading engine capable of processing tick data, providing custom aggregation, managing trades, and supporting backtesting in a highly accurate and efficient manner.
+
+## Key Features
+- **Trading Engine**: At the core of the platform is a trading engine that processes tick data in real time. This engine is responsible for aggregating data and managing the execution of trades, ensuring precision and speed in trade placement and execution.
+
+- **High-Fidelity Backtesting Environment**: ability to backtest strategies with 1:1 precision - meaning a tick-by-tick backtesting. This level of precision in backtesting, down to millisecond accuracy, mirrors live trading environments and is vital for developing and testing high-frequency trading strategies.
+
+- **Custom Data Aggregation:** The platform includes a data aggregator that allows for custom aggregation rules. This flexibility supports a variety of data analysis approaches, including non-time based bars and other unique criteria.
+
+- **Indicators** Contains inbuild [tulipy](https://tulipindicators.org/list) [ta-lib](https://ta-lib.github.io/ta-lib-python/) and templates for custom build multioutputs stateful indicators.
+
+- **Machine Learning Integration:** Recently, the platform has expanded to incorporate machine learning capabilities. This includes modules for both training and inference, supporting the complete ML lifecycle. These ML models can be utilized within trading strategies for classification and exploiting statistical advantages.
+
+**Technology Stack**
+**Backend and API:** The backbone of the platform is built with Python, utilizing libraries such as FastAPI, NumPy, Keras, and JAX, ensuring high performance and scalability.
+**Frontend:** The client-side is developed with Vanilla JavaScript and jQuery, employing LightweightCharts for charting purposes. Additional modules enhance the platform's functionality. The frontend is slated for a future refactoring to modern frameworks like Vue.js and Vuetify for a more robust user interface.
+
+While the platform is fully functional and growing, ongoing development is planned, particularly in the realm of frontend enhancements and further integration of advanced machine learning techniques.
+
+**Contributions**
+Contributions to this project are welcome. Whether it's improving the frontend, enhancing the backend capabilities, or experimenting with new trading strategies and machine learning models, your input can help take this platform to the next level.
+
+This repository represents a sophisticated and evolving tool for algorithmic traders, offering precision, speed, and a level of customization that is unparalleled in open-source systems. Join us in shaping the future of algorithmic trading.
+
+<p align="center">
+  Main screen with entry/exit points and stoploss lines<br>
+  <img width="700" alt="Main screen with entry/exit points and stoploss lines" src="https://github.com/drew2323/v2trading/assets/28433232/751d5b0e-ef64-453f-8e76-89a39db679c5">
+</p>
+
+<p align="center">
+  Main screen with tick based indicators<br>
+  <img width="700" alt="Main screen with tick based indicators" src="https://github.com/drew2323/v2trading/assets/28433232/4bf6128c-9b36-4e88-9da1-5a33319976a1">
+</p>
+
+<p align="center">
+  Indicator editor<br>
+  <img width="700" alt="Indicator editor" src="https://github.com/drew2323/v2trading/assets/28433232/cc417393-7b88-4eea-afcb-3a00402d0a8d">
+</p>
+
+<p align="center">
+  Strategy editor<br>
+  <img width="700" alt="Strategy editor" src="https://github.com/drew2323/v2trading/assets/28433232/74f67e7a-1efc-4f63-b763-7827b2337b6a">
+</p>
+
+<p align="center">
+  Strategy analytical tools<br>
+  <img width="700" alt="Strategy analytical tools" src="https://github.com/drew2323/v2trading/assets/28433232/4bf8b3c3-e430-4250-831a-e5876bb6b743">
+</p>
+
+
+# Installation Instructions
+This document outlines the steps for installing and setting up the necessary environment for the application. These instructions are applicable for both Windows and Linux operating systems. Please follow the steps carefully to ensure a smooth setup.
+
+## Prerequisites
+Before beginning the installation process, ensure the following prerequisites are met:
+
+- TA-Lib Library:
+  - Windows: Download and build the TA-Lib library. Install Visual Studio Community with the Visual C++ feature. Navigate to `C:\ta-lib\c\make\cdr\win32\msvc` in the command prompt and build the library using the available makefile.
+  - Linux: Install TA-Lib using your distribution's package manager or compile from source following the instructions available on the TA-Lib GitHub repository.
+ 
+- Alpaca Paper Trading Account: Create an account at [Alpaca Markets](https://alpaca.markets/) and generate `API_KEY` and `SECRET_KEY` for your paper trading account.
+
+## Installation Steps
+**Clone the Repository:** Clone the remote repository to your local machine.
+   `git clone git@github.com:drew2323/v2trading.git <name_of_local_folder>`
+   
+**Install Python:** Ensure Python 3.10.11 is installed on your system.
+
+**Create a Virtual Environment:** Set up a Python virtual environment.
+   `python -m venv <path_to_venv_folder>`
+   
+**Activate Virtual Environment:**
+   - Windows: `source ./<venv_folder>/Scripts/activate`
+   - Linux: `source ./<venv_folder>/bin/activate`
+
+**Install Dependencies:** Install the program requirements.
+   pip install -r requirements.txt
+   Note: It's permissible to comment out references to `keras` and `tensorflow` modules, as well as the `ml-room` repository in `requirements.txt`.
+
+**Environment Variables:** In `run.sh`, modify the `VIRTUAL_ENV_DIR` and `PYTHON_TO_USE` variables as necessary.
+
+**Data Directory:** Navigate to `DATA_DIR` and create folders: `aggcache`, `tradecache`, and `models`.
+
+**Media and Static Folders:** Create `media` and `static` folders one level above the repository directory. Also create `.env` file there.
+
+**Database Setup:** Create the `v2trading.db` file using SQL commands from `v2trading_create_db.sql`.
+```
+    import sqlite3
+    with open("v2trading_create_db.sql", "r") as f:
+        sql_statements = f.read()
+    conn = sqlite3.connect('v2trading.db')
+    cursor = conn.cursor()
+    cursor.executescript(sql_statements)
+    conn.commit()
+    conn.close()
+```
+Ensure the `config_table` is not empty by making an initial entry.
+
+**Start the Application:** Run `main.py` in VSCode to start the application.
+
+**Accessing the Application:** If the uvicorn server runs successfully at `http://0.0.0.0:8000`, access the application at `http://localhost:8000/static/`.
+
+**Database Configuration:** Add dynamic button and JS configurations to the `config_table` in `v2trading.db` via the "Config" section on the main page.
+Please replace placeholders (e.g., `<name_of_local_folder>`, `<path_to_venv_folder>`) with your actual paths and details. Follow these instructions to ensure the application is set up correctly and ready for use.
+
+## Environmental variables
+Trading platform can support N different accounts. Their API keys are stored as environmental variables in .env file located in the root directory.
+Account for trading api is selected when each strategy is run. However for realtime websocket data), always ACCOUNT1 is used for all strategies. The data point selection (iex vs sip) is set by LIVE_DATA_FEED environment variable.  
+
+.env file should contain:
+
+```
+ACCOUNT1_LIVE_API_KEY=<ACCOUNT1_LIVE_API_KEY>
+ACCOUNT1_LIVE_SECRET_KEY=<ACCOUNT1_LIVE_SECRET_KEY>
+ACCOUNT1_LIVE_FEED=sip
+ACCOUNT1_PAPER_API_KEY=<ACCOUNT1_PAPER_API_KEY>
+ACCOUNT1_PAPER_SECRET_KEY=<ACCOUNT1_PAPER_SECRET_KEY>
+ACCOUNT1_PAPER_FEED=sip
+ACCOUNT2_PAPER_API_KEY=<ACCOUNT2_PAPER_API_KEY>
+ACCOUNT2_PAPER_SECRET_KEY=ACCOUNT2_PAPER_SECRET_KEY<>
+ACCOUNT2_PAPER_FEED=iex
+WEB_API_KEY=<pass-for-webapi>
+```
+
+

_run_scheduler.sh

@@ -0,0 +1,51 @@
+#!/bin/bash
+
+# Approach: (https://chat.openai.com/c/43be8685-b27b-4e3b-bd18-0856f8d23d7e)
+# cron runs this script every minute New York in range of 9:20 - 16:20 US time
+# Also this scripts writes the "heartbeat" message to log file, so the user knows
+#that cron is running
+
+# Installation steps required:
+#chmod +x run_scheduler.sh
+#install tzdata package: sudo apt-get install tzdata
+#crontab -e
+#CRON_TZ=America/New_York
+# * 9-16 * * 1-5 /home/david/v2trading/run_scheduler.sh
+#
+# (Runs every minute of every hour on every day-of-week from Monday to Friday) US East time
+
+# Path to the Python script
+PYTHON_SCRIPT="v2realbot/scheduler/scheduler.py"
+
+# Log file path
+LOG_FILE="job.log"
+
+# Timezone for New York
+TZ='America/New_York'
+NY_DATE_TIME=$(TZ=$TZ date +'%Y-%m-%d %H:%M:%S')
+echo "NY_DATE_TIME: $NY_DATE_TIME"
+
+# Check if log file exists, create it if it doesn't
+if [ ! -f "$LOG_FILE" ]; then
+    touch "$LOG_FILE"
+fi
+
+# Check the last line of the log file
+LAST_LINE=$(tail -n 1 "$LOG_FILE")
+
+# Cron trigger message
+CRON_TRIGGER="Cron trigger: $NY_DATE_TIME"
+
+# Update the log
+if [[ "$LAST_LINE" =~ "Cron trigger:".* ]]; then
+    # Replace the last line with the new trigger message
+    sed -i '' '$ d' "$LOG_FILE"
+    echo "$CRON_TRIGGER" >> "$LOG_FILE"
+else
+    # Append a new cron trigger message
+    echo "$CRON_TRIGGER" >> "$LOG_FILE"
+fi
+
+
+# FOR DEBUG - Run the Python script and append output to log file
+python3 "$PYTHON_SCRIPT" >> "$LOG_FILE" 2>&1

deployall.sh

@@ -0,0 +1,7 @@
+#!/bin/bash
+
+# Navigate to your git repository directory
+
+# Execute git commands
+git push deploytest master
+git push deploy master

jobs.log

@@ -0,0 +1 @@
+Current 0 scheduled jobs: []

requirements.txt

@@ -30,10 +30,12 @@ dateparser==1.1.8
 decorator==5.1.1
 defusedxml==0.7.1
 dill==0.3.7
+dm-tree==0.1.8
 entrypoints==0.4
 exceptiongroup==1.1.3
 executing==1.2.0
 fastapi==0.95.0
+filelock==3.13.1
 Flask==2.2.3
 flatbuffers==23.5.26
 fonttools==4.39.0
@@ -46,7 +48,7 @@ google-auth-oauthlib==1.0.0
 google-pasta==0.2.0
 grpcio==1.58.0
 h11==0.14.0
-h5py==3.9.0
+h5py==3.10.0
 icecream==2.1.3
 idna==3.4
 imageio==2.31.6
@@ -54,12 +56,18 @@ importlib-metadata==6.1.0
 ipython==8.17.2
 ipywidgets==8.1.1
 itsdangerous==2.1.2
+jax==0.4.23
+jaxlib==0.4.23
 jedi==0.19.1
 Jinja2==3.1.2
 joblib==1.3.2
 jsonschema==4.17.3
 jupyterlab-widgets==3.0.9
-keras
+keras==3.0.2
+keras-core==0.1.7
+keras-nightly==3.0.3.dev2024010203
+keras-nlp-nightly==0.7.0.dev2024010203
+keras-tcn @ git+https://github.com/drew2323/keras-tcn.git@4bddb17a02cb2f31c9fe2e8f616b357b1ddb0e11
 kiwisolver==1.4.4
 libclang==16.0.6
 llvmlite==0.39.1
@@ -69,12 +77,12 @@ MarkupSafe==2.1.2
 matplotlib==3.8.2
 matplotlib-inline==0.1.6
 mdurl==0.1.2
-ml-dtypes==0.2.0
-mlroom @ git+https://github.com/drew2323/mlroom.git
-keras-tcn @ git+https://github.com/drew2323/keras-tcn.git
+ml-dtypes==0.3.1
+mlroom @ git+https://github.com/drew2323/mlroom.git@692900e274c4e0542d945d231645c270fc508437
 mplfinance==0.12.10b0
 msgpack==1.0.4
 mypy-extensions==1.0.0
+namex==0.0.7
 newtulipy==0.4.6
 numba==0.56.4
 numpy==1.23.5
@@ -85,6 +93,7 @@ packaging==23.0
 pandas==1.5.3
 param==1.13.0
 parso==0.8.3
+patsy==0.5.6
 pexpect==4.8.0
 Pillow==9.4.0
 plotly==5.13.1
@@ -111,6 +120,7 @@ python-multipart==0.0.6
 pytz==2022.7.1
 pytz-deprecation-shim==0.1.0.post0
 pyviz-comms==2.2.1
+PyWavelets==1.5.0
 PyYAML==6.0
 regex==2023.10.3
 requests==2.31.0
@@ -128,11 +138,21 @@ sniffio==1.3.0
 sseclient-py==1.7.2
 stack-data==0.6.3
 starlette==0.26.1
+statsmodels==0.14.1
 streamlit==1.20.0
 structlog==23.1.0
 TA-Lib==0.4.28
+tb-nightly==2.16.0a20240102
 tenacity==8.2.2
+tensorboard==2.15.1
+tensorboard-data-server==0.7.1
+tensorflow-addons==0.23.0
+tensorflow-estimator==2.15.0
+tensorflow-io-gcs-filesystem==0.34.0
 termcolor==2.3.0
+tf-estimator-nightly==2.14.0.dev2023080308
+tf-nightly==2.16.0.dev20240101
+tf_keras-nightly==2.16.0.dev2023123010
 threadpoolctl==3.2.0
 tinydb==4.7.1
 tinydb-serialization==2.1.0
@@ -143,12 +163,13 @@ toolz==0.12.0
 tornado==6.2
 tqdm==4.65.0
 traitlets==5.13.0
+typeguard==2.13.3
 typing_extensions==4.5.0
 tzdata==2023.2
 tzlocal==4.3
 urllib3==1.26.14
 uvicorn==0.21.1
--e git+https://github.com/drew2323/v2trading.git@523905ece6d99bf48a8952d39ced6a13f3b9a84e#egg=v2realbot
+-e git+https://github.com/drew2323/v2trading.git@b58639454be921f9f0c9dd1880491cfcfdfdf3b7#egg=v2realbot
 validators==0.20.0
 wcwidth==0.2.9
 webencodings==0.5.1

requirements_new.txt

@@ -1,21 +1,34 @@
 absl-py==2.0.0
 alpaca==1.0.0
-alpaca-py==0.7.1
+alpaca-py==0.18.1
 altair==4.2.2
+annotated-types==0.6.0
 anyio==3.6.2
 appdirs==1.4.4
+appnope==0.1.3
+APScheduler==3.10.4
+argon2-cffi==23.1.0
+argon2-cffi-bindings==21.2.0
+arrow==1.3.0
 asttokens==2.2.1
 astunparse==1.6.3
+async-lru==2.0.4
 attrs==22.2.0
+Babel==2.15.0
+beautifulsoup4==4.12.3
 better-exceptions==0.3.3
 bleach==6.0.0
 blinker==1.5
+bottle==0.12.25
 cachetools==5.3.0
+CD==1.1.0
 certifi==2022.12.7
+cffi==1.16.0
 chardet==5.1.0
 charset-normalizer==3.0.1
 click==8.1.3
 colorama==0.4.6
+comm==0.1.4
 contourpy==1.0.7
 cycler==0.11.0
 dash==2.9.1
@@ -23,90 +36,189 @@ dash-bootstrap-components==1.4.1
 dash-core-components==2.0.0
 dash-html-components==2.0.0
 dash-table==5.0.0
+dateparser==1.1.8
+debugpy==1.8.1
 decorator==5.1.1
+defusedxml==0.7.1
+dill==0.3.7
+dm-tree==0.1.8
 entrypoints==0.4
+exceptiongroup==1.1.3
 executing==1.2.0
-fastapi==0.95.0
+fastapi==0.109.2
+fastjsonschema==2.19.1
+filelock==3.13.1
 Flask==2.2.3
 flatbuffers==23.5.26
 fonttools==4.39.0
+fpdf2==2.7.6
+fqdn==1.5.1
 gast==0.4.0
 gitdb==4.0.10
 GitPython==3.1.31
 google-auth==2.23.0
 google-auth-oauthlib==1.0.0
 google-pasta==0.2.0
+greenlet==3.0.3
 grpcio==1.58.0
 h11==0.14.0
-h5py==3.9.0
+h5py==3.10.0
+html2text==2024.2.26
+httpcore==1.0.5
+httpx==0.27.0
+humanize==4.9.0
 icecream==2.1.3
 idna==3.4
+imageio==2.31.6
 importlib-metadata==6.1.0
+ipykernel==6.29.4
+ipython==8.17.2
+ipywidgets==8.1.1
+isoduration==20.11.0
+itables==2.0.1
 itsdangerous==2.1.2
+jax==0.4.23
+jaxlib==0.4.23
+jedi==0.19.1
 Jinja2==3.1.2
 joblib==1.3.2
-jsonschema==4.17.3
-keras==2.13.1
+json5==0.9.25
+jsonpointer==2.4
+jsonschema==4.22.0
+jsonschema-specifications==2023.12.1
+jupyter-events==0.10.0
+jupyter-lsp==2.2.5
+jupyter_client==8.6.1
+jupyter_core==5.7.2
+jupyter_server==2.14.0
+jupyter_server_terminals==0.5.3
+jupyterlab==4.1.8
+jupyterlab-widgets==3.0.9
+jupyterlab_pygments==0.3.0
+jupyterlab_server==2.27.1
+kaleido==0.2.1
+keras==3.0.2
+keras-core==0.1.7
+keras-nightly==3.0.3.dev2024010203
+keras-nlp-nightly==0.7.0.dev2024010203
+keras-tcn @ git+https://github.com/drew2323/keras-tcn.git@4bddb17a02cb2f31c9fe2e8f616b357b1ddb0e11
 kiwisolver==1.4.4
 libclang==16.0.6
+lightweight-charts @ git+https://github.com/drew2323/lightweight-charts-python@10fd42f785182edfbf6b46a19a4ef66e85985a23
+llvmlite==0.39.1
 Markdown==3.4.3
 markdown-it-py==2.2.0
 MarkupSafe==2.1.2
-matplotlib==3.7.1
+matplotlib==3.8.2
+matplotlib-inline==0.1.6
 mdurl==0.1.2
+mistune==3.0.2
+ml-dtypes==0.3.1
+mlroom @ git+https://github.com/drew2323/mlroom.git@692900e274c4e0542d945d231645c270fc508437
+mplfinance==0.12.10b0
 msgpack==1.0.4
+mypy-extensions==1.0.0
+namex==0.0.7
+nbclient==0.10.0
+nbconvert==7.16.4
+nbformat==5.10.4
+nest-asyncio==1.6.0
 newtulipy==0.4.6
-numpy==1.24.2
+notebook_shim==0.2.4
+numba==0.56.4
+numpy==1.23.5
 oauthlib==3.2.2
 opt-einsum==3.3.0
+orjson==3.9.10
+overrides==7.7.0
 packaging==23.0
-pandas==1.5.3
+pandas==2.2.1
+pandocfilters==1.5.1
 param==1.13.0
+parso==0.8.3
+patsy==0.5.6
+pexpect==4.8.0
 Pillow==9.4.0
-plotly==5.13.1
+platformdirs==4.2.0
+plotly==5.22.0
+prometheus_client==0.20.0
+prompt-toolkit==3.0.39
 proto-plus==1.22.2
 protobuf==3.20.3
+proxy-tools==0.1.0
+psutil==5.9.8
+ptyprocess==0.7.0
+pure-eval==0.2.2
 pyarrow==11.0.0
 pyasn1==0.4.8
 pyasn1-modules==0.2.8
+pycparser==2.22
 pyct==0.5.0
-pydantic==1.10.5
+pydantic==2.6.4
+pydantic_core==2.16.3
 pydeck==0.8.0
 Pygments==2.14.0
 pyinstrument==4.5.3
 Pympler==1.0.1
+pyobjc-core==10.3
+pyobjc-framework-Cocoa==10.3
+pyobjc-framework-Security==10.3
+pyobjc-framework-WebKit==10.3
 pyparsing==3.0.9
 pyrsistent==0.19.3
 pysos==1.3.0
 python-dateutil==2.8.2
 python-dotenv==1.0.0
+python-json-logger==2.0.7
+python-multipart==0.0.6
 pytz==2022.7.1
 pytz-deprecation-shim==0.1.0.post0
 pyviz-comms==2.2.1
+PyWavelets==1.5.0
+pywebview==5.1
 PyYAML==6.0
+pyzmq==25.1.2
+referencing==0.35.1
+regex==2023.10.3
 requests==2.31.0
 requests-oauthlib==1.3.1
+rfc3339-validator==0.1.4
+rfc3986-validator==0.1.1
 rich==13.3.1
+rpds-py==0.18.0
 rsa==4.9
-scikit-learn==1.3.1
+schedule==1.2.1
+scikit-learn==1.3.2
 scipy==1.11.2
 seaborn==0.12.2
 semver==2.13.0
+Send2Trash==1.8.3
 six==1.16.0
 smmap==5.0.0
 sniffio==1.3.0
+soupsieve==2.5
+SQLAlchemy==2.0.27
 sseclient-py==1.7.2
-starlette==0.26.1
+stack-data==0.6.3
+starlette==0.36.3
+statsmodels==0.14.1
 streamlit==1.20.0
 structlog==23.1.0
+TA-Lib==0.4.28
+tb-nightly==2.16.0a20240102
 tenacity==8.2.2
-tensorboard==2.13.0
+tensorboard==2.15.1
 tensorboard-data-server==0.7.1
-tensorflow==2.13.0
-tensorflow-estimator==2.13.0
+tensorflow-addons==0.23.0
+tensorflow-estimator==2.15.0
 tensorflow-io-gcs-filesystem==0.34.0
 termcolor==2.3.0
+terminado==0.18.1
+tf-estimator-nightly==2.14.0.dev2023080308
+tf-nightly==2.16.0.dev20240101
+tf_keras-nightly==2.16.0.dev2023123010
 threadpoolctl==3.2.0
+tinycss2==1.3.0
 tinydb==4.7.1
 tinydb-serialization==2.1.0
 tinyflux==0.4.0
@@ -115,15 +227,24 @@ tomli==2.0.1
 toolz==0.12.0
 tornado==6.2
 tqdm==4.65.0
-typing_extensions==4.5.0
+traitlets==5.13.0
+typeguard==2.13.3
+types-python-dateutil==2.9.0.20240316
+typing_extensions==4.9.0
 tzdata==2023.2
 tzlocal==4.3
+uri-template==1.3.0
 urllib3==1.26.14
 uvicorn==0.21.1
-#-e git+https://github.com/drew2323/v2trading.git@940348412f67ecd551ef8d0aaedf84452abf1320#egg=v2realbot
+-e git+https://github.com/drew2323/v2trading.git@1f85b271dba2b9baf2c61b591a08849e9d684374#egg=v2realbot
 validators==0.20.0
+vectorbtpro @ file:///Users/davidbrazda/Downloads/vectorbt.pro-2024.2.22
+wcwidth==0.2.9
+webcolors==1.13
 webencodings==0.5.1
-websockets==10.4
+websocket-client==1.7.0
+websockets==11.0.3
 Werkzeug==2.2.3
-wrapt==1.15.0
+widgetsnbextension==4.0.9
+wrapt==1.14.1
 zipp==3.15.0

requirements_newest.txt

@@ -0,0 +1,243 @@
+absl-py
+alpaca
+alpaca-py
+altair
+annotated-types
+anyio
+appdirs
+appnope
+APScheduler
+argon2-cffi
+argon2-cffi-bindings
+arrow
+asttokens
+astunparse
+async-lru
+attrs
+Babel
+beautifulsoup4
+better-exceptions
+bleach
+blinker
+bottle
+cachetools
+CD
+certifi
+cffi
+chardet
+charset-normalizer
+click
+colorama
+comm
+contourpy
+cycler
+dash
+dash-bootstrap-components
+dash-core-components
+dash-html-components
+dash-table
+dateparser
+debugpy
+decorator
+defusedxml
+dill
+dm-tree
+entrypoints
+exceptiongroup
+executing
+fastapi
+fastjsonschema
+filelock
+Flask
+flatbuffers
+fonttools
+fpdf2
+fqdn
+gast
+gitdb
+GitPython
+google-auth
+google-auth-oauthlib
+google-pasta
+greenlet
+grpcio
+h11
+h5py
+html2text
+httpcore
+httpx
+humanize
+icecream
+idna
+imageio
+importlib-metadata
+ipykernel
+ipython
+ipywidgets
+isoduration
+itables
+itsdangerous
+jax
+jaxlib
+jedi
+Jinja2
+joblib
+json5
+jsonpointer
+jsonschema
+jsonschema-specifications
+jupyter-events
+jupyter-lsp
+jupyter_client
+jupyter_core
+jupyter_server
+jupyter_server_terminals
+jupyterlab
+jupyterlab-widgets
+jupyterlab_pygments
+jupyterlab_server
+kaleido
+keras
+keras-core
+keras-nightly
+keras-nlp-nightly
+keras-tcn @ git+https://github.com/drew2323/keras-tcn.git
+kiwisolver
+libclang
+lightweight-charts @ git+https://github.com/drew2323/lightweight-charts-python.git
+llvmlite
+Markdown
+markdown-it-py
+MarkupSafe
+matplotlib
+matplotlib-inline
+mdurl
+mistune
+ml-dtypes
+mlroom @ git+https://github.com/drew2323/mlroom.git
+mplfinance
+msgpack
+mypy-extensions
+namex
+nbclient
+nbconvert
+nbformat
+nest-asyncio
+newtulipy
+notebook_shim
+numba
+numpy
+oauthlib
+opt-einsum
+orjson
+overrides
+packaging
+pandas
+pandocfilters
+param
+parso
+patsy
+pexpect
+Pillow
+platformdirs
+plotly
+prometheus_client
+prompt-toolkit
+proto-plus
+protobuf
+proxy-tools
+psutil
+ptyprocess
+pure-eval
+pyarrow
+pyasn1
+pyasn1-modules
+pycparser
+pyct
+pydantic
+pydantic_core
+pydeck
+Pygments
+pyinstrument
+pyparsing
+pyrsistent
+pysos
+python-dateutil
+python-dotenv
+python-json-logger
+python-multipart
+pytz
+pytz-deprecation-shim
+pyviz-comms
+PyWavelets
+pywebview
+PyYAML
+pyzmq
+referencing
+regex
+requests
+requests-oauthlib
+rfc3339-validator
+rfc3986-validator
+rich
+rpds-py
+rsa
+schedule
+scikit-learn
+scipy
+seaborn
+semver
+Send2Trash
+six
+smmap
+sniffio
+soupsieve
+SQLAlchemy
+sseclient-py
+stack-data
+starlette
+statsmodels
+streamlit
+structlog
+TA-Lib
+tb-nightly
+tenacity
+tensorboard
+tensorboard-data-server
+tensorflow-addons
+tensorflow-estimator
+tensorflow-io-gcs-filesystem
+termcolor
+terminado
+tf-estimator-nightly
+tf-nightly
+tf_keras-nightly
+threadpoolctl
+tinycss2
+tinydb
+tinydb-serialization
+tinyflux
+toml
+tomli
+toolz
+tornado
+tqdm
+traitlets
+typeguard
+types-python-dateutil
+typing_extensions
+tzdata
+tzlocal
+uri-template
+urllib3
+uvicorn
+validators
+wcwidth
+webcolors
+webencodings
+websocket-client
+websockets
+Werkzeug
+widgetsnbextension
+wrapt
+zipp

research/get_trades_at_once.ipynb

@@ -0,0 +1,410 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Loading trades and vectorized aggregation\n",
+    "Describes how to fetch trades (remote/cached) and use new vectorized aggregation to aggregate bars of given type (time, volume, dollar) and resolution\n",
+    "\n",
+    "`fetch_trades_parallel` enables to fetch trades of given symbol and interval, also can filter conditions and minimum size. return `trades_df`\n",
+    "`aggregate_trades` acceptss `trades_df` and ressolution and type of bars (VOLUME, TIME, DOLLAR) and return aggregated ohlcv dataframe `ohlcv_df`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Activating profile profile1\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "Activating profile profile1\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "trades_df-BAC-2024-01-11T09:30:00-2024-01-12T16:00:00.parquet\n",
+      "trades_df-SPY-2024-01-01T09:30:00-2024-05-14T16:00:00.parquet\n",
+      "ohlcv_df-BAC-2024-01-11T09:30:00-2024-01-12T16:00:00.parquet\n",
+      "ohlcv_df-SPY-2024-01-01T09:30:00-2024-05-14T16:00:00.parquet\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "from numba import jit\n",
+    "from alpaca.data.historical import StockHistoricalDataClient\n",
+    "from v2realbot.config import ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, DATA_DIR\n",
+    "from alpaca.data.requests import StockTradesRequest\n",
+    "from v2realbot.enums.enums import BarType\n",
+    "import time\n",
+    "from datetime import datetime\n",
+    "from v2realbot.utils.utils import parse_alpaca_timestamp, ltp, zoneNY, send_to_telegram, fetch_calendar_data\n",
+    "import pyarrow\n",
+    "from v2realbot.loader.aggregator_vectorized import fetch_daily_stock_trades, fetch_trades_parallel, generate_time_bars_nb, aggregate_trades\n",
+    "import vectorbtpro as vbt\n",
+    "import v2realbot.utils.config_handler as cfh\n",
+    "\n",
+    "vbt.settings.set_theme(\"dark\")\n",
+    "vbt.settings['plotting']['layout']['width'] = 1280\n",
+    "vbt.settings.plotting.auto_rangebreaks = True\n",
+    "# Set the option to display with pagination\n",
+    "pd.set_option('display.notebook_repr_html', True)\n",
+    "pd.set_option('display.max_rows', 20)  # Number of rows per page\n",
+    "# pd.set_option('display.float_format', '{:.9f}'.format)\n",
+    "\n",
+    "\n",
+    "#trade filtering\n",
+    "exclude_conditions = cfh.config_handler.get_val('AGG_EXCLUDED_TRADES') #standard ['C','O','4','B','7','V','P','W','U','Z','F']\n",
+    "minsize = 100\n",
+    "\n",
+    "symbol = \"SPY\"\n",
+    "#datetime in zoneNY \n",
+    "day_start = datetime(2024, 1, 1, 9, 30, 0)\n",
+    "day_stop = datetime(2024, 1, 14, 16, 00, 0)\n",
+    "day_start = zoneNY.localize(day_start)\n",
+    "day_stop = zoneNY.localize(day_stop)\n",
+    "#filename of trades_df parquet, date are in isoformat but without time zone part\n",
+    "dir = DATA_DIR + \"/notebooks/\"\n",
+    "#parquet interval cache contains exclude conditions and minsize filtering\n",
+    "file_trades = dir + f\"trades_df-{symbol}-{day_start.strftime('%Y-%m-%dT%H:%M:%S')}-{day_stop.strftime('%Y-%m-%dT%H:%M:%S')}-{exclude_conditions}-{minsize}.parquet\"\n",
+    "#file_trades = dir + f\"trades_df-{symbol}-{day_start.strftime('%Y-%m-%dT%H:%M:%S')}-{day_stop.strftime('%Y-%m-%dT%H:%M:%S')}.parquet\"\n",
+    "file_ohlcv = dir + f\"ohlcv_df-{symbol}-{day_start.strftime('%Y-%m-%dT%H:%M:%S')}-{day_stop.strftime('%Y-%m-%dT%H:%M:%S')}-{exclude_conditions}-{minsize}.parquet\"\n",
+    "\n",
+    "#PRINT all parquet in directory\n",
+    "import os\n",
+    "files = [f for f in os.listdir(dir) if f.endswith(\".parquet\")]\n",
+    "for f in files:\n",
+    "    print(f)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "NOT FOUND. Fetching from remote\n"
+     ]
+    },
+    {
+     "ename": "KeyboardInterrupt",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[2], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m trades_df \u001b[38;5;241m=\u001b[39m \u001b[43mfetch_daily_stock_trades\u001b[49m\u001b[43m(\u001b[49m\u001b[43msymbol\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mday_start\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mday_stop\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mexclude_conditions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mexclude_conditions\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mminsize\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mminsize\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mforce_remote\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmax_retries\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbackoff_factor\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m      2\u001b[0m trades_df\n",
+      "File \u001b[0;32m~/Documents/Development/python/v2trading/v2realbot/loader/aggregator_vectorized.py:200\u001b[0m, in \u001b[0;36mfetch_daily_stock_trades\u001b[0;34m(symbol, start, end, exclude_conditions, minsize, force_remote, max_retries, backoff_factor)\u001b[0m\n\u001b[1;32m    198\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m attempt \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(max_retries):\n\u001b[1;32m    199\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 200\u001b[0m         tradesResponse \u001b[38;5;241m=\u001b[39m \u001b[43mclient\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_stock_trades\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstockTradeRequest\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    201\u001b[0m         is_empty \u001b[38;5;241m=\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m tradesResponse[symbol]\n\u001b[1;32m    202\u001b[0m         \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRemote fetched: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mis_empty\u001b[38;5;132;01m=}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m, start, end)\n",
+      "File \u001b[0;32m~/Documents/Development/python/v2trading/.venv/lib/python3.10/site-packages/alpaca/data/historical/stock.py:144\u001b[0m, in \u001b[0;36mStockHistoricalDataClient.get_stock_trades\u001b[0;34m(self, request_params)\u001b[0m\n\u001b[1;32m    141\u001b[0m params \u001b[38;5;241m=\u001b[39m request_params\u001b[38;5;241m.\u001b[39mto_request_fields()\n\u001b[1;32m    143\u001b[0m \u001b[38;5;66;03m# paginated get request for market data api\u001b[39;00m\n\u001b[0;32m--> 144\u001b[0m raw_trades \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_data_get\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    145\u001b[0m \u001b[43m    \u001b[49m\u001b[43mendpoint_data_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtrades\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m    146\u001b[0m \u001b[43m    \u001b[49m\u001b[43mendpoint_asset_class\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstocks\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m    147\u001b[0m \u001b[43m    \u001b[49m\u001b[43mapi_version\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mv2\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m    148\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mparams\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    149\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    151\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_use_raw_data:\n\u001b[1;32m    152\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m raw_trades\n",
+      "File \u001b[0;32m~/Documents/Development/python/v2trading/.venv/lib/python3.10/site-packages/alpaca/data/historical/stock.py:338\u001b[0m, in \u001b[0;36mStockHistoricalDataClient._data_get\u001b[0;34m(self, endpoint_asset_class, endpoint_data_type, api_version, symbol_or_symbols, limit, page_limit, extension, **kwargs)\u001b[0m\n\u001b[1;32m    335\u001b[0m params[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlimit\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m actual_limit\n\u001b[1;32m    336\u001b[0m params[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpage_token\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m page_token\n\u001b[0;32m--> 338\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mparams\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mapi_version\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mapi_version\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    340\u001b[0m \u001b[38;5;66;03m# TODO: Merge parsing if possible\u001b[39;00m\n\u001b[1;32m    341\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m extension \u001b[38;5;241m==\u001b[39m DataExtensionType\u001b[38;5;241m.\u001b[39mSNAPSHOT:\n",
+      "File \u001b[0;32m~/Documents/Development/python/v2trading/.venv/lib/python3.10/site-packages/alpaca/common/rest.py:221\u001b[0m, in \u001b[0;36mRESTClient.get\u001b[0;34m(self, path, data, **kwargs)\u001b[0m\n\u001b[1;32m    210\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget\u001b[39m(\u001b[38;5;28mself\u001b[39m, path: \u001b[38;5;28mstr\u001b[39m, data: Union[\u001b[38;5;28mdict\u001b[39m, \u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m HTTPResult:\n\u001b[1;32m    211\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Performs a single GET request\u001b[39;00m\n\u001b[1;32m    212\u001b[0m \n\u001b[1;32m    213\u001b[0m \u001b[38;5;124;03m    Args:\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    219\u001b[0m \u001b[38;5;124;03m        dict: The response\u001b[39;00m\n\u001b[1;32m    220\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m--> 221\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_request\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mGET\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/Documents/Development/python/v2trading/.venv/lib/python3.10/site-packages/alpaca/common/rest.py:129\u001b[0m, in \u001b[0;36mRESTClient._request\u001b[0;34m(self, method, path, data, base_url, api_version)\u001b[0m\n\u001b[1;32m    127\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m retry \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m    128\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 129\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_one_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mopts\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mretry\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    130\u001b[0m     \u001b[38;5;28;01mexcept\u001b[39;00m RetryException:\n\u001b[1;32m    131\u001b[0m         time\u001b[38;5;241m.\u001b[39msleep(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_retry_wait)\n",
+      "File \u001b[0;32m~/Documents/Development/python/v2trading/.venv/lib/python3.10/site-packages/alpaca/common/rest.py:193\u001b[0m, in \u001b[0;36mRESTClient._one_request\u001b[0;34m(self, method, url, opts, retry)\u001b[0m\n\u001b[1;32m    174\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_one_request\u001b[39m(\u001b[38;5;28mself\u001b[39m, method: \u001b[38;5;28mstr\u001b[39m, url: \u001b[38;5;28mstr\u001b[39m, opts: \u001b[38;5;28mdict\u001b[39m, retry: \u001b[38;5;28mint\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28mdict\u001b[39m:\n\u001b[1;32m    175\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Perform one request, possibly raising RetryException in the case\u001b[39;00m\n\u001b[1;32m    176\u001b[0m \u001b[38;5;124;03m    the response is 429. Otherwise, if error text contain \"code\" string,\u001b[39;00m\n\u001b[1;32m    177\u001b[0m \u001b[38;5;124;03m    then it decodes to json object and returns APIError.\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    191\u001b[0m \u001b[38;5;124;03m        dict: The response data\u001b[39;00m\n\u001b[1;32m    192\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m--> 193\u001b[0m     response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_session\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mopts\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    195\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m    196\u001b[0m         response\u001b[38;5;241m.\u001b[39mraise_for_status()\n",
+      "File \u001b[0;32m~/Documents/Development/python/v2trading/.venv/lib/python3.10/site-packages/requests/sessions.py:589\u001b[0m, in \u001b[0;36mSession.request\u001b[0;34m(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)\u001b[0m\n\u001b[1;32m    584\u001b[0m send_kwargs \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m    585\u001b[0m     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtimeout\u001b[39m\u001b[38;5;124m\"\u001b[39m: timeout,\n\u001b[1;32m    586\u001b[0m     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mallow_redirects\u001b[39m\u001b[38;5;124m\"\u001b[39m: allow_redirects,\n\u001b[1;32m    587\u001b[0m }\n\u001b[1;32m    588\u001b[0m send_kwargs\u001b[38;5;241m.\u001b[39mupdate(settings)\n\u001b[0;32m--> 589\u001b[0m resp \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msend\u001b[49m\u001b[43m(\u001b[49m\u001b[43mprep\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43msend_kwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    591\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m resp\n",
+      "File \u001b[0;32m~/Documents/Development/python/v2trading/.venv/lib/python3.10/site-packages/requests/sessions.py:703\u001b[0m, in \u001b[0;36mSession.send\u001b[0;34m(self, request, **kwargs)\u001b[0m\n\u001b[1;32m    700\u001b[0m start \u001b[38;5;241m=\u001b[39m preferred_clock()\n\u001b[1;32m    702\u001b[0m \u001b[38;5;66;03m# Send the request\u001b[39;00m\n\u001b[0;32m--> 703\u001b[0m r \u001b[38;5;241m=\u001b[39m \u001b[43madapter\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msend\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    705\u001b[0m \u001b[38;5;66;03m# Total elapsed time of the request (approximately)\u001b[39;00m\n\u001b[1;32m    706\u001b[0m elapsed \u001b[38;5;241m=\u001b[39m preferred_clock() \u001b[38;5;241m-\u001b[39m start\n",
+      "File \u001b[0;32m~/Documents/Development/python/v2trading/.venv/lib/python3.10/site-packages/requests/adapters.py:486\u001b[0m, in \u001b[0;36mHTTPAdapter.send\u001b[0;34m(self, request, stream, timeout, verify, cert, proxies)\u001b[0m\n\u001b[1;32m    483\u001b[0m     timeout \u001b[38;5;241m=\u001b[39m TimeoutSauce(connect\u001b[38;5;241m=\u001b[39mtimeout, read\u001b[38;5;241m=\u001b[39mtimeout)\n\u001b[1;32m    485\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 486\u001b[0m     resp \u001b[38;5;241m=\u001b[39m \u001b[43mconn\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43murlopen\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    487\u001b[0m \u001b[43m        \u001b[49m\u001b[43mmethod\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    488\u001b[0m \u001b[43m        \u001b[49m\u001b[43murl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    489\u001b[0m \u001b[43m        \u001b[49m\u001b[43mbody\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbody\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    490\u001b[0m \u001b[43m        \u001b[49m\u001b[43mheaders\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    491\u001b[0m \u001b[43m        \u001b[49m\u001b[43mredirect\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    492\u001b[0m \u001b[43m        \u001b[49m\u001b[43massert_same_host\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    493\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpreload_content\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    494\u001b[0m \u001b[43m        \u001b[49m\u001b[43mdecode_content\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    495\u001b[0m \u001b[43m        \u001b[49m\u001b[43mretries\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmax_retries\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    496\u001b[0m \u001b[43m        \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    497\u001b[0m \u001b[43m        \u001b[49m\u001b[43mchunked\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mchunked\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    498\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    500\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (ProtocolError, \u001b[38;5;167;01mOSError\u001b[39;00m) \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[1;32m    501\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mConnectionError\u001b[39;00m(err, request\u001b[38;5;241m=\u001b[39mrequest)\n",
+      "File \u001b[0;32m~/Documents/Development/python/v2trading/.venv/lib/python3.10/site-packages/urllib3/connectionpool.py:703\u001b[0m, in \u001b[0;36mHTTPConnectionPool.urlopen\u001b[0;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)\u001b[0m\n\u001b[1;32m    700\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_prepare_proxy(conn)\n\u001b[1;32m    702\u001b[0m \u001b[38;5;66;03m# Make the request on the httplib connection object.\u001b[39;00m\n\u001b[0;32m--> 703\u001b[0m httplib_response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_make_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    704\u001b[0m \u001b[43m    \u001b[49m\u001b[43mconn\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    705\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    706\u001b[0m \u001b[43m    \u001b[49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    707\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout_obj\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    708\u001b[0m \u001b[43m    \u001b[49m\u001b[43mbody\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbody\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    709\u001b[0m \u001b[43m    \u001b[49m\u001b[43mheaders\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    710\u001b[0m \u001b[43m    \u001b[49m\u001b[43mchunked\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mchunked\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    711\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    713\u001b[0m \u001b[38;5;66;03m# If we're going to release the connection in ``finally:``, then\u001b[39;00m\n\u001b[1;32m    714\u001b[0m \u001b[38;5;66;03m# the response doesn't need to know about the connection. Otherwise\u001b[39;00m\n\u001b[1;32m    715\u001b[0m \u001b[38;5;66;03m# it will also try to release it and we'll have a double-release\u001b[39;00m\n\u001b[1;32m    716\u001b[0m \u001b[38;5;66;03m# mess.\u001b[39;00m\n\u001b[1;32m    717\u001b[0m response_conn \u001b[38;5;241m=\u001b[39m conn \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m release_conn \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n",
+      "File \u001b[0;32m~/Documents/Development/python/v2trading/.venv/lib/python3.10/site-packages/urllib3/connectionpool.py:449\u001b[0m, in \u001b[0;36mHTTPConnectionPool._make_request\u001b[0;34m(self, conn, method, url, timeout, chunked, **httplib_request_kw)\u001b[0m\n\u001b[1;32m    444\u001b[0m             httplib_response \u001b[38;5;241m=\u001b[39m conn\u001b[38;5;241m.\u001b[39mgetresponse()\n\u001b[1;32m    445\u001b[0m         \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m    446\u001b[0m             \u001b[38;5;66;03m# Remove the TypeError from the exception chain in\u001b[39;00m\n\u001b[1;32m    447\u001b[0m             \u001b[38;5;66;03m# Python 3 (including for exceptions like SystemExit).\u001b[39;00m\n\u001b[1;32m    448\u001b[0m             \u001b[38;5;66;03m# Otherwise it looks like a bug in the code.\u001b[39;00m\n\u001b[0;32m--> 449\u001b[0m             \u001b[43msix\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mraise_from\u001b[49m\u001b[43m(\u001b[49m\u001b[43me\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m    450\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (SocketTimeout, BaseSSLError, SocketError) \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m    451\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_raise_timeout(err\u001b[38;5;241m=\u001b[39me, url\u001b[38;5;241m=\u001b[39murl, timeout_value\u001b[38;5;241m=\u001b[39mread_timeout)\n",
+      "File \u001b[0;32m<string>:3\u001b[0m, in \u001b[0;36mraise_from\u001b[0;34m(value, from_value)\u001b[0m\n",
+      "File \u001b[0;32m~/Documents/Development/python/v2trading/.venv/lib/python3.10/site-packages/urllib3/connectionpool.py:444\u001b[0m, in \u001b[0;36mHTTPConnectionPool._make_request\u001b[0;34m(self, conn, method, url, timeout, chunked, **httplib_request_kw)\u001b[0m\n\u001b[1;32m    441\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m:\n\u001b[1;32m    442\u001b[0m     \u001b[38;5;66;03m# Python 3\u001b[39;00m\n\u001b[1;32m    443\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 444\u001b[0m         httplib_response \u001b[38;5;241m=\u001b[39m \u001b[43mconn\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgetresponse\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    445\u001b[0m     \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m    446\u001b[0m         \u001b[38;5;66;03m# Remove the TypeError from the exception chain in\u001b[39;00m\n\u001b[1;32m    447\u001b[0m         \u001b[38;5;66;03m# Python 3 (including for exceptions like SystemExit).\u001b[39;00m\n\u001b[1;32m    448\u001b[0m         \u001b[38;5;66;03m# Otherwise it looks like a bug in the code.\u001b[39;00m\n\u001b[1;32m    449\u001b[0m         six\u001b[38;5;241m.\u001b[39mraise_from(e, \u001b[38;5;28;01mNone\u001b[39;00m)\n",
+      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/http/client.py:1375\u001b[0m, in \u001b[0;36mHTTPConnection.getresponse\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1373\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m   1374\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1375\u001b[0m         \u001b[43mresponse\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbegin\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1376\u001b[0m     \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mConnectionError\u001b[39;00m:\n\u001b[1;32m   1377\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mclose()\n",
+      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/http/client.py:318\u001b[0m, in \u001b[0;36mHTTPResponse.begin\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    316\u001b[0m \u001b[38;5;66;03m# read until we get a non-100 response\u001b[39;00m\n\u001b[1;32m    317\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[0;32m--> 318\u001b[0m     version, status, reason \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_read_status\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    319\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m status \u001b[38;5;241m!=\u001b[39m CONTINUE:\n\u001b[1;32m    320\u001b[0m         \u001b[38;5;28;01mbreak\u001b[39;00m\n",
+      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/http/client.py:279\u001b[0m, in \u001b[0;36mHTTPResponse._read_status\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    278\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_read_status\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[0;32m--> 279\u001b[0m     line \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mstr\u001b[39m(\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreadline\u001b[49m\u001b[43m(\u001b[49m\u001b[43m_MAXLINE\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124miso-8859-1\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m    280\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(line) \u001b[38;5;241m>\u001b[39m _MAXLINE:\n\u001b[1;32m    281\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m LineTooLong(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstatus line\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
+      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/socket.py:705\u001b[0m, in \u001b[0;36mSocketIO.readinto\u001b[0;34m(self, b)\u001b[0m\n\u001b[1;32m    703\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[1;32m    704\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 705\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_sock\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrecv_into\u001b[49m\u001b[43m(\u001b[49m\u001b[43mb\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    706\u001b[0m     \u001b[38;5;28;01mexcept\u001b[39;00m timeout:\n\u001b[1;32m    707\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_timeout_occurred \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n",
+      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/ssl.py:1274\u001b[0m, in \u001b[0;36mSSLSocket.recv_into\u001b[0;34m(self, buffer, nbytes, flags)\u001b[0m\n\u001b[1;32m   1270\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m flags \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m   1271\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m   1272\u001b[0m           \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnon-zero flags not allowed in calls to recv_into() on \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m%\u001b[39m\n\u001b[1;32m   1273\u001b[0m           \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m)\n\u001b[0;32m-> 1274\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnbytes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbuffer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1275\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m   1276\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28msuper\u001b[39m()\u001b[38;5;241m.\u001b[39mrecv_into(buffer, nbytes, flags)\n",
+      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/ssl.py:1130\u001b[0m, in \u001b[0;36mSSLSocket.read\u001b[0;34m(self, len, buffer)\u001b[0m\n\u001b[1;32m   1128\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m   1129\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m buffer \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m-> 1130\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_sslobj\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbuffer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1131\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m   1132\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_sslobj\u001b[38;5;241m.\u001b[39mread(\u001b[38;5;28mlen\u001b[39m)\n",
+      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
+     ]
+    }
+   ],
+   "source": [
+    "trades_df = fetch_daily_stock_trades(symbol, day_start, day_stop, exclude_conditions=exclude_conditions, minsize=minsize, force_remote=False, max_retries=5, backoff_factor=1)\n",
+    "trades_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Either load trades or ohlcv from parquet if exists\n",
+    "\n",
+    "#trades_df = fetch_trades_parallel(symbol, day_start, day_stop, exclude_conditions=exclude_conditions, minsize=50, max_workers=20) #exclude_conditions=['C','O','4','B','7','V','P','W','U','Z','F'])\n",
+    "# trades_df.to_parquet(file_trades, engine='pyarrow', compression='gzip')\n",
+    "\n",
+    "trades_df = pd.read_parquet(file_trades,engine='pyarrow')\n",
+    "ohlcv_df = aggregate_trades(symbol=symbol, trades_df=trades_df, resolution=1, type=BarType.TIME)\n",
+    "ohlcv_df.to_parquet(file_ohlcv, engine='pyarrow', compression='gzip')\n",
+    "\n",
+    "# ohlcv_df = pd.read_parquet(file_ohlcv,engine='pyarrow')\n",
+    "# trades_df = pd.read_parquet(file_trades,engine='pyarrow')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#list all files is dir directory with parquet extension\n",
+    "dir = DATA_DIR + \"/notebooks/\"\n",
+    "import os\n",
+    "files = [f for f in os.listdir(dir) if f.endswith(\".parquet\")]\n",
+    "file_name = \"\"\n",
+    "ohlcv_df = pd.read_parquet(file_ohlcv,engine='pyarrow')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ohlcv_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "# Calculate daily returns\n",
+    "ohlcv_df['returns'] = ohlcv_df['close'].pct_change().dropna()\n",
+    "#same as above but pct_change is from 3 datapoints back, but only if it is the same date, else na\n",
+    "\n",
+    "\n",
+    "# Plot the probability distribution curve\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "sns.histplot(df['returns'].dropna(), kde=True, stat='probability', bins=30)\n",
+    "plt.title('Probability Distribution of Daily Returns')\n",
+    "plt.xlabel('Daily Returns')\n",
+    "plt.ylabel('Probability')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.preprocessing import StandardScaler\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "from sklearn.metrics import accuracy_score\n",
+    "\n",
+    "# Define the intervals from 5 to 20 s, returns for each interval\n",
+    "#maybe use rolling window?\n",
+    "intervals = range(5, 21, 5)\n",
+    "\n",
+    "# Create columns for percentage returns\n",
+    "rolling_window = 50\n",
+    "\n",
+    "# Normalize the returns using rolling mean and std\n",
+    "for N in intervals:\n",
+    "    column_name = f'returns_{N}'\n",
+    "    rolling_mean = ohlcv_df[column_name].rolling(window=rolling_window).mean()\n",
+    "    rolling_std = ohlcv_df[column_name].rolling(window=rolling_window).std()\n",
+    "    ohlcv_df[f'norm_{column_name}'] = (ohlcv_df[column_name] - rolling_mean) / rolling_std\n",
+    "\n",
+    "# Display the dataframe with normalized return columns\n",
+    "ohlcv_df\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Calculate the sum of the normalized return columns for each row\n",
+    "ohlcv_df['sum_norm_returns'] = ohlcv_df[[f'norm_returns_{N}' for N in intervals]].sum(axis=1)\n",
+    "\n",
+    "# Sort the DataFrame based on the sum of normalized returns in descending order\n",
+    "df_sorted = ohlcv_df.sort_values(by='sum_norm_returns', ascending=False)\n",
+    "\n",
+    "# Display the top rows with the highest sum of normalized returns\n",
+    "df_sorted\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Drop initial rows with NaN values due to pct_change\n",
+    "ohlcv_df.dropna(inplace=True)\n",
+    "\n",
+    "# Plotting the probability distribution curves\n",
+    "plt.figure(figsize=(14, 8))\n",
+    "for N in intervals:\n",
+    "    sns.kdeplot(ohlcv_df[f'returns_{N}'].dropna(), label=f'Returns {N}', fill=True)\n",
+    "\n",
+    "plt.title('Probability Distribution of Percentage Returns')\n",
+    "plt.xlabel('Percentage Return')\n",
+    "plt.ylabel('Density')\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "# Plot the probability distribution curve\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "sns.histplot(ohlcv_df['returns'].dropna(), kde=True, stat='probability', bins=30)\n",
+    "plt.title('Probability Distribution of Daily Returns')\n",
+    "plt.xlabel('Daily Returns')\n",
+    "plt.ylabel('Probability')\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#show only rows from ohlcv_df where returns > 0.005\n",
+    "ohlcv_df[ohlcv_df['returns'] > 0.0005]\n",
+    "\n",
+    "#ohlcv_df[ohlcv_df['returns'] < -0.005]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#ohlcv where index = date 2024-03-13 and between hour 12\n",
+    "\n",
+    "a = ohlcv_df.loc['2024-03-13 12:00:00':'2024-03-13 13:00:00']\n",
+    "a"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ohlcv_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "trades_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ohlcv_df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "trades_df.to_parquet(\"trades_df-spy-0111-0111.parquett\", engine='pyarrow', compression='gzip')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "trades_df.to_parquet(\"trades_df-spy-111-0516.parquett\", engine='pyarrow', compression='gzip', allow_truncated_timestamps=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ohlcv_df.to_parquet(\"ohlcv_df-spy-111-0516.parquett\", engine='pyarrow', compression='gzip')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "basic_data = vbt.Data.from_data(vbt.symbol_dict({symbol: ohlcv_df}), tz_convert=zoneNY)\n",
+    "vbt.settings['plotting']['auto_rangebreaks'] = True\n",
+    "basic_data.ohlcv.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#access just BCA\n",
+    "#df_filtered = df.loc[\"BAC\"]"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

research/test1sbars.ipynb

@@ -0,0 +1,421 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from v2realbot.tools.loadbatch import load_batch\n",
+    "from v2realbot.utils.utils import zoneNY\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import vectorbtpro as vbt\n",
+    "from itables import init_notebook_mode, show\n",
+    "\n",
+    "init_notebook_mode(all_interactive=True)\n",
+    "\n",
+    "vbt.settings.set_theme(\"dark\")\n",
+    "vbt.settings['plotting']['layout']['width'] = 1280\n",
+    "vbt.settings.plotting.auto_rangebreaks = True\n",
+    "# Set the option to display with pagination\n",
+    "pd.set_option('display.notebook_repr_html', True)\n",
+    "pd.set_option('display.max_rows', 10)  # Number of rows per page\n",
+    "\n",
+    "res, df = load_batch(batch_id=\"0fb5043a\", #46 days 1.3 - 6.5.\n",
+    "                     space_resolution_evenly=False,\n",
+    "                     indicators_columns=[\"Rsi14\"],\n",
+    "                     main_session_only=True,\n",
+    "                     verbose = False)\n",
+    "if res < 0:\n",
+    "    print(\"Error\" + str(res) + str(df))\n",
+    "df = df[\"bars\"]\n",
+    "\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# filter dates"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#filter na dny\n",
+    "# dates_of_interest = pd.to_datetime(['2024-04-22', '2024-04-23']).tz_localize('US/Eastern')\n",
+    "# filtered_df = df.loc[df.index.normalize().isin(dates_of_interest)]\n",
+    "\n",
+    "# df = filtered_df\n",
+    "# df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import plotly.io as pio\n",
+    "pio.renderers.default = 'notebook'\n",
+    "\n",
+    "#naloadujeme do vbt symbol as column\n",
+    "basic_data = vbt.Data.from_data({\"BAC\": df}, tz_convert=zoneNY)\n",
+    "start_date = pd.Timestamp('2024-03-12 09:30', tz=zoneNY)\n",
+    "end_date = pd.Timestamp('2024-03-13 16:00', tz=zoneNY)\n",
+    "\n",
+    "#basic_data = basic_data.transform(lambda df: df[df.index.date == start_date.date()])\n",
+    "#basic_data = basic_data.transform(lambda df: df[(df.index >= start_date) & (df.index <= end_date)])\n",
+    "#basic_data.data[\"BAC\"].info()\n",
+    "\n",
+    "# fig = basic_data.plot(plot_volume=False)\n",
+    "# pivot_info = basic_data.run(\"pivotinfo\", up_th=0.003, down_th=0.002)\n",
+    "# #pivot_info.plot()\n",
+    "# pivot_info.plot(fig=fig, conf_value_trace_kwargs=dict(visible=True))\n",
+    "# fig.show()\n",
+    "\n",
+    "\n",
+    "# rsi14 = basic_data.data[\"BAC\"][\"Rsi14\"].rename(\"Rsi14\")\n",
+    "\n",
+    "# rsi14.vbt.plot().show()\n",
+    "#basic_data.xloc[\"09:30\":\"10:00\"].data[\"BAC\"].vbt.ohlcv.plot().show()\n",
+    "\n",
+    "vbt.settings.plotting.auto_rangebreaks = True\n",
+    "#basic_data.data[\"BAC\"].vbt.ohlcv.plot()\n",
+    "\n",
+    "#basic_data.data[\"BAC\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "m1_data = basic_data[['Open', 'High', 'Low', 'Close', 'Volume']]\n",
+    "\n",
+    "m1_data.data[\"BAC\"]\n",
+    "#m5_data = m1_data.resample(\"5T\")\n",
+    "\n",
+    "#m5_data.data[\"BAC\"].head(10)\n",
+    "\n",
+    "# m15_data = m1_data.resample(\"15T\")\n",
+    "\n",
+    "# m15 = m15_data.data[\"BAC\"]\n",
+    "\n",
+    "# m15.vbt.ohlcv.plot()\n",
+    "\n",
+    "# m1_data.wrapper.index\n",
+    "\n",
+    "# m1_resampler = m1_data.wrapper.get_resampler(\"1T\")\n",
+    "# m1_resampler.index_difference(reverse=True)\n",
+    "\n",
+    "\n",
+    "# m5_resampler.prettify()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# defining ENTRY WINDOW and forced EXIT window"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#m1_data.data[\"BAC\"].info()\n",
+    "import datetime\n",
+    "# Define the market open and close times\n",
+    "market_open = datetime.time(9, 30)\n",
+    "market_close = datetime.time(16, 0)\n",
+    "entry_window_opens = 1\n",
+    "entry_window_closes = 350\n",
+    "\n",
+    "forced_exit_start = 380\n",
+    "forced_exit_end = 390\n",
+    "\n",
+    "forced_exit = m1_data.symbol_wrapper.fill(False)\n",
+    "entry_window_open=  m1_data.symbol_wrapper.fill(False)\n",
+    "\n",
+    "# Calculate the time difference in minutes from market open for each timestamp\n",
+    "elapsed_min_from_open = (forced_exit.index.hour - market_open.hour) * 60 + (forced_exit.index.minute - market_open.minute)\n",
+    "\n",
+    "entry_window_open[(elapsed_min_from_open >= entry_window_opens) & (elapsed_min_from_open < entry_window_closes)] = True\n",
+    "forced_exit[(elapsed_min_from_open >= forced_exit_start) & (elapsed_min_from_open < forced_exit_end)] = True\n",
+    "\n",
+    "#entry_window_open.info()\n",
+    "# forced_exit.tail(100)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "close = m1_data.close\n",
+    "\n",
+    "rsi = vbt.RSI.run(close, window=14)\n",
+    "\n",
+    "long_entries = (rsi.rsi.vbt.crossed_below(20) & entry_window_open)\n",
+    "long_exits = (rsi.rsi.vbt.crossed_above(70) | forced_exit)\n",
+    "#long_entries.info()\n",
+    "#number of trues and falses in long_entries\n",
+    "long_entries.value_counts()\n",
+    "#long_exits.value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_rsi(rsi, close, entries, exits):\n",
+    "    fig = vbt.make_subplots(rows=1, cols=1, shared_xaxes=True, specs=[[{\"secondary_y\": True}]], vertical_spacing=0.02, subplot_titles=(\"RSI\", \"Price\" ))\n",
+    "    close.vbt.plot(fig=fig, add_trace_kwargs=dict(secondary_y=True))\n",
+    "    rsi.plot(fig=fig, add_trace_kwargs=dict(secondary_y=False))\n",
+    "    entries.vbt.signals.plot_as_entries(rsi.rsi, fig=fig, add_trace_kwargs=dict(secondary_y=False))  \n",
+    "    exits.vbt.signals.plot_as_exits(rsi.rsi, fig=fig, add_trace_kwargs=dict(secondary_y=False))  \n",
+    "    return fig\n",
+    "\n",
+    "plot_rsi(rsi, close, long_entries, long_exits)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "vbt.phelp(vbt.Portfolio.from_signals)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sl_stop = np.arange(0.03/100, 0.2/100, 0.02/100).tolist()\n",
+    "# Using the round function\n",
+    "sl_stop = [round(val, 4) for val in sl_stop]\n",
+    "print(sl_stop)\n",
+    "sl_stop = vbt.Param(sl_stop) #np.nan mean s no stoploss\n",
+    "\n",
+    "pf = vbt.Portfolio.from_signals(close=close, entries=long_entries, sl_stop=sl_stop, tp_stop = sl_stop, exits=long_exits,fees=0.0167/100, freq=\"1s\") #sl_stop=sl_stop, tp_stop = sl_stop, \n",
+    "\n",
+    "#pf.stats()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pf.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pf[(0.0015,0.0013)].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pf[0.03].plot_trade_signals()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# pristup k pf jako multi index"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#pf[0.03].plot()\n",
+    "#pf.order_records\n",
+    "pf[(0.03)].stats()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#zgrupovane statistiky\n",
+    "stats_df = pf.stats([\n",
+    "    'total_return',\n",
+    "    'total_trades',\n",
+    "    'win_rate',\n",
+    "    'expectancy'\n",
+    "], agg_func=None)\n",
+    "stats_df\n",
+    "\n",
+    "\n",
+    "stats_df.nlargest(50, 'Total Return [%]')\n",
+    "#stats_df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pf[(0.0011,0.0013)].plot()\n",
+    "\n",
+    "#pf[(0.0011,0.0013000000000000002)].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pandas.tseries.offsets import DateOffset\n",
+    "\n",
+    "temp_data = basic_data['2024-4-22']\n",
+    "temp_data\n",
+    "res1m = temp_data[[\"Open\", \"High\", \"Low\", \"Close\", \"Volume\"]]\n",
+    "\n",
+    "# Define a custom date offset that starts at 9:30 AM and spans 4 hours\n",
+    "custom_offset = DateOffset(hours=4, minutes=30)\n",
+    "\n",
+    "# res1m = res1m.get().resample(\"4H\").agg({  \n",
+    "#     \"Open\": \"first\",\n",
+    "#     \"High\": \"max\",\n",
+    "#     \"Low\": \"min\",\n",
+    "#     \"Close\": \"last\",\n",
+    "#     \"Volume\": \"sum\"\n",
+    "# })\n",
+    "\n",
+    "res4h = res1m.resample(\"1h\", resample_kwargs=dict(origin=\"start\"))\n",
+    "\n",
+    "res4h.data\n",
+    "\n",
+    "res15m = res1m.resample(\"15T\", resample_kwargs=dict(origin=\"start\"))\n",
+    "\n",
+    "res15m.data[\"BAC\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "@vbt.njit\n",
+    "def long_entry_place_func_nb(c, low, close, time_in_ns, rsi14, window_open, window_close):\n",
+    "    market_open_minutes = 570  # 9 hours * 60 minutes + 30 minutes\n",
+    "\n",
+    "    for out_i in range(len(c.out)):\n",
+    "        i = c.from_i + out_i\n",
+    "\n",
+    "        current_minutes = vbt.dt_nb.hour_nb(time_in_ns[i]) * 60 + vbt.dt_nb.minute_nb(time_in_ns[i])\n",
+    "        #print(\"current_minutes\", current_minutes)\n",
+    "        # Calculate elapsed minutes since market open at 9:30 AM\n",
+    "        elapsed_from_open = current_minutes - market_open_minutes\n",
+    "        elapsed_from_open = elapsed_from_open if elapsed_from_open >= 0 else 0\n",
+    "        #print( \"elapsed_from_open\", elapsed_from_open)\n",
+    "\n",
+    "        #elapsed_from_open = elapsed_minutes_from_open_nb(time_in_ns) \n",
+    "        in_window = elapsed_from_open > window_open and elapsed_from_open < window_close\n",
+    "        #print(\"in_window\", in_window)\n",
+    "        # if in_window:\n",
+    "        #     print(\"in window\")\n",
+    "\n",
+    "        if in_window and rsi14[i] > 60: # and low[i, c.col] <= hit_price: # and hour == 9:  # (4)!\n",
+    "            return out_i\n",
+    "    return -1\n",
+    "\n",
+    "@vbt.njit\n",
+    "def long_exit_place_func_nb(c, high, close, time_index, tp, sl):  # (5)!\n",
+    "    entry_i = c.from_i - c.wait\n",
+    "    entry_price = close[entry_i, c.col]\n",
+    "    hit_price = entry_price * (1 + tp)\n",
+    "    stop_price = entry_price * (1 - sl)\n",
+    "    for out_i in range(len(c.out)):\n",
+    "        i = c.from_i + out_i\n",
+    "        last_bar_of_day = vbt.dt_nb.day_changed_nb(time_index[i], time_index[i + 1])\n",
+    "\n",
+    "        #print(next_day)\n",
+    "        if last_bar_of_day: #pokud je dalsi next day, tak zavirame posledni\n",
+    "            print(\"ted\",out_i)\n",
+    "            return out_i\n",
+    "        if close[i, c.col] >= hit_price or close[i, c.col] <= stop_price :\n",
+    "            return out_i\n",
+    "    return -1\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = pd.DataFrame(np.random.random(size=(5, 10)), columns=list('abcdefghij'))\n",
+    "\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.sum()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

restart.sh

@@ -0,0 +1,45 @@
+#!/bin/bash
+
+# file: restart.sh
+ 
+# Usage: ./restart.sh [test|prod|all]
+
+# Define server addresses
+TEST_SERVER="david@142.132.188.109"
+PROD_SERVER="david@5.161.179.223"
+
+# Define the remote directory where the script is located
+REMOTE_DIR="v2trading"
+
+# Check for argument
+if [ "$#" -ne 1 ]; then
+  echo "Usage: $0 [test|prod|all]"
+  exit 1
+fi
+
+# Function to restart a server
+restart_server() {
+  local server=$1
+  echo "Connecting to $server to restart the Python app..."
+  ssh -t $server "cd $REMOTE_DIR && . ~/.bashrc && ./run.sh restart"  # Sourcing .bashrc here
+  echo "Operation completed on $server."
+}
+
+# Select the server based on the input argument
+case $1 in
+  test)
+    restart_server $TEST_SERVER
+    ;;
+  prod)
+    restart_server $PROD_SERVER
+    ;;
+  all)
+    restart_server $TEST_SERVER
+    restart_server $PROD_SERVER
+    ;;
+  *)
+    echo "Invalid argument: $1. Use 'test', 'prod', or 'all'."
+    exit 1
+    ;;
+esac
+

testdoc.md

@@ -0,0 +1,107 @@
+# Plotly
+
+* MAKE_SUBPLOT Defines layout (if more then 1x1 or secondary y axis are required)
+
+```python
+fig = vbt.make_subplots(rows=2, cols=1, shared_xaxes=True, 
+                        specs=[[{"secondary_y": True}], [{"secondary_y": False}]], 
+                        vertical_spacing=0.02, subplot_titles=("Row 1 title", "Row 2 title"))
+```
+
+Then the different [sr/df generic accessor](http://5.161.179.223:8000/static/js/vbt/api/generic/accessors/index.html#vectorbtpro.generic.accessors.GenericAccessor.areaplot) are added with ADD_TRACE_KWARGS and TRACE_KWARGS. Other types of plot available in [plotting module](http://5.161.179.223:8000/static/js/vbt/api/generic/plotting/index.html)
+
+```python
+#using accessor
+close.vbt.plot(fig=fig, add_trace_kwargs=dict(secondary_y=False,row=1, col=1), trace_kwargs=dict(line=dict(color="blue")))
+indvolume.vbt.barplot(fig=fig, add_trace_kwargs=dict(secondary_y=False, row=2, col=1))
+#using plotting module
+vbt.Bar(indvolume, fig=fig, add_trace_kwargs=dict(secondary_y=False, row=2, col=1))
+```
+
+* ADD_TRACE_KWARGS - determines positioning withing subplot
+```python
+add_trace_kwargs=dict(secondary_y=False,row=1, col=1)
+```
+* TRACE_KWARGS - other styling of trace
+```python
+trace_kwargs=dict(name="LONGS",
+                  line=dict(color="#ffe476"),
+                  marker=dict(color="limegreen"),
+                  fill=None,
+                  connectgaps=True)
+```
+
+## Example
+
+```python
+    fig = vbt.make_subplots(rows=2, cols=1, shared_xaxes=True, 
+                            specs=[[{"secondary_y": True}], [{"secondary_y": False}]], 
+                            vertical_spacing=0.02, subplot_titles=("Price and Indicators", "Volume"))
+
+    # Plotting the close price
+    close.vbt.plot(fig=fig, add_trace_kwargs=dict(secondary_y=False,row=1, col=1), trace_kwargs=dict(line=dict(color="blue")))
+```
+
+# Data
+## Resampling
+```python
+t1data = basic_data[['open', 'high', 'low', 'close', 'volume','vwap','buyvolume','sellvolume']].resample("1T")
+t1data = t1data.transform(lambda df: df.between_time('09:30', '16:00').dropna()) #main session data only, no nans
+
+t5data = basic_data[['open', 'high', 'low', 'close', 'volume','vwap','buyvolume','sellvolume']].resample("5T")
+t5data = t5data.transform(lambda df: df.between_time('09:30', '16:00').dropna())
+
+dailydata = basic_data[['open', 'high', 'low', 'close', 'volume', 'vwap']].resample("D").dropna()
+
+#realign 5min close to 1min so it can be compared with 1min
+t5data_close_realigned = t5data.close.vbt.realign_closing("1T").between_time('09:30', '16:00').dropna() 
+#same with open
+t5data.open.vbt.realign_opening("1h")
+```
+### Define resample function for custom column
+Example of custom feature config [Binance Data](http://5.161.179.223:8000/static/js/vbt/api/data/custom/binance/index.html#vectorbtpro.data.custom.binance.BinanceData.feature_config).
+Other [reduced functions available](http://5.161.179.223:8000/static/js/vbt/api/generic/nb/apply_reduce/index.html). (mean, min, max, median, nth ...)
+```python
+from vectorbtpro.utils.config import merge_dicts, Config, HybridConfig
+from vectorbtpro import _typing as tp
+from vectorbtpro.generic import nb as generic_nb
+
+_feature_config: tp.ClassVar[Config] = HybridConfig(
+    {
+        "buyvolume": dict(
+            resample_func=lambda self, obj, resampler: obj.vbt.resample_apply(
+                resampler,
+                generic_nb.sum_reduce_nb,
+            )
+        ),
+        "sellvolume": dict(
+            resample_func=lambda self, obj, resampler: obj.vbt.resample_apply(
+                resampler,
+                generic_nb.sum_reduce_nb,
+            )
+        )
+    }
+)
+
+basic_data._feature_config = _feature_config
+```
+
+### Validate resample
+```python
+t2dataclose = t2data.close.rename("15MIN - realigned").vbt.realign_closing("1T")
+fig = t1data.close.rename("1MIN").vbt.plot()
+t2data.close.rename("15MIN").vbt.plot(fig=fig)
+t2dataclose.vbt.plot(fig=fig)
+```
+## Persisting
+```python
+basic_data.to_parquet(partition_by="day", compression="gzip")  
+day_data = vbt.ParquetData.pull("BAC", filters=[("group", "==", "2024-05-03")]) 
+vbt.print_dir_tree("BTC-USD")#overeni directory structure
+```
+# Discover
+```python
+vbt.phelp(vbt.talib(“atr”).run) #parameters it accepts
+vbt.pdir(pf) - get available properties and methods
+vbt.pprint(basic_data) #to get correct shape, info about instance
+```

testy/archive/alpacaGetHistoryBars.py

@@ -23,12 +23,12 @@ clientTrading = TradingClient(ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY,
 
 #get previous days bar
 
-datetime_object_from = datetime.datetime(2023, 10, 11, 4, 0, 00, tzinfo=datetime.timezone.utc)
-datetime_object_to = datetime.datetime(2023, 10, 16, 16, 1, 00, tzinfo=datetime.timezone.utc)
-calendar_request = GetCalendarRequest(start=datetime_object_from,end=datetime_object_to)
-cal_dates = clientTrading.get_calendar(calendar_request)
-print(cal_dates)
-bar_request = StockBarsRequest(symbol_or_symbols="BAC",timeframe=TimeFrame.Day, start=datetime_object_from, end=datetime_object_to, feed=DataFeed.SIP)
+datetime_object_from = datetime.datetime(2024, 3, 9, 13, 29, 00, tzinfo=datetime.timezone.utc)
+datetime_object_to = datetime.datetime(2024, 3, 11, 20, 1, 00, tzinfo=datetime.timezone.utc)
+# calendar_request = GetCalendarRequest(start=datetime_object_from,end=datetime_object_to)
+# cal_dates = clientTrading.get_calendar(calendar_request)
+# print(cal_dates)
+bar_request = StockBarsRequest(symbol_or_symbols="BAC",timeframe=TimeFrame.Minute, start=datetime_object_from, end=datetime_object_to, feed=DataFeed.SIP)
 
 # bars = client.get_stock_bars(bar_request).df
 

testy/archive/config.py

@@ -1,3 +1,3 @@
-API_KEY = 'PKGGEWIEYZOVQFDRY70L'
-SECRET_KEY = 'O5Kt8X4RLceIOvM98i5LdbalItsX7hVZlbPYHy8Y'
+API_KEY = ''
+SECRET_KEY = ''
 MAX_BATCH_SIZE = 1

testy/createbatchimage.py

@@ -0,0 +1,18 @@
+import argparse
+import v2realbot.reporting.metricstoolsimage as mt
+
+# Parse the command-line arguments
+# parser = argparse.ArgumentParser(description="Generate trading report image with batch ID")
+# parser.add_argument("batch_id", type=str, help="The batch ID for the report")
+# args = parser.parse_args()
+
+# batch_id = args.batch_id
+
+# Generate the report image
+res, val = mt.generate_trading_report_image(batch_id="4d7dc163")
+
+# Print the result
+if res == 0:
+    print("BATCH REPORT CREATED")
+else:
+    print(f"BATCH REPORT ERROR - {val}")

testy/gethistorytrades.py

@@ -1,7 +1,9 @@
 import os,sys
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 print(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-from alpaca.data.historical import CryptoHistoricalDataClient, StockHistoricalDataClient
+import pandas as pd
+import numpy as np
+from alpaca.data.historical import StockHistoricalDataClient
 from alpaca.data.requests import CryptoLatestTradeRequest, StockLatestTradeRequest, StockLatestBarRequest, StockTradesRequest
 from alpaca.data.enums import DataFeed
 from v2realbot.config import ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY

testy/getrunnerdetail.py

@@ -0,0 +1,89 @@
+
+from v2realbot.common.model import RunDay, StrategyInstance, Runner, RunRequest, RunArchive, RunArchiveView, RunArchiveViewPagination, RunArchiveDetail, RunArchiveChange, Bar, TradeEvent, TestList, Intervals, ConfigItem, InstantIndicator, DataTablesRequest
+import v2realbot.controller.services as cs
+from v2realbot.utils.utils import slice_dict_lists,zoneUTC,safe_get, AttributeDict
+id = "b11c66d9-a9b6-475a-9ac1-28b11e1b4edf"
+state = AttributeDict(vars={})
+
+##základ pro init_attached_data in strategy.init
+
+# def get_previous_runner(state):
+#     runner : Runner
+#     res, runner = cs.get_runner(state.runner_id)
+#     if res < 0:
+#         print(f"Not running {id}")
+#         return 0, None
+    
+#     return 0, runner.batch_id
+
+def attach_previous_data(state):
+    runner : Runner
+    #get batch_id of current runer
+    res, runner = cs.get_runner(state.runner_id)
+    if res < 0 or runner.batch_id is None:
+        print(f"Couldnt get previous runner {val}")
+        return None
+    
+    batch_id = runner.batch_id
+    #batch_id = "6a6b0bcf"
+
+    res, runner_ids =cs.get_archived_runnerslist_byBatchID(batch_id, "desc")
+    if res < 0:
+        msg = f"error whne fetching runners of batch {batch_id} {runner_ids}"
+        print(msg)
+        return None
+    
+    if runner_ids is None or len(runner_ids) == 0:
+        print(f"no runners found for batch {batch_id} {runner_ids}")
+        return None
+    
+    last_runner = runner_ids[0]
+    print("Previous runner identified:", last_runner)
+
+    #get details from the runner
+    res, val = cs.get_archived_runner_details_byID(last_runner)
+    if res < 0:
+        print(f"no archived runner {last_runner}")
+
+    detail = RunArchiveDetail(**val)
+    #print("toto jsme si dotahnuli", detail.bars)
+
+    # from stratvars directives 
+    attach_previous_bars_indicators = safe_get(state.vars, "attach_previous_bars_indicators", 50)
+    attach_previous_cbar_indicators = safe_get(state.vars, "attach_previous_cbar_indicators", 50)
+    # [stratvars]
+    #     attach_previous_bars_indicators = 50
+    #     attach_previous_cbar_indicators = 50
+
+    #indicators datetime utc
+    indicators = slice_dict_lists(d=detail.indicators[0],last_item=attach_previous_bars_indicators, time_to_datetime=True)
+
+    #time -datetime utc, updated - timestamp float
+    bars = slice_dict_lists(d=detail.bars, last_item=attach_previous_bars_indicators, time_to_datetime=True)
+
+    #cbar_indicatzors #float
+    cbar_inds = slice_dict_lists(d=detail.indicators[1],last_item=attach_previous_cbar_indicators)
+
+    #USE these as INITs - TADY SI TO JESTE ZASTAVIT a POROVNAT
+    print(f"{state.indicators=} NEW:{indicators=}")
+    state.indicators = indicators
+    print(f"{state.bars=} NEW:{bars=}")
+    state.bars = bars
+    print(f"{state.cbar_indicators=} NEW:{cbar_inds=}")
+    state.cbar_indicators = cbar_inds
+
+    print("BARS and INDS INITIALIZED")
+    #bars
+
+
+    #tady budou pripadne dalsi inicializace, z ext_data
+    print("EXT_DATA", detail.ext_data)
+    #podle urciteho nastaveni napr.v konfiguraci se pouziji urcite promenne
+
+    #pridavame dailyBars z extData
+    # if hasattr(detail, "ext_data") and "dailyBars" in detail.ext_data:
+    #     state.dailyBars = detail.ext_data["dailyBars"]
+
+
+if __name__ == "__main__":
+    attach_previous_data(state)

testy/tablesizes.py

@@ -0,0 +1,74 @@
+import queue
+import sqlite3
+import threading
+from appdirs import user_data_dir
+
+DATA_DIR = user_data_dir("v2realbot")
+sqlite_db_file = DATA_DIR + "/v2trading.db"
+
+class ConnectionPool:
+    def __init__(self, max_connections):
+        self.max_connections = max_connections
+        self.connections = queue.Queue(max_connections)
+        self.lock = threading.Lock()
+
+    def get_connection(self):
+        with self.lock:
+            if self.connections.empty():
+                return self.create_connection()
+            else:
+                return self.connections.get()
+
+    def release_connection(self, connection):
+        with self.lock:
+            self.connections.put(connection)
+
+    def create_connection(self):
+        connection = sqlite3.connect(sqlite_db_file, check_same_thread=False)
+        return connection
+
+
+pool = ConnectionPool(10)
+
+def get_table_sizes_in_mb():
+    # Connect to the SQLite database
+    conn = pool.get_connection()
+    cursor = conn.cursor()
+
+    # Get the list of tables
+    cursor.execute("SELECT name FROM sqlite_master WHERE type='table';")
+    tables = cursor.fetchall()
+
+    # Dictionary to store table sizes
+    table_sizes = {}
+
+    for table in tables:
+        table_name = table[0]
+
+        # Get total number of rows in the table
+        cursor.execute(f"SELECT COUNT(*) FROM {table_name};")
+        row_count = cursor.fetchone()[0]
+
+        if row_count > 0:
+            # Sample a few rows (e.g., 10 rows) and calculate average row size
+            cursor.execute(f"SELECT * FROM {table_name} LIMIT 10;")
+            sample_rows = cursor.fetchall()
+            total_sample_size = sum(sum(len(str(cell)) for cell in row) for row in sample_rows)
+            avg_row_size = total_sample_size / len(sample_rows)
+
+            # Estimate table size in megabytes
+            size_in_mb = (avg_row_size * row_count) / (1024 * 1024)
+        else:
+            size_in_mb = 0
+
+        table_sizes[table_name] = {'size_mb': size_in_mb, 'rows': row_count}
+
+    conn.close()
+    return table_sizes
+
+# Usage example
+db_path = 'path_to_your_database.db'
+table_sizes = get_table_sizes_in_mb()
+for table, info in table_sizes.items():
+    print(f"Table: {table}, Size: {info['size_mb']} MB, Rows: {info['rows']}")
+

testy/vectorbt/testHtml2MD.py

@@ -0,0 +1,66 @@
+import os
+from bs4 import BeautifulSoup
+import html2text
+
+def convert_html_to_markdown(html_content, link_mapping):
+    h = html2text.HTML2Text()
+    h.ignore_links = False
+
+    # Update internal links to point to the relevant sections in the Markdown
+    soup = BeautifulSoup(html_content, 'html.parser')
+    for a in soup.find_all('a', href=True):
+        href = a['href']
+        if href in link_mapping:
+            a['href'] = f"#{link_mapping[href]}"
+    
+    return h.handle(str(soup))
+
+def create_link_mapping(root_dir):
+    link_mapping = {}
+    for subdir, _, files in os.walk(root_dir):
+        for file in files:
+            if file == "index.html":
+                relative_path = os.path.relpath(os.path.join(subdir, file), root_dir)
+                chapter_id = relative_path.replace(os.sep, '-').replace('index.html', '')
+                link_mapping[relative_path] = chapter_id
+                link_mapping[relative_path.replace(os.sep, '/')] = chapter_id  # for URLs with slashes
+    return link_mapping
+
+def read_html_files(root_dir, link_mapping):
+    markdown_content = []
+    
+    for subdir, _, files in os.walk(root_dir):
+        relative_path = os.path.relpath(subdir, root_dir)
+        if files and any(file == "index.html" for file in files):
+            # Add directory as a heading based on its depth
+            heading_level = relative_path.count(os.sep) + 1
+            markdown_content.append(f"{'#' * heading_level} {relative_path}\n")
+        
+        for file in files:
+            if file == "index.html":
+                file_path = os.path.join(subdir, file)
+                with open(file_path, 'r', encoding='utf-8') as f:
+                    html_content = f.read()
+                    soup = BeautifulSoup(html_content, 'html.parser')
+                    title = soup.title.string if soup.title else "No Title"
+                    chapter_id = os.path.relpath(file_path, root_dir).replace(os.sep, '-').replace('index.html', '')
+                    markdown_content.append(f"<a id='{chapter_id}'></a>\n")
+                    markdown_content.append(f"{'#' * (heading_level + 1)} {title}\n")
+                    markdown_content.append(convert_html_to_markdown(html_content, link_mapping))
+    
+    return "\n".join(markdown_content)
+
+def save_to_markdown_file(content, output_file):
+    with open(output_file, 'w', encoding='utf-8') as f:
+        f.write(content)
+
+def main():
+    root_dir =  "./v2realbot/static/js/vbt/"
+    output_file = "output.md"
+    link_mapping = create_link_mapping(root_dir)
+    markdown_content = read_html_files(root_dir, link_mapping)
+    save_to_markdown_file(markdown_content, output_file)
+    print(f"Markdown document created at {output_file}")
+
+if __name__ == "__main__":
+    main()

v2realbot/ENTRY_ClassicSL_v01.py

@@ -3,7 +3,7 @@ sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 from v2realbot.strategy.base import StrategyState
 from v2realbot.strategy.StrategyOrderLimitVykladaciNormalizedMYSELL import StrategyOrderLimitVykladaciNormalizedMYSELL
 from v2realbot.enums.enums import RecordType, StartBarAlign, Mode, Account
-from v2realbot.utils.utils import zoneNY, print
+from v2realbot.utils.utils import zoneNY, print, fetch_calendar_data, send_to_telegram
 from v2realbot.utils.historicals import get_historical_bars
 from datetime import datetime, timedelta
 from rich import print as printanyway
@@ -16,9 +16,9 @@ from v2realbot.strategyblocks.newtrade.signals import signal_search
 from v2realbot.strategyblocks.activetrade.activetrade_hub import manage_active_trade
 from v2realbot.strategyblocks.inits.init_indicators import initialize_dynamic_indicators
 from v2realbot.strategyblocks.inits.init_directives import intialize_directive_conditions
-from alpaca.trading.requests import GetCalendarRequest
+from v2realbot.strategyblocks.inits.init_attached_data import attach_previous_data
 from alpaca.trading.client import TradingClient
-from v2realbot.config import ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, DATA_DIR, OFFLINE_MODE
+from v2realbot.config import ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, DATA_DIR
 from alpaca.trading.models import Calendar
 from v2realbot.indicators.oscillators import rsi
 from v2realbot.indicators.moving_averages import sma
@@ -116,6 +116,10 @@ def init(state: StrategyState):
     #models
     state.vars.loaded_models = {}
 
+    #state attributes for martingale sizing mngmt
+    state.vars["transferables"] = {}
+    state.vars["transferables"]["martingale"] = dict(cont_loss_series_cnt=0)
+    
     #INITIALIZE CBAR INDICATORS - do vlastni funkce
     #state.cbar_indicators['ivwap'] = []
     state.vars.last_tick_price = 0
@@ -129,6 +133,9 @@ def init(state: StrategyState):
     initialize_dynamic_indicators(state)
     intialize_directive_conditions(state)
 
+    #attach part of yesterdays data, bars, indicators, cbar_indicators
+    attach_previous_data(state)
+
     #intitialize indicator mapping (for use in operation) -  mozna presunout do samostatne funkce prip dat do base kdyz se osvedci
     local_dict_cbar_inds = {key: state.cbar_indicators[key] for key in state.cbar_indicators.keys() if key != "time"}
     local_dict_inds = {key: state.indicators[key] for key in state.indicators.keys() if key != "time"}
@@ -167,10 +174,13 @@ def init(state: StrategyState):
     today = time_to.date()
     several_days_ago = today - timedelta(days=60)
     #printanyway(f"{today=}",f"{several_days_ago=}")
-    clientTrading = TradingClient(ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, raw_data=False)
+    #clientTrading = TradingClient(ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, raw_data=False)
     #get all market days from here to 40days ago
-    calendar_request = GetCalendarRequest(start=several_days_ago,end=today)
-    cal_dates = clientTrading.get_calendar(calendar_request)
+
+    #calendar_request = GetCalendarRequest(start=several_days_ago,end=today)
+
+    cal_dates = fetch_calendar_data(several_days_ago, today)
+    #cal_dates = clientTrading.get_calendar(calendar_request)
 
     #find the first market day - 40days ago
     #history_datetime_from = zoneNY.localize(cal_dates[0].open)
@@ -197,7 +207,12 @@ def init(state: StrategyState):
 
     #NOTE zatim pridano takto do baru dalsi indikatory
     #BUDE PREDELANO - v rámci custom rozliseni a static indikátoru
-
+    if state.dailyBars is None:
+        print("Nepodařilo se načíst denní bary")
+        err_msg = f"Nepodařilo se načíst denní bary (get_historical_bars) pro {state.symbol} od {history_datetime_from} do {history_datetime_to} ve strat.init. Probably wrong symbol?"
+        send_to_telegram(err_msg)
+        raise Exception(err_msg)
+    
     #RSI vraci pouze pro vsechny + prepend with zeros nepocita prvnich N (dle rsi length)
     rsi_calculated = rsi(state.dailyBars["vwap"], 14).tolist()
     num_zeros_to_prepend = len(state.dailyBars["vwap"]) - len(rsi_calculated)

v2realbot/backtesting/backtester.py

@@ -40,10 +40,10 @@
 from uuid import UUID, uuid4
 from alpaca.trading.enums import OrderSide, OrderStatus, TradeEvent, OrderType
 from v2realbot.common.model import TradeUpdate, Order
-#from rich import print
+from rich import print as printanyway
 import threading
 import asyncio
-from v2realbot.config import BT_DELAYS, DATA_DIR, BT_FILL_CONDITION_BUY_LIMIT, BT_FILL_CONDITION_SELL_LIMIT, BT_FILL_LOG_SURROUNDING_TRADES, BT_FILL_CONS_TRADES_REQUIRED,BT_FILL_PRICE_MARKET_ORDER_PREMIUM
+from v2realbot.config import DATA_DIR
 from v2realbot.utils.utils import AttributeDict, ltp, zoneNY, trunc, count_decimals, print
 from v2realbot.utils.tlog import tlog
 from v2realbot.enums.enums import FillCondition
@@ -60,6 +60,7 @@ from v2realbot.utils.dash_save_html import make_static
 import dash_bootstrap_components as dbc
 from dash.dependencies import Input, Output
 from dash import dcc, html, dash_table, Dash
+import v2realbot.utils.config_handler as cfh
 """"
 LATENCY DELAYS
 .000 trigger - last_trade_time (.4246266)
@@ -171,7 +172,7 @@ class Backtester:
                 todel.append(order)
             elif not self.symbol or order.symbol == self.symbol:
                 #pricteme mininimalni latency od submittu k fillu
-                if order.submitted_at.timestamp() + BT_DELAYS.sub_to_fill > float(intime):
+                if order.submitted_at.timestamp() + cfh.config_handler.get_val('BT_DELAYS','sub_to_fill') > float(intime):
                     print(f"too soon for {order.id}")
                 #try to execute
                 else:
@@ -197,7 +198,7 @@ class Backtester:
         #Mazeme, jinak je to hruza
         #nechavame na konci trady, které muzeme potrebovat pro consekutivni pravidlo
         #osetrujeme, kdy je malo tradu a oriznuti by slo do zaporu
-        del_to_index = index_end-2-BT_FILL_CONS_TRADES_REQUIRED
+        del_to_index = index_end-2-cfh.config_handler.get_val('BT_FILL_CONS_TRADES_REQUIRED')
         del_to_index = del_to_index if del_to_index > 0 else 0
         del self.btdata[0:del_to_index]
         ##ic("after delete",len(self.btdata[0:index_end]))
@@ -218,7 +219,7 @@ class Backtester:
 
         fill_time = None
         fill_price = None
-        order_min_fill_time = o.submitted_at.timestamp() + BT_DELAYS.sub_to_fill
+        order_min_fill_time = o.submitted_at.timestamp() + cfh.config_handler.get_val('BT_DELAYS','sub_to_fill')
         #ic(order_min_fill_time)
         #ic(len(work_range))
 
@@ -240,17 +241,18 @@ class Backtester:
                     #NASTVENI PODMINEK PLNENI
                     fast_fill_condition = i[1] <= o.limit_price
                     slow_fill_condition = i[1] < o.limit_price
-                    if BT_FILL_CONDITION_BUY_LIMIT == FillCondition.FAST:
+                    fill_cond_buy_limit = cfh.config_handler.get_val('BT_FILL_CONDITION_BUY_LIMIT')
+                    if fill_cond_buy_limit == FillCondition.FAST:
                         fill_condition = fast_fill_condition
-                    elif BT_FILL_CONDITION_BUY_LIMIT == FillCondition.SLOW:
+                    elif fill_cond_buy_limit == FillCondition.SLOW:
                         fill_condition = slow_fill_condition
                     else:
                         print("unknow fill condition")
                         return -1
 
-                    if float(i[0]) > float(order_min_fill_time+BT_DELAYS.limit_order_offset) and fill_condition:
+                    if float(i[0]) > float(order_min_fill_time+cfh.config_handler.get_val('BT_DELAYS','limit_order_offset')) and fill_condition:
                         consec_cnt += 1
-                        if consec_cnt == BT_FILL_CONS_TRADES_REQUIRED:
+                        if consec_cnt == cfh.config_handler.get_val('BT_FILL_CONS_TRADES_REQUIRED'):
 
                             #(1679081919.381649, 27.88)
                             #ic(i)
@@ -261,10 +263,10 @@ class Backtester:
                             #fill_price = i[1]
 
                             print("FILL LIMIT BUY at", fill_time, datetime.fromtimestamp(fill_time).astimezone(zoneNY), "at",i[1])
-                            if BT_FILL_LOG_SURROUNDING_TRADES != 0:
+                            if cfh.config_handler.get_val('BT_FILL_LOG_SURROUNDING_TRADES') != 0:
                                 #TODO loguru
-                                print("FILL SURR TRADES: before",work_range[index-BT_FILL_LOG_SURROUNDING_TRADES:index])
-                                print("FILL SURR TRADES: fill and after",work_range[index:index+BT_FILL_LOG_SURROUNDING_TRADES])
+                                print("FILL SURR TRADES: before",work_range[index-cfh.config_handler.get_val('BT_FILL_LOG_SURROUNDING_TRADES'):index])
+                                print("FILL SURR TRADES: fill and after",work_range[index:index+cfh.config_handler.get_val('BT_FILL_LOG_SURROUNDING_TRADES')])
                             break
                     else:
                         consec_cnt = 0
@@ -275,17 +277,18 @@ class Backtester:
                     #NASTVENI PODMINEK PLNENI
                     fast_fill_condition = i[1] >= o.limit_price
                     slow_fill_condition = i[1] > o.limit_price
-                    if BT_FILL_CONDITION_SELL_LIMIT == FillCondition.FAST:
+                    fill_conf_sell_cfg = cfh.config_handler.get_val('BT_FILL_CONDITION_SELL_LIMIT')
+                    if fill_conf_sell_cfg == FillCondition.FAST:
                         fill_condition = fast_fill_condition
-                    elif BT_FILL_CONDITION_SELL_LIMIT == FillCondition.SLOW:
+                    elif fill_conf_sell_cfg == FillCondition.SLOW:
                         fill_condition = slow_fill_condition
                     else:
                         print("unknown fill condition")
                         return -1
 
-                    if float(i[0]) > float(order_min_fill_time+BT_DELAYS.limit_order_offset) and fill_condition:
+                    if float(i[0]) > float(order_min_fill_time+cfh.config_handler.get_val('BT_DELAYS','limit_order_offset')) and fill_condition:
                         consec_cnt += 1
-                        if consec_cnt == BT_FILL_CONS_TRADES_REQUIRED:
+                        if consec_cnt == cfh.config_handler.get_val('BT_FILL_CONS_TRADES_REQUIRED'):
                             #(1679081919.381649, 27.88)
                             #ic(i)
                             fill_time = i[0]
@@ -297,10 +300,11 @@ class Backtester:
 
                             #fill_price = i[1]
                             print("FILL LIMIT SELL at", fill_time, datetime.fromtimestamp(fill_time).astimezone(zoneNY), "at",i[1])
-                            if BT_FILL_LOG_SURROUNDING_TRADES != 0:
+                            surr_trades_cfg = cfh.config_handler.get_val('BT_FILL_LOG_SURROUNDING_TRADES')
+                            if surr_trades_cfg != 0:
                                 #TODO loguru
-                                print("FILL SELL SURR TRADES: before",work_range[index-BT_FILL_LOG_SURROUNDING_TRADES:index])
-                                print("FILL SELL SURR TRADES: fill and after",work_range[index:index+BT_FILL_LOG_SURROUNDING_TRADES])
+                                print("FILL SELL SURR TRADES: before",work_range[index-surr_trades_cfg:index])
+                                print("FILL SELL SURR TRADES: fill and after",work_range[index:index+surr_trades_cfg])
                             break
                     else:
                         consec_cnt = 0
@@ -314,11 +318,16 @@ class Backtester:
                     #ic(i)
                     fill_time = i[0]
                     fill_price = i[1]
-                    #přičteme MARKET PREMIUM z konfigurace (do budoucna mozna rozdilne pro BUY/SELL a nebo mozna z konfigurace pro dany itutl)
+                    #přičteme MARKET PREMIUM z konfigurace (je v pct nebo abs) (do budoucna mozna rozdilne pro BUY/SELL a nebo mozna z konfigurace pro dany titul)
+                    cfg_premium = cfh.config_handler.get_val('BT_FILL_PRICE_MARKET_ORDER_PREMIUM')
+                    if cfg_premium < 0: #configured as percentage
+                        premium = abs(cfg_premium) * fill_price / 100.0
+                    else: #configured as absolute value
+                        premium = cfg_premium           
                     if o.side == OrderSide.BUY:
-                        fill_price = fill_price + BT_FILL_PRICE_MARKET_ORDER_PREMIUM
+                        fill_price = fill_price + premium
                     elif o.side == OrderSide.SELL:
-                        fill_price = fill_price - BT_FILL_PRICE_MARKET_ORDER_PREMIUM
+                        fill_price = fill_price - premium
                     
                     print("FILL ",o.side,"MARKET at", fill_time, datetime.fromtimestamp(fill_time).astimezone(zoneNY), "cena", i[1])
                     break
@@ -367,7 +376,7 @@ class Backtester:
     def _do_notification_with_callbacks(self, tradeupdate: TradeUpdate, time: float):
     
         #do callbacku je třeba zpropagovat filltime čas (včetně latency pro notifikaci), aby se pripadne akce v callbacku udály s tímto časem
-        self.time = time + float(BT_DELAYS.fill_to_not)
+        self.time = time + float(cfh.config_handler.get_val('BT_DELAYS','fill_to_not'))
         print("current bt.time",self.time)
         #print("FILL NOTIFICATION: ", tradeupdate)
         res = asyncio.run(self.order_fill_callback(tradeupdate))
@@ -470,11 +479,11 @@ class Backtester:
         print("BT: submit order entry")
 
         if not time or time < 0:
-            print("time musi byt vyplneny")
+            printanyway("time musi byt vyplneny")
             return -1
 
         if not size or int(size) < 0:
-            print("size musi byt vetsi nez 0")
+            printanyway("size musi byt vetsi nez 0")
             return -1
 
         if (order_type != OrderType.MARKET) and (order_type != OrderType.LIMIT):
@@ -482,11 +491,11 @@ class Backtester:
             return -1
 
         if not side == OrderSide.BUY and not side == OrderSide.SELL:
-            print("side buy/sell required")
+            printanyway("side buy/sell required")
             return -1
         
         if order_type == OrderType.LIMIT and count_decimals(price) > 2:
-            print("only 2 decimals supported", price)
+            printanyway("only 2 decimals supported", price)
             return -1
     
         #pokud neexistuje klic v accountu vytvorime si ho
@@ -508,14 +517,14 @@ class Backtester:
             
             actual_minus_reserved = int(self.account[symbol][0]) - reserved 
             if actual_minus_reserved > 0 and actual_minus_reserved - int(size) < 0:
-                print("not enough shares available to sell or shorting while long position",self.account[symbol][0],"reserved",reserved,"available",int(self.account[symbol][0]) - reserved,"selling",size)
+                printanyway("not enough shares available to sell or shorting while long position",self.account[symbol][0],"reserved",reserved,"available",int(self.account[symbol][0]) - reserved,"selling",size)
                 return -1
             
             #if is shorting - check available cash to short
             if actual_minus_reserved <= 0:
                 cena = price if price else self.get_last_price(time, self.symbol)
                 if (self.cash - reserved_price - float(int(size)*float(cena))) < 0:
-                    print("not enough cash for shorting. cash",self.cash,"reserved",reserved,"available",self.cash-reserved,"needed",float(int(size)*float(cena)))
+                    printanyway("ERROR: not enough cash for shorting. cash",self.cash,"reserved",reserved,"available",self.cash-reserved,"needed",float(int(size)*float(cena)))
                     return -1               
 
         #check for available cash
@@ -534,14 +543,14 @@ class Backtester:
             
             #jde o uzavreni shortu
             if actual_plus_reserved_qty < 0 and (actual_plus_reserved_qty + int(size)) > 0:
-                print("nejprve je treba uzavrit short pozici pro buy res_qty, size", actual_plus_reserved_qty, size)
+                printanyway("nejprve je treba uzavrit short pozici pro buy res_qty, size", actual_plus_reserved_qty, size)
                 return -1
 
             #jde o standardni long, kontroluju cash
             if actual_plus_reserved_qty >= 0:
                 cena = price if price else self.get_last_price(time, self.symbol)
                 if (self.cash - reserved_price - float(int(size)*float(cena))) < 0:
-                    print("not enough cash to buy long. cash",self.cash,"reserved_qty",reserved_qty,"reserved_price",reserved_price, "available",self.cash-reserved_price,"needed",float(int(size)*float(cena)))
+                    printanyway("ERROR: not enough cash to buy long. cash",self.cash,"reserved_qty",reserved_qty,"reserved_price",reserved_price, "available",self.cash-reserved_price,"needed",float(int(size)*float(cena)))
                     return -1
 
         id = str(uuid4())
@@ -568,11 +577,11 @@ class Backtester:
         print("BT: replace order entry",id,size,price)
 
         if not price and not size:
-            print("size or price required")
+            printanyway("size or price required")
             return -1
 
         if len(self.open_orders) == 0:
-            print("BT: order doesnt exist")
+            printanyway("BT: order doesnt exist")
             return 0
         #with lock:
         for o in self.open_orders:
@@ -600,7 +609,7 @@ class Backtester:
         """
         print("BT: cancel order entry",id)
         if len(self.open_orders) == 0:
-            print("BTC: order doesnt exist")
+            printanyway("BTC: order doesnt exist")
             return 0
         #with lock:
         for o in self.open_orders:
@@ -820,10 +829,10 @@ class Backtester:
             Trades:''' + str(len(self.trades)))
         textik8 = html.Div('''
             Profit:''' + str(state.profit))
-        textik9 = html.Div(f"{BT_FILL_CONS_TRADES_REQUIRED=}")
-        textik10 = html.Div(f"{BT_FILL_LOG_SURROUNDING_TRADES=}")
-        textik11 = html.Div(f"{BT_FILL_CONDITION_BUY_LIMIT=}")
-        textik12 = html.Div(f"{BT_FILL_CONDITION_SELL_LIMIT=}")
+        textik9 = html.Div(f"{cfh.config_handler.get_val('BT_FILL_CONS_TRADES_REQUIRED')=}")
+        textik10 = html.Div(f"{cfh.config_handler.get_val('BT_FILL_LOG_SURROUNDING_TRADES')=}")
+        textik11 = html.Div(f"{cfh.config_handler.get_val('BT_FILL_CONDITION_BUY_LIMIT')=}")
+        textik12 = html.Div(f"{cfh.config_handler.get_val('BT_FILL_CONDITION_SELL_LIMIT')=}")
         
         orders_title = dcc.Markdown('## Open orders')
         trades_title = dcc.Markdown('## Trades')

v2realbot/common/db.py

@@ -1,11 +1,8 @@
-from v2realbot.config import DATA_DIR
 import sqlite3
 import queue
 import threading
 import time
-from v2realbot.common.model import RunArchive, RunArchiveView
-from datetime import datetime
-import orjson
+from v2realbot.config import DATA_DIR
 
 sqlite_db_file = DATA_DIR + "/v2trading.db"
 # Define the connection pool
@@ -31,7 +28,7 @@ class ConnectionPool:
         return connection
 
 
-def execute_with_retry(cursor: sqlite3.Cursor, statement: str, params = None, retry_interval: int = 1) -> sqlite3.Cursor:
+def execute_with_retry(cursor: sqlite3.Cursor, statement: str, params = None, retry_interval: int = 2) -> sqlite3.Cursor:
     """get connection from pool and execute SQL statement with retry logic if required.
 
     Args:
@@ -60,53 +57,4 @@ def execute_with_retry(cursor: sqlite3.Cursor, statement: str, params = None, re
 pool = ConnectionPool(10)
 #for one shared connection (used for writes only in WAL mode)
 insert_conn = sqlite3.connect(sqlite_db_file, check_same_thread=False)
-insert_queue = queue.Queue()
-
-#prevede dict radku zpatky na objekt vcetme retypizace
-def row_to_runarchiveview(row: dict) -> RunArchiveView:
-    return RunArchive(
-        id=row['runner_id'],
-        strat_id=row['strat_id'],
-        batch_id=row['batch_id'],
-        symbol=row['symbol'],
-        name=row['name'],
-        note=row['note'],
-        started=datetime.fromisoformat(row['started']) if row['started'] else None,
-        stopped=datetime.fromisoformat(row['stopped']) if row['stopped'] else None,
-        mode=row['mode'],
-        account=row['account'],
-        bt_from=datetime.fromisoformat(row['bt_from']) if row['bt_from'] else None,
-        bt_to=datetime.fromisoformat(row['bt_to']) if row['bt_to'] else None,
-        ilog_save=bool(row['ilog_save']),
-        profit=float(row['profit']),
-        trade_count=int(row['trade_count']),
-        end_positions=int(row['end_positions']),
-        end_positions_avgp=float(row['end_positions_avgp']),
-        metrics=orjson.loads(row['metrics']) if row['metrics'] else None
-    )
-
-#prevede dict radku zpatky na objekt vcetme retypizace
-def row_to_runarchive(row: dict) -> RunArchive:
-    return RunArchive(
-        id=row['runner_id'],
-        strat_id=row['strat_id'],
-        batch_id=row['batch_id'],
-        symbol=row['symbol'],
-        name=row['name'],
-        note=row['note'],
-        started=datetime.fromisoformat(row['started']) if row['started'] else None,
-        stopped=datetime.fromisoformat(row['stopped']) if row['stopped'] else None,
-        mode=row['mode'],
-        account=row['account'],
-        bt_from=datetime.fromisoformat(row['bt_from']) if row['bt_from'] else None,
-        bt_to=datetime.fromisoformat(row['bt_to']) if row['bt_to'] else None,
-        strat_json=orjson.loads(row['strat_json']),
-        settings=orjson.loads(row['settings']),
-        ilog_save=bool(row['ilog_save']),
-        profit=float(row['profit']),
-        trade_count=int(row['trade_count']),
-        end_positions=int(row['end_positions']),
-        end_positions_avgp=float(row['end_positions_avgp']),
-        metrics=orjson.loads(row['metrics']),
-        stratvars_toml=row['stratvars_toml']
-    )
+insert_queue = queue.Queue()

v2realbot/common/model.py

@@ -1,13 +1,16 @@
-from uuid import UUID
+from uuid import UUID, uuid4
 from alpaca.trading.enums import OrderSide, OrderStatus, TradeEvent,OrderType
 #from utils import AttributeDict
 from rich import print
 from typing import Any, Optional, List, Union
 from datetime import datetime, date
-from pydantic import BaseModel
-from v2realbot.enums.enums import Mode, Account
+from pydantic import BaseModel, Field
+from v2realbot.enums.enums import Mode, Account, SchedulerStatus, Moddus, Market
 from alpaca.data.enums import Exchange
 
+
+
+
 #models for server side datatables
 # Model for individual column data
 class ColumnData(BaseModel):
@@ -91,12 +94,12 @@ class TestList(BaseModel):
 class Trade(BaseModel):
     symbol: str
     timestamp: datetime
-    exchange: Optional[Union[Exchange, str]]
+    exchange: Optional[Union[Exchange, str]] = None
     price: float
     size: float
     id: int
-    conditions: Optional[List[str]]
-    tape: Optional[str]
+    conditions: Optional[List[str]] = None
+    tape: Optional[str] = None
 
 
 #persisted object in pickle
@@ -111,8 +114,20 @@ class StrategyInstance(BaseModel):
     close_rush: int = 0
     stratvars_conf: str
     add_data_conf: str
-    note: Optional[str] 
-    history: Optional[str]
+    note: Optional[str]  = None
+    history: Optional[str] = None
+
+    def __setstate__(self, state: dict[Any, Any]) -> None:
+        """
+        Hack to allow unpickling models stored from pydantic V1
+        """
+        state.setdefault("__pydantic_extra__", {})
+        state.setdefault("__pydantic_private__", {})
+
+        if "__pydantic_fields_set__" not in state:
+            state["__pydantic_fields_set__"] = state.get("__fields_set__")
+
+        super().__setstate__(state)
 
 class RunRequest(BaseModel):
     id: UUID
@@ -122,8 +137,8 @@ class RunRequest(BaseModel):
     debug: bool = False
     strat_json: Optional[str] = None
     ilog_save: bool = False
-    bt_from: datetime = None
-    bt_to: datetime = None
+    bt_from: Optional[datetime] = None
+    bt_to: Optional[datetime] = None
     #weekdays filter
     #pokud je uvedeny filtrujeme tyto dny
     weekdays_filter: Optional[list] = None
@@ -134,7 +149,34 @@ class RunRequest(BaseModel):
     cash: int = 100000
     skip_cache: Optional[bool] = False
 
-
+#Trida, která je nadstavbou runrequestu a pouzivame ji v scheduleru, je zde navic jen par polí
+class RunManagerRecord(BaseModel):
+    moddus: Moddus
+    id: UUID = Field(default_factory=uuid4) 
+    strat_id: UUID
+    symbol: Optional[str] = None
+    account: Account
+    mode: Mode
+    note: Optional[str] = None
+    ilog_save: bool = False
+    market: Optional[Market] = Market.US
+    bt_from: Optional[datetime] = None
+    bt_to: Optional[datetime] = None
+    #weekdays filter
+    #pokud je uvedeny filtrujeme tyto dny
+    weekdays_filter: Optional[list] = None #list of strings 0-6 representing days to run
+    #GENERATED ID v ramci runu, vaze vsechny runnery v batchovem behu
+    batch_id: Optional[str] = None
+    testlist_id: Optional[str] = None
+    start_time: str #time (HH:MM) that start function is called
+    stop_time: Optional[str] = None #time  (HH:MM) that stop function is called
+    status: SchedulerStatus
+    last_processed: Optional[datetime] = None
+    history: Optional[str] = None
+    valid_from: Optional[datetime] = None # US East time zone daetime
+    valid_to: Optional[datetime] = None # US East time zone daetime
+    runner_id: Optional[UUID] = None #last runner_id from scheduler after stratefy is started
+    strat_running: Optional[bool] = None #automatically updated field based on status of runner_id above, it is added by row_to_RunManagerRecord
 class RunnerView(BaseModel):
     id: UUID
     strat_id: UUID
@@ -164,10 +206,10 @@ class Runner(BaseModel):
     run_name: Optional[str] = None
     run_note: Optional[str] = None
     run_ilog_save: Optional[bool] = False
-    run_trade_count: Optional[int]
-    run_profit: Optional[float]
-    run_positions: Optional[int]
-    run_avgp: Optional[float]
+    run_trade_count: Optional[int] = None
+    run_profit: Optional[float] = None
+    run_positions: Optional[int] = None
+    run_avgp: Optional[float] = None
     run_strat_json: Optional[str] = None
     run_stopped: Optional[datetime] = None
     run_paused: Optional[datetime] = None   
@@ -201,41 +243,41 @@ class Bar(BaseModel):
     low: float
     close: float
     volume: float
-    trade_count: Optional[float]
-    vwap: Optional[float]
+    trade_count: Optional[float] = 0
+    vwap: Optional[float] = 0
 
 class Order(BaseModel):
     id: UUID
     submitted_at: datetime
-    filled_at: Optional[datetime]
-    canceled_at: Optional[datetime]
+    filled_at: Optional[datetime] = None
+    canceled_at: Optional[datetime] = None
     symbol: str
     qty: int
     status: OrderStatus
     order_type: OrderType
-    filled_qty: Optional[int]
-    filled_avg_price: Optional[float]
+    filled_qty: Optional[int] = None
+    filled_avg_price: Optional[float] = None
     side: OrderSide
-    limit_price: Optional[float]
+    limit_price: Optional[float] = None
 
 #entita pro kazdy kompletni FILL, je navazana na prescribed_trade 
 class TradeUpdate(BaseModel):
     event: Union[TradeEvent, str]
-    execution_id: Optional[UUID]
+    execution_id: Optional[UUID] = None
     order: Order
     timestamp: datetime
-    position_qty: Optional[float]
-    price: Optional[float]
-    qty: Optional[float]
-    value: Optional[float]
-    cash: Optional[float]
-    pos_avg_price: Optional[float]
-    profit: Optional[float]
-    profit_sum: Optional[float]
-    rel_profit: Optional[float]
-    rel_profit_cum: Optional[float]
-    signal_name: Optional[str]
-    prescribed_trade_id: Optional[str]
+    position_qty: Optional[float] = None
+    price: Optional[float] = None
+    qty: Optional[float] = None
+    value: Optional[float] = None
+    cash: Optional[float] = None
+    pos_avg_price: Optional[float] = None
+    profit: Optional[float] = None
+    profit_sum: Optional[float] = None
+    rel_profit: Optional[float] = None
+    rel_profit_cum: Optional[float] = None
+    signal_name: Optional[str] = None
+    prescribed_trade_id: Optional[str] = None
 
 
 class RunArchiveChange(BaseModel):
@@ -260,8 +302,7 @@ class RunArchive(BaseModel):
     bt_from: Optional[datetime] = None
     bt_to: Optional[datetime] = None
     strat_json: Optional[str] = None
-    ##bude decomiss, misto toho stratvars_toml
-    stratvars: Optional[dict] = None
+    transferables: Optional[dict] = None #varaibles that are transferrable to next run
     settings: Optional[dict] = None
     ilog_save: Optional[bool] = False
     profit: float = 0
@@ -291,6 +332,8 @@ class RunArchiveView(BaseModel):
     end_positions: int = 0
     end_positions_avgp: float = 0
     metrics: Union[dict, str] = None
+    batch_profit: float = 0  # Total profit for the batch - now calculated during query
+    batch_count: int = 0  # Count of runs in the batch - now calculated during query
 
 #same but with pagination
 class RunArchiveViewPagination(BaseModel):
@@ -301,7 +344,7 @@ class RunArchiveViewPagination(BaseModel):
 
 #trida pro ukladani historie stoplossy do ext_data
 class SLHistory(BaseModel):
-    id: Optional[UUID]
+    id: Optional[UUID] = None
     time: datetime
     sl_val: float
 
@@ -314,7 +357,7 @@ class RunArchiveDetail(BaseModel):
     indicators: List[dict]
     statinds: dict
     trades: List[TradeUpdate]
-    ext_data: Optional[dict]
+    ext_data: Optional[dict] = None
     
 
 class InstantIndicator(BaseModel):

v2realbot/common/transform.py

@@ -0,0 +1,87 @@
+from v2realbot.common.model import RunArchive, RunArchiveView, RunManagerRecord
+from datetime import datetime
+import orjson
+import v2realbot.controller.services as cs
+
+#prevede dict radku zpatky na objekt vcetme retypizace
+def row_to_runmanager(row: dict) -> RunManagerRecord:
+    is_running = cs.is_runner_running(row['runner_id']) if row['runner_id'] else False
+    res = RunManagerRecord(
+        moddus=row['moddus'],
+        id=row['id'],
+        strat_id=row['strat_id'],
+        symbol=row['symbol'],
+        mode=row['mode'],
+        account=row['account'],
+        note=row['note'],
+        ilog_save=bool(row['ilog_save']),
+        market=row['market'] if row['market'] is not None else None,
+        bt_from=datetime.fromisoformat(row['bt_from']) if row['bt_from'] else None,
+        bt_to=datetime.fromisoformat(row['bt_to']) if row['bt_to'] else None,
+        weekdays_filter=[int(x) for x in row['weekdays_filter'].split(',')] if row['weekdays_filter'] else [],
+        batch_id=row['batch_id'],
+        testlist_id=row['testlist_id'],
+        start_time=row['start_time'],
+        stop_time=row['stop_time'],
+        status=row['status'],
+        #last_started=zoneNY.localize(datetime.fromisoformat(row['last_started'])) if row['last_started'] else None,
+        last_processed=datetime.fromisoformat(row['last_processed']) if row['last_processed'] else None,
+        history=row['history'],
+        valid_from=datetime.fromisoformat(row['valid_from']) if row['valid_from'] else None,
+        valid_to=datetime.fromisoformat(row['valid_to']) if row['valid_to'] else None,
+        runner_id = row['runner_id'] if row['runner_id'] and is_running else None,  #runner_id is only present if it is running
+        strat_running = is_running) #cant believe this when called from separate process  as not current
+    return res
+
+#prevede dict radku zpatky na objekt vcetme retypizace
+def row_to_runarchiveview(row: dict) -> RunArchiveView:
+    a =  RunArchiveView(
+        id=row['runner_id'],
+        strat_id=row['strat_id'],
+        batch_id=row['batch_id'],
+        symbol=row['symbol'],
+        name=row['name'],
+        note=row['note'],
+        started=datetime.fromisoformat(row['started']) if row['started'] else None,
+        stopped=datetime.fromisoformat(row['stopped']) if row['stopped'] else None,
+        mode=row['mode'],
+        account=row['account'],
+        bt_from=datetime.fromisoformat(row['bt_from']) if row['bt_from'] else None,
+        bt_to=datetime.fromisoformat(row['bt_to']) if row['bt_to'] else None,
+        ilog_save=bool(row['ilog_save']),
+        profit=float(row['profit']),
+        trade_count=int(row['trade_count']),
+        end_positions=int(row['end_positions']),
+        end_positions_avgp=float(row['end_positions_avgp']),
+        metrics=orjson.loads(row['metrics']) if row['metrics'] else None,
+        batch_profit=int(row['batch_profit']) if row['batch_profit'] and row['batch_id'] else 0,
+        batch_count=int(row['batch_count']) if row['batch_count'] and row['batch_id'] else 0,
+    )
+    return a
+
+#prevede dict radku zpatky na objekt vcetme retypizace
+def row_to_runarchive(row: dict) -> RunArchive:
+    return RunArchive(
+        id=row['runner_id'],
+        strat_id=row['strat_id'],
+        batch_id=row['batch_id'],
+        symbol=row['symbol'],
+        name=row['name'],
+        note=row['note'],
+        started=datetime.fromisoformat(row['started']) if row['started'] else None,
+        stopped=datetime.fromisoformat(row['stopped']) if row['stopped'] else None,
+        mode=row['mode'],
+        account=row['account'],
+        bt_from=datetime.fromisoformat(row['bt_from']) if row['bt_from'] else None,
+        bt_to=datetime.fromisoformat(row['bt_to']) if row['bt_to'] else None,
+        strat_json=orjson.loads(row['strat_json']),
+        settings=orjson.loads(row['settings']),
+        ilog_save=bool(row['ilog_save']),
+        profit=float(row['profit']),
+        trade_count=int(row['trade_count']),
+        end_positions=int(row['end_positions']),
+        end_positions_avgp=float(row['end_positions_avgp']),
+        metrics=orjson.loads(row['metrics']),
+        stratvars_toml=row['stratvars_toml'],
+        transferables=orjson.loads(row['transferables']) if row['transferables'] else None
+    )

v2realbot/config.py

@@ -2,66 +2,41 @@ from alpaca.data.enums import DataFeed
 from v2realbot.enums.enums import Mode, Account, FillCondition
 from appdirs import user_data_dir
 from pathlib import Path
+import os
+from collections import defaultdict
+from dotenv import load_dotenv
+# Global flag to track if the ml module has been imported (solution for long import times of tensorflow)
+#the first occurence of using it will load it globally
+_ml_module_loaded = False
 
 #directory for generated images and basic reports
 MEDIA_DIRECTORY = Path(__file__).parent.parent.parent / "media"
 RUNNER_DETAIL_DIRECTORY = Path(__file__).parent.parent.parent / "runner_detail"
 
 #location of strat.log - it is used to fetch by gui
+LOG_PATH = Path(__file__).parent.parent
 LOG_FILE = Path(__file__).parent.parent / "strat.log"
+JOB_LOG_FILE = Path(__file__).parent.parent / "job.log"
+DOTENV_DIRECTORY = Path(__file__).parent.parent.parent
+ENV_FILE = DOTENV_DIRECTORY / '.env'
 
-#'0.0.0.0',
-#currently only prod server has acces to LIVE
-PROD_SERVER_HOSTNAMES = ['tradingeastcoast','David-MacBook-Pro.local'] #,'David-MacBook-Pro.local'
-TEST_SERVER_HOSTNAMES = ['tradingtest'] 
 
-#TODO vybrane dat do config db a managovat pres GUI
-
-#DEFAULT AGGREGATOR filter trades
-#NOTE pridana F - Inter Market Sweep Order - obcas vytvarela spajky
-AGG_EXCLUDED_TRADES = ['C','O','4','B','7','V','P','W','U','Z','F']
-
-OFFLINE_MODE = False
-
-# ilog lvls = 0,1 - 0 debug, 1 info
-ILOG_SAVE_LEVEL_FROM  = 1
-
-#minimalni vzdalenost mezi trady, kterou agregator pousti pro CBAR(0.001 - blokuje mensi nez 1ms)
-GROUP_TRADES_WITH_TIMESTAMP_LESS_THAN = 0.003
-#normalized price for tick 0.01
-NORMALIZED_TICK_BASE_PRICE = 30.00
-LOG_RUNNER_EVENTS = False
-#no print in console
-QUIET_MODE = True
-#how many consecutive trades with the fill price are necessary for LIMIT fill to happen in backtesting
-#0 - optimistic, every knot high will fill the order
-#N - N consecutive trades required
-#not impl.yet
-#minimum is 1, na alpace live to vetsinou vychazi 7-8 u BAC, je to hodne podobne tomu, nez je cena překonaná pul centu. tzn. 7-8 a nebo FillCondition.SLOW
-BT_FILL_CONS_TRADES_REQUIRED = 2
-#during bt trade execution logs X-surrounding trades of the one that triggers the fill
-BT_FILL_LOG_SURROUNDING_TRADES = 10
-#fill condition for limit order in bt
-# fast - price has to be equal or bigger <=
-# slow - price has to be bigger <
-BT_FILL_CONDITION_BUY_LIMIT = FillCondition.SLOW
-BT_FILL_CONDITION_SELL_LIMIT = FillCondition.SLOW
-#TBD TODO not implemented yet
-BT_FILL_PRICE_MARKET_ORDER_PREMIUM = 0.005
-#backend counter of api requests
-COUNT_API_REQUESTS = False
 #stratvars that cannot be changed in gui
 STRATVARS_UNCHANGEABLES = ['pendingbuys', 'blockbuy', 'jevylozeno', 'limitka']
-DATA_DIR = user_data_dir("v2realbot")
+DATA_DIR = user_data_dir("v2realbot", False)
 MODEL_DIR = Path(DATA_DIR)/"models"
 #BT DELAYS
 #profiling
 PROFILING_NEXT_ENABLED = False
 PROFILING_OUTPUT_DIR = DATA_DIR
 
-#FILL CONFIGURATION CLASS FOR BACKTESTING
+#NALOADUJEME DOTENV ENV VARIABLES
+if load_dotenv(ENV_FILE, verbose=True) is False:
+    print(f"Error loading.env file {ENV_FILE}. Now depending on ENV VARIABLES set externally.")
+else:
+    print(f"Loaded env variables from file {ENV_FILE}")
 
-#WIP 
+#WIP - FILL CONFIGURATION CLASS FOR BACKTESTING
 class BT_FILL_CONF:
     """"
     Trida pro konfiguraci backtesting fillu pro dany symbol, pokud neexistuje tak fallback na obecny viz vyse-
@@ -75,24 +50,6 @@ class BT_FILL_CONF:
         self.BT_FILL_CONDITION_SELL_LIMIT=BT_FILL_CONDITION_SELL_LIMIT
         self.BT_FILL_PRICE_MARKET_ORDER_PREMIUM=BT_FILL_PRICE_MARKET_ORDER_PREMIUM
 
-
-""""
-LATENCY DELAYS for LIVE eastcoast
-.000 trigger - last_trade_time (.4246266)
-+.020 vstup do strategie a BUY (.444606)
-+.023 submitted (.469198)
-+.008    filled (.476695552)
-+.023   fill not(.499888)
-"""
-#TODO změnit názvy delay promennych vystizneji a obecneji
-class BT_DELAYS:
-    trigger_to_strat: float = 0.020
-    strat_to_sub: float = 0.023
-    sub_to_fill: float = 0.008
-    fill_to_not: float = 0.023
-    #doplnit dle live
-    limit_order_offset: float = 0
- 
 class Keys:
     def __init__(self, api_key, secret_key, paper, feed) -> None:
         self.API_KEY = api_key
@@ -101,7 +58,8 @@ class Keys:
         self.FEED = feed
 
 # podle modu (PAPER, LIVE) vrati objekt
-# obsahujici klice pro pripojeni k alpace
+# obsahujici klice pro pripojeni k alpace - používá se pro Trading API a order updates websockets (pristupy relevantni per strategie)
+#pro real time data se bere LIVE_DATA_API_KEY, LIVE_DATA_SECRET_KEY, LIVE_DATA_FEED nize - jelikoz jde o server wide nastaveni
 def get_key(mode: Mode, account: Account):
     if mode not in [Mode.PAPER, Mode.LIVE]:
         print("has to be LIVE or PAPER only")
@@ -120,36 +78,85 @@ def get_key(mode: Mode, account: Account):
 #strategy instance main loop heartbeat
 HEARTBEAT_TIMEOUT=5
 
-WEB_API_KEY="david"
+WEB_API_KEY=os.environ.get('WEB_API_KEY')
 
 #PRIMARY PAPER
-ACCOUNT1_PAPER_API_KEY = 'PKGGEWIEYZOVQFDRY70L'
-ACCOUNT1_PAPER_SECRET_KEY = 'O5Kt8X4RLceIOvM98i5LdbalItsX7hVZlbPYHy8Y'
+ACCOUNT1_PAPER_API_KEY = os.environ.get('ACCOUNT1_PAPER_API_KEY')
+ACCOUNT1_PAPER_SECRET_KEY = os.environ.get('ACCOUNT1_PAPER_SECRET_KEY')
 ACCOUNT1_PAPER_MAX_BATCH_SIZE = 1
 ACCOUNT1_PAPER_PAPER = True
-ACCOUNT1_PAPER_FEED = DataFeed.SIP
+#ACCOUNT1_PAPER_FEED = DataFeed.SIP
+
+# Load the data feed type from environment variable
+data_feed_type_str = os.environ.get('ACCOUNT1_PAPER_FEED', 'iex')  # Default to 'sip' if not set
+
+# Convert the string to DataFeed enum
+try:
+    ACCOUNT1_PAPER_FEED = DataFeed(data_feed_type_str)
+except ValueError:
+    # Handle the case where the environment variable does not match any enum member
+    print(f"Invalid data feed type: {data_feed_type_str} in ACCOUNT1_PAPER_FEED defaulting to 'iex'")
+    ACCOUNT1_PAPER_FEED = DataFeed.SIP
 
 #PRIMARY LIVE
-ACCOUNT1_LIVE_API_KEY = 'AKB5HD32LPDZC9TPUWJT'
-ACCOUNT1_LIVE_SECRET_KEY = 'Xq1wPSNOtwmlMTAd4cEmdKvNDgfcUYfrOaCccaAs'
+ACCOUNT1_LIVE_API_KEY = os.environ.get('ACCOUNT1_LIVE_API_KEY')
+ACCOUNT1_LIVE_SECRET_KEY = os.environ.get('ACCOUNT1_LIVE_SECRET_KEY')
 ACCOUNT1_LIVE_MAX_BATCH_SIZE = 1
 ACCOUNT1_LIVE_PAPER = False
-ACCOUNT1_LIVE_FEED = DataFeed.SIP
+#ACCOUNT1_LIVE_FEED = DataFeed.SIP
 
+# Load the data feed type from environment variable
+data_feed_type_str = os.environ.get('ACCOUNT1_LIVE_FEED', 'iex')  # Default to 'sip' if not set
+
+# Convert the string to DataFeed enum
+try:
+    ACCOUNT1_LIVE_FEED = DataFeed(data_feed_type_str)
+except ValueError:
+    # Handle the case where the environment variable does not match any enum member
+    print(f"Invalid data feed type: {data_feed_type_str} in ACCOUNT1_LIVE_FEED defaulting to 'iex'")
+    ACCOUNT1_LIVE_FEED = DataFeed.IEX
 
 #SECONDARY PAPER - Martin
-ACCOUNT2_PAPER_API_KEY = 'PKPDTCQLNHCBC2D9GQFB'
-ACCOUNT2_PAPER_SECRET_KEY = 'c1Z2V0gBleQmwHYCreqqTs45Jy33RqPGrofuSayz'
+ACCOUNT2_PAPER_API_KEY = os.environ.get('ACCOUNT2_PAPER_API_KEY')
+ACCOUNT2_PAPER_SECRET_KEY = os.environ.get('ACCOUNT2_PAPER_SECRET_KEY')
 ACCOUNT2_PAPER_MAX_BATCH_SIZE = 1
 ACCOUNT2_PAPER_PAPER = True
-ACCOUNT2_PAPER_FEED = DataFeed.IEX
+#ACCOUNT2_PAPER_FEED = DataFeed.IEX
 
-# #SECONDARY PAPER
-# ACCOUNT2_PAPER_API_KEY = 'PK0OQHZG03PUZ1SC560V'
-# ACCOUNT2_PAPER_SECRET_KEY = 'cTglhm7kwRcZfFT27fQWz31sXaxadzQApFDW6Lat'
-# ACCOUNT2_PAPER_MAX_BATCH_SIZE = 1
-# ACCOUNT2_PAPER_PAPER = True
-# ACCOUNT2_PAPER_FEED = DataFeed.IEX
+# Load the data feed type from environment variable
+data_feed_type_str = os.environ.get('ACCOUNT2_PAPER_FEED', 'iex')  # Default to 'sip' if not set
+
+# Convert the string to DataFeed enum
+try:
+    ACCOUNT2_PAPER_FEED = DataFeed(data_feed_type_str)
+except ValueError:
+    # Handle the case where the environment variable does not match any enum member
+    print(f"Invalid data feed type: {data_feed_type_str} in ACCOUNT2_PAPER_FEED defaulting to 'iex'")
+    ACCOUNT2_PAPER_FEED = DataFeed.IEX
+
+
+#SECONDARY LIVE - Martin
+# ACCOUNT2_LIVE_API_KEY = os.environ.get('ACCOUNT2_LIVE_API_KEY')
+# ACCOUNT2_LIVE_SECRET_KEY = os.environ.get('ACCOUNT2_LIVE_SECRET_KEY')
+# ACCOUNT2_LIVE_MAX_BATCH_SIZE = 1
+# ACCOUNT2_LIVE_PAPER = True
+# #ACCOUNT2_LIVE_FEED = DataFeed.IEX
+
+# # Load the data feed type from environment variable
+# data_feed_type_str = os.environ.get('ACCOUNT2_LIVE_FEED', 'iex')  # Default to 'sip' if not set
+
+# # Convert the string to DataFeed enum
+# try:
+#     ACCOUNT2_LIVE_FEED = DataFeed(data_feed_type_str)
+# except ValueError:
+#     # Handle the case where the environment variable does not match any enum member
+#     print(f"Invalid data feed type: {data_feed_type_str} in ACCOUNT2_LIVE_FEED defaulting to 'iex'")
+#     ACCOUNT2_LIVE_FEED = DataFeed.IEX
+
+#zatim jsou LIVE_DATA nastaveny jako z account1_paper
+LIVE_DATA_API_KEY = ACCOUNT1_PAPER_API_KEY
+LIVE_DATA_SECRET_KEY = ACCOUNT1_PAPER_SECRET_KEY
+#LIVE_DATA_FEED je nastaveny v config_handleru
 
 class KW:
     activate: str = "activate"

v2realbot/controller/configs.py

@@ -0,0 +1,112 @@
+
+import v2realbot.common.db as db
+from v2realbot.common.model import ConfigItem
+import v2realbot.utils.config_handler as ch
+
+# region CONFIG db services
+#TODO vytvorit modul pro dotahovani z pythonu (get_from_config(var_name, def_value) {)- stejne jako v js 
+#TODO zvazit presunuti do TOML z JSONu
+def get_all_config_items():
+    conn = db.pool.get_connection()
+    try:
+        cursor = conn.cursor()
+        cursor.execute('SELECT id, item_name, json_data FROM config_table')
+        config_items = [{"id": row[0], "item_name": row[1], "json_data": row[2]} for row in cursor.fetchall()]
+    finally:
+        db.pool.release_connection(conn)
+    return 0, config_items
+
+# Function to get a config item by ID
+def get_config_item_by_id(item_id):
+    conn = db.pool.get_connection()
+    try:
+        cursor = conn.cursor()
+        cursor.execute('SELECT item_name, json_data FROM config_table WHERE id = ?', (item_id,))
+        row = cursor.fetchone()
+    finally:
+        db.pool.release_connection(conn)
+    if row is None:
+        return -2, "not found"
+    else:
+        return 0, {"item_name": row[0], "json_data": row[1]}
+
+# Function to get a config item by ID
+def get_config_item_by_name(item_name):
+    #print(item_name)
+    conn = db.pool.get_connection()
+    try:
+        cursor = conn.cursor()
+        query = f"SELECT item_name, json_data FROM config_table WHERE item_name = '{item_name}'"
+        #print(query)
+        cursor.execute(query)
+        row = cursor.fetchone()
+        #print(row)
+    finally:
+        db.pool.release_connection(conn)
+    if row is None:
+        return -2, "not found"
+    else:
+        return 0, {"item_name": row[0], "json_data": row[1]}
+
+# Function to create a new config item
+def create_config_item(config_item: ConfigItem):
+    conn = db.pool.get_connection()
+    try:
+        try:
+            cursor = conn.cursor()
+            cursor.execute('INSERT INTO config_table (item_name, json_data) VALUES (?, ?)', (config_item.item_name, config_item.json_data))
+            item_id = cursor.lastrowid
+            conn.commit()
+            print(item_id)
+        finally:
+            db.pool.release_connection(conn)
+
+        return 0, {"id": item_id, "item_name":config_item.item_name, "json_data":config_item.json_data}
+    except Exception as e:
+        return -2, str(e)
+
+# Function to update a config item by ID
+def update_config_item(item_id, config_item: ConfigItem):
+    conn = db.pool.get_connection()
+    try:
+        try:
+            cursor = conn.cursor()
+            cursor.execute('UPDATE config_table SET item_name = ?, json_data = ? WHERE id = ?', (config_item.item_name, config_item.json_data, item_id))
+            conn.commit()
+
+            #refresh active item je zatím řešena takto natvrdo při updatu položky "active_profile" a při startu aplikace
+            if config_item.item_name == "active_profile":
+                ch.config_handler.activate_profile()
+        finally:
+            db.pool.release_connection(conn)
+        return 0, {"id": item_id, **config_item.dict()}
+    except Exception as e:
+        return -2, str(e)
+    
+# Function to delete a config item by ID
+def delete_config_item(item_id):
+    conn = db.pool.get_connection()
+    try:
+        cursor = conn.cursor()
+        cursor.execute('DELETE FROM config_table WHERE id = ?', (item_id,))
+        conn.commit()
+    finally:
+       db.pool.release_connection(conn) 
+    return 0, {"id": item_id}
+
+# endregion
+
+#Example of using config directive
+# config_directive = "overrides"
+# ret, res = get_config_item_by_name(config_directive)
+# if ret < 0:
+#     print(f"CONFIG OVERRIDE {config_directive} Error {res}")
+# else:
+#     config = orjson.loads(res["json_data"])
+
+#     print("OVERRIDN CFG:", config)
+#     for key, value in config.items():
+#         if hasattr(cfg, key):
+#             print(f"Overriding {key} with {value}")
+#             setattr(cfg, key, value)
+

v2realbot/controller/run_manager.py

@@ -0,0 +1,463 @@
+from typing import Any, List, Tuple
+from uuid import UUID, uuid4
+from v2realbot.common.model import RunManagerRecord, StrategyInstance, RunDay, StrategyInstance, Runner, RunRequest, RunArchive, RunArchiveView, RunArchiveViewPagination, RunArchiveDetail, RunArchiveChange, Bar, TradeEvent, TestList, Intervals, ConfigItem, InstantIndicator, DataTablesRequest
+from v2realbot.utils.utils import validate_and_format_time, AttributeDict, zoneNY, zonePRG, safe_get, dict_replace_value, Store, parse_toml_string, json_serial, is_open_hours, send_to_telegram, concatenate_weekdays, transform_data
+from v2realbot.utils.ilog import delete_logs
+from v2realbot.common.PrescribedTradeModel import Trade, TradeDirection, TradeStatus, TradeStoplossType
+from datetime import datetime
+from v2realbot.loader.trade_offline_streamer import Trade_Offline_Streamer
+from threading import Thread, current_thread, Event, enumerate
+from v2realbot.config import STRATVARS_UNCHANGEABLES, ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, ACCOUNT1_LIVE_API_KEY, ACCOUNT1_LIVE_SECRET_KEY, DATA_DIR,MEDIA_DIRECTORY, RUNNER_DETAIL_DIRECTORY
+import importlib
+from alpaca.trading.requests import GetCalendarRequest
+from alpaca.trading.client import TradingClient
+#from alpaca.trading.models import Calendar
+from queue import Queue
+from tinydb import TinyDB, Query, where
+from tinydb.operations import set
+import orjson
+import numpy as np
+from rich import print
+import pandas as pd
+from traceback import format_exc
+from datetime import timedelta, time
+from threading import Lock
+import v2realbot.common.db as db
+import v2realbot.common.transform as tr
+from sqlite3 import OperationalError, Row
+import v2realbot.strategyblocks.indicators.custom as ci
+from v2realbot.strategyblocks.inits.init_indicators import initialize_dynamic_indicators
+from v2realbot.strategyblocks.indicators.indicators_hub import populate_dynamic_indicators
+from v2realbot.interfaces.backtest_interface import BacktestInterface
+import os
+import v2realbot.reporting.metricstoolsimage as mt
+import gzip
+import os
+import msgpack
+import v2realbot.controller.services as cs
+import v2realbot.scheduler.ap_scheduler as aps
+
+# Functions for your 'run_manager' table
+
+# CREATE TABLE "run_manager" (
+# 	"moddus"	TEXT NOT NULL,
+# 	"id"	varchar(32),
+# 	"strat_id"	varchar(32) NOT NULL,
+# 	"symbol"	TEXT,
+# 	"account"	TEXT NOT NULL,
+# 	"mode"	TEXT NOT NULL,
+# 	"note"	TEXT,
+# 	"ilog_save"	BOOLEAN,
+# 	"bt_from"	TEXT,
+# 	"bt_to"	TEXT,
+# 	"weekdays_filter"	TEXT,
+# 	"batch_id"	TEXT,
+# 	"start_time"	TEXT NOT NULL,
+# 	"stop_time"	TEXT NOT NULL,
+# 	"status"	TEXT NOT NULL,
+# 	"last_processed"	TEXT,
+# 	"history"	TEXT,
+# 	"valid_from"	TEXT,
+# 	"valid_to"	TEXT,
+# 	"testlist_id"	TEXT,
+# 	"runner_id"	varchar2(32),
+# 	PRIMARY KEY("id")
+# )
+
+# CREATE INDEX idx_moddus ON run_manager (moddus);
+# CREATE INDEX idx_status ON run_manager (status);
+# CREATE INDEX idx_status_moddus ON run_manager (status, moddus);
+# CREATE INDEX idx_valid_from_to ON run_manager (valid_from, valid_to);
+# CREATE INDEX idx_stopped_batch_id ON runner_header (stopped, batch_id); 
+# CREATE INDEX idx_search_value ON runner_header (strat_id, batch_id);
+
+
+##weekdays are stored as comma separated values
+# Fetching (assume 'weekdays' field is a comma-separated string)
+# weekday_str = record['weekdays']
+# weekdays = [int(x) for x in weekday_str.split(',')]
+
+# # ... logic to check whether today's weekday is in 'weekdays'
+
+# # Storing 
+# weekdays = [1, 2, 5]  # Example 
+# weekday_str = ",".join(str(x) for x in weekdays)
+# update_data = {'weekdays': weekday_str} 
+# # ... use in an SQL UPDATE statement
+
+        # for row in records:
+        #     row['weekdays_filter'] = [int(x) for x in row['weekdays_filter'].split(',')] if row['weekdays_filter'] else []
+
+
+#get stratin info return
+# strat : StrategyInstance = None
+# result, strat = cs.get_stratin("625760ac-6376-47fa-8989-1e6a3f6ab66a")
+# if result == 0:
+#     print(strat)
+# else:
+#     print("Error:", strat)
+
+
+# Fetch all
+#result, records = fetch_all_run_manager_records()
+
+#TODO zvazit rozsireni vystupu o strat_status (running/stopped)
+
+
+def fetch_all_run_manager_records() -> list[RunManagerRecord]:
+    conn = db.pool.get_connection()
+    try:
+        conn.row_factory = Row
+        cursor = conn.cursor()
+        cursor.execute('SELECT * FROM run_manager')
+        rows = cursor.fetchall()
+        results = []
+        #Transform row to object
+        for row in rows:
+            #add transformed object into result list
+            results.append(tr.row_to_runmanager(row))
+
+        return 0, results
+    finally:
+        conn.row_factory = None
+        db.pool.release_connection(conn)
+
+# Fetch by strategy_id
+# result, record = fetch_run_manager_record_by_id('625760ac-6376-47fa-8989-1e6a3f6ab66a')
+def fetch_run_manager_record_by_id(strategy_id) -> RunManagerRecord:
+    conn = db.pool.get_connection()
+    try:
+        conn.row_factory = Row
+        cursor = conn.cursor()
+        cursor.execute('SELECT * FROM run_manager WHERE id = ?', (str(strategy_id),))
+        row = cursor.fetchone()
+        if row is None:
+            return -2, "not found"
+        else:
+            return 0, tr.row_to_runmanager(row)
+
+    except Exception as e:
+        print("ERROR while fetching all records:", str(e) + format_exc())
+        return -2, str(e) + format_exc()
+    finally:
+        conn.row_factory = None
+        db.pool.release_connection(conn)
+
+def add_run_manager_record(new_record: RunManagerRecord):
+    #validation/standardization of time
+    new_record.start_time = validate_and_format_time(new_record.start_time)
+    if new_record.start_time is None:
+        return -2, f"Invalid start_time format {new_record.start_time}"
+
+    if new_record.stop_time is not None:
+        new_record.stop_time = validate_and_format_time(new_record.stop_time)
+        if new_record.stop_time is None:
+            return -2, f"Invalid stop_time format {new_record.stop_time}"
+
+    if new_record.batch_id is None:
+        new_record.batch_id = str(uuid4())[:8]
+
+    conn = db.pool.get_connection()
+    try:
+
+        strat : StrategyInstance = None
+        result, strat = cs.get_stratin(id=str(new_record.strat_id))
+        if result == 0:
+            new_record.symbol = strat.symbol
+        else:
+            return -1, f"Strategy {new_record.strat_id} not found"
+
+        cursor = conn.cursor()
+
+        # Construct a suitable INSERT query based on your RunManagerRecord fields
+        insert_query = """
+            INSERT INTO run_manager (moddus, id, strat_id, symbol,account, mode, note,ilog_save,
+                                    market, bt_from, bt_to, weekdays_filter, batch_id,
+                                    start_time, stop_time, status, last_processed,
+                                    history, valid_from, valid_to, testlist_id)
+            VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?,?) 
+        """
+        values = [
+            new_record.moddus, str(new_record.id), str(new_record.strat_id), new_record.symbol, new_record.account, new_record.mode, new_record.note,
+            int(new_record.ilog_save), new_record.market,
+            new_record.bt_from.isoformat() if new_record.bt_from is not None else None,
+            new_record.bt_to.isoformat() if new_record.bt_to is not None else None,
+            ",".join(str(x) for x in new_record.weekdays_filter) if new_record.weekdays_filter else None,
+            new_record.batch_id, new_record.start_time, 
+            new_record.stop_time, new_record.status,
+            new_record.last_processed.isoformat() if new_record.last_processed is not None else None,
+            new_record.history,
+            new_record.valid_from.isoformat() if new_record.valid_from is not None else None,
+            new_record.valid_to.isoformat() if new_record.valid_to is not None else None,
+            new_record.testlist_id
+        ]
+        db.execute_with_retry(cursor, insert_query, values)
+        conn.commit()
+
+        #Add APS scheduler job refresh
+        res, result = aps.initialize_jobs()
+        if res < 0:
+            return -2, f"Error initializing jobs: {res} {result}"
+
+        return 0, new_record.id  # Assuming success, you might return something more descriptive
+    except Exception as e:
+        print("ERROR while adding record:", str(e) + format_exc())
+        return -2, str(e) + format_exc()
+    finally:
+        db.pool.release_connection(conn)
+
+# Update (example)
+# update_data = {'last_started': '2024-02-13 10:35:00'}  
+# result, message = update_run_manager_record('625760ac-6376-47fa-8989-1e6a3f6ab66a', update_data)
+def update_run_manager_record(record_id, updated_record: RunManagerRecord):
+    #validation/standardization of time
+    updated_record.start_time = validate_and_format_time(updated_record.start_time)
+    if updated_record.start_time is None:
+        return -2, f"Invalid start_time format {updated_record.start_time}"
+
+    if updated_record.stop_time is not None:
+        updated_record.stop_time = validate_and_format_time(updated_record.stop_time)
+        if updated_record.stop_time is None:
+            return -2, f"Invalid stop_time format {updated_record.stop_time}"
+
+    conn = db.pool.get_connection()
+    try:
+        cursor = conn.cursor()
+
+        #strategy lookup check, if strategy still exists
+        strat : StrategyInstance = None
+        result, strat = cs.get_stratin(id=str(updated_record.strat_id))
+        if result == 0:
+            updated_record.symbol = strat.symbol
+        else:
+            return -1, f"Strategy {updated_record.strat_id} not found"
+
+        #remove values with None, so they are not updated
+        #updated_record_dict = updated_record.dict(exclude_none=True)
+
+        # Construct update query and handle weekdays conversion
+        update_query = 'UPDATE run_manager SET '
+        update_params = []
+        for key, value in updated_record.dict().items():  # Iterate over model attributes
+            if key in ['id', 'strat_running']:  # Skip updating the primary key
+                continue
+            update_query += f"{key} = ?, "
+            if key == "ilog_save":
+                value = int(value)
+            elif key in ["strat_id", "runner_id"]:
+                value = str(value) if value else None
+            elif key == "weekdays_filter":
+                value = ",".join(str(x) for x in value) if value else None
+            elif key in ['valid_from', 'valid_to', 'bt_from', 'bt_to', 'last_processed']:
+                value = value.isoformat() if value else None
+            update_params.append(value)
+        # if 'weekdays_filter' in updated_record.dict():  
+        #     updated_record.weekdays_filter = ",".join(str(x) for x in updated_record.weekdays_filter)
+        update_query = update_query[:-2]  # Remove trailing comma and space
+        update_query += ' WHERE id = ?'
+        update_params.append(str(record_id))
+
+        db.execute_with_retry(cursor, update_query, update_params)
+        #cursor.execute(update_query, update_params)
+        conn.commit()
+
+        #Add APS scheduler job refresh
+        res, result = aps.initialize_jobs()
+        if res < 0:
+            return -2, f"Error initializing jobs: {res} {result}"
+
+    except Exception as e:
+        print("ERROR while updating record:", str(e) + format_exc())
+        return -2, str(e) + format_exc()
+    finally:
+        db.pool.release_connection(conn)
+    return 0, record_id
+
+# result, message = delete_run_manager_record('625760ac-6376-47fa-8989-1e6a3f6ab66a')
+def delete_run_manager_record(record_id):
+    conn = db.pool.get_connection()
+    try:
+        cursor = conn.cursor()
+        db.execute_with_retry(cursor, 'DELETE FROM run_manager WHERE id = ?', (str(record_id),))
+        #cursor.execute('DELETE FROM run_manager WHERE id = ?', (str(strategy_id),))
+        conn.commit()
+    except Exception as e:
+        print("ERROR while deleting record:", str(e) + format_exc())
+        return -2, str(e) + format_exc()
+    finally:
+        db.pool.release_connection(conn)
+    return 0, record_id
+
+def fetch_scheduled_candidates_for_start_and_stop(market_datetime_now, market) -> tuple[int, dict]:
+    """
+    Fetches all active records from the 'run_manager' table where the mode is 'schedule'. It checks if the current 
+    time in the America/New_York timezone is within the operational intervals specified by 'start_time' and 'stop_time' 
+    for each record. This function is designed to correctly handle scenarios where the operational interval crosses 
+    midnight, as well as intervals contained within a single day.
+
+    The function localizes 'valid_from', 'valid_to', 'start_time', and 'stop_time' using the 'zoneNY' timezone object 
+    for accurate comparison with the current time. 
+
+    Parameters:
+        market_datetime_now (datetime): The current date and time in the America/New_York timezone.
+        market (str): The market identifier.
+
+    Returns:
+        Tuple[int, dict]: A tuple where the first element is a status code (0 for success, -2 for error), and the 
+        second element is a dictionary. This dictionary has keys 'start' and 'stop', each containing a list of 
+        RunManagerRecord objects meeting the respective criteria. If an error occurs, the second element is a 
+        descriptive error message.
+
+    Note:
+        - This function assumes that the 'zoneNY' pytz timezone object is properly defined and configured to represent 
+          the America/New York timezone.
+        - It also assumes that the 'run_manager' table exists in the database with the required columns.
+        - 'start_time' and 'stop_time' are expected to be strings representing times in 24-hour format.
+        - If 'valid_from', 'valid_to', 'start_time', or 'stop_time' are NULL in the database, they are considered as 
+          having unlimited boundaries.
+    
+    Pozor: je jeste jeden okrajovy pripad, kdy by to nemuselo zafungovat: kdyby casy byly nastaveny pro
+    beh strategie pres pulnoc, ale zapla by se pozdeji az po pulnoci
+    (https://chat.openai.com/c/3c77674a-8a2c-45aa-afbd-ab140f473e07)
+
+    """
+    conn = db.pool.get_connection()
+    try:
+        conn.row_factory = Row
+        cursor = conn.cursor()
+
+        # Get current datetime in America/New York timezone
+        market_datetime_now_str = market_datetime_now.strftime('%Y-%m-%d %H:%M:%S')
+        current_time_str = market_datetime_now.strftime('%H:%M')
+        print("current_market_datetime_str:", market_datetime_now_str)
+        print("current_time_str:", current_time_str)
+
+        # Select also supports scenarios where strategy runs overnight
+        # SQL query to fetch records with active status and date constraints for both start and stop times
+        query = """
+        SELECT *,
+        CASE 
+            WHEN start_time <= stop_time AND (? >= start_time AND ? < stop_time) OR
+                 start_time > stop_time AND (? >= start_time OR ? < stop_time) THEN 1 
+            ELSE 0 
+        END as is_start_time,
+        CASE 
+            WHEN start_time <= stop_time AND (? >= stop_time OR ? < start_time) OR
+                 start_time > stop_time AND (? >= stop_time AND ? < start_time) THEN 1 
+            ELSE 0 
+        END as is_stop_time
+        FROM run_manager 
+        WHERE status = 'active' AND moddus = 'schedule' AND
+        ((valid_from IS NULL OR strftime('%Y-%m-%d %H:%M:%S', valid_from) <= ?) AND 
+         (valid_to IS NULL OR strftime('%Y-%m-%d %H:%M:%S', valid_to) >= ?))
+        """
+        cursor.execute(query, (current_time_str, current_time_str, current_time_str, current_time_str, 
+                               current_time_str, current_time_str, current_time_str, current_time_str,
+                               market_datetime_now_str, market_datetime_now_str))
+        rows = cursor.fetchall()
+
+        start_candidates = []
+        stop_candidates = []
+        for row in rows:
+            run_manager_record = tr.row_to_runmanager(row)
+            if row['is_start_time']:
+                start_candidates.append(run_manager_record)
+            if row['is_stop_time']:
+                stop_candidates.append(run_manager_record)
+
+        results = {'start': start_candidates, 'stop': stop_candidates}
+
+        return 0, results
+    except Exception as e:
+        msg_err = f"ERROR while fetching records for start and stop times with datetime {market_datetime_now_str}: {str(e)}  {format_exc()}"
+        print(msg_err)
+        return -2, msg_err  
+    finally:
+        conn.row_factory = None
+        db.pool.release_connection(conn)
+
+
+def fetch_startstop_scheduled_candidates(market_datetime_now, time_check, market = "US") -> tuple[int, list[RunManagerRecord]]:
+    """
+    Fetches all active records from the 'run_manager' table where moddus is schedule, the current date and time 
+    in the America/New_York timezone falls between the 'valid_from' and 'valid_to' datetime 
+    fields, and either 'start_time' or 'stop_time' matches the specified condition with the current time.
+    If 'valid_from', 'valid_to', or the time column ('start_time'/'stop_time') are NULL, they are considered 
+    as having unlimited boundaries.
+
+    The function localizes the 'valid_from', 'valid_to', and the time column times using the 'zoneNY' 
+    timezone object for accurate comparison with the current time. 
+
+    Parameters:
+        market_datetime_now (datetime): Current datetime in the market timezone.
+        market (str): The market for which to fetch candidates.
+        time_check (str): Either 'start' or 'stop', indicating which time condition to check.
+
+    Returns:
+        Tuple[int, list[RunManagerRecord]]: A tuple where the first element is a status code 
+        (0 for success, -2 for error), and the second element is a list of RunManagerRecord 
+        objects meeting the criteria. If an error occurs, the second element is a descriptive 
+        error message.
+
+    Note:
+        This function assumes that the 'zoneNY' pytz timezone object is properly defined and 
+        configured to represent the America/New York timezone. It also assumes that the 
+        'run_manager' table exists in the database with the columns as described in the 
+        provided schema.
+    """
+    if time_check not in ['start', 'stop']:
+        return -2, "Invalid time_check parameter. Must be 'start' or 'stop'."
+
+    conn = db.pool.get_connection()
+    try:
+        conn.row_factory = Row
+        cursor = conn.cursor()
+
+        # Get current datetime in America/New York timezone
+        market_datetime_now_str = market_datetime_now.strftime('%Y-%m-%d %H:%M:%S')
+        current_time_str = market_datetime_now.strftime('%H:%M')
+        print("current_market_datetime_str:", market_datetime_now_str)
+        print("current_time_str:", current_time_str)
+
+        # SQL query to fetch records with active status, date constraints, and time condition
+        time_column = 'start_time' if time_check == 'start' else 'stop_time'
+        query = f"""
+        SELECT * FROM run_manager 
+        WHERE status = 'active' AND moddus = 'schedule' AND
+        ((valid_from IS NULL OR strftime('%Y-%m-%d %H:%M:%S', valid_from) <= ?) AND 
+        (valid_to IS NULL OR strftime('%Y-%m-%d %H:%M:%S', valid_to) >= ?)) AND
+        ({time_column} IS NULL OR {time_column} <= ?)
+        """
+        cursor.execute(query, (market_datetime_now_str, market_datetime_now_str, current_time_str))
+        rows = cursor.fetchall()
+        results = [tr.row_to_runmanager(row) for row in rows]
+
+        return 0, results
+    except Exception as e:
+        msg_err = f"ERROR while fetching records based on {time_check} time with datetime {market_datetime_now_str}: {str(e)}  {format_exc()}"
+        print(msg_err)
+        return -2, msg_err  
+    finally:
+        conn.row_factory = None
+        db.pool.release_connection(conn)
+
+
+if __name__ == "__main__":
+    res, sada = fetch_startstop_scheduled_candidates(datetime.now().astimezone(zoneNY), "start")
+    if res == 0:
+        print(sada)
+    else:
+        print("Error:", sada)
+
+# from apscheduler.schedulers.background import BackgroundScheduler
+# import time
+
+# def print_hello():
+#     print("Hello")
+
+# def schedule_job():
+#     scheduler = BackgroundScheduler()
+#     scheduler.add_job(print_hello, 'interval', seconds=10)
+#     scheduler.start()
+
+# schedule_job()

v2realbot/controller/services.py

@@ -3,7 +3,7 @@ from uuid import UUID, uuid4
 import pickle
 from alpaca.data.historical import StockHistoricalDataClient
 from alpaca.data.requests import StockTradesRequest, StockBarsRequest
-from alpaca.data.enums import DataFeed
+from alpaca.data.enums import DataFeed 
 from alpaca.data.timeframe import TimeFrame
 from v2realbot.strategy.base import StrategyState
 from v2realbot.enums.enums import RecordType, StartBarAlign, Mode, Account, OrderSide
@@ -14,7 +14,7 @@ from v2realbot.common.PrescribedTradeModel import Trade, TradeDirection, TradeSt
 from datetime import datetime
 from v2realbot.loader.trade_offline_streamer import Trade_Offline_Streamer
 from threading import Thread, current_thread, Event, enumerate
-from v2realbot.config import STRATVARS_UNCHANGEABLES, ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, ACCOUNT1_LIVE_API_KEY, ACCOUNT1_LIVE_SECRET_KEY, DATA_DIR,BT_FILL_CONS_TRADES_REQUIRED,BT_FILL_LOG_SURROUNDING_TRADES,BT_FILL_CONDITION_BUY_LIMIT,BT_FILL_CONDITION_SELL_LIMIT, GROUP_TRADES_WITH_TIMESTAMP_LESS_THAN, MEDIA_DIRECTORY, RUNNER_DETAIL_DIRECTORY, OFFLINE_MODE
+from v2realbot.config import STRATVARS_UNCHANGEABLES, ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, ACCOUNT1_PAPER_FEED, ACCOUNT1_LIVE_API_KEY, ACCOUNT1_LIVE_SECRET_KEY, ACCOUNT1_LIVE_FEED, DATA_DIR, MEDIA_DIRECTORY, RUNNER_DETAIL_DIRECTORY
 import importlib
 from alpaca.trading.requests import GetCalendarRequest
 from alpaca.trading.client import TradingClient
@@ -24,23 +24,25 @@ from tinydb import TinyDB, Query, where
 from tinydb.operations import set
 import orjson
 import numpy as np
-from numpy import ndarray
 from rich import print
 import pandas as pd
 from traceback import format_exc
 from datetime import timedelta, time
 from threading import Lock
-from v2realbot.common.db import pool, execute_with_retry, row_to_runarchive, row_to_runarchiveview
+from v2realbot.common.db import pool, execute_with_retry
+import v2realbot.common.transform as tr
 from sqlite3 import OperationalError, Row
 import v2realbot.strategyblocks.indicators.custom as ci
 from v2realbot.strategyblocks.inits.init_indicators import initialize_dynamic_indicators
 from v2realbot.strategyblocks.indicators.indicators_hub import populate_dynamic_indicators
+from v2realbot.strategyblocks.inits.init_attached_data import attach_previous_data
 from v2realbot.interfaces.backtest_interface import BacktestInterface
 import os
-from v2realbot.reporting.metricstoolsimage import generate_trading_report_image
-import msgpack
+import v2realbot.reporting.metricstoolsimage as mt
 import gzip
 import os
+import msgpack
+import v2realbot.utils.config_handler as cfh
 #import gc
 #from pyinstrument import Profiler
 #adding lock to ensure thread safety of TinyDB (in future will be migrated to proper db)
@@ -81,7 +83,7 @@ def get_all_stratins():
     else:
         return (0, [])
      
-def get_stratin(id: UUID):
+def get_stratin(id: UUID) -> List[StrategyInstance]:
     for i in db.stratins:
         if str(i.id) == str(id):
             return (0, i)
@@ -101,12 +103,12 @@ def create_stratin(si: StrategyInstance):
     #validate toml
     res, stp = parse_toml_string(si.stratvars_conf)
     if res < 0:
-        return (-1,"stratvars invalid")
+        return (-1,f"stratvars invalid: {stp}")
     res, adp = parse_toml_string(si.add_data_conf)
     if res < 0:
-        return (-1, "None")
+        return (-1, f"add data conf invalid {adp}") 
     si.id = uuid4()
-    print(si)
+    #print(si)
     db.stratins.append(si)
     db.save()
     #print(db.stratins)
@@ -118,10 +120,10 @@ def modify_stratin(si: StrategyInstance, id: UUID):
         return (-1, "strat is running, use modify_stratin_running")
     res, stp = parse_toml_string(si.stratvars_conf)
     if res < 0:
-        return (-1, "stratvars invalid")
+        return (-1, f"stratvars invalid {stp}")
     res, adp = parse_toml_string(si.add_data_conf)
     if res < 0:
-        return (-1, "add data conf invalid") 
+        return (-1, f"add data conf invalid {adp}") 
     for i in db.stratins:
         if str(i.id) == str(id):
             #print("removing",i)
@@ -179,14 +181,14 @@ def modify_stratin_running(si: StrategyInstance, id: UUID):
         #validate toml
         res,stp = parse_toml_string(si.stratvars_conf)
         if res < 0:
-            return (-1, "new stratvars format invalid")
+            return (-1, f"new stratvars format invalid {stp}")
         for i in db.stratins:
             if str(i.id) == str(id):
                 if not is_stratin_running(id=str(id)):
                     return (-1, "not running")
                 res,stp_old = parse_toml_string(i.stratvars_conf)
                 if res < 0:
-                    return (-1, "current stratin stratvars invalid")
+                    return (-1, f"current stratin stratvars invalid {stp_old}")
                 #TODO reload running strat
                 #print(stp)
                 #print("starting injection", stp)
@@ -243,13 +245,14 @@ def pause_runner(id: UUID):
             return (0, "paused runner " + str(i.id))
     print("no ID found")
     return (-1, "not running instance found")
-
-def stop_runner(id: UUID = None):
+#allows to delete runner based on runner_id, strat_id or all (both none)
+#podpruje i hodnotu strat_id v id
+def stop_runner(id: UUID = None, strat_id: UUID = None):
     chng = []
     try:
         for i in db.runners:
             #print(i['id'])
-            if id is None or str(i.id) == id:
+            if (id is None and strat_id is None) or str(i.id) == str(id) or str(i.strat_id) == str(strat_id) or str(i.strat_id) == str(id):
                 chng.append(i.id)
                 print("Sending STOP signal to Runner", i.id)
                 #just sending the signal, update is done in stop after plugin
@@ -349,13 +352,28 @@ def capsule(target: object, db: object, inter_batch_params: dict = None):
                 db.runners.remove(i)
                 #vytvoreni report image pro RUNNER
                 try:
-                    res, val = generate_trading_report_image(runner_ids=[str(i.id)])
+                    res, val = mt.generate_trading_report_image(runner_ids=[str(i.id)])
                     if res == 0:
                         print("DAILY REPORT IMAGE CREATED")
                     else:
                         print(f"Daily report ERROR - {val}")
                 except Exception as e:
-                    print("Nepodarilo se vytvorit report image", str(e)+format_exc())       
+                    err_msg = "Nepodarilo se vytvorit daily report image" + str(e)+format_exc()
+                    send_to_telegram(err_msg)
+                    print(err_msg)
+                #PRO LIVE a PAPER pri vyplnenem batchi vytvarime batchovy soubor zde (pro BT ridi batch_manager)
+                if i.run_mode in [Mode.LIVE, Mode.PAPER] and i.batch_id is not None:
+                    try:
+                        res, val = mt.generate_trading_report_image(batch_id=i.batch_id)
+                        if res == 0:
+                            print("BATCH REPORT CREATED")
+                        else:
+                            print(f"BATCH REPORT ERROR - {val}")
+                    except Exception as e:
+                        err_msg = f"Nepodarilo se vytvorit batchj report image pro {i.strat_id} a batch{i.batch_id}" + str(e)+format_exc()
+                        send_to_telegram(err_msg)
+                        print(err_msg)
+
         target.release()
     print("Runner STOPPED")
 
@@ -395,7 +413,7 @@ def run_batch_stratin(id: UUID, runReq: RunRequest):
     def get_market_days_in_interval(datefrom, dateto, note = None, id = None):
         #getting dates from calendat
         clientTrading = TradingClient(ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, raw_data=False, paper=True)        
-        calendar_request = GetCalendarRequest(start=datefrom,end=dateto)
+        calendar_request = GetCalendarRequest(start=datefrom.date(),end=dateto.date())
         cal_dates = clientTrading.get_calendar(calendar_request)
         #list(Calendar)
         # Calendar
@@ -429,7 +447,7 @@ def run_batch_stratin(id: UUID, runReq: RunRequest):
             cal_list.append(RunDay(start = start_time, end = end_time, note = note, id = id))
 
         print(f"Getting interval dates from - to - RESULT ({len(cal_list)}):")
-        print(cal_list)
+        #print(cal_list)
         return cal_list
     
     #getting days to run into RunDays format
@@ -476,6 +494,9 @@ def run_batch_stratin(id: UUID, runReq: RunRequest):
 # bud ceka na dokonceni v runners nebo to bude ridit jinak a bude mit jednoho runnera?
 # nejak vymyslet.
 # logovani zatim jen do print
+
+##OFFLINE BATCH RUN MANAGER (generuje batch_id, ridi datove provazani runnerů(inter_batch_data) a generuje batch report
+## a samozrejme spousti jednotlivé dny
 def batch_run_manager(id: UUID, runReq: RunRequest, rundays: list[RunDay]):
     #zde muzu iterovat nad intervaly
     #cekat az dobehne jeden interval a pak spustit druhy
@@ -567,14 +588,16 @@ def batch_run_manager(id: UUID, runReq: RunRequest, rundays: list[RunDay]):
     runReq = None
     #vytvoreni report image pro batch
     try:
-        res, val = generate_trading_report_image(batch_id=batch_id)
+        res, val = mt.generate_trading_report_image(batch_id=batch_id)
         if res == 0:
             print("BATCH REPORT CREATED")
         else:
             print(f"BATCH REPORT ERROR - {val}")
 
     except Exception as e:
-        print("Nepodarilo se vytvorit report image", str(e)+format_exc())       
+        err_msg = "Nepodarilo se vytvorit batch report image" + str(e)+format_exc()
+        send_to_telegram(err_msg)
+        print(err_msg)       
 
     #gc.collect()
 
@@ -596,10 +619,10 @@ def run_stratin(id: UUID, runReq: RunRequest, synchronous: bool = False, inter_b
                 #validate toml
                 res, stp = parse_toml_string(i.stratvars_conf)
                 if res < 0:
-                    return (-1, "stratvars invalid")
+                    return (-1, f"stratvars invalid {stp}")
                 res, adp = parse_toml_string(i.add_data_conf)
                 if res < 0:
-                    return (-1, "add data conf invalid")
+                    return (-1, f"add data conf invalid {adp}")
                 id = uuid4()
                 print(f"RUN {id} INITIATED")
                 name = i.name
@@ -697,7 +720,7 @@ def get_trade_history(symbol: str, timestamp_from: float, timestamp_to:float):
         #datetime_object_from = datetime(2023, 4, 14, 15, 51, 38, tzinfo=zoneNY)
         #datetime_object_to = datetime(2023, 4, 14, 15, 51, 39, tzinfo=zoneNY)   
         client = StockHistoricalDataClient(ACCOUNT1_LIVE_API_KEY, ACCOUNT1_LIVE_SECRET_KEY, raw_data=False)
-        trades_request = StockTradesRequest(symbol_or_symbols=symbol, feed = DataFeed.SIP, start=datetime_object_from, end=datetime_object_to)
+        trades_request = StockTradesRequest(symbol_or_symbols=symbol, feed = ACCOUNT1_LIVE_FEED, start=datetime_object_from, end=datetime_object_to)
         all_trades = client.get_stock_trades(trades_request)
         #print(all_trades[symbol])
         return 0, all_trades[symbol]
@@ -866,13 +889,9 @@ def archive_runner(runner: Runner, strat: StrategyInstance, inter_batch_params:
                         rectype=strat.state.rectype,
                         cache_used=strat.dataloader.cache_used if isinstance(strat.dataloader, Trade_Offline_Streamer) else None,
                         configs=dict(
-                            GROUP_TRADES_WITH_TIMESTAMP_LESS_THAN=GROUP_TRADES_WITH_TIMESTAMP_LESS_THAN,
-                            BT_FILL_CONS_TRADES_REQUIRED=BT_FILL_CONS_TRADES_REQUIRED,
-                            BT_FILL_LOG_SURROUNDING_TRADES=BT_FILL_LOG_SURROUNDING_TRADES,
-                            BT_FILL_CONDITION_BUY_LIMIT=BT_FILL_CONDITION_BUY_LIMIT,
-                            BT_FILL_CONDITION_SELL_LIMIT=BT_FILL_CONDITION_SELL_LIMIT))
+                            CONFIG_HANDLER=dict(profile=cfh.config_handler.active_profile, values=cfh.config_handler.active_config)))
 
-        
+    
         #add profit of this batch iteration to batch_sum_profit
         if inter_batch_params is not None:
             inter_batch_params["batch_profit"] += round(float(strat.state.profit),2)
@@ -907,7 +926,8 @@ def archive_runner(runner: Runner, strat: StrategyInstance, inter_batch_params:
                                             end_positions=strat.state.positions,
                                             end_positions_avgp=round(float(strat.state.avgp),3),
                                             metrics=results_metrics,
-                                            stratvars_toml=runner.run_stratvars_toml
+                                            stratvars_toml=runner.run_stratvars_toml,
+                                            transferables=strat.state.vars["transferables"]
                                             )
         
         #flatten indicators from numpy array
@@ -915,7 +935,7 @@ def archive_runner(runner: Runner, strat: StrategyInstance, inter_batch_params:
         #pole indicatoru, kazdy ma svoji casovou osu time
         flattened_indicators_list = []
         for key, value in strat.state.indicators.items():
-                if isinstance(value, ndarray):
+                if isinstance(value, np.ndarray):
                     #print("is numpy", key,value)
                     flattened_indicators[key]= value.tolist()
                     #print("changed numpy:",value.tolist())
@@ -925,7 +945,7 @@ def archive_runner(runner: Runner, strat: StrategyInstance, inter_batch_params:
         flattened_indicators_list.append(flattened_indicators)
         flattened_indicators = {}
         for key, value in strat.state.cbar_indicators.items():
-                if isinstance(value, ndarray):
+                if isinstance(value, np.ndarray):
                     #print("is numpy", key,value)
                     flattened_indicators[key]= value.tolist()
                     #print("changed numpy:",value.tolist())
@@ -988,7 +1008,7 @@ def get_all_archived_runners() -> list[RunArchiveView]:
         rows = c.fetchall()
         results = []
         for row in rows:
-            results.append(row_to_runarchiveview(row))
+            results.append(tr.row_to_runarchiveview(row))
     finally:
         conn.row_factory = None
         pool.release_connection(conn)        
@@ -1018,7 +1038,7 @@ def get_all_archived_runners() -> list[RunArchiveView]:
 #         c.execute(paginated_query)
 #         rows = c.fetchall()
 
-#         results = [row_to_runarchiveview(row) for row in rows]
+#         results = [tr.row_to_runarchiveview(row) for row in rows]
 
 #     finally:
 #         conn.row_factory = None
@@ -1032,7 +1052,7 @@ def get_all_archived_runners() -> list[RunArchiveView]:
 
 #new version to support search and ordering
 #TODO index nad strat_id a batch_id mam?
-def get_all_archived_runners_p(request: DataTablesRequest) -> Tuple[int, RunArchiveViewPagination]:
+def get_all_archived_runners_p_original(request: DataTablesRequest) -> Tuple[int, RunArchiveViewPagination]:
     conn = pool.get_connection()
     search_value = request.search.value  # Extract the search value from the request
     try:
@@ -1068,7 +1088,80 @@ def get_all_archived_runners_p(request: DataTablesRequest) -> Tuple[int, RunArch
         c.execute(filtered_count_query, {'search_value': f'%{search_value}%'})
         filtered_count = c.fetchone()[0]
 
-        results = [row_to_runarchiveview(row) for row in rows]
+        results = [tr.row_to_runarchiveview(row) for row in rows]
+
+    finally:
+        conn.row_factory = None
+        pool.release_connection(conn)
+
+    try:
+        obj = RunArchiveViewPagination(draw=request.draw, recordsTotal=total_count, recordsFiltered=filtered_count, data=results)
+        return 0, obj
+    except Exception as e:
+        return -2, str(e) + format_exc()
+
+
+#new version with batch_id asc sortin https://chat.openai.com/c/64511445-5181-411b-b9d0-51d16930bf71
+#Tato verze správně groupuje záznamy se stejnym batch_id (podle maximalniho batche) a non batch zaznamy prolne mezi ne podle jeho stopped date - vlozi zaznam po nebo pred jednotlivou skupinu (dle jejiho max.date)
+#diky tomu se mi radi batche a nonbatche spravne a pokud do batche pridame zaznam zobrazi se nam batch nahore
+def get_all_archived_runners_p(request: DataTablesRequest) -> Tuple[int, RunArchiveViewPagination]:
+    conn = pool.get_connection()
+    search_value = request.search.value  # Extract the search value from the request
+    try:
+        conn.row_factory = Row
+        c = conn.cursor()
+
+        # Total count query
+        total_count_query = """
+        SELECT COUNT(*) FROM runner_header
+        WHERE (:search_value = '' OR strat_id LIKE :search_value OR batch_id LIKE :search_value OR symbol like :search_value OR name like :search_value)
+        """
+        c.execute(total_count_query, {'search_value': f'%{search_value}%'})
+        total_count = c.fetchone()[0]
+
+        # Paginated query with advanced sorting logic
+        paginated_query = f"""
+        WITH GroupedData AS (
+            SELECT runner_id, strat_id, batch_id, symbol, name, note, started, 
+                stopped, mode, account, bt_from, bt_to, ilog_save, profit, 
+                trade_count, end_positions, end_positions_avgp, metrics,
+                MAX(stopped) OVER (PARTITION BY batch_id) AS max_stopped,
+                SUM(profit) OVER (PARTITION BY batch_id) AS batch_profit,
+                COUNT(*) OVER (PARTITION BY batch_id) AS batch_count
+            FROM runner_header
+            WHERE (:search_value = '' OR strat_id LIKE :search_value OR batch_id LIKE :search_value OR symbol like :search_value OR name like :search_value)
+        ),
+        InterleavedGroups AS (
+            SELECT *,
+                CASE 
+                    WHEN batch_id IS NOT NULL THEN max_stopped
+                    ELSE stopped
+                END AS sort_key
+            FROM GroupedData
+        )
+        SELECT runner_id, strat_id, batch_id, symbol, name, note, started, 
+            stopped, mode, account, bt_from, bt_to, ilog_save, profit, 
+            trade_count, end_positions, end_positions_avgp, metrics, 
+            batch_profit, batch_count
+        FROM InterleavedGroups
+        ORDER BY 
+            sort_key DESC,
+            CASE WHEN batch_id IS NOT NULL THEN 0 ELSE 1 END,
+            stopped DESC
+        LIMIT {request.length} OFFSET {request.start}
+        """
+        c.execute(paginated_query, {'search_value': f'%{search_value}%'})
+        rows = c.fetchall()
+
+        # Filtered count query
+        filtered_count_query = """
+        SELECT COUNT(*) FROM runner_header
+        WHERE (:search_value = '' OR strat_id LIKE :search_value OR batch_id LIKE :search_value OR symbol like :search_value OR name like :search_value)
+        """
+        c.execute(filtered_count_query, {'search_value': f'%{search_value}%'})
+        filtered_count = c.fetchone()[0]
+
+        results = [tr.row_to_runarchiveview(row) for row in rows]
 
     finally:
         conn.row_factory = None
@@ -1103,7 +1196,7 @@ def get_archived_runner_header_byID(id: UUID) -> RunArchive:
         row = c.fetchone()
 
         if row:
-            return 0, row_to_runarchive(row)
+            return 0, tr.row_to_runarchive(row)
         else:
             return -2, "not found"
 
@@ -1129,17 +1222,43 @@ def get_archived_runner_header_byID(id: UUID) -> RunArchive:
 #     else:
 #         return 0, res
 
-#vrátí seznam runneru s danym batch_id
-def get_archived_runnerslist_byBatchID(batch_id: str):
+# #vrátí seznam runneru s danym batch_id
+# def get_archived_runnerslist_byBatchID(batch_id: str):
+#     conn = pool.get_connection()
+#     try:
+#         cursor = conn.cursor()
+#         cursor.execute(f"SELECT runner_id FROM runner_header WHERE batch_id='{str(batch_id)}'")
+#         runner_list = [row[0] for row in cursor.fetchall()]
+#     finally:
+#         pool.release_connection(conn)
+#     return 0, runner_list
+
+#update that allows to sort
+def get_archived_runnerslist_byBatchID(batch_id: str, sort_order: str = "asc"):
+    """
+    Fetches all runner records by batch_id, sorted by the 'started' column.
+
+    :param batch_id: The batch ID to filter runners by.
+    :param sort_order: The sort order of the 'started' column. Defaults to 'asc'.
+                       Accepts 'asc' for ascending or 'desc' for descending order.
+    :return: A tuple with the first element being a status code and the second being the list of runner_ids.
+    """
+    # Validate sort_order
+    if sort_order.lower() not in ['asc', 'desc']:
+        return -1, []  # Returning an error code and an empty list in case of invalid sort_order
+    
     conn = pool.get_connection()
     try:
         cursor = conn.cursor()
-        cursor.execute(f"SELECT runner_id FROM runner_header WHERE batch_id='{str(batch_id)}'")
+        query = f"""SELECT runner_id FROM runner_header 
+                    WHERE batch_id=? 
+                    ORDER BY datetime(started) {sort_order.upper()}"""
+        cursor.execute(query, (batch_id,))
         runner_list = [row[0] for row in cursor.fetchall()]
     finally:
         pool.release_connection(conn)
     return 0, runner_list
-    
+
 def insert_archive_header(archeader: RunArchive):
     conn = pool.get_connection()
     try:
@@ -1148,11 +1267,11 @@ def insert_archive_header(archeader: RunArchive):
 
         res = c.execute("""
             INSERT INTO runner_header 
-            (runner_id, strat_id, batch_id, symbol, name, note, started, stopped, mode, account, bt_from, bt_to, strat_json, settings, ilog_save, profit, trade_count, end_positions, end_positions_avgp, metrics, stratvars_toml) 
+            (runner_id, strat_id, batch_id, symbol, name, note, started, stopped, mode, account, bt_from, bt_to, strat_json, settings, ilog_save, profit, trade_count, end_positions, end_positions_avgp, metrics, stratvars_toml, transferables) 
             VALUES
-            (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+            (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
             """,
-            (str(archeader.id), str(archeader.strat_id), archeader.batch_id, archeader.symbol, archeader.name, archeader.note, archeader.started, archeader.stopped, archeader.mode, archeader.account, archeader.bt_from, archeader.bt_to, orjson.dumps(archeader.strat_json).decode('utf-8'), orjson.dumps(archeader.settings).decode('utf-8'), archeader.ilog_save, archeader.profit, archeader.trade_count, archeader.end_positions, archeader.end_positions_avgp, orjson.dumps(archeader.metrics, default=json_serial, option=orjson.OPT_PASSTHROUGH_DATETIME).decode('utf-8'), archeader.stratvars_toml))
+            (str(archeader.id), str(archeader.strat_id), archeader.batch_id, archeader.symbol, archeader.name, archeader.note, archeader.started, archeader.stopped, archeader.mode, archeader.account, archeader.bt_from, archeader.bt_to, orjson.dumps(archeader.strat_json).decode('utf-8'), orjson.dumps(archeader.settings).decode('utf-8'), archeader.ilog_save, archeader.profit, archeader.trade_count, archeader.end_positions, archeader.end_positions_avgp, orjson.dumps(archeader.metrics, default=json_serial, option=orjson.OPT_PASSTHROUGH_DATETIME).decode('utf-8'), archeader.stratvars_toml, orjson.dumps(archeader.transferables).decode('utf-8')))
 
         #retry not yet supported for statement format above
         #res = execute_with_retry(c,statement)
@@ -1476,7 +1595,7 @@ def preview_indicator_byTOML(id: UUID, indicator: InstantIndicator, save: bool =
         # print(row)
         res, toml_parsed = parse_toml_string(tomlino)
         if res < 0:
-            return (-2, "toml invalid")
+            return (-2, f"toml invalid: {toml_parsed}")
         
         #print("parsed toml", toml_parsed)
 
@@ -1571,9 +1690,17 @@ def preview_indicator_byTOML(id: UUID, indicator: InstantIndicator, save: bool =
         state.ind_mapping = {**local_dict_inds, **local_dict_bars, **local_dict_cbar_inds}
         #print("IND MAPPING DONE:", state.ind_mapping)
 
+        ##intialize required vars from strat init
+        state.vars["loaded_models"] = {}
+        #state attributes for martingale sizing mngmt
+        state.vars["transferables"] = {}
+        state.vars["transferables"]["martingale"] = dict(cont_loss_series_cnt=0)
+
         ##intialize dynamic indicators
         initialize_dynamic_indicators(state)
-                    
+        #TODO vazit attached data (z toho potrebuji jen transferables, tzn. najit nejak predchozi runner a prelipnout transferables od zacatku)
+        #nejspis upravit attach_previous_data a nebo udelat specialni verzi
+        #attach_previous_data(state)     
 
         # print("subtype")   
         # function = "ci."+subtype+"."+subtype
@@ -1714,10 +1841,10 @@ def preview_indicator_byTOML(id: UUID, indicator: InstantIndicator, save: bool =
 
         #vracime list, kde pozice 0 je bar indicators, pozice 1 je ticks indicators
         if output == "bar":
-            return 0, [output_dict, []]
+            return 0, [output_dict, {}]
             #return 0, [new_inds[indicator.name], []]
         else:
-            return 0, [[], output_dict]
+            return 0, [{}, output_dict]
             #return 0, [[], new_tick_inds[indicator.name]]
 
     except Exception as e:
@@ -1757,107 +1884,18 @@ def delete_indicator_byName(id: UUID, indicator: InstantIndicator):
         print(str(e) + format_exc())
         return -2, str(e)
 
-# region CONFIG db services
-#TODO vytvorit modul pro dotahovani z pythonu (get_from_config(var_name, def_value) {)- stejne jako v js 
-#TODO zvazit presunuti do TOML z JSONu
-def get_all_config_items():
-    conn = pool.get_connection()
-    try:
-        cursor = conn.cursor()
-        cursor.execute('SELECT id, item_name, json_data FROM config_table')
-        config_items = [{"id": row[0], "item_name": row[1], "json_data": row[2]} for row in cursor.fetchall()]
-    finally:
-        pool.release_connection(conn)
-    return 0, config_items
-
-# Function to get a config item by ID
-def get_config_item_by_id(item_id):
-    conn = pool.get_connection()
-    try:
-        cursor = conn.cursor()
-        cursor.execute('SELECT item_name, json_data FROM config_table WHERE id = ?', (item_id,))
-        row = cursor.fetchone()
-    finally:
-        pool.release_connection(conn)
-    if row is None:
-        return -2, "not found"
-    else:
-        return 0, {"item_name": row[0], "json_data": row[1]}
-
-# Function to get a config item by ID
-def get_config_item_by_name(item_name):
-    #print(item_name)
-    conn = pool.get_connection()
-    try:
-        cursor = conn.cursor()
-        query = f"SELECT item_name, json_data FROM config_table WHERE item_name = '{item_name}'"
-        #print(query)
-        cursor.execute(query)
-        row = cursor.fetchone()
-        #print(row)
-    finally:
-        pool.release_connection(conn)
-    if row is None:
-        return -2, "not found"
-    else:
-        return 0, {"item_name": row[0], "json_data": row[1]}
-
-# Function to create a new config item
-def create_config_item(config_item: ConfigItem):
-    conn = pool.get_connection()
-    try:
-        try:
-            cursor = conn.cursor()
-            cursor.execute('INSERT INTO config_table (item_name, json_data) VALUES (?, ?)', (config_item.item_name, config_item.json_data))
-            item_id = cursor.lastrowid
-            conn.commit()
-            print(item_id)
-        finally:
-            pool.release_connection(conn)
-
-        return 0, {"id": item_id, "item_name":config_item.item_name, "json_data":config_item.json_data}
-    except Exception as e:
-        return -2, str(e)
-
-# Function to update a config item by ID
-def update_config_item(item_id, config_item: ConfigItem):
-    conn = pool.get_connection()
-    try:
-        try:
-            cursor = conn.cursor()
-            cursor.execute('UPDATE config_table SET item_name = ?, json_data = ? WHERE id = ?', (config_item.item_name, config_item.json_data, item_id))
-            conn.commit()
-        finally:
-            pool.release_connection(conn)
-        return 0, {"id": item_id, **config_item.dict()}
-    except Exception as e:
-        return -2, str(e)
-    
-# Function to delete a config item by ID
-def delete_config_item(item_id):
-    conn = pool.get_connection()
-    try:
-        cursor = conn.cursor()
-        cursor.execute('DELETE FROM config_table WHERE id = ?', (item_id,))
-        conn.commit()
-    finally:
-       pool.release_connection(conn) 
-    return 0, {"id": item_id}
-
-# endregion
-
 #returns b
 def get_alpaca_history_bars(symbol: str, datetime_object_from: datetime, datetime_object_to: datetime, timeframe: TimeFrame):
     """Returns Bar object
     """
     try:
+        result = []
         client = StockHistoricalDataClient(ACCOUNT1_LIVE_API_KEY, ACCOUNT1_LIVE_SECRET_KEY, raw_data=False)
         #datetime_object_from = datetime(2023, 2, 27, 18, 51, 38, tzinfo=datetime.timezone.utc)
         #datetime_object_to = datetime(2023, 2, 27, 21, 51, 39, tzinfo=datetime.timezone.utc)
-        bar_request = StockBarsRequest(symbol_or_symbols=symbol,timeframe=timeframe, start=datetime_object_from, end=datetime_object_to, feed=DataFeed.SIP)
+        bar_request = StockBarsRequest(symbol_or_symbols=symbol,timeframe=timeframe, start=datetime_object_from, end=datetime_object_to, feed=ACCOUNT1_LIVE_FEED)
         #print("before df")
         bars = client.get_stock_bars(bar_request)
-        result = []
         ##pridavame pro jistotu minutu z obou stran kvuli frontendu
         business_hours = {
             # monday = 0, tuesday = 1, ... same pattern as date.weekday()
@@ -1888,12 +1926,25 @@ def get_alpaca_history_bars(symbol: str, datetime_object_from: datetime, datetim
         #bars.data[symbol]
         return 0, result
     except Exception as e:
-        print(str(e) + format_exc())
-        if OFFLINE_MODE:
-            print("OFFLINE MODE ENABLED")
-            return 0, []
-        return -2, str(e)    
+        # Workaround of error when no data foun d AttributeError and has the specific message
+        if isinstance(e, AttributeError) and str(e) == "'NoneType' object has no attribute 'items'":
+            print("Caught the specific AttributeError: 'NoneType' object has no attribute 'items' means NO DATA FOUND")
+            print(str(e) + format_exc())        
+            return 0, result            
+        else:
+            print(str(e) + format_exc())
+            if cfh.config_handler.get_val('OFFLINE_MODE'):
+                print("OFFLINE MODE ENABLED")
+                return 0, []
+            return -2, str(e)    
 # change_archived_runner
 # delete_archived_runner_details
 
-
+#Example of using config directive
+# config_directive = "python"
+# ret, res = get_config_item_by_name(config_directive)
+# if ret < 0:
+#     print(f"Error {res}")
+# else:
+#     config = orjson.loads(res["json_data"])
+#     print(config)

v2realbot/enums/enums.py

@@ -1,6 +1,11 @@
 from enum import Enum
 from alpaca.trading.enums import OrderSide, OrderStatus, OrderType
 
+class BarType(str, Enum):
+    TIME = "time"
+    VOLUME = "volume"
+    DOLLAR = "dollar"
+
 class Env(str, Enum):
     PROD = "prod"
     TEST = "test"
@@ -52,6 +57,16 @@ class Account(str, Enum):
     """
     ACCOUNT1 = "ACCOUNT1"
     ACCOUNT2 = "ACCOUNT2"
+
+class Moddus(str, Enum):
+    """
+    Moddus for RunManager record
+
+    schedule - scheduled record
+    queue - queued record
+    """
+    SCHEDULE = "schedule"
+    QUEUE = "queue"
 class RecordType(str, Enum):
     """
     Represents output of aggregator
@@ -64,6 +79,15 @@ class RecordType(str, Enum):
     CBARRENKO = "cbarrenko"
     TRADE = "trade"
 
+class SchedulerStatus(str, Enum):
+    """
+    ACTIVE - active scheduling
+    SUSPENDED - suspended for scheduling
+    """
+
+    ACTIVE = "active"
+    SUSPENDED = "suspended"
+
 class Mode(str, Enum):
     """
     LIVE - live on production
@@ -77,7 +101,6 @@ class Mode(str, Enum):
     BT = "backtest"
     PREP = "prep"
 
-
 class StartBarAlign(str, Enum):
     """
     Represents first bar start time alignement according to timeframe
@@ -85,4 +108,10 @@ class StartBarAlign(str, Enum):
         RANDOM = first bar starts when first trade occurs
     """ 
     ROUND = "round"
-    RANDOM = "random"
+    RANDOM = "random"
+
+class Market(str, Enum):
+    US = "US"
+    CRYPTO = "CRYPTO"
+
+     

v2realbot/interfaces/backtest_interface.py

@@ -2,9 +2,9 @@ from alpaca.trading.enums import OrderSide, OrderType
 from threading import Lock
 from v2realbot.interfaces.general_interface import GeneralInterface
 from v2realbot.backtesting.backtester import Backtester
-from v2realbot.config import BT_DELAYS, COUNT_API_REQUESTS
 from datetime import datetime
 from v2realbot.utils.utils import zoneNY
+import v2realbot.utils.config_handler as cfh
 
 """"
 backtester methods can be called
@@ -19,7 +19,7 @@ class BacktestInterface(GeneralInterface):
     def __init__(self, symbol, bt: Backtester) -> None:
         self.symbol = symbol
         self.bt = bt
-        self.count_api_requests = COUNT_API_REQUESTS
+        self.count_api_requests = cfh.config_handler.get_val('COUNT_API_REQUESTS')
         self.mincnt = list([dict(minute=0,count=0)])
         #TODO time v API nejspis muzeme dat pryc a BT bude si to brat primo ze self.time (nezapomenout na + BT_DELAYS)
         # self.time = self.bt.time
@@ -43,33 +43,33 @@ class BacktestInterface(GeneralInterface):
     def buy(self, size = 1, repeat: bool = False):
         self.count()
         #add REST API latency
-        return self.bt.submit_order(time=self.bt.time + BT_DELAYS.strat_to_sub,symbol=self.symbol,side=OrderSide.BUY,size=size,order_type = OrderType.MARKET) 
+        return self.bt.submit_order(time=self.bt.time + cfh.config_handler.get_val('BT_DELAYS','strat_to_sub'),symbol=self.symbol,side=OrderSide.BUY,size=size,order_type = OrderType.MARKET) 
     
     """buy limit"""
     def buy_l(self, price: float, size: int = 1, repeat: bool = False, force: int = 0):
         self.count()
-        return self.bt.submit_order(time=self.bt.time + BT_DELAYS.strat_to_sub,symbol=self.symbol,side=OrderSide.BUY,size=size,price=price,order_type = OrderType.LIMIT) 
+        return self.bt.submit_order(time=self.bt.time + cfh.config_handler.get_val('BT_DELAYS','strat_to_sub'),symbol=self.symbol,side=OrderSide.BUY,size=size,price=price,order_type = OrderType.LIMIT) 
     
     """sell market"""
     def sell(self, size = 1, repeat: bool = False):
         self.count()
-        return self.bt.submit_order(time=self.bt.time + BT_DELAYS.strat_to_sub,symbol=self.symbol,side=OrderSide.SELL,size=size,order_type = OrderType.MARKET) 
+        return self.bt.submit_order(time=self.bt.time + cfh.config_handler.get_val('BT_DELAYS','strat_to_sub'),symbol=self.symbol,side=OrderSide.SELL,size=size,order_type = OrderType.MARKET) 
 
     """sell limit"""
     async def sell_l(self, price: float, size = 1, repeat: bool = False):
         self.count()
-        return self.bt.submit_order(time=self.bt.time + BT_DELAYS.strat_to_sub,symbol=self.symbol,side=OrderSide.SELL,size=size,price=price,order_type = OrderType.LIMIT)        
+        return self.bt.submit_order(time=self.bt.time + cfh.config_handler.get_val('BT_DELAYS','strat_to_sub'),symbol=self.symbol,side=OrderSide.SELL,size=size,price=price,order_type = OrderType.LIMIT)        
 
     """replace order"""
     async def repl(self, orderid: str, price: float = None, size: int = None, repeat: bool = False):
         self.count()
-        return self.bt.replace_order(time=self.bt.time + BT_DELAYS.strat_to_sub,id=orderid,size=size,price=price)
+        return self.bt.replace_order(time=self.bt.time + cfh.config_handler.get_val('BT_DELAYS','strat_to_sub'),id=orderid,size=size,price=price)
     
     """cancel order"""
     #TBD exec predtim?
     def cancel(self, orderid: str):
         self.count()
-        return self.bt.cancel_order(time=self.bt.time + BT_DELAYS.strat_to_sub, id=orderid)
+        return self.bt.cancel_order(time=self.bt.time + cfh.config_handler.get_val('BT_DELAYS','strat_to_sub'), id=orderid)
 
     """get positions ->(size,avgp)"""
     #TBD exec predtim?

v2realbot/interfaces/live_interface.py

@@ -40,7 +40,9 @@ class LiveInterface(GeneralInterface):
             
             return market_order.id
         except Exception as e:
-            print("Nepodarilo se odeslat buy", str(e))
+            reason = "Nepodarilo se market buy:" + str(e) + format_exc()
+            print(reason)
+            send_to_telegram(reason)
             return -1
 
     """buy limit"""
@@ -65,7 +67,9 @@ class LiveInterface(GeneralInterface):
 
             return limit_order.id
         except Exception as e:
-            print("Nepodarilo se odeslat limitku", str(e))
+            reason = "Nepodarilo se odeslat buy limitku:" + str(e) + format_exc()
+            print(reason)
+            send_to_telegram(reason)
             return -1
 
     """sell market"""
@@ -87,7 +91,9 @@ class LiveInterface(GeneralInterface):
             
             return market_order.id
         except Exception as e:
-            print("Nepodarilo se odeslat sell", str(e))
+            reason = "Nepodarilo se odeslat sell:" + str(e) + format_exc()
+            print(reason)
+            send_to_telegram(reason)
             return -1
 
     """sell limit"""
@@ -112,8 +118,9 @@ class LiveInterface(GeneralInterface):
             return limit_order.id
         
         except Exception as e:
-            print("Nepodarilo se odeslat sell_l", str(e))
-            #raise Exception(e)
+            reason = "Nepodarilo se odeslat sell limitku:" + str(e) + format_exc()
+            print(reason)
+            send_to_telegram(reason)
             return -1
         
     """order replace"""
@@ -136,7 +143,9 @@ class LiveInterface(GeneralInterface):
             if e.code == 42210000: return orderid
             else:
                 ##mozna tady proste vracet vzdy ok
-                print("Neslo nahradit profitku. Problem",str(e))
+                reason = "Neslo nahradit profitku. Problem:" + str(e) + format_exc()
+                print(reason)
+                send_to_telegram(reason)
                 return -1
                 #raise Exception(e)
 
@@ -150,7 +159,9 @@ class LiveInterface(GeneralInterface):
             #order doesnt exist
             if e.code == 40410000: return 0
             else:
-                print("nepovedlo se zrusit objednavku", str(e))
+                reason = "Nepovedlo se zrusit objednavku:" + str(e) + format_exc()
+                print(reason)
+                send_to_telegram(reason)
                 #raise Exception(e)
                 return -1
             
@@ -178,7 +189,9 @@ class LiveInterface(GeneralInterface):
             #list of Orders (orderlist[0].id)
             return orderlist
         except Exception as e:
-            print("Chyba pri dotazeni objednávek.", str(e))
+            reason = "Chyba pri dotazeni objednávek:" + str(e) + format_exc()
+            print(reason)
+            send_to_telegram(reason)
             #raise Exception (e)
             return -1
     

v2realbot/loader/aggregator.py

@@ -11,10 +11,10 @@ import threading
 from copy import deepcopy
 from msgpack import unpackb
 import os
-from v2realbot.config import DATA_DIR, GROUP_TRADES_WITH_TIMESTAMP_LESS_THAN, AGG_EXCLUDED_TRADES
-import pickle
+from v2realbot.config import DATA_DIR
 import dill
 import gzip
+import v2realbot.utils.config_handler as cfh
 
 class TradeAggregator:  
     def __init__(self,
@@ -25,7 +25,7 @@ class TradeAggregator:
                  align: StartBarAlign = StartBarAlign.ROUND,
                  mintick: int = 0,
                  exthours: bool = False,
-                 excludes: list = AGG_EXCLUDED_TRADES,
+                 excludes: list = cfh.config_handler.get_val('AGG_EXCLUDED_TRADES'),
                  skip_cache: bool = False):
         """
         UPDATED VERSION - vrací více záznamů
@@ -48,7 +48,7 @@ class TradeAggregator:
         self.excludes = excludes
         self.skip_cache = skip_cache
 
-        if mintick >= resolution:
+        if resolution > 0 and mintick >= resolution:
             print("Mintick musi byt mensi nez resolution")
             raise Exception
 
@@ -293,7 +293,7 @@ class TradeAggregator:
             self.diff_price = True    
         self.last_price = data['p'] 
 
-        if float(data['t']) - float(self.lasttimestamp) < GROUP_TRADES_WITH_TIMESTAMP_LESS_THAN:
+        if float(data['t']) - float(self.lasttimestamp) < cfh.config_handler.get_val('GROUP_TRADES_WITH_TIMESTAMP_LESS_THAN'):
             self.trades_too_close = True
         else:
             self.trades_too_close = False
@@ -320,13 +320,13 @@ class TradeAggregator:
             #TODO: do budoucna vymyslet, kdyz bude mene tradu, tak to radit vzdy do spravneho intervalu
             #zarovname time prvniho baru podle timeframu kam patří (např. 5, 10, 15 ...) (ROUND)
             if self.align == StartBarAlign.ROUND and self.bar_start == 0:
-                t = datetime.fromtimestamp(data['t'])
+                t = datetime.fromtimestamp(data['t'], tz=zoneUTC)
                 t = t - timedelta(seconds=t.second % self.resolution,microseconds=t.microsecond)
                 self.bar_start = datetime.timestamp(t)
             #nebo pouzijeme datum tradu zaokrouhlene na vteriny (RANDOM)
             else:
                 #ulozime si jeho timestamp (odtum pocitame resolution)
-                t = datetime.fromtimestamp(int(data['t']))
+                t = datetime.fromtimestamp(int(data['t']), tz=zoneUTC)
                 #timestamp
                 self.bar_start = int(data['t'])
             
@@ -376,7 +376,7 @@ class TradeAggregator:
             if self.mintick != 0 and self.lastBarConfirmed:
                #d zacatku noveho baru musi ubehnout x sekund nez posilame updazte
                 #pocatek noveho baru + Xs  musi byt vetsi nez aktualni trade              
-                if (self.newBar['time'] + timedelta(seconds=self.mintick)) > datetime.fromtimestamp(data['t']):
+                if (self.newBar['time'] + timedelta(seconds=self.mintick)) > datetime.fromtimestamp(data['t'], tz=zoneUTC):
                     #print("waiting for mintick")
                     return []
                 else:
@@ -540,7 +540,7 @@ class TradeAggregator:
             self.diff_price = True    
         self.last_price = data['p'] 
 
-        if float(data['t']) - float(self.lasttimestamp) < GROUP_TRADES_WITH_TIMESTAMP_LESS_THAN:
+        if float(data['t']) - float(self.lasttimestamp) < cfh.config_handler.get_val('GROUP_TRADES_WITH_TIMESTAMP_LESS_THAN'):
             self.trades_too_close = True
         else:
             self.trades_too_close = False
@@ -712,7 +712,7 @@ class TradeAggregator:
             self.diff_price = True    
         self.last_price = data['p'] 
 
-        if float(data['t']) - float(self.lasttimestamp) < GROUP_TRADES_WITH_TIMESTAMP_LESS_THAN:
+        if float(data['t']) - float(self.lasttimestamp) < cfh.config_handler.get_val('GROUP_TRADES_WITH_TIMESTAMP_LESS_THAN'):
             self.trades_too_close = True
         else:
             self.trades_too_close = False
@@ -756,8 +756,14 @@ class TradeAggregator:
         Ve strategii je třeba počítat s tím, že open v nepotvrzeném baru není finální.
         """""
 
+        if self.resolution < 0:  # Treat as percentage
+            reference_price = self.lastConfirmedBar['close'] if self.lastConfirmedBar is not None else float(data['p'])
+            brick_size = abs(self.resolution) * reference_price / 100.0
+        else:  # Treat as absolute value pocet ticku
+            brick_size = self.resolution
+
         #pocet ticku např. 10ticků, případně pak na procenta
-        brick_size = self.resolution
+        #brick_size = self.resolution
         #potvrzene pripravene k vraceni
         confirmedBars = []
         #potvrdi existujici a nastavi k vraceni
@@ -866,7 +872,7 @@ class TradeAggregator:
             self.diff_price = True    
         self.last_price = data['p'] 
 
-        if float(data['t']) - float(self.lasttimestamp) < GROUP_TRADES_WITH_TIMESTAMP_LESS_THAN:
+        if float(data['t']) - float(self.lasttimestamp) < cfh.config_handler.get_val('GROUP_TRADES_WITH_TIMESTAMP_LESS_THAN'):
             self.trades_too_close = True
         else:
             self.trades_too_close = False
@@ -962,7 +968,7 @@ class TradeAggregator2Queue(TradeAggregator):
     Child of TradeAggregator - sends items to given queue
     In the future others will be added - TradeAggToTxT etc.
     """
-    def __init__(self, symbol: str, queue: Queue, rectype: RecordType = RecordType.BAR, resolution: int = 5, minsize: int = 100, update_ltp: bool = False, align: StartBarAlign = StartBarAlign.ROUND, mintick: int = 0, exthours: bool = False, excludes: list = AGG_EXCLUDED_TRADES, skip_cache: bool = False):
+    def __init__(self, symbol: str, queue: Queue, rectype: RecordType = RecordType.BAR, resolution: int = 5, minsize: int = 100, update_ltp: bool = False, align: StartBarAlign = StartBarAlign.ROUND, mintick: int = 0, exthours: bool = False, excludes: list = cfh.config_handler.get_val('AGG_EXCLUDED_TRADES'), skip_cache: bool = False):
         super().__init__(rectype=rectype, resolution=resolution, minsize=minsize, update_ltp=update_ltp, align=align, mintick=mintick, exthours=exthours, excludes=excludes, skip_cache=skip_cache)
         self.queue = queue
         self.symbol = symbol
@@ -1007,7 +1013,7 @@ class TradeAggregator2List(TradeAggregator):
     """"
     stores records to the list
     """
-    def __init__(self, symbol: str, btdata: list, rectype: RecordType = RecordType.BAR, resolution: int = 5, minsize: int = 100, update_ltp: bool = False, align: StartBarAlign = StartBarAlign.ROUND, mintick: int = 0, exthours: bool = False, excludes: list = AGG_EXCLUDED_TRADES, skip_cache: bool = False):
+    def __init__(self, symbol: str, btdata: list, rectype: RecordType = RecordType.BAR, resolution: int = 5, minsize: int = 100, update_ltp: bool = False, align: StartBarAlign = StartBarAlign.ROUND, mintick: int = 0, exthours: bool = False, excludes: list = cfh.config_handler.get_val('AGG_EXCLUDED_TRADES'), skip_cache: bool = False):
         super().__init__(rectype=rectype, resolution=resolution, minsize=minsize, update_ltp=update_ltp, align=align, mintick=mintick, exthours=exthours, excludes=excludes, skip_cache=skip_cache)
         self.btdata = btdata
         self.symbol = symbol

v2realbot/loader/aggregator_vectorized.py

@@ -0,0 +1,570 @@
+import pandas as pd
+import numpy as np
+from numba import jit
+from alpaca.data.historical import StockHistoricalDataClient
+from sqlalchemy import column
+from v2realbot.config import ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, DATA_DIR
+from alpaca.data.requests import StockTradesRequest
+import time as time_module
+from v2realbot.utils.utils import parse_alpaca_timestamp, ltp, zoneNY, send_to_telegram, fetch_calendar_data
+import pyarrow
+from traceback import format_exc
+from datetime import timedelta, datetime, time
+from concurrent.futures import ThreadPoolExecutor
+import os
+import gzip
+import pickle
+import random
+from alpaca.data.models import BarSet, QuoteSet, TradeSet
+import v2realbot.utils.config_handler as cfh
+from v2realbot.enums.enums import BarType
+from tqdm import tqdm
+""""
+Module used for vectorized aggregation of trades.
+
+Includes fetch (remote/cached) methods and numba aggregator function for TIME BASED, VOLUME BASED and DOLLAR BARS
+
+"""""
+
+def aggregate_trades(symbol: str, trades_df: pd.DataFrame, resolution: int, type: BarType = BarType.TIME):
+    """"
+    Accepts dataframe with trades keyed by symbol. Preparess dataframe to 
+    numpy and calls Numba optimized aggregator for given bar type. (time/volume/dollar)
+    """""
+    trades_df = trades_df.loc[symbol]
+    trades_df= trades_df.reset_index()
+    ticks = trades_df[['timestamp', 'price', 'size']].to_numpy()
+    # Extract the timestamps column (assuming it's the first column)
+    timestamps = ticks[:, 0]
+    # Convert the timestamps to Unix timestamps in seconds with microsecond precision
+    unix_timestamps_s = np.array([ts.timestamp() for ts in timestamps], dtype='float64')
+    # Replace the original timestamps in the NumPy array with the converted Unix timestamps
+    ticks[:, 0] = unix_timestamps_s
+    ticks = ticks.astype(np.float64)
+    #based on type, specific aggregator function is called
+    match type:
+        case BarType.TIME:
+            ohlcv_bars = generate_time_bars_nb(ticks, resolution)
+        case BarType.VOLUME:
+            ohlcv_bars = generate_volume_bars_nb(ticks, resolution)
+        case BarType.DOLLAR:
+            ohlcv_bars = generate_dollar_bars_nb(ticks, resolution)
+        case _:
+            raise ValueError("Invalid bar type. Supported types are 'time', 'volume' and 'dollar'.")
+    # Convert the resulting array back to a DataFrame
+    columns = ['time', 'open', 'high', 'low', 'close', 'volume', 'trades']
+    if type == BarType.DOLLAR:
+        columns.append('amount')
+    columns.append('updated')
+    if type == BarType.TIME:
+        columns.append('vwap')
+        columns.append('buyvolume')
+        columns.append('sellvolume')
+    if type == BarType.VOLUME:
+        columns.append('buyvolume')
+        columns.append('sellvolume')
+    ohlcv_df = pd.DataFrame(ohlcv_bars, columns=columns)
+    ohlcv_df['time'] = pd.to_datetime(ohlcv_df['time'], unit='s').dt.tz_localize('UTC').dt.tz_convert(zoneNY)
+    #print(ohlcv_df['updated'])
+    ohlcv_df['updated'] = pd.to_datetime(ohlcv_df['updated'], unit="s").dt.tz_localize('UTC').dt.tz_convert(zoneNY)
+    # Round to microseconds to maintain six decimal places
+    ohlcv_df['updated'] = ohlcv_df['updated'].dt.round('us')
+
+    ohlcv_df.set_index('time', inplace=True)
+    #ohlcv_df.index = ohlcv_df.index.tz_localize('UTC').tz_convert(zoneNY)
+    return ohlcv_df
+
+# Function to ensure fractional seconds are present
+def ensure_fractional_seconds(timestamp):
+    if '.' not in timestamp:
+        # Inserting .000000 before the timezone indicator 'Z'
+        return timestamp.replace('Z', '.000000Z')
+    else:
+        return timestamp
+
+def convert_dict_to_multiindex_df(tradesResponse):
+    """"
+    Converts dictionary from cache or from remote (raw input) to multiindex dataframe.
+    with microsecond precision (from nanoseconds in the raw data)
+    """""
+    # Create a DataFrame for each key and add the key as part of the MultiIndex
+    dfs = []
+    for key, values in tradesResponse.items():
+        df = pd.DataFrame(values)
+        # Rename columns
+        # Select and order columns explicitly
+        #print(df)
+        df = df[['t', 'x', 'p', 's', 'i', 'c','z']]
+        df.rename(columns={'t': 'timestamp', 'c': 'conditions', 'p': 'price', 's': 'size', 'x': 'exchange', 'z':'tape', 'i':'id'}, inplace=True)
+        df['symbol'] = key  # Add ticker as a column
+
+        # Apply the function to ensure all timestamps have fractional seconds
+        #zvazit zda toto ponechat a nebo dat jen pri urcitem erroru pri to_datetime
+        #pripadne pak pridelat efektivnejsi pristup, aneb nahrazeni NaT - https://chatgpt.com/c/d2be6f87-b38f-4050-a1c6-541d100b1474
+        df['timestamp'] = df['timestamp'].apply(ensure_fractional_seconds)
+
+        df['timestamp'] = pd.to_datetime(df['timestamp'], errors='coerce')  # Convert 't' from string to datetime before setting it as an index
+
+        #Adjust to microsecond precision
+        df.loc[df['timestamp'].notna(), 'timestamp'] = df['timestamp'].dt.floor('us')
+
+        df.set_index(['symbol', 'timestamp'], inplace=True)  # Set the multi-level index using both 'ticker' and 't'
+        df = df.tz_convert(zoneNY, level='timestamp')
+        dfs.append(df)
+
+    # Concatenate all DataFrames into a single DataFrame with MultiIndex
+    final_df = pd.concat(dfs)
+
+    return final_df
+
+def dict_to_df(tradesResponse, start, end, exclude_conditions = None, minsize = None):
+    """"
+    Transforms dict to Tradeset, then df and to zone aware
+    Also filters to start and end if necessary (ex. 9:30 to 15:40 is required only)
+   
+   NOTE: prepodkladame, ze tradesResponse je dict from Raw data (cached/remote)
+   """""
+
+    df = convert_dict_to_multiindex_df(tradesResponse)
+
+    #REQUIRED FILTERING
+    #pokud je zacatek pozdeji nebo konec driv tak orizneme
+    if (start.time() > time(9, 30) or end.time() < time(16, 0)):
+        print(f"filtrujeme {start.time()} {end.time()}")
+        # Define the time range
+        # start_time = pd.Timestamp(start.time(), tz=zoneNY).time()
+        # end_time = pd.Timestamp(end.time(), tz=zoneNY).time()
+
+        # Create a mask to filter rows within the specified time range
+        mask = (df.index.get_level_values('timestamp') >= start) & \
+            (df.index.get_level_values('timestamp') <= end)
+
+        # Apply the mask to the DataFrame
+        df = df[mask]
+
+    if exclude_conditions is not None:
+        print(f"excluding conditions {exclude_conditions}")
+        # Create a mask to exclude rows with any of the specified conditions
+        mask = df['conditions'].apply(lambda x: any(cond in exclude_conditions for cond in x))
+
+        # Filter out the rows with specified conditions
+        df = df[~mask]
+
+    if minsize is not None:
+        print(f"minsize {minsize}")
+        #exclude conditions
+        df = df[df['size'] >= minsize]
+    return df
+
+def fetch_daily_stock_trades(symbol, start, end, exclude_conditions=None, minsize=None, force_remote=False, max_retries=5, backoff_factor=1):
+    #doc for this function
+    """
+    Attempts to fetch stock trades either from cache or remote. When remote, it uses retry mechanism with exponential backoff.
+    Also it stores the data to cache if it is not already there.
+    by using force_remote - forcess using remote data always and thus refreshing cache for these dates
+        Attributes:
+        :param symbol: The stock symbol to fetch trades for.
+        :param start: The start time for the trade data.
+        :param end: The end time for the trade data.
+        :exclude_conditions: list of string conditions to exclude from the data
+        :minsize minimum size of trade to be included in the data
+        :force_remote will always use remote data and refresh cache
+        :param max_retries: Maximum number of retries.
+        :param backoff_factor: Factor to determine the next sleep time.
+        :return: TradesResponse object.
+        :raises: ConnectionError if all retries fail.
+    
+    We use tradecache only for main sessison requests = 9:30 to 16:00
+    Do budoucna ukládat celý den BAC-20240203.cache.gz a z toho si pak filtrovat bud main sesssionu a extended
+    Ale zatim je uloženo jen main session v BAC-timestampopenu-timestampclose.cache.gz
+    """
+    is_same_day = start.date() == end.date()
+    # Determine if the requested times fall within the main session
+    in_main_session = (time(9, 30) <= start.time() < time(16, 0)) and (time(9, 30) <= end.time() <= time(16, 0))
+    file_path = ''
+    
+    if in_main_session:
+        filename_start = zoneNY.localize(datetime.combine(start.date(), time(9, 30)))
+        filename_end = zoneNY.localize(datetime.combine(end.date(), time(16, 0)))
+        daily_file = f"{symbol}-{int(filename_start.timestamp())}-{int(filename_end.timestamp())}.cache.gz"
+        file_path = f"{DATA_DIR}/tradecache/{daily_file}"
+        if not force_remote and os.path.exists(file_path):
+            print(f"Searching {str(start.date())} cache: " + daily_file)
+            with gzip.open(file_path, 'rb') as fp:
+                tradesResponse = pickle.load(fp)
+                print("FOUND in CACHE", daily_file)
+                return dict_to_df(tradesResponse, start, end, exclude_conditions, minsize)
+
+    print("NOT FOUND. Fetching from remote")
+    client = StockHistoricalDataClient(ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, raw_data=True)
+    stockTradeRequest = StockTradesRequest(symbol_or_symbols=symbol, start=start, end=end)
+    last_exception = None
+
+    for attempt in range(max_retries):
+        try:
+            tradesResponse = client.get_stock_trades(stockTradeRequest)
+            is_empty = not tradesResponse[symbol]
+            print(f"Remote fetched: {is_empty=}", start, end)
+            if in_main_session and not is_empty:
+                current_time = datetime.now().astimezone(zoneNY)
+                if not (start < current_time < end):
+                    with gzip.open(file_path, 'wb') as fp:
+                        pickle.dump(tradesResponse, fp)
+                        print("Saving to Trade CACHE", file_path)
+
+                else:  # Don't save the cache if the market is still open
+                    print("Not saving trade cache, market still open today")
+            return pd.DataFrame() if is_empty else dict_to_df(tradesResponse, start, end, exclude_conditions, minsize) 
+        except Exception as e:
+            print(f"Attempt {attempt + 1} failed: {e}")
+            last_exception = e
+            time_module.sleep(backoff_factor * (2 ** attempt) + random.uniform(0, 1))  # Adding random jitter
+
+    print("All attempts to fetch data failed.")
+    raise ConnectionError(f"Failed to fetch stock trades after {max_retries} retries. Last exception: {str(last_exception)} and {format_exc()}")
+
+
+def fetch_trades_parallel(symbol, start_date, end_date, exclude_conditions = cfh.config_handler.get_val('AGG_EXCLUDED_TRADES'), minsize = 100, force_remote = False, max_workers=None):
+    """
+    Fetches trades for each day between start_date and end_date during market hours (9:30-16:00) in parallel and concatenates them into a single DataFrame.
+
+    :param symbol: Stock symbol.
+    :param start_date: Start date as datetime.
+    :param end_date: End date as datetime.
+    :return: DataFrame containing all trades from start_date to end_date.
+    """
+    futures = []
+    results = []
+    
+    market_open_days = fetch_calendar_data(start_date, end_date)
+    day_count = len(market_open_days)
+    print("Contains", day_count, " market days")
+    max_workers = min(10, max(2, day_count // 2)) if max_workers is None else max_workers  # Heuristic: half the days to process, but at least 1 and no more than 10
+
+    with ThreadPoolExecutor(max_workers=max_workers) as executor:
+        #for single_date in (start_date + timedelta(days=i) for i in range((end_date - start_date).days + 1)):
+        for market_day in tqdm(market_open_days, desc="Processing market days"):
+            #start = datetime.combine(single_date, time(9, 30))  # Market opens at 9:30 AM
+            #end = datetime.combine(single_date, time(16, 0))   # Market closes at 4:00 PM
+            
+            interval_from = zoneNY.localize(market_day.open)
+            interval_to = zoneNY.localize(market_day.close)
+
+            #pripadne orizneme pokud je pozadovane pozdejsi zacatek a drivejsi konek
+            start = start_date if interval_from < start_date else interval_from
+            #start = max(start_date, interval_from)
+            end = end_date if interval_to > end_date else interval_to
+            #end = min(end_date, interval_to)
+
+            future = executor.submit(fetch_daily_stock_trades, symbol, start, end, exclude_conditions, minsize, force_remote)
+            futures.append(future)
+        
+        for future in tqdm(futures, desc="Fetching data"):
+            try:
+                result = future.result()
+                results.append(result)
+            except Exception as e:
+                print(f"Error fetching data for a day: {e}")
+
+    # Batch concatenation to improve speed
+    batch_size = 10
+    batches = [results[i:i + batch_size] for i in range(0, len(results), batch_size)]
+    final_df = pd.concat([pd.concat(batch, ignore_index=False) for batch in batches], ignore_index=False)
+
+    return final_df
+
+    #original version
+    #return pd.concat(results, ignore_index=False)
+
+@jit(nopython=True)
+def generate_dollar_bars_nb(ticks, amount_per_bar):
+    """"
+    Generates Dollar based bars from ticks.
+
+    There is also simple prevention of aggregation from different days
+    as described here https://chatgpt.com/c/17804fc1-a7bc-495d-8686-b8392f3640a2
+    Downside: split days by UTC (which is ok for main session, but when extended hours it should be reworked by preprocessing new column identifying session)
+    
+    
+    When trade is split into multiple bars it is counted as trade in each of the bars.
+    Other option: trade count can be proportionally distributed by weight (0.2 to 1st bar, 0.8 to 2nd bar) - but this is not implemented yet
+    https://chatgpt.com/c/ff4802d9-22a2-4b72-8ab7-97a91e7a515f
+    """""
+    ohlcv_bars = []
+    remaining_amount = amount_per_bar
+
+    # Initialize bar values based on the first tick to avoid uninitialized values
+    open_price = ticks[0, 1]
+    high_price = ticks[0, 1]
+    low_price = ticks[0, 1]
+    close_price = ticks[0, 1]
+    volume = 0
+    trades_count = 0
+    current_day = np.floor(ticks[0, 0] / 86400)  # Calculate the initial day from the first tick timestamp
+    bar_time = ticks[0, 0]  # Initialize bar time with the time of the first tick
+
+    for tick in ticks:
+        tick_time = tick[0]
+        price = tick[1]
+        tick_volume = tick[2]
+        tick_amount = price * tick_volume
+        tick_day = np.floor(tick_time / 86400)  # Calculate the day of the current tick
+
+        # Check if the new tick is from a different day, then close the current bar
+        if tick_day != current_day:
+            if trades_count > 0:
+                ohlcv_bars.append([bar_time, open_price, high_price, low_price, close_price, volume, trades_count, amount_per_bar, tick_time])
+            # Reset for the new day using the current tick data
+            open_price = price
+            high_price = price
+            low_price = price
+            close_price = price
+            volume = 0
+            trades_count = 0
+            remaining_amount = amount_per_bar
+            current_day = tick_day
+            bar_time = tick_time
+
+        # Start new bar if needed because of the dollar value
+        while tick_amount > 0:
+            if tick_amount < remaining_amount:
+                # Add the entire tick to the current bar
+                high_price = max(high_price, price)
+                low_price = min(low_price, price)
+                close_price = price
+                volume += tick_volume
+                remaining_amount -= tick_amount
+                trades_count += 1
+                tick_amount = 0
+            else:
+                # Calculate the amount of volume that fits within the remaining dollar amount
+                volume_to_add = remaining_amount / price
+                volume += volume_to_add  # Update the volume here before appending and resetting
+
+                # Append the partially filled bar to the list
+                ohlcv_bars.append([bar_time, open_price, high_price, low_price, close_price, volume, trades_count + 1, amount_per_bar, tick_time])
+
+                # Fill the current bar and continue with a new bar
+                tick_volume -= volume_to_add
+                tick_amount -= remaining_amount
+
+                # Reset bar values for the new bar using the current tick data
+                open_price = price
+                high_price = price
+                low_price = price
+                close_price = price
+                volume = 0  # Reset volume for the new bar
+                trades_count = 0
+                remaining_amount = amount_per_bar
+                
+                # Increment bar time if splitting a trade
+                if tick_volume > 0: #pokud v tradu je jeste zbytek nastavujeme cas o nanosekundu vetsi
+                    bar_time = tick_time + 1e-6
+                else:
+                    bar_time = tick_time #jinak nastavujeme cas ticku
+                #bar_time = tick_time
+
+    # Add the last bar if it contains any trades
+    if trades_count > 0:
+        ohlcv_bars.append([bar_time, open_price, high_price, low_price, close_price, volume, trades_count, amount_per_bar, tick_time])
+
+    return np.array(ohlcv_bars)
+
+
+@jit(nopython=True)
+def generate_volume_bars_nb(ticks, volume_per_bar):
+    """"
+    Generates Volume based bars from ticks.
+    
+    NOTE: UTC day split here (doesnt aggregate trades from different days)
+    but realized from UTC (ok for main session) - but needs rework for extension by preprocessing ticks_df and introduction sesssion column
+    
+    When trade is split into multiple bars it is counted as trade in each of the bars.
+    Other option: trade count can be proportionally distributed by weight (0.2 to 1st bar, 0.8 to 2nd bar) - but this is not implemented yet
+    https://chatgpt.com/c/ff4802d9-22a2-4b72-8ab7-97a91e7a515f
+    """""
+    ohlcv_bars = []
+    remaining_volume = volume_per_bar
+
+    # Initialize bar values based on the first tick to avoid uninitialized values
+    open_price = ticks[0, 1]
+    high_price = ticks[0, 1]
+    low_price = ticks[0, 1]
+    close_price = ticks[0, 1]
+    volume = 0
+    trades_count = 0
+    current_day = np.floor(ticks[0, 0] / 86400)  # Calculate the initial day from the first tick timestamp
+    bar_time = ticks[0, 0]  # Initialize bar time with the time of the first tick
+    buy_volume = 0  # Volume of buy trades
+    sell_volume = 0  # Volume of sell trades
+    prev_price = ticks[0, 1]  # Initialize previous price for the first tick
+
+    for tick in ticks:
+        tick_time = tick[0]
+        price = tick[1]
+        tick_volume = tick[2]
+        tick_day = np.floor(tick_time / 86400)  # Calculate the day of the current tick
+
+        # Check if the new tick is from a different day, then close the current bar
+        if tick_day != current_day:
+            if trades_count > 0:
+                ohlcv_bars.append([bar_time, open_price, high_price, low_price, close_price, volume, trades_count, tick_time, buy_volume, sell_volume])
+            # Reset for the new day using the current tick data
+            open_price = price
+            high_price = price
+            low_price = price
+            close_price = price
+            volume = 0
+            trades_count = 0
+            remaining_volume = volume_per_bar
+            current_day = tick_day
+            bar_time = tick_time  # Update bar time to the current tick time
+            buy_volume = 0
+            sell_volume = 0
+            # Reset previous tick price (calulating imbalance for each day from the start)
+            prev_price = price
+
+        # Start new bar if needed because of the volume
+        while tick_volume > 0:
+            if tick_volume < remaining_volume:
+                # Add the entire tick to the current bar
+                high_price = max(high_price, price)
+                low_price = min(low_price, price)
+                close_price = price
+                volume += tick_volume
+                remaining_volume -= tick_volume
+                trades_count += 1
+                
+                # Update buy and sell volumes
+                if price > prev_price:
+                    buy_volume += tick_volume
+                elif price < prev_price:
+                    sell_volume += tick_volume
+                
+                tick_volume = 0
+            else:
+                # Fill the current bar and continue with a new bar
+                volume_to_add = remaining_volume
+                volume += volume_to_add
+                tick_volume -= volume_to_add
+                trades_count += 1
+                
+                # Update buy and sell volumes
+                if price > prev_price:
+                    buy_volume += volume_to_add
+                elif price < prev_price:
+                    sell_volume += volume_to_add
+                
+                # Append the completed bar to the list
+                ohlcv_bars.append([bar_time, open_price, high_price, low_price, close_price, volume, trades_count, tick_time, buy_volume, sell_volume])
+
+                # Reset bar values for the new bar using the current tick data
+                open_price = price
+                high_price = price
+                low_price = price
+                close_price = price
+                volume = 0
+                trades_count = 0
+                remaining_volume = volume_per_bar
+                buy_volume = 0
+                sell_volume = 0
+                
+                # Increment bar time if splitting a trade
+                if tick_volume > 0: # If there's remaining volume in the trade, set bar time slightly later
+                    bar_time = tick_time + 1e-6
+                else:
+                    bar_time = tick_time # Otherwise, set bar time to the tick time
+
+        prev_price = price
+
+    # Add the last bar if it contains any trades
+    if trades_count > 0:
+        ohlcv_bars.append([bar_time, open_price, high_price, low_price, close_price, volume, trades_count, tick_time, buy_volume, sell_volume])
+
+    return np.array(ohlcv_bars)
+
+@jit(nopython=True)
+def generate_time_bars_nb(ticks, resolution):
+    # Initialize the start and end time
+    start_time = np.floor(ticks[0, 0] / resolution) * resolution
+    end_time = np.floor(ticks[-1, 0] / resolution) * resolution
+    
+    # # Calculate number of bars
+    # num_bars = int((end_time - start_time) // resolution + 1)
+    
+    # Using a list to append data only when trades exist
+    ohlcv_bars = []
+    
+    # Variables to track the current bar
+    current_bar_index = -1
+    open_price = 0
+    high_price = -np.inf
+    low_price = np.inf
+    close_price = 0
+    volume = 0
+    trades_count = 0
+    vwap_cum_volume_price = 0  # Cumulative volume * price
+    cum_volume = 0  # Cumulative volume for VWAP
+    buy_volume = 0  # Volume of buy trades
+    sell_volume = 0  # Volume of sell trades
+    prev_price = ticks[0, 1]  # Initialize previous price for the first tick
+    prev_day = np.floor(ticks[0, 0] / 86400)  # Calculate the initial day from the first tick timestamp
+    
+    for tick in ticks:
+        curr_time = tick[0] #updated time
+        tick_time = np.floor(tick[0] / resolution) * resolution
+        price = tick[1]
+        tick_volume = tick[2]
+        tick_day = np.floor(tick_time / 86400)  # Calculate the day of the current tick
+
+        #if the new tick is from a new day, reset previous tick price (calculating imbalance starts over)
+        if tick_day != prev_day:
+            prev_price = price
+            prev_day = tick_day
+
+        # Check if the tick belongs to a new bar
+        if tick_time != start_time + current_bar_index * resolution:
+            if current_bar_index >= 0 and trades_count > 0:  # Save the previous bar if trades happened
+                vwap = vwap_cum_volume_price / cum_volume if cum_volume > 0 else 0
+                ohlcv_bars.append([start_time + current_bar_index * resolution, open_price, high_price, low_price, close_price, volume, trades_count, curr_time, vwap, buy_volume, sell_volume])
+            
+            # Reset bar values
+            current_bar_index = int((tick_time - start_time) / resolution)
+            open_price = price
+            high_price = price
+            low_price = price
+            volume = 0
+            trades_count = 0
+            vwap_cum_volume_price = 0
+            cum_volume = 0
+            buy_volume = 0
+            sell_volume = 0
+        
+        # Update the OHLCV values for the current bar
+        high_price = max(high_price, price)
+        low_price = min(low_price, price)
+        close_price = price
+        volume += tick_volume
+        trades_count += 1
+        vwap_cum_volume_price += price * tick_volume
+        cum_volume += tick_volume
+
+        # Update buy and sell volumes
+        if price > prev_price:
+            buy_volume += tick_volume
+        elif price < prev_price:
+            sell_volume += tick_volume
+        
+        prev_price = price
+
+    # Save the last processed bar
+    if trades_count > 0:
+        vwap = vwap_cum_volume_price / cum_volume if cum_volume > 0 else 0
+        ohlcv_bars.append([start_time + current_bar_index * resolution, open_price, high_price, low_price, close_price, volume, trades_count, curr_time, vwap, buy_volume, sell_volume])
+    
+    return np.array(ohlcv_bars)
+
+# Example usage
+if __name__ == '__main__':
+    pass
+    #example in agg_vect.ipynb

v2realbot/loader/trade_offline_streamer.py

@@ -1,14 +1,13 @@
 from v2realbot.loader.aggregator import TradeAggregator, TradeAggregator2List, TradeAggregator2Queue
 #from v2realbot.loader.cacher import get_cached_agg_data
 from alpaca.trading.requests import GetCalendarRequest
-from alpaca.trading.client import TradingClient
 from alpaca.data.live import StockDataStream
-from v2realbot.config import ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, DATA_DIR, OFFLINE_MODE
+from v2realbot.config import ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, DATA_DIR
 from alpaca.data.enums import DataFeed
 from alpaca.data.historical import StockHistoricalDataClient
 from alpaca.data.requests import StockLatestQuoteRequest, StockBarsRequest, StockTradesRequest
 from threading import Thread, current_thread
-from v2realbot.utils.utils import parse_alpaca_timestamp, ltp, zoneNY
+from v2realbot.utils.utils import parse_alpaca_timestamp, ltp, zoneNY, send_to_telegram, fetch_calendar_data
 from v2realbot.utils.tlog import tlog
 from datetime import datetime, timedelta, date
 from threading import Thread
@@ -26,13 +25,15 @@ from tqdm import tqdm
 import time
 from traceback import format_exc
 from collections import defaultdict
+import requests
+import v2realbot.utils.config_handler as cfh
 """
     Trade offline data streamer, based on Alpaca historical data.
 """
 class Trade_Offline_Streamer(Thread):
     #pro BT se pripojujeme vzdy k primarnimu uctu - pouze tahame historicka data + calendar
     client =  StockHistoricalDataClient(ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, raw_data=True)
-    clientTrading = TradingClient(ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, raw_data=False)
+    #clientTrading = TradingClient(ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, raw_data=False)
     def __init__(self, time_from: datetime, time_to: datetime, btdata) -> None:
        # Call the Thread class's init function
        Thread.__init__(self)
@@ -64,6 +65,35 @@ class Trade_Offline_Streamer(Thread):
     def stop(self):
         pass
 
+    def fetch_stock_trades(self, symbol, start, end, max_retries=5, backoff_factor=1):
+        """
+        Attempts to fetch stock trades with exponential backoff. Raises an exception if all retries fail.
+
+        :param symbol: The stock symbol to fetch trades for.
+        :param start: The start time for the trade data.
+        :param end: The end time for the trade data.
+        :param max_retries: Maximum number of retries.
+        :param backoff_factor: Factor to determine the next sleep time.
+        :return: TradesResponse object.
+        :raises: ConnectionError if all retries fail.
+        """
+        stockTradeRequest = StockTradesRequest(symbol_or_symbols=symbol, start=start, end=end)
+        last_exception = None
+
+        for attempt in range(max_retries):
+            try:
+                tradesResponse = self.client.get_stock_trades(stockTradeRequest)
+                print("Remote Fetch DAY DATA Complete", start, end)
+                return tradesResponse
+            except Exception as e:
+                print(f"Attempt {attempt + 1} failed: {e}")
+                last_exception = e
+                time.sleep(backoff_factor * (2 ** attempt))
+
+        print("All attempts to fetch data failed.")
+        send_to_telegram(f"Failed to fetch stock trades after {max_retries} retries. Last exception: {str(last_exception)} and {format_exc()}")
+        raise ConnectionError(f"Failed to fetch stock trades after {max_retries} retries. Last exception: {str(last_exception)} and {format_exc()}")
+
    # Override the run() function of Thread class
    #odebrano async
     def main(self):
@@ -74,6 +104,8 @@ class Trade_Offline_Streamer(Thread):
             print("call add streams to queue first")
             return 0
         
+        cfh.config_handler.print_current_config()
+
         #iterujeme nad streamy
         for i in self.streams:
             self.uniquesymbols.add(i.symbol)
@@ -107,25 +139,21 @@ class Trade_Offline_Streamer(Thread):
         #datetime.fromtimestamp(data['updated']).astimezone(zoneNY))
         #REFACTOR STARTS HERE
         #print(f"{self.time_from=} {self.time_to=}")
-              
-        if OFFLINE_MODE:
+ 
+        if cfh.config_handler.get_val('OFFLINE_MODE'):
             #just one day - same like time_from
             den = str(self.time_to.date())
             bt_day = Calendar(date=den,open="9:30",close="16:00")
             cal_dates = [bt_day]
         else:
-            calendar_request = GetCalendarRequest(start=self.time_from,end=self.time_to)
-
-            #toto zatim workaround - dat do retry funkce a obecne vymyslet exception handling, abych byl notifikovan a bylo videt okamzite v logu a na frontendu
-            try:
-                cal_dates = self.clientTrading.get_calendar(calendar_request)
-            except Exception as e:
-                print("CHYBA - retrying in 4s: " + str(e) + format_exc())
-                time.sleep(5)
-                cal_dates = self.clientTrading.get_calendar(calendar_request)
+            start_date = self.time_from  # Assuming this is your start date
+            end_date = self.time_to  # Assuming this is your end date
+            cal_dates = fetch_calendar_data(start_date, end_date)
 
             #zatim podpora pouze main session
         
+        live_data_feed = cfh.config_handler.get_val('LIVE_DATA_FEED')
+
         #zatim podpora pouze 1 symbolu, predelat na froloop vsech symbolu ze symbpole
         #minimalni jednotka pro CACHE je 1 den - a to jen marketopen to marketclose (extended hours not supported yet)
         for day in cal_dates:
@@ -168,9 +196,10 @@ class Trade_Offline_Streamer(Thread):
             #         stream.send_cache_to_output(cache)
             #         to_rem.append(stream)
 
-            #cache resime jen kdyz backtestujeme cely den
+            #cache resime jen kdyz backtestujeme cely den a mame sip datapoint (iex necachujeme)
             #pokud ne tak ani necteme, ani nezapisujeme do cache
-            if self.time_to >= day.close and self.time_from <= day.open:
+
+            if (self.time_to >= day.close and self.time_from <= day.open) and live_data_feed == DataFeed.SIP:
                 #tento odstavec obchazime pokud je nastaveno "dont_use_cache"
                 stream_btdata = self.to_run[symbpole[0]][0]
                 cache_btdata, file_btdata = stream_btdata.get_cache(day.open, day.close)
@@ -213,14 +242,22 @@ class Trade_Offline_Streamer(Thread):
                     print("Loading from Trade CACHE", file_path)
             #daily file doesnt exist
             else:
-                # TODO refactor pro zpracovani vice symbolu najednou(multithreads), nyni predpokladame pouze 1 
-                stockTradeRequest = StockTradesRequest(symbol_or_symbols=symbpole[0], start=day.open,end=day.close)
-                tradesResponse = self.client.get_stock_trades(stockTradeRequest)
+
+                #implement retry mechanism
+                symbol = symbpole[0]  # Assuming symbpole[0] is your target symbol
+                day_open = day.open  # Assuming day.open is the start time
+                day_close = day.close  # Assuming day.close is the end time
+
+                tradesResponse = self.fetch_stock_trades(symbol, day_open, day_close)
+
+                # # TODO refactor pro zpracovani vice symbolu najednou(multithreads), nyni predpokladame pouze 1 
+                # stockTradeRequest = StockTradesRequest(symbol_or_symbols=symbpole[0], start=day.open,end=day.close)
+                # tradesResponse = self.client.get_stock_trades(stockTradeRequest)
                 print("Remote Fetch DAY DATA Complete", day.open, day.close)
 
-                #pokud jde o dnešní den a nebyl konec trhu tak cache neukládáme
-                if day.open < datetime.now().astimezone(zoneNY) < day.close:
-                    print("not saving trade cache, market still open today")
+                #pokud jde o dnešní den a nebyl konec trhu tak cache neukládáme, pripadne pri iex datapointu necachujeme
+                if (day.open < datetime.now().astimezone(zoneNY) < day.close) or live_data_feed == DataFeed.IEX:
+                    print("not saving trade cache, market still open today or IEX datapoint")
                     #ic(datetime.now().astimezone(zoneNY))
                     #ic(day.open, day.close)
                 else:
@@ -258,7 +295,7 @@ class Trade_Offline_Streamer(Thread):
                 cnt = 1
                 
                 
-                for t in tqdm(tradesResponse[symbol]):
+                for t in tqdm(tradesResponse[symbol], desc="Loading Trades"):
                     
                     #protoze je zde cely den, poustime dal, jen ty relevantni
                     #pokud je    start_time < trade < end_time
@@ -271,6 +308,9 @@ class Trade_Offline_Streamer(Thread):
                     #tmp = to_datetime(t['t'], utc=True).timestamp()
                     
 
+                    #obcas se v response objevoval None radek
+                    if t is None:
+                        continue
 
                     datum = to_datetime(t['t'], utc=True)
 

v2realbot/loader/trade_ws_streamer.py

@@ -4,7 +4,7 @@
 """
 from v2realbot.loader.aggregator import TradeAggregator2Queue
 from alpaca.data.live import StockDataStream
-from v2realbot.config import ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, ACCOUNT1_PAPER_FEED
+from v2realbot.config import LIVE_DATA_API_KEY, LIVE_DATA_SECRET_KEY
 from alpaca.data.historical import StockHistoricalDataClient
 from alpaca.data.requests import StockLatestQuoteRequest, StockBarsRequest, StockTradesRequest
 from threading import Thread, current_thread
@@ -12,6 +12,7 @@ from v2realbot.utils.utils import parse_alpaca_timestamp, ltp
 from datetime import datetime, timedelta
 from threading import Thread, Lock
 from msgpack import packb
+import v2realbot.utils.config_handler as cfh
 
 """
     Shared streamer (can be shared amongst concurrently running strategies)
@@ -19,9 +20,12 @@ from msgpack import packb
     by strategies
 """
 class Trade_WS_Streamer(Thread):
-
+    live_data_feed = cfh.config_handler.get_val('LIVE_DATA_FEED')
     ##tento ws streamer je pouze jeden pro vsechny, tzn. vyuziváme natvrdo placena data primarniho uctu (nezalezi jestli paper nebo live)
-    client = StockDataStream(ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, raw_data=True, websocket_params={}, feed=ACCOUNT1_PAPER_FEED)
+    msg = f"Realtime Websocket connection will use FEED: {live_data_feed} and credential of ACCOUNT1"
+    print(msg)
+    #cfh.config_handler.print_current_config()
+    client = StockDataStream(LIVE_DATA_API_KEY, LIVE_DATA_SECRET_KEY, raw_data=True, websocket_params={}, feed=live_data_feed)
     #uniquesymbols = set()
     _streams = []
     #to_run = dict()
@@ -38,10 +42,23 @@ class Trade_WS_Streamer(Thread):
         return False
 
     def add_stream(self, obj: TradeAggregator2Queue):
+        print(Trade_WS_Streamer.msg)
         print("stav pred pridavanim", Trade_WS_Streamer._streams)
         Trade_WS_Streamer._streams.append(obj)
         if Trade_WS_Streamer.client._running is False:
             print("websocket zatim nebezi, pouze pridavame do pole")
+
+            #zde delame refresh clienta (pokud se zmenilo live_data_feed)
+
+            # live_data_feed = cfh.config_handler.get_val('LIVE_DATA_FEED')
+            # #po otestování přepnout jen pokud se live_data_feed změnil
+            # #if live_data_feed != Trade_WS_Streamer.live_data_feed:
+            # #    Trade_WS_Streamer.live_data_feed = live_data_feed
+            # msg = f"REFRESH OF CLIENT! Realtime Websocket connection will use FEED: {live_data_feed} and credential of ACCOUNT1"
+            # print(msg)
+            # #cfh.config_handler.print_current_config()
+            # Trade_WS_Streamer.client = StockDataStream(LIVE_DATA_API_KEY, LIVE_DATA_SECRET_KEY, raw_data=True, websocket_params={}, feed=live_data_feed)
+
         else:
             print("websocket client bezi")
             if self.symbol_exists(obj.symbol):
@@ -59,7 +76,12 @@ class Trade_WS_Streamer(Thread):
         #if it is the last item at all, stop the client from running
         if len(Trade_WS_Streamer._streams) == 0:
             print("removed last item from WS, stopping the client")
-            Trade_WS_Streamer.client.stop()
+            #Trade_WS_Streamer.client.stop_ws()
+            #Trade_WS_Streamer.client.stop()
+            #zkusíme explicitně zavolat kroky pro disconnect od ws
+            if Trade_WS_Streamer.client._stop_stream_queue.empty():
+                Trade_WS_Streamer.client._stop_stream_queue.put_nowait({"should_stop": True})
+            Trade_WS_Streamer.client._should_run = False
             return
         
         if not self.symbol_exists(obj.symbol):

v2realbot/main.py

@@ -1,7 +1,7 @@
 import os,sys
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 os.environ["KERAS_BACKEND"] = "jax"
-from v2realbot.config import WEB_API_KEY, DATA_DIR, MEDIA_DIRECTORY, LOG_FILE, MODEL_DIR
+from v2realbot.config import WEB_API_KEY, DATA_DIR, MEDIA_DIRECTORY, LOG_PATH, MODEL_DIR
 from alpaca.data.timeframe import TimeFrame, TimeFrameUnit
 from datetime import datetime
 from rich import print
@@ -9,16 +9,16 @@ from fastapi import FastAPI, Depends, HTTPException, status, File, UploadFile, R
 from fastapi.security import APIKeyHeader
 import uvicorn
 from uuid import UUID
-import v2realbot.controller.services as cs
 from v2realbot.utils.ilog import get_log_window
-from v2realbot.common.model import StrategyInstance, RunnerView, RunRequest, Trade, RunArchive, RunArchiveView, RunArchiveViewPagination, RunArchiveDetail, Bar, RunArchiveChange, TestList, ConfigItem, InstantIndicator, DataTablesRequest, AnalyzerInputs
-from fastapi import FastAPI, WebSocket, WebSocketDisconnect, Depends, HTTPException, status, WebSocketException, Cookie, Query
+from v2realbot.common.model import RunManagerRecord, StrategyInstance, RunnerView, RunRequest, Trade, RunArchive, RunArchiveView, RunArchiveViewPagination, RunArchiveDetail, Bar, RunArchiveChange, TestList, ConfigItem, InstantIndicator, DataTablesRequest, AnalyzerInputs
+from fastapi import FastAPI, WebSocket, WebSocketDisconnect, Depends, HTTPException, status, WebSocketException, Cookie, Query, Request
 from fastapi.responses import FileResponse, StreamingResponse, JSONResponse
 from fastapi.staticfiles import StaticFiles
 from fastapi.security import HTTPBasic, HTTPBasicCredentials
 from v2realbot.enums.enums import Env, Mode
 from typing import Annotated
 import os
+import psutil
 import uvicorn
 import orjson
 from queue import Queue, Empty
@@ -36,9 +36,15 @@ from traceback import format_exc
 #from v2realbot.reporting.optimizecutoffs import find_optimal_cutoff
 import v2realbot.reporting.analyzer as ci
 import shutil
-from starlette.responses import JSONResponse
+from starlette.responses import JSONResponse, HTMLResponse, FileResponse, RedirectResponse
 import mlroom
 import mlroom.utils.mlutils as ml
+from typing import List
+import v2realbot.controller.run_manager as rm
+import v2realbot.scheduler.ap_scheduler as aps
+import re
+import v2realbot.controller.configs as cf
+import v2realbot.controller.services as cs
 #from async io import Queue, QueueEmpty
 #              
 # install()
@@ -69,14 +75,52 @@ def api_key_auth(api_key: str = Depends(X_API_KEY)):
             status_code=status.HTTP_401_UNAUTHORIZED,
             detail="Forbidden"
         )  
-     
+
+def authenticate_user(credentials: HTTPBasicCredentials = Depends(HTTPBasic())):
+    correct_username = "david"
+    correct_password = "david"
+    
+    if credentials.username == correct_username and credentials.password == correct_password:
+        return True
+    else:
+        raise HTTPException(
+            status_code=status.HTTP_401_UNAUTHORIZED,
+            detail="Incorrect username or password",
+            headers={"WWW-Authenticate": "Basic"},
+        )
+
+
 app = FastAPI()
 root = os.path.dirname(os.path.abspath(__file__))
-app.mount("/static", StaticFiles(html=True, directory=os.path.join(root, 'static')), name="static")
+#app.mount("/static", StaticFiles(html=True, directory=os.path.join(root, 'static')), name="static")
 app.mount("/media", StaticFiles(directory=str(MEDIA_DIRECTORY)), name="media")
 #app.mount("/", StaticFiles(html=True, directory=os.path.join(root, 'static')), name="www")
 
 security = HTTPBasic()
+@app.get("/static/{path:path}")
+async def static_files(request: Request, path: str, authenticated: bool = Depends(authenticate_user)):
+    root = os.path.dirname(os.path.abspath(__file__))
+    static_dir = os.path.join(root, 'static')
+
+    if not path or path == "/":
+        file_path = os.path.join(static_dir, 'index.html')
+    else:
+        file_path = os.path.join(static_dir, path)
+
+    # Check if path is a directory
+    if os.path.isdir(file_path):
+        # If it's a directory, try to serve index.html within that directory
+        index_path = os.path.join(file_path, 'index.html')
+        if os.path.exists(index_path):
+            return FileResponse(index_path)
+        else:
+            # Optionally, you can return a directory listing or a custom 404 page here
+            return HTMLResponse("Directory listing not enabled.", status_code=403) 
+
+    if not os.path.exists(file_path):
+        raise HTTPException(status_code=404, detail="File not found")
+
+    return FileResponse(file_path)
 
 def get_current_username(
     credentials: Annotated[HTTPBasicCredentials, Depends(security)]
@@ -98,9 +142,9 @@ async def get_api_key(
     return session or api_key
 
 #TODO predelat z Async?
-@app.get("/static")
-async def get(username: Annotated[str, Depends(get_current_username)]):
-    return FileResponse("index.html")
+# @app.get("/static")
+# async def get(username: Annotated[str, Depends(get_current_username)]):
+#     return FileResponse("index.html")
 
 @app.websocket("/runners/{runner_id}/ws")
 async def websocket_endpoint(
@@ -249,11 +293,13 @@ def _run_stratin(stratin_id: UUID, runReq: RunRequest):
         runReq.bt_to = zoneNY.localize(runReq.bt_to)  
     #pokud jedeme nad test intervaly anebo je požadováno více dní - pouštíme jako batch day by day
     #do budoucna dát na FE jako flag
-    if runReq.mode != Mode.LIVE and runReq.test_batch_id is not None or (runReq.bt_from.date() != runReq.bt_to.date()):
+    #print(runReq)
+    if runReq.mode not in [Mode.LIVE, Mode.PAPER] and (runReq.test_batch_id is not None or (runReq.bt_from is not None and runReq.bt_to is not None and runReq.bt_from.date() != runReq.bt_to.date())):
         res, id = cs.run_batch_stratin(id=stratin_id, runReq=runReq)
     else:
-        if runReq.weekdays_filter is not None:
-                raise HTTPException(status_code=status.HTTP_406_NOT_ACCEPTABLE, detail=f"Weekday only for backtest mode with batch (not single day)")
+        #not necessary for live/paper the weekdays are simply ignored, in the future maybe add validation if weekdays are presented
+        #if runReq.weekdays_filter is not None:
+        #        raise HTTPException(status_code=status.HTTP_406_NOT_ACCEPTABLE, detail=f"Weekday only for backtest mode with batch (not single day)")
         res, id = cs.run_stratin(id=stratin_id, runReq=runReq)
     if res == 0: return id
     elif res < 0:
@@ -552,30 +598,68 @@ def _get_archived_runner_log_byID(runner_id: UUID, timestamp_from: float, timest
     else:
         raise HTTPException(status_code=404, detail=f"No logs found with id: {runner_id} and between {timestamp_from} and {timestamp_to}")
 
+def remove_ansi_codes(text):
+    ansi_escape = re.compile(r'\x1B[@-_][0-?]*[ -/]*[@-~]')
+    return ansi_escape.sub('', text)
+
 # endregion 
 # A simple function to read the last lines of a file
-def tail(file_path, n=10, buffer_size=1024):
-    with open(file_path, 'rb') as f:
-        f.seek(0, 2)  # Move to the end of the file
-        file_size = f.tell()
-        lines = []
-        buffer = bytearray()
+# def tail(file_path, n=10, buffer_size=1024):
+#     try:
+#         with open(file_path, 'rb') as f:
+#             f.seek(0, 2)  # Move to the end of the file
+#             file_size = f.tell()
+#             lines = []
+#             buffer = bytearray()
 
-        for i in range(file_size // buffer_size + 1):
-            read_start = max(-buffer_size * (i + 1), -file_size)
-            f.seek(read_start, 2)
-            read_size = min(buffer_size, file_size - buffer_size * i)
-            buffer[0:0] = f.read(read_size)  # Prepend to buffer
+#             for i in range(file_size // buffer_size + 1):
+#                 read_start = max(-buffer_size * (i + 1), -file_size)
+#                 f.seek(read_start, 2)
+#                 read_size = min(buffer_size, file_size - buffer_size * i)
+#                 buffer[0:0] = f.read(read_size)  # Prepend to buffer
 
-            if buffer.count(b'\n') >= n + 1:
-                break
+#                 if buffer.count(b'\n') >= n + 1:
+#                     break
 
-        lines = buffer.decode(errors='ignore').splitlines()[-n:]
-        return lines
+#             lines = buffer.decode(errors='ignore').splitlines()[-n:]
+#             lines = [remove_ansi_codes(line) for line in lines]
+#             return lines
+#     except Exception as e:
+#         return [str(e) + format_exc()]
 
+#updated version that reads lines line by line
+def tail(file_path, n=10):
+    try:
+        with open(file_path, 'rb') as f:
+            f.seek(0, 2)  # Move to the end of the file
+            file_size = f.tell()
+            lines = []
+            line = b''
+
+            f.seek(-1, 2)  # Start at the last byte
+            while len(lines) < n and f.tell() != 0:
+                byte = f.read(1)
+                if byte == b'\n':
+                    # Decode, remove ANSI codes, and append the line
+                    lines.append(remove_ansi_codes(line.decode(errors='ignore')))
+                    line = b''
+                else:
+                    line = byte + line
+                f.seek(-2, 1)  # Move backwards by two bytes
+
+            if line:
+                # Append any remaining line after removing ANSI codes
+                lines.append(remove_ansi_codes(line.decode(errors='ignore')))
+
+            return lines[::-1]  # Reverse the list to get the lines in correct order
+    except Exception as e:
+        return [str(e)]
+
+
+    
 @app.get("/log", dependencies=[Depends(api_key_auth)])
-def read_log(lines: int = 10):
-    log_path = LOG_FILE
+def read_log(lines: int = 700, logfile: str = "strat.log"):
+    log_path = LOG_PATH  / logfile
     return {"lines": tail(log_path, lines)}
 
 #get alpaca history bars
@@ -609,7 +693,7 @@ def _generate_report_image(runner_ids: list[UUID]):
         res, stream = generate_trading_report_image(runner_ids=runner_ids,stream=True)
         if res == 0: return StreamingResponse(stream, media_type="image/png",headers={"Content-Disposition": "attachment; filename=report.png"})
         elif res < 0:
-            raise HTTPException(status_code=status.HTTP_406_NOT_ACCEPTABLE, detail=f"Error: {res}:{id}")
+            raise HTTPException(status_code=status.HTTP_406_NOT_ACCEPTABLE, detail=f"Error: {res}:{stream}")
     except Exception as e:
             raise HTTPException(status_code=status.HTTP_406_NOT_ACCEPTABLE, detail=f"Error: {str(e)}" + format_exc())        
 
@@ -645,7 +729,8 @@ def _generate_analysis(analyzerInputs: AnalyzerInputs):
 
         if res == 0: return StreamingResponse(stream, media_type="image/png")
         elif res < 0:
-            raise HTTPException(status_code=status.HTTP_406_NOT_ACCEPTABLE, detail=f"Error: {res}:{id}")
+            print("Error when generating analysis: ",str(stream))
+            raise HTTPException(status_code=status.HTTP_406_NOT_ACCEPTABLE, detail=f"Error: {res}:{stream}")
     except Exception as e:
             raise HTTPException(status_code=status.HTTP_406_NOT_ACCEPTABLE, detail=f"Error: {str(e)}" + format_exc())        
 
@@ -674,7 +759,7 @@ def get_testlists():
         raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=f"No data found")
 
 # API endpoint to retrieve a single record by ID
-@app.get('/testlists/{record_id}')
+@app.get('/testlists/{record_id}', dependencies=[Depends(api_key_auth)])
 def get_testlist(record_id: str):
     res, testlist = cs.get_testlist_byID(record_id=record_id)
 
@@ -684,7 +769,7 @@ def get_testlist(record_id: str):
         raise HTTPException(status_code=404, detail='Record not found')
 
 # API endpoint to update a record
-@app.put('/testlists/{record_id}')
+@app.put('/testlists/{record_id}', dependencies=[Depends(api_key_auth)])
 def update_testlist(record_id: str, testlist: TestList):
     # Check if the record exists
     conn = pool.get_connection()
@@ -704,7 +789,7 @@ def update_testlist(record_id: str, testlist: TestList):
     return testlist
 
 # API endpoint to delete a record
-@app.delete('/testlists/{record_id}')
+@app.delete('/testlists/{record_id}', dependencies=[Depends(api_key_auth)])
 def delete_testlist(record_id: str):
     # Check if the record exists
     conn = pool.get_connection()
@@ -727,7 +812,7 @@ def delete_testlist(record_id: str):
 # Get all config items
 @app.get("/config-items/", dependencies=[Depends(api_key_auth)])
 def get_all_items() -> list[ConfigItem]:
-    res, sada = cs.get_all_config_items()
+    res, sada = cf.get_all_config_items()
     if res == 0:
         return sada
     else:
@@ -737,7 +822,7 @@ def get_all_items() -> list[ConfigItem]:
 # Get a config item by ID
 @app.get("/config-items/{item_id}", dependencies=[Depends(api_key_auth)])
 def get_item(item_id: int)-> ConfigItem:
-    res, sada = cs.get_config_item_by_id(item_id)
+    res, sada = cf.get_config_item_by_id(item_id)
     if res == 0:
         return sada
     else:
@@ -746,7 +831,7 @@ def get_item(item_id: int)-> ConfigItem:
 # Get a config item by Name
 @app.get("/config-items-by-name/", dependencies=[Depends(api_key_auth)])
 def get_item(item_name: str)-> ConfigItem:
-    res, sada = cs.get_config_item_by_name(item_name)
+    res, sada = cf.get_config_item_by_name(item_name)
     if res == 0:
         return sada
     else:
@@ -755,7 +840,7 @@ def get_item(item_name: str)-> ConfigItem:
 # Create a new config item
 @app.post("/config-items/", dependencies=[Depends(api_key_auth)], status_code=status.HTTP_200_OK)
 def create_item(config_item: ConfigItem) -> ConfigItem:
-    res, sada = cs.create_config_item(config_item)
+    res, sada = cf.create_config_item(config_item)
     if res == 0: return sada
     else:
         raise HTTPException(status_code=status.HTTP_406_NOT_ACCEPTABLE, detail=f"Error not created: {res}:{id} {sada}")
@@ -764,11 +849,11 @@ def create_item(config_item: ConfigItem) -> ConfigItem:
 # Update a config item by ID
 @app.put("/config-items/{item_id}", dependencies=[Depends(api_key_auth)])
 def update_item(item_id: int, config_item: ConfigItem) -> ConfigItem:
-    res, sada = cs.get_config_item_by_id(item_id)
+    res, sada = cf.get_config_item_by_id(item_id)
     if res != 0:
         raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=f"No data found")
 
-    res, sada = cs.update_config_item(item_id, config_item)
+    res, sada = cf.update_config_item(item_id, config_item)
     if res == 0: return sada
     else:
         raise HTTPException(status_code=status.HTTP_406_NOT_ACCEPTABLE, detail=f"Error not created: {res}:{id}")
@@ -777,17 +862,77 @@ def update_item(item_id: int, config_item: ConfigItem) -> ConfigItem:
 # Delete a config item by ID
 @app.delete("/config-items/{item_id}", dependencies=[Depends(api_key_auth)])
 def delete_item(item_id: int) -> dict:
-    res, sada = cs.get_config_item_by_id(item_id)
+    res, sada = cf.get_config_item_by_id(item_id)
     if res != 0:
         raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=f"No data found")
 
-    res, sada = cs.delete_config_item(item_id)
+    res, sada = cf.delete_config_item(item_id)
     if res == 0: return sada
     else:
         raise HTTPException(status_code=status.HTTP_406_NOT_ACCEPTABLE, detail=f"Error not created: {res}:{id}")
 
 # endregion
 
+# region scheduler
+# 1. Fetch All RunManagerRecords
+@app.get("/run_manager_records/", dependencies=[Depends(api_key_auth)], response_model=List[RunManagerRecord])
+#TODO zvazit rozsireni vystupu o strat_status (running/stopped)
+def get_all_run_manager_records():
+    result, records = rm.fetch_all_run_manager_records()
+    if result != 0:
+        raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail="Error fetching records")
+    return records
+
+# 2. Fetch RunManagerRecord by ID
+@app.get("/run_manager_records/{record_id}", dependencies=[Depends(api_key_auth)], response_model=RunManagerRecord)
+#TODO zvazit rozsireni vystupu o strat_status (running/stopped)
+def get_run_manager_record(record_id: UUID):
+    result, record = rm.fetch_run_manager_record_by_id(record_id)
+    if result == -2:  # Record not found
+        raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Record not found")
+    elif result != 0:
+        raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail="Error fetching record")
+    return record
+
+# 3. Update RunManagerRecord 
+@app.patch("/run_manager_records/{record_id}", dependencies=[Depends(api_key_auth)], status_code=status.HTTP_200_OK)
+def update_run_manager_record(record_id: UUID, update_data: RunManagerRecord):
+    #make dates zone aware zoneNY
+    # if update_data.valid_from is not None:
+    #     update_data.valid_from = zoneNY.localize(update_data.valid_from)
+    # if update_data.valid_to is not None:
+    #     update_data.valid_to = zoneNY.localize(update_data.valid_to)
+    result, message = rm.update_run_manager_record(record_id, update_data)
+    if result == -2:  # Update failed
+        raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=message) 
+    elif result != 0:
+        raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=f"Error during update {result} {message}")
+    return {"message": "Record updated successfully"} 
+
+# 4. Delete RunManagerRecord
+@app.delete("/run_manager_records/{record_id}", dependencies=[Depends(api_key_auth)], status_code=status.HTTP_200_OK)
+def delete_run_manager_record(record_id: UUID):
+    result, message = rm.delete_run_manager_record(record_id)
+    if result == -2:  # Delete failed
+        raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=message)
+    elif result != 0:
+        raise HTTPException(status_code=status.HTTP_406_NOT_ACCEPTABLE, detail=f"Error during deletion {result} {message}")
+    return {"message": "Record deleted successfully"} 
+
+@app.post("/run_manager_records/", status_code=status.HTTP_201_CREATED)
+def create_run_manager_record(new_record: RunManagerRecord, api_key_auth: Depends = Depends(api_key_auth)): 
+    #make date zone aware - convert to zoneNY
+    # if new_record.valid_from is not None:
+    #     new_record.valid_from = zoneNY.localize(new_record.valid_from)
+    # if new_record.valid_to is not None:
+    #     new_record.valid_to = zoneNY.localize(new_record.valid_to)
+
+    result, record_id = rm.add_run_manager_record(new_record)
+    if result != 0:
+        raise HTTPException(status_code=status.HTTP_406_NOT_ACCEPTABLE, detail=f"Error during record creation: {result} {record_id}")
+    return {"id": record_id}
+# endregion
+
 #model section
 #UPLOAD MODEL
 @app.post("/model/upload_model", dependencies=[Depends(api_key_auth)])
@@ -881,7 +1026,25 @@ def get_metadata(model_name: str):
     #         "last_modified": os.path.getmtime(model_path),
     #         # ... other metadata fields ...
     #     }
-
+@app.get("/system-info")
+def get_system_info():
+    """Get system info, e.g. disk free space, used percentage ... """
+    disk_total = round(psutil.disk_usage('/').total / 1024**3, 1)
+    disk_used = round(psutil.disk_usage('/').used / 1024**3, 1)
+    disk_free = round(psutil.disk_usage('/').free / 1024**3, 1)
+    disk_used_percentage = round(psutil.disk_usage('/').percent, 1)
+    # memory_total = round(psutil.virtual_memory().total / 1024**3, 1)
+    # memory_perc = round(psutil.virtual_memory().percent, 1)
+    # cpu_time_user = round(psutil.cpu_times().user,1)
+    # cpu_time_system = round(psutil.cpu_times().system,1)
+    # cpu_time_idle = round(psutil.cpu_times().idle,1)
+    # network_sent = round(psutil.net_io_counters().bytes_sent / 1024**3, 6)
+    # network_recv = round(psutil.net_io_counters().bytes_recv / 1024**3, 6)
+    return {"disk_space": {"total": disk_total, "used": disk_used, "free" : disk_free, "used_percentage" : disk_used_percentage},
+            # "memory": {"total": memory_total, "used_percentage": memory_perc},
+            # "cpu_time" : {"user": cpu_time_user, "system": cpu_time_system, "idle": cpu_time_idle},
+            # "network": {"sent": network_sent, "received": network_recv}
+            }
 
 # Thread function to insert data from the queue into the database
 def insert_queue2db():
@@ -924,7 +1087,22 @@ if __name__ == "__main__":
         insert_thread = Thread(target=insert_queue2db)
         insert_thread.start()
 
+        #attach debugGER to be able to debug scheduler jobs (run in separate threads)
+        # debugpy.listen(('localhost', 5678))
+        # print("Waiting for debugger to attach...")
+        # debugpy.wait_for_client()  # Script will pause here until debugger is attached
+
+        #init scheduled tasks from schedule table
+        #Add APS scheduler job refresh
+        res, result = aps.initialize_jobs()
+        if res < 0:
+            #raise exception
+            raise Exception(f"Error {res} initializing APS jobs, error {result}")
+
         uvicorn.run("__main__:app", host="0.0.0.0", port=8000, reload=False)
+    except Exception as e:
+        print("Error intializing app: " + str(e) + format_exc())
+        aps.scheduler.shutdown(wait=False)
     finally:
         print("closing insert_conn connection")
         insert_conn.close()

v2realbot/scheduler/ap_scheduler.py

@@ -0,0 +1,310 @@
+from uuid import UUID
+from typing import Any, List, Tuple
+from uuid import UUID, uuid4
+from v2realbot.enums.enums import Moddus, SchedulerStatus, RecordType, StartBarAlign, Mode, Account, OrderSide
+from v2realbot.common.model import RunManagerRecord, StrategyInstance, RunDay, StrategyInstance, Runner, RunRequest, RunArchive, RunArchiveView, RunArchiveViewPagination, RunArchiveDetail, RunArchiveChange, Bar, TradeEvent, TestList, Intervals, ConfigItem, InstantIndicator, DataTablesRequest, Market
+from v2realbot.utils.utils import validate_and_format_time, AttributeDict, zoneNY, zonePRG, safe_get, dict_replace_value, Store, parse_toml_string, json_serial, is_open_hours, send_to_telegram, concatenate_weekdays, transform_data
+from v2realbot.common.PrescribedTradeModel import Trade, TradeDirection, TradeStatus, TradeStoplossType
+from datetime import datetime
+from v2realbot.config import JOB_LOG_FILE, STRATVARS_UNCHANGEABLES, ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, ACCOUNT1_LIVE_API_KEY, ACCOUNT1_LIVE_SECRET_KEY, DATA_DIR, MEDIA_DIRECTORY, RUNNER_DETAIL_DIRECTORY
+import numpy as np
+from rich import print as richprint
+import v2realbot.controller.services as cs
+import v2realbot.controller.run_manager as rm
+import v2realbot.scheduler.scheduler as sch
+from apscheduler.schedulers.background import BackgroundScheduler
+from apscheduler.triggers.cron import CronTrigger
+from apscheduler.job import Job
+
+#NOTE zatím není podporováno spouštění strategie přes půlnoc - musí se dořešit weekday_filter
+#který je zatím jen jeden jak pro start_time tak stop_time - což by v případě strategií běžících
+#přes půlnoc nezafungovalo (stop by byl následující den a scheduler by jej nespustil)
+
+def format_apscheduler_jobs(jobs: list[Job]) -> list[dict]:
+    if not jobs:
+        print("No scheduled jobs.")
+        return
+
+    jobs_info = []
+
+    for job in jobs:
+        job_info = {
+            "Job ID": job.id,
+            "Next Run Time": job.next_run_time,
+            "Job Function": job.func.__name__,
+            "Trigger": str(job.trigger),
+            "Job Args": ', '.join(map(str, job.args)),
+            "Job Kwargs": ', '.join(f"{k}={v}" for k, v in job.kwargs.items())
+        }
+        jobs_info.append(job_info)
+
+    return jobs_info
+
+def get_day_of_week(weekdays_filter):
+    if not weekdays_filter:
+        return '*'  # All days of the week
+    return ','.join(map(str, weekdays_filter))
+
+#initialize_jobs se spousti 
+#- pri spusteni
+#- triggerovano z add/update a delete
+
+#zatim cely refresh, v budoucnu upravime jen na zmene menene polozky - viz 
+#https://chat.openai.com/c/2a1423ee-59df-47ff-b073-0c49ade51ed7
+
+#pomocna funkce, ktera vraci strat_id, ktera jsou v scheduleru vickrat (logika pro ne se lisi)
+def stratin_occurences(all_records: list[RunManagerRecord]):
+    # Count occurrences
+    strat_id_counts = {}
+    for record in all_records:
+        if record.strat_id in strat_id_counts:
+            strat_id_counts[record.strat_id] += 1
+        else:
+            strat_id_counts[record.strat_id] = 1
+
+    # Find strat_id values that appear twice or more
+    repeated_strat_ids = [strat_id for strat_id, count in strat_id_counts.items() if count >= 2]
+
+    return 0, repeated_strat_ids
+
+
+def initialize_jobs(run_manager_records: RunManagerRecord = None):
+    """
+    Initialize all scheduled jobs from RunManagerRecords with moddus = "schedule"
+    Triggered on app init and update of table
+    It deleted all "schedule_" prefixed jobs and schedule new ones base on runmanager table
+    prefiX of "schedule_" in aps scheduler allows to distinguisd schedule types jobs and allows more jobs categories
+
+    Parameters
+    ----------
+    run_manager_records : RunManagerRecord, optional
+        RunManagerRecords to initialize the jobs from, by default None
+
+    Returns
+    -------
+    Tuple[int, Union[List[dict], str]]
+        A tuple containing an error code and a message. If there is no error, the
+        message will contain a list of dictionaries with information about the
+        scheduled jobs, otherwise it will contain an error message.
+    """
+    if run_manager_records is None:
+        res, run_manager_records = rm.fetch_all_run_manager_records()
+        if res < 0:
+            err_msg= f"Error {res} fetching all runmanager records, error {run_manager_records}"
+            print(err_msg)
+            return -2, err_msg  
+
+    scheduled_jobs = scheduler.get_jobs()
+
+    #print(f"Current {len(scheduled_jobs)} scheduled jobs: {str(scheduled_jobs)}")
+    for job in scheduled_jobs:
+        if job.id.startswith("scheduler_"):
+            scheduler.remove_job(job.id)
+    record : RunManagerRecord = None
+    for record in run_manager_records:
+        if record.status == SchedulerStatus.ACTIVE and record.moddus == Moddus.SCHEDULE:
+            day_of_week = get_day_of_week(record.weekdays_filter)
+
+            hour, minute = map(int, record.start_time.split(':'))
+            start_trigger = CronTrigger(day_of_week=day_of_week, hour=hour, minute=minute, 
+                                        start_date=record.valid_from, end_date=record.valid_to, timezone=zoneNY)
+            stop_hour, stop_minute = map(int, record.stop_time.split(':'))
+            stop_trigger = CronTrigger(day_of_week=day_of_week, hour=stop_hour, minute=stop_minute, 
+                                    start_date=record.valid_from, end_date=record.valid_to, timezone=zoneNY)
+
+            # Schedule new jobs with the 'scheduler_' prefix
+            scheduler.add_job(start_runman_record, start_trigger, id=f"scheduler_start_{record.id}", args=[record.id])
+            scheduler.add_job(stop_runman_record, stop_trigger, id=f"scheduler_stop_{record.id}", args=[record.id])
+                        
+    #scheduler.add_job(print_hello, 'interval', seconds=10, id=
+    # f"scheduler_testinterval")
+    scheduled_jobs = scheduler.get_jobs()
+    print(f"APS jobs refreshed ({len(scheduled_jobs)})")
+    current_jobs_dict = format_apscheduler_jobs(scheduled_jobs)
+    richprint(current_jobs_dict)
+    return 0, current_jobs_dict
+
+#zastresovaci funkce resici error handling a printing
+def start_runman_record(id: UUID, debug_date = None):
+    record = None
+    res, record, msg = _start_runman_record(id=id, debug_date=debug_date)
+
+    if record is not None:
+        market_time_now = datetime.now().astimezone(zoneNY) if debug_date is None else debug_date
+        record.last_processed = market_time_now
+        formatted_date = market_time_now.strftime("%y.%m.%d %H:%M:%S")
+        history_string = f"{formatted_date}"
+        history_string += " STARTED" if res == 0 else "NOTE:" + msg if res == -1 else "ERROR:" + msg 
+        print(history_string)
+        if record.history is None:
+            record.history = history_string
+        else:
+            record.history += "\n" + history_string
+
+        rs, msg_rs = update_runman_record(record)
+        if rs < 0:
+            msg_rs = f"Error saving result to history: {msg_rs}"
+            print(msg_rs)
+            send_to_telegram(msg_rs)
+
+
+    if res < -1:
+        msg = f"START JOB: {id} ERROR\n" + msg
+        send_to_telegram(msg)
+        print(msg)
+    else:
+        print(f"START JOB: {id} FINISHED {res}")
+
+
+def update_runman_record(record: RunManagerRecord):
+    #update record (nejspis jeste upravit - last_run a history)
+    res, set = rm.update_run_manager_record(record.id, record)
+    if res == 0:
+        print(f"Record updated {set}")
+        return 0, "OK"
+    else:
+        err_msg= f"STOP: Error updating {record.id} errir {set} with values {record}"
+        return -2, err_msg#toto stopne zpracovani dalsich zaznamu pri chybe, zvazit continue
+
+def stop_runman_record(id: UUID, debug_date = None):
+    res, record, msg = _stop_runman_record(id=id, debug_date=debug_date)
+    #results : 0 - ok, -1 not running/already running/not specific, -2 error
+
+    #report vzdy zapiseme do history, pokud je record not None, pripadna chyba se stala po dotazeni recordu
+    if record is not None:
+        market_time_now = datetime.now().astimezone(zoneNY) if debug_date is None else debug_date
+        record.last_processed = market_time_now
+        formatted_date = market_time_now.strftime("%y.%m.%d %H:%M:%S")
+        history_string = f"{formatted_date}"
+        history_string += " STOPPED" if res == 0 else "NOTE:" + msg if res == -1 else "ERROR:" + msg 
+        print(history_string)
+        if record.history is None:
+            record.history = history_string
+        else:
+            record.history += "\n" + history_string
+
+        rs, msg_rs = update_runman_record(record)
+        if rs < 0:
+            msg_rs = f"Error saving result to history: {msg_rs}"
+            print(msg_rs)
+            send_to_telegram(msg_rs)
+
+    if res < -1:
+        msg = f"STOP JOB: {id} ERROR\n" + msg
+        send_to_telegram(msg)
+        print(msg)
+    else:
+        print(f"STOP JOB: {id} FINISHED")
+
+#start function that is called from the job
+def _start_runman_record(id: UUID, debug_date = None):
+    print(f"Start scheduled record {id}")
+
+    record : RunManagerRecord = None
+    res, result = rm.fetch_run_manager_record_by_id(id)
+    if res < 0:
+        result = "Error fetching run manager record by id: " + str(id) + " Error: " + str(result)
+        return res, record, result
+    
+    record = result
+
+    if record.market == Market.US or record.market == Market.CRYPTO:
+        res, sada = sch.get_todays_market_times(market=record.market, debug_date=debug_date)
+        if res == 0:
+            market_time_now, market_open_datetime, market_close_datetime = sada
+            print(f"OPEN:{market_open_datetime} CLOSE:{market_close_datetime}")
+        else:
+            sada = f"Market {record.market} Error getting market times (CLOSED): " + str(sada)
+            return res, record, sada
+    else:
+        print("Market type is unknown.")
+    if cs.is_stratin_running(record.strat_id):
+        return -1, record, f"Stratin {record.strat_id} is already running"
+
+    res, result = sch.run_scheduled_strategy(record)
+    if res < 0:
+        result = "Error running strategy: " + str(result)
+        return res, record, result
+    else:
+        record.runner_id = UUID(result)
+
+    return 0, record, record.runner_id
+
+#stop function that is called from the job
+def _stop_runman_record(id: UUID, debug_date = None):
+    record = None
+    #get all records
+    print(f"Stopping record {id}")
+    res, all_records = rm.fetch_all_run_manager_records()
+    if res < 0:
+        err_msg= f"Error {res} fetching all runmanager records, error {all_records}"
+        return -2, record, err_msg  
+    
+    record : RunManagerRecord = None
+    for rec in all_records:
+        if rec.id == id:
+            record = rec
+            break
+    
+    if record is None:
+        return -2, record, f"Record id {id} not found"
+
+    #strat_ids that are repeated
+    res, repeated_strat_ids = stratin_occurences(all_records)
+    if res < 0:
+        err_msg= f"Error {res} finding repeated strat_ids, error {repeated_strat_ids}"
+        return -2, record, err_msg
+    
+    if record.strat_running is True:
+        #stopneme na zaklade record.runner_id
+        #this code
+        id_to_stop = record.runner_id
+
+    #pokud existuje manualne spustena stejna strategie a neni jich vic - je to jednoznacne - stopneme ji
+    elif cs.is_stratin_running(record.strat_id) and record.strat_id not in repeated_strat_ids:
+        #stopneme na zaklade record.strat_id
+        id_to_stop = record.strat_id
+
+    else:
+        msg = f"strategy {record.strat_id} not RUNNING or not distinctive (manually launched or two strat_ids in scheduler)"
+        print(msg)
+        return -1, record, msg
+
+    print(f"Requesting STOP {id_to_stop}")
+    res, msg = cs.stop_runner(id=id_to_stop)
+    if res < 0:
+        msg = f"ERROR while STOPPING runner_id/strat_id {id_to_stop} {msg}"
+        return -2, record, msg    
+    else:
+        record.runner_id = None
+
+    return 0, record, "finished"
+
+# Global scheduler instance
+scheduler = BackgroundScheduler(timezone=zoneNY)
+scheduler.start()
+
+
+if __name__ == "__main__":
+   #use naive datetoime
+    debug_date = None
+    debug_date = datetime(2024, 2, 16, 9, 37, 0, 0)
+    #debug_date = datetime(2024, 2, 16, 10, 30, 0, 0)
+    #debug_date = datetime(2024, 2, 16, 16, 1, 0, 0)
+
+    id = UUID("bc4ec7d2-249b-4799-a02f-f1ce66f83d4a")
+
+    if debug_date is not None:
+        # Localize the naive datetime object to the Eastern timezone
+        debug_date = zoneNY.localize(debug_date)
+        #debugdate formatted as string in format "23.12.2024 9:30"
+        formatted_date = debug_date.strftime("%d.%m.%Y %H:%M") 
+        print("Scheduler.py NY time: ", formatted_date)
+        print("ISoformat", debug_date.isoformat())
+
+    # res, result = start_runman_record(id=id, market = "US", debug_date = debug_date)
+    # print(f"CALL FINISHED, with {debug_date} RESULT: {res}, {result}")
+
+
+    res, result = stop_runman_record(id=id, debug_date = debug_date)
+    print(f"CALL FINISHED, with {debug_date} RESULT: {res}, {result}")

v2realbot/scheduler/scheduler.py

@@ -0,0 +1,439 @@
+import json
+import datetime
+import v2realbot.controller.services as cs
+import v2realbot.controller.run_manager as rm
+from v2realbot.common.model import RunnerView, RunManagerRecord, StrategyInstance, Runner, RunRequest, Trade, RunArchive, RunArchiveView, RunArchiveViewPagination, RunArchiveDetail, Bar, RunArchiveChange, TestList, ConfigItem, InstantIndicator, DataTablesRequest, AnalyzerInputs, Market
+from uuid import uuid4, UUID
+from v2realbot.utils.utils import json_serial, send_to_telegram, zoneNY, zonePRG, zoneUTC, fetch_calendar_data
+from datetime import datetime, timedelta, time
+from traceback import format_exc
+from rich import print
+import requests
+from v2realbot.config import WEB_API_KEY
+
+#Puvodni varainta schedulera, ktera mela bezet v pravidelnych intervalech
+#a spoustet scheduled items v RunManagerRecord
+#Nově bylo zrefaktorováno a využitý apscheduler - knihovna v pythonu
+#umožňující plánování jobů, tzn. nyní je každý scheduled záznam RunManagerRecord
+#naplanovany jako samostatni job a triggerován pouze jednou v daný čas pro start a stop 
+#novy kod v aps_scheduler.py
+
+def is_US_market_day(date):
+    cal_dates = fetch_calendar_data(date, date)
+    if len(cal_dates) == 0:
+        print("Today is not a market day.")
+        return False, cal_dates
+    else:
+        print("Market is open")
+        return True, cal_dates
+
+def get_todays_market_times(market, debug_date = None):
+    try:
+        if market == Market.US:
+            #zjistit vsechny podminky - mozna loopovat - podminky jsou vlevo
+            if debug_date is not None:
+                nowNY = debug_date
+            else:
+                nowNY = datetime.now().astimezone(zoneNY)
+            nowNY_date = nowNY.date()
+            #is market open - nyni pouze US
+            stat, calendar_dates = is_US_market_day(nowNY_date)
+            if stat:
+            #zatim podpora pouze main session
+            #pouze main session
+                market_open_datetime = zoneNY.localize(calendar_dates[0].open)
+                market_close_datetime = zoneNY.localize(calendar_dates[0].close)
+                return 0, (nowNY, market_open_datetime, market_close_datetime)
+            else:
+                return -1, "Market is closed."
+        elif market == Market.CRYPTO:
+            now_market_datetime = datetime.now().astimezone(zoneUTC)
+            market_open_datetime = datetime.combine(datetime.now(), time.min)
+            matket_close_datetime = datetime.combine(datetime.now(), time.max)
+            return 0, (now_market_datetime, market_open_datetime, matket_close_datetime)
+        else:
+            return -1, "Market not supported"
+    except Exception as e:
+        err_msg = f"General error in {e} {format_exc()}"
+        print(err_msg)
+        return -2, err_msg
+
+def get_running_strategies():
+    # Construct the URL for the local REST API endpoint on port 8000
+    api_url = "http://localhost:8000/runners/"
+
+    # Headers for the request
+    headers = {
+        "X-API-Key": WEB_API_KEY
+    }
+
+    try:
+        # Make the GET request to the API with the headers
+        response = requests.get(api_url, headers=headers)
+
+        # Check if the request was successful
+        if response.status_code == 200:
+            runners = response.json()
+            print("Successfully fetched runners.")
+            strat_ids = []
+            ids = []
+
+            for runner_view in runners:
+                strat_ids.append(UUID(runner_view["strat_id"]))
+                ids.append(UUID(runner_view["id"]))
+
+            return 0, (strat_ids, ids)
+        else:
+            err_msg = f"Failed to fetch runners. Status Code: {response.status_code}, Response: {response.text}"
+            print(err_msg)
+            return -2, err_msg
+    except requests.RequestException as e:
+        err_msg = f"Request failed: {str(e)}"
+        print(err_msg)
+        return -2, err_msg
+
+def stop_strategy(runner_id):
+    # Construct the URL for the local REST API endpoint on port 8000 #option 127.0.0.1
+    api_url = f"http://localhost:8000/runners/{runner_id}/stop"
+
+    # Headers for the request
+    headers = {
+        "X-API-Key": WEB_API_KEY
+    }
+
+    try:
+        # Make the PUT request to the API with the headers
+        response = requests.put(api_url, headers=headers)
+
+        # Check if the request was successful
+        if response.status_code == 200:
+            print(f"Runner/strat_id {runner_id} stopped successfully.")
+            return 0, runner_id
+        else:
+            err_msg = f"Failed to stop runner {runner_id}. Status Code: {response.status_code}, Response: {response.text}"
+            print(err_msg)
+            return -2, err_msg
+    except requests.RequestException as e:
+        err_msg = f"Request failed: {str(e)}"
+        print(err_msg)
+        return -2, err_msg
+    
+def fetch_stratin(stratin_id):
+    # Construct the URL for the REST API endpoint
+    api_url = f"http://localhost:8000/stratins/{stratin_id}"
+
+    # Headers for the request
+    headers = {
+        "X-API-Key": WEB_API_KEY
+    }
+
+    try:
+        # Make the GET request to the API with the headers
+        response = requests.get(api_url, headers=headers)
+
+        # Check if the request was successful
+        if response.status_code == 200:
+            # Parse the response as a StrategyInstance object
+            strategy_instance = response.json() 
+            #strategy_instance = response # Assuming the response is in JSON format
+            print(f"StrategyInstance fetched: {stratin_id}")
+            return 0, strategy_instance
+        else:
+            err_msg = f"Failed to fetch StrategyInstance {stratin_id}. " \
+                      f"Status Code: {response.status_code}, Response: {response.text}"
+            print(err_msg)
+            return -1, err_msg
+    except requests.RequestException as e:
+        err_msg = f"Request failed: {str(e)}"
+        print(err_msg)
+        return -2, err_msg
+
+#return list of strat_ids that are in the scheduled table more than once
+#TODO toto je workaround dokud nebude canndidates logika ze selectu nyni presunuta na fetch_all_run_manager_records a logiku v pythonu
+def stratin_occurences():
+#get all records
+    res, all_records = rm.fetch_all_run_manager_records()
+    if res < 0:
+        err_msg= f"Error {res} fetching all runmanager records, error {all_records}"
+        print(err_msg)
+        return -2, err_msg        
+
+    # Count occurrences
+    strat_id_counts = {}
+    for record in all_records:
+        if record.strat_id in strat_id_counts:
+            strat_id_counts[record.strat_id] += 1
+        else:
+            strat_id_counts[record.strat_id] = 1
+
+    # Find strat_id values that appear twice or more
+    repeated_strat_ids = [strat_id for strat_id, count in strat_id_counts.items() if count >= 2]
+
+    return 0, repeated_strat_ids
+
+# in case debug_date is not provided, it takes current time of the given market
+    #V budoucnu zde bude loopa pro kazdy obsluhovany market, nyni pouze US 
+def startstop_scheduled(debug_date = None, market = "US") -> tuple[int, str]:
+    res, sada = get_todays_market_times(market=market, debug_date=debug_date)
+    if res == 0:
+        market_time_now, market_open_datetime, market_close_datetime = sada
+        print(f"OPEN:{market_open_datetime} CLOSE:{market_close_datetime}")
+    else:
+        return res, sada
+
+    #its market day
+    res, candidates = rm.fetch_scheduled_candidates_for_start_and_stop(market_time_now, market)
+    if res == 0:
+        print(f"Candidates fetched, start: {len(candidates['start'])} stop: {len(candidates['stop'])}")
+    else:
+        return res, candidates
+
+    if candidates is None or (len(candidates["start"]) == 0 and len(candidates["stop"]) == 0):
+        return -1, f"No candidates found for {market_time_now} and {market}"
+    #do budoucna, az budou runnery persistovane, bude stav kazde strategie v RunManagerRecord
+    #get current runners (mozna optimalizace, fetch per each section start/stop) 
+    res, sada = get_running_strategies()
+    if res < 0:
+        err_msg= f"Error fetching running strategies, error {sada}"
+        print(err_msg)
+        send_to_telegram(err_msg)
+        return -2, err_msg
+    strat_ids_running, runnerids_running = sada
+    print(f"Currently running: {len(strat_ids_running)}")
+
+    #IERATE over START CAndidates
+    record: RunManagerRecord = None
+    print(f"START - Looping over {len(candidates['start'])} candidates")
+    for record in candidates['start']:
+        print("Candidate: ", record)
+
+        if record.weekdays_filter is not None and len(record.weekdays_filter) > 0:
+            curr_weekday = market_time_now.weekday()
+            if curr_weekday not in record.weekdays_filter:
+                print(f"Strategy {record.strat_id} not started, today{curr_weekday} not in weekdays filter {record.weekdays_filter}")
+                continue
+        #one strat_id can run only once at time
+        if record.strat_id in strat_ids_running:
+            msg = f"strategy already {record.strat_id} is running"
+            continue
+
+        res, result = run_scheduled_strategy(record)
+        if res < 0:
+            send_to_telegram(result)
+            print(result)
+        else:
+            record.runner_id = UUID(result)
+            strat_ids_running.append(record.strat_id)
+            runnerids_running.append(record.runner_id)
+
+        record.last_processed = market_time_now
+        history_string = f"{market_time_now.isoformat()} strategy STARTED" if res == 0 else "ERROR:" + result
+
+        if record.history is None:
+            record.history = history_string
+        else:
+            record.history += "\n" + history_string
+
+        #update record (nejspis jeste upravit - last_run a history)
+        res, set = rm.update_run_manager_record(record.id, record)
+        if res == 0:
+            print(f"Record in db updated {set}")
+            #return 0, set
+        else:
+            err_msg= f"Error updating {record.id} errir {set} with values {record}. Process stopped."
+            print(err_msg)
+            send_to_telegram(msg)
+            return -2, err_msg #toto stopne dalsi zpracovani, zvazit continue
+
+    #if stop candidates, then fetch existing runners
+    stop_candidates_cnt = len(candidates['stop'])
+
+    if stop_candidates_cnt > 0:
+        res, repeated_strat_ids = stratin_occurences()
+        if res < 0:
+            err_msg= f"Error {res} in callin stratin_occurences, error {repeated_strat_ids}"
+            send_to_telegram(err_msg)
+            return -2, err_msg
+
+    #dalsi OPEN ISSUE pri STOPu:
+    # má STOP_TIME strategie záviset na dni v týdnu? jinými slovy pokud je strategie
+    # nastavená na 9:30-10 v pondělí. Mohu si ji manuálně spustit v úterý a systém ji neshodí?
+    # Zatím to je postaveno, že předpis určuje okno, kde má strategie běžet a mimo tuto dobu bude 
+    # automaticky shozena. Druhou možností je potom, že scheduler si striktně hlídá jen strategie,
+    # které byly jím zapnuté a ostatní jsou mu putna. V tomto případě pak např. později ručně spuštěmá 
+    # strategie (např. kvůli opravě bugu) bude scheduler ignorovat a nevypne ji i kdyz je nastavena na vypnuti.
+    # Dopady: weekdays pri stopu a stratin_occurences
+
+    #IERATE over STOP Candidates
+    record: RunManagerRecord = None
+    print(f"STOP - Looping over {stop_candidates_cnt} candidates")
+    for record in candidates['stop']:
+        print("Candidate: ", record)
+
+        #Tento šelmostroj se stratin_occurences tu je jen proto, aby scheduler zafungoval i na manualne spustene strategie (ve vetsine pripadu)
+        # Při stopu evaluace kandidátů na vypnutí
+        #     - pokud mám v schedules jen 1 strategii s konkretnim strat_id, můžu jet přes strat_id - bezici strategie s timto strat_id bude vypnuta (i manualne startnuta)
+        #     - pokud jich mám více, musím jet přes runnery uložené v schedules
+        #         (v tomto případě je omezení: ručně pouštěna strategii nebude automaticky
+        #          stopnuta - systém neví, která to je)
+
+        #zjistime zda strategie bezi
+
+        #strategii mame v scheduleru pouze jednou, muzeme pouzit strat_id
+        if record.strat_id not in repeated_strat_ids:
+            if record.strat_id not in strat_ids_running:
+                msg = f"strategy {record.strat_id} NOT RUNNING"
+                print(msg)
+                continue
+            else:
+                #do stop
+                id_to_stop = record.strat_id
+        #strat_id je pouzito v scheduleru vicekrat, musime pouzit runner_id
+        elif record.runner_id is not None and record.runner_id in runnerids_running:
+            #do stop
+            id_to_stop = record.runner_id
+        #no distinctive condition
+        else:
+            #dont do anything
+            print(f"strategy {record.strat_id} not RUNNING or not distinctive (manually launched or two strat_ids in scheduler)")
+            continue
+
+        print(f"Requesting STOP {id_to_stop}")
+        res, msg = stop_strategy(id_to_stop)
+        if res < 0:
+            msg = f"ERROR while STOPPING runner_id/strat_id {id_to_stop} {msg}"
+            send_to_telegram(msg)      
+        else:
+            if record.strat_id in strat_ids_running:
+                strat_ids_running.remove(record.strat_id)
+            if record.runner_id is not None and record.runner_id in runnerids_running:
+                runnerids_running.remove(record.runner_id)
+            record.runner_id = None
+
+        record.last_processed = market_time_now
+        history_string = f"{market_time_now.isoformat()} strategy {record.strat_id}" + "STOPPED" if res == 0 else "ERROR:" + msg
+        if record.history is None:
+            record.history = history_string
+        else:
+            record.history += "\n" + history_string
+
+        #update record (nejspis jeste upravit - last_run a history)
+        res, set = rm.update_run_manager_record(record.id, record)
+        if res == 0:
+            print(f"Record updated {set}")
+        else:
+            err_msg= f"Error updating {record.id} errir {set} with values {record}"
+            print(err_msg)
+            send_to_telegram(err_msg)  
+            return -2, err_msg#toto stopne zpracovani dalsich zaznamu pri chybe, zvazit continue
+
+    return 0, "DONE"
+
+##LIVE or PAPER
+#tato verze využívate REST API, po predelani jobu na apscheduler uz muze vyuzivat prime volani cs.run_stratin
+#TODO predelat
+def run_scheduled_strategy(record: RunManagerRecord):
+    #get strat_json
+    sada : StrategyInstance = None
+    res, sada = fetch_stratin(record.strat_id)
+    if res == 0:
+        # #TODO toto overit jestli je stejny vystup jako JS
+        # print("Sada", sada)
+        # #strategy_instance = StrategyInstance(**sada)
+        strat_json = json.dumps(sada, default=json_serial)
+        # Replace escaped characters with their unescaped versions so it matches the JS output
+        #strat_json = strat_json.replace('\\r\\n', '\r\n')
+        #print(f"Strat_json fetched, {strat_json}")
+    else:
+        err_msg= f"Strategy {record.strat_id} not found. ERROR {sada}"
+        print(err_msg)
+        return -2, err_msg
+
+    #TBD mozna customizovat NOTE
+
+    #pokud neni batch_id pak vyhgeneruju a ulozim do db
+    # if record.batch_id is None:
+    #     record.batch_id = str(uuid4())[:8]
+
+    api_url = f"http://localhost:8000/stratins/{record.strat_id}/run"
+
+    # Initialize RunRequest with record values
+    runReq = {
+        "id": str(record.strat_id),
+        "strat_json": strat_json,
+        "mode": record.mode,
+        "account": record.account,
+        "ilog_save": record.ilog_save,
+        "weekdays_filter": record.weekdays_filter,
+        "test_batch_id": record.testlist_id,
+        "batch_id": record.batch_id or str(uuid4())[:8],
+        "bt_from": record.bt_from.isoformat() if record.bt_from else None,
+        "bt_to": record.bt_to.isoformat() if record.bt_to else None,
+        "note": f"SCHED {record.start_time}-" + record.stop_time if record.stop_time else "" + record.note if record.note is not None else ""
+    }
+
+    # Headers for the request
+    headers = {
+        "X-API-Key": WEB_API_KEY
+    }
+
+    try:
+        # Make the PUT request to the API with the headers
+        response = requests.put(api_url, json=runReq, headers=headers)
+
+        # Check if the request was successful
+        if response.status_code == 200:
+            print(f"Strategy {record.strat_id} started successfully.")
+            return 0, response.json()
+        else:
+            err_msg = f"Strategy {record.strat_id} NOT started. Status Code: {response.status_code}, Response: {response.text}"
+            print(err_msg)
+            return -2, err_msg
+    except requests.RequestException as e:
+        err_msg = f"Request failed: {str(e)}"
+        print(err_msg)
+        return -2, err_msg
+
+    # #intiializae RunRequest with record values
+    # runReq = RunRequest(id=record.strat_id,
+    #                     strat_json=strat_json,
+    #                     mode=record.mode,
+    #                     account=record.account,
+    #                     ilog_save=record.ilog_save,
+    #                     weekdays_filter=record.weekdays_filter,
+    #                     test_batch_id=record.testlist_id,
+    #                     batch_id=record.batch_id,
+    #                     bt_from=record.bt_from,
+    #                     bt_to=record.bt_to,
+    #                     note=record.note)
+    # #call rest API to start strategy
+
+    
+    # #start strategy
+    # res, sada = cs.run_stratin(id=record.strat_id, runReq=runReq, inter_batch_params=None)
+    # if res == 0:
+    #     print(f"Strategy {sada} started")
+    #     return 0, sada
+    # else:
+    #     err_msg= f"Strategy {record.strat_id} NOT started. ERROR {sada}"
+    #     print(err_msg)
+    #     return -2, err_msg
+
+
+if __name__ == "__main__":
+    #use naive datetoime
+    debug_date = None
+    debug_date = datetime(2024, 2, 16, 16, 37, 0, 0)
+    #debug_date = datetime(2024, 2, 16, 10, 30, 0, 0)
+    #debug_date = datetime(2024, 2, 16, 16, 1, 0, 0)
+
+    if debug_date is not None:
+        # Localize the naive datetime object to the Eastern timezone
+        debug_date = zoneNY.localize(debug_date)
+        #debugdate formatted as string in format "23.12.2024 9:30"
+        formatted_date = debug_date.strftime("%d.%m.%Y %H:%M") 
+        print("Scheduler.py NY time: ", formatted_date)
+        print("ISoformat", debug_date.isoformat())
+
+    res, msg = startstop_scheduled(debug_date=debug_date, market="US")
+    print(f"CALL FINISHED, with {debug_date} RESULT: {res}, {msg}")

v2realbot/static/index.html

@@ -26,7 +26,7 @@
 
 
         <!-- <script src="https://code.jquery.com/jquery-3.6.4.js" integrity="sha256-a9jBBRygX1Bh5lt8GZjXDzyOB+bWve9EiO7tROUtj/E=" crossorigin="anonymous"></script> -->
-        <script src="/static/js/libs/jquery-3.6.4.js" integrity="sha256-a9jBBRygX1Bh5lt8GZjXDzyOB+bWve9EiO7tROUtj/E=" crossorigin="anonymous"></script>
+        <script src="/static/js/libs/jquery-3.6.4.js"></script>
          
         <!-- <script src="https://cdn.datatables.net/1.13.4/js/jquery.dataTables.min.js"></script> -->
         <script src="/static/js/libs/jquery.dataTables.min.js"></script>
@@ -57,7 +57,7 @@
              <!-- <script src="https://code.jquery.com/jquery-3.5.1.js"></script> -->  
 
 
-        <link rel="stylesheet" href="/static/main.css?v=1.06">
+        <link rel="stylesheet" href="/static/main.css?v=1.07">
         <!-- <script src="https://cdnjs.cloudflare.com/ajax/libs/mousetrap/1.4.6/mousetrap.min.js"></script> -->
 
         <script src="/static/js/libs/mousetrap.min.js"></script>
@@ -131,9 +131,29 @@
 
         <!-- <script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/monaco-editor/0.41.0/min/vs/editor/editor.main.js"></script>  -->
         <!-- <script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/monaco-editor/0.41.0/min/vs/loader.min.js"></script>   -->
+        <script src="/static/js/systeminfo.js"> </script>
     </head>
     <body>
         <div id="main" class="mainConteiner flex-container content">
+            <div id="system-info" class="flex-items"> 
+                <label data-bs-toggle="collapse" data-bs-target="#system-info-inner" aria-expanded="true">
+                    <h4>System Info </h4>
+                </label>
+                <div id="system-info-inner" class="collapse">
+                    <div id="system-info-output"></div>
+                    <div id="graphical-output"> 
+                        <div id="disk-gauge-container">
+                            <span id="title"> Disk Space: </span>
+                            <span id="free-space">Free: -- GB</span> | 
+                            <span id="total-space">Total: -- GB</span> | 
+                            <span id="used-percent">Used: -- %</span>
+                            <div id="disk-gauge">
+                            <div id="disk-gauge-bar"></div>
+                            </div>
+                        </div>
+                    </div>
+                </div>
+            </div>
             <div id="chartContainer" class="flex-items">
                 <label data-bs-toggle="collapse" data-bs-target="#chartContainerInner" aria-expanded="true">
                     <h4>Chart</h4>
@@ -215,7 +235,7 @@
                 </div>
             </div>
             <div id="hist-trades" class="flex-items">
-                <div id="form-trades">
+                <div id="form-trades">               
                     <label data-bs-toggle="collapse" data-bs-target="#trades-data">
                         <h4>Trade History</h4>
                     </label>
@@ -230,6 +250,7 @@
                         <!-- <table id="trades-data-table" class="dataTable no-footer" style="width: 300px;display: contents;"></table> -->
                 </div>
             </div>
+
             <div id="runner-table" class="flex-items">
                 <label data-bs-toggle="collapse" data-bs-target="#runner-table-inner">
                     <h4>Running Strategies</h4>
@@ -298,6 +319,252 @@
                             </div>
                         </div>
                 </div>
+            </div>
+             <!-- SCHEDULER -->
+             <div id="runmanager-table" class="flex-items">
+                <label data-bs-toggle="collapse" data-bs-target="#runmanager-table-inner">
+                    <h4>Run Manager</h4>
+                </label>
+                <div id="runmanager-table-inner" class="collapse show collapsible-section" style="width:58%">
+                    <div id="controls">
+                        <button title="Create new" id="button_add_sched" class="btn btn-outline-success btn-sm">Add</button>
+                        <button title="Edit selected" id="button_edit_sched" class="btn btn-outline-success btn-sm">Edit</button>
+                        <button title="Delete selected" id="button_delete_sched" class="btn btn-outline-success btn-sm">Delete</button>
+                        <button title="History" id="button_history_sched" class="btn btn-outline-success btn-sm">History</button>
+                        <button title="Refresh" id="button_refresh_sched" class="btn btn-outline-success btn-sm">Refresh</button>
+                        <div class="btn-group btn-group-toggle" data-toggle="buttons">
+                            <!-- <input type="radio" class="btn-check" name="filterOptions" id="filterNone" autocomplete="off" checked>
+                            <label class="btn btn-outline-primary" for="filterNone">All</label> -->
+                        
+                            <input type="radio" class="btn-check" name="filterOptions" id="filterSchedule" autocomplete="off" checked>
+                            <label class="btn btn-outline-primary" for="filterSchedule">Scheduled</label>
+                        
+                            <input type="radio" class="btn-check" name="filterOptions" id="filterQueue" autocomplete="off">
+                            <label class="btn btn-outline-primary" for="filterQueue">Queued</label>
+                        </div>
+                    </div>
+                    <table id="runmanagerTable" class="table-striped table dataTable" style="width:100%; border-color: #dce1dc;">
+                        <thead>
+                            <tr>
+                                <th>Id</th>
+                                <th>Type</th>
+                                <th>Strat_Id</th>
+                                <th>Symbol</th>
+                                <th>Account</th>
+                                <th>Mode</th>
+                                <th>Note</th>
+                                <th>Log</th>
+                                <th>BT_from</th>
+                                <th>BT_to</th>
+                                <th>days</th>
+                                <th>batch_id</th>
+                                <th>start</th>
+                                <th>stop</th>
+                                <th>status</th>
+                                <th>last_processed</th>
+                                <th>history</th>
+                                <th>valid_from</th>
+                                <th>valid_to</th>
+                                <th>testlist_id</th>
+                                <th>Running</th>
+                                <th>RunnerId</th>
+                                <th>Market</th>
+                            </tr>
+                        </thead>
+                        <tbody></tbody>
+                    </table>
+                </div>                  
+                <div id="delModalRunmanager" class="modal fade">
+                    <div class="modal-dialog">
+                        <form method="post" id="delFormRunmanager">
+                            <div class="modal-content">
+                                <div class="modal-header">
+                                    <h4 class="modal-title"><i class="fa fa-plus"></i> Delete record</h4>
+                                    <button type="button" class="btn-close" data-bs-dismiss="modal" aria-label="Close"></button>
+                                </div>
+                                <div class="modal-body">
+                                    <div class="form-group">
+                                        <label for="delidrunmanager" class="form-label">Id</label>
+                                        <!-- <div id="listofids"></div> -->
+                                        <input type="text" class="form-control" id="delidrunmanager" name="id" placeholder="id" readonly>			
+                                    </div>				
+                                </div>
+                                <div class="modal-footer">
+                                    <input type="submit" name="delete" id="deleterunmanager" class="btn btn-primary" value="Delete" />
+                                    <button type="button" class="btn btn-secondary" data-bs-dismiss="modal">Close</button>
+                                </div>
+                            </div>
+                        </form>
+                    </div>
+                </div>                
+                <div id="addeditModalRunmanager" class="modal fade">
+                    <div class="modal-dialog">
+                        <form method="post" id="addeditFormRunmanager">
+                            <div class="modal-content">
+                                <div class="modal-header">
+                                    <h4 class="modal-title_run"><i class="fa fa-plus"></i> Add scheduler record</h4>
+                                    <button type="button" class="btn-close" data-bs-dismiss="modal" aria-label="Close"></button>
+                                </div>
+                                <div class="modal-body">
+                                    <div class="form-group">
+                                        <label for="runmanid" class="form-label">Record Id</label>
+                                        <input type="text" class="form-control" id="runmanid" name="id" placeholder="auto generated id" readonly>			
+                                    </div>
+                                    <div class="form-group">
+                                        <label for="runmanmoddus" class="form-label">Type</label>
+                                        <input type="text" class="form-control" id="runmanmoddus" name="moddus" readonly>	
+                                    </div>
+                                    <div class="form-group">
+                                        <label for="runmanstrat_id" class="form-label">StrategyId</label>
+                                        <input type="text" class="form-control" id="runmanstrat_id" name="strat_id" placeholder="strategy id">			
+                                    </div>
+                                    <div class="form-group">
+                                        <label for="runmode" class="form-label">Mode</label>
+                                        <select class="form-control" id="runmanmode" name="mode"><option value="paper">paper</option><option value="live">live</option><option value="backtest">backtest</option><option value="prep">prep</option></select>		
+                                    </div>
+                                    <div class="form-group">
+                                        <label for="account" class="form-label">Account</label>
+                                        <select class="form-control" id="runmanaccount" name="account"><option value="ACCOUNT1">ACCOUNT1</option><option value="ACCOUNT2">ACCOUNT2</option></select>		
+                                    </div>
+                                    <div class="form-group">
+                                        <label for="status" class="form-label">Status</label>
+                                        <select class="form-control" id="runmanstatus" name="status"><option value="active">active</option><option value="suspended">suspended</option></select>		
+                                    </div>
+                                    <div class="form-group" id="runmanstart_time_div">
+                                        <label for="start" class="form-label">Start Time</label>							
+                                        <input type="text" class="form-control" id="runmanstart_time" name="start_time" value="9:30" step="1">							
+                                    </div>	   	
+                                    <div class="form-group" id="runmanstop_time_div">
+                                        <label for="stop" class="form-label">Stop Time</label>							
+                                        <input type="text-local" class="form-control" id="runmanstop_time" name="stop_time" value="16:00" step="1">							
+                                    </div>
+
+                                    <!-- pro budouci queueing backtestu -->
+                                    <div class="form-group" id="runmanbt_from_div">
+                                        <label for="bt_from" class="form-label">bt_from</label>							
+                                        <input type="datetime-local" class="form-control" id="runmanbt_from" name="bt_from" placeholder="2023-04-06T09:00:00Z" step="1">							
+                                    </div>	   	
+                                    <div class="form-group" id="runmanbt_to_div">
+                                        <label for="bt_to" class="form-label">bt_to</label>							
+                                        <input type="datetime-local" class="form-control" id="runmanbt_to" name="bt_to" placeholder="2023-04-06T09:00:00Z" step="1">							
+                                    </div> 
+                                    <div class="form-group" id="runmantestlist_id_div">
+                                        <label for="test_batch_id" class="form-label">Test List ID</label>							
+                                        <input type="text" class="form-control" id="runmantestlist_id" name="testlist_id" placeholder="test intervals ID">							
+                                    </div>
+                                    <!-- pro budouci queueing backtestu -->
+
+                                    <!-- Initial Checkbox for Enabling Weekday Selection -->
+                                    <div class="form-group">
+                                        <div style="display:inline-flex">
+                                            <label for="runman_enable_weekdays" class="form-label">Limit to Weekdays</label>							
+                                            <input type="checkbox" class="form-check" id="runman_enable_weekdays" name="enable_weekdays" aria-label="Enable Weekday Selection">							
+                                        </div>
+                                    </div>
+
+                                    <!-- Weekday Checkboxes -->
+                                    <div class="form-group weekday-checkboxes" style="display:none;">
+                                        <!-- <label class="form-label">Select Weekdays:</label> -->
+                                        <div>
+                                            <input type="checkbox" id="monday" name="weekdays" value="monday">
+                                            <label for="monday">Monday</label>
+                                        </div>
+                                        <div>
+                                            <input type="checkbox" id="tuesday" name="weekdays" value="tuesday">
+                                            <label for="tuesday">Tuesday</label>
+                                        </div>
+                                        <div>
+                                            <input type="checkbox" id="wednesday" name="weekdays" value="wednesday">
+                                            <label for="wednesday">Wednesday</label>
+                                        </div>
+                                        <div>
+                                            <input type="checkbox" id="thursday" name="weekdays" value="thursday">
+                                            <label for="thursday">Thursday</label>
+                                        </div>
+                                        <div>
+                                            <input type="checkbox" id="friday" name="weekdays" value="friday">
+                                            <label for="friday">Friday</label>
+                                        </div>
+                                    </div>
+
+                                    <div class="form-group" id="runmanvalid_from_div">
+                                        <label for="runmanvalid_from" class="form-label">Valid from</label>							
+                                        <input type="datetime-local" class="form-control" id="runmanvalid_from" name="valid_from" placeholder="2023-04-06T09:00:00Z" step="1">							
+                                    </div>	   	
+                                    <div class="form-group" id="runmanvalid_to_div">
+                                        <label for="runmanvalid_to" class="form-label">Valid to</label>							
+                                        <input type="datetime-local" class="form-control" id="runmanvalid_to" name="valid_to" placeholder="2023-04-06T09:00:00Z" step="1">							
+                                    </div>
+
+                                    <div class="form-group">
+                                        <label for="batch_id" class="form-label">Batch ID</label>							
+                                        <input type="text" class="form-control" id="runmanbatch_id" name="batch_id" placeholder="batch id">							
+                                    </div>
+                                    <div class="form-group">
+                                        <div style="display:inline-flex">
+                                          <label for="ilog_save" class="form-label">Enable logs</label>							
+                                          <input type="checkbox" class="form-check" id="runmanilog_save" name="ilog_save" aria-label="Enable logs">							
+                                        </div>
+                                    </div>
+                                    <div class="form-group">
+                                        <label for="note" class="form-label">note</label>							
+                                        <textarea class="form-control" rows="1" id="runmannote" name="note"></textarea>							
+                                    </div>				
+                                </div>
+                                <div class="modal-footer">
+                                    <input type="hidden" name="runner_id" id="runmanrunner_id" />
+                                    <input type="hidden" name="history" id="runmanhistory" />
+                                    <input type="hidden" name="last_processed" id="runmanlast_processed" />
+                                    <!--<input type="hidden" name="action" id="action" value="" />-->
+                                    <input type="submit" id="runmanagersubmit" class="btn btn-primary" value="Add" />
+                                    <button type="button" class="btn btn-secondary" data-bs-dismiss="modal">Close</button>
+                                </div>
+                            </div>
+                        </form>
+                    </div>
+                </div>
+                <div id="historyModalRunmanager" class="modal fade">
+                    <div class="modal-dialog">
+                        <form method="post" id="historyModalRunmanagerForm">
+                            <div class="modal-content">
+                                <div class="modal-header">
+                                    <h4 class="modal-title"><i class="fa fa-plus"></i>View History</h4>
+                                    <button type="button" class="btn-close" data-bs-dismiss="modal" aria-label="Close"></button>
+                                </div>
+                                <div class="modal-body">
+                                    <div class="form-group">
+                                        <label for="RunmanId" class="form-label">Id</label>
+                                        <input type="text" class="form-control" id="RunmanId" name="id" placeholder="id" readonly>			
+                                    </div>
+                                    <div class="form-group">
+                                        <label for="Runmanlast_processed" class="form-label">Last processed</label>	
+                                        <input type="text" class="form-control" id="Runmanlast_processed" name="last_processed" readonly>													
+                                    </div>
+                                    <div class="form-group">
+                                        <label for="Runmanhistory" class="form-label">History</label>							
+                                        <textarea class="form-control" rows="8" id="Runmanhistory" name="history" readonly></textarea>							
+                                    </div>
+                                    <!-- <div class="form-group">
+                                        <label for="metrics" class="form-label">Metrics</label>							
+                                        <textarea class="form-control" rows="8" id="metrics" name="metrics"></textarea>							
+                                    </div>
+                                    <div class="form-group">
+                                        <label for="stratvars" class="form-label">Stratvars</label>							
+                                        <textarea class="form-control" rows="8" id="editstratvars" name="stratvars"></textarea>							
+                                    </div>
+                                    <div class="form-group">
+                                        <label for="strat_json" class="form-label">Strat JSON</label>							
+                                        <textarea class="form-control" rows="6" id="editstratjson" name="stratjson"></textarea>							
+                                    </div>			 -->
+                                </div>
+                                <div class="modal-footer">
+                                    <!-- <input type="submit" name="delete" id="editarchive" class="btn btn-primary" value="Edit" /> -->
+                                    <button type="button" class="btn btn-secondary" data-bs-dismiss="modal">Close</button>
+                                </div>
+                            </div>
+                        </form>
+                    </div>
+                </div>
             </div>
             <div id="archive-table" class="flex-items">
                 <label data-bs-toggle="collapse" data-bs-target="#archive-table-inner">
@@ -316,6 +583,7 @@
                         <button id="button_refresh" class="refresh btn btn-outline-success btn-sm">Refresh</button>
                         <button title="Compare selected days" id="button_compare_arch" class="refresh btn btn-outline-success btn-sm">Compare</button>
                         <button title="Run selected day" id="button_runagain_arch" class="refresh btn btn-outline-success btn-sm">Run Again(r)</button>
+                        <button title="Runs LIVE/PAPER in BT mode with same dates" id="button_runbt_arch" class="refresh btn btn-outline-success btn-sm">Backtest same period</button>
                         <button title="Select all days on the page" id="button_selpage" class="btn btn-outline-success btn-sm">Select all</button>
                         <button title="Export selected days to XML" id="button_export_xml" class="btn btn-outline-success btn-sm">Export xml</button>
                         <button title="Export selected days to CSV" id="button_export_csv" class="btn btn-outline-success btn-sm">Export csv</button>
@@ -350,7 +618,9 @@
                                 <th>pos</th>	
                                 <th>avgp</th>	
                                 <th>metrics</th>
-                                <th>batchid</th>	
+                                <th>batchid</th>
+                                <th>batchprofit</th>
+                                <th>batchcount</th>	
                             </tr>
                         </thead>
                         <tbody></tbody>
@@ -403,27 +673,34 @@
                 </div>
                 <div id="logModal" class="modal fade" style="--bs-modal-width: 825px;">
                     <div class="modal-dialog">
-                            <div class="modal-content">
-                                <div class="modal-header">
-                                    <h4 class="modal-title"><i class="fa fa-plus"></i>Log</h4>
-                                    <button type="button" class="btn-close" data-bs-dismiss="modal" aria-label="Close"></button>
+                        <div class="modal-content">
+                            <div class="modal-header">
+                                <h4 class="modal-title"><i class="fa fa-plus"></i>Log</h4>
+                                <button type="button" class="btn-close" data-bs-dismiss="modal" aria-label="Close"></button>
+                            </div>
+                            <div class="modal-body">
+                                <div class="form-group">
+                                    <label for="logFileSelect" class="form-label">Select Log File</label>
+                                    <select class="form-select" id="logFileSelect" aria-label="Log file select">
+                                        <!-- <option selected>Select a log file</option> -->
+                                        <option value="strat.log" selected>strat.log</option>
+                                        <option value="job.log">job.log</option>
+                                    </select>
                                 </div>
-                                <div class="modal-body">
-                                    <div class="form-group">
-                                        <label for="logHere" class="form-label">Log</label>
-                                        <div id="log-container">
-                                            <pre id="log-content"></pre>
-                                        </div>
-                                        <!-- <input type="text" class="form-control" id="delidarchive" name="delidarchive" placeholder="id">			 -->
-                                    </div>				
-                                </div>
-                                <div class="modal-footer">
-                                    <button type="button" class="btn btn-primary" id="logRefreshButton"  value="Refresh">Refresh</button>
-                                    <button type="button" class="btn btn-secondary" data-bs-dismiss="modal">Close</button>
+                                <div class="form-group mt-3">
+                                    <label for="logHere" class="form-label">Log</label>
+                                    <div id="log-container"style="height:700px;border:1px solid black;">
+                                        <!-- <pre id="log-content"></pre> -->
+                                    </div>
                                 </div>
                             </div>
+                            <div class="modal-footer">
+                                <button type="button" class="btn btn-primary" id="logRefreshButton" value="Refresh">Refresh</button>
+                                <button type="button" class="btn btn-secondary" id="closeLogModal" data-bs-dismiss="modal">Close</button>
+                            </div>
+                        </div>
                     </div>
-                </div>
+                </div>                
                 <div id="editModalArchive" class="modal fade">
                     <div class="modal-dialog">
                         <form method="post" id="editFormArchive">
@@ -449,6 +726,10 @@
                                         <label for="stratvars" class="form-label">Stratvars</label>							
                                         <textarea class="form-control" rows="8" id="editstratvars" name="stratvars"></textarea>							
                                     </div>
+                                    <div class="form-group">
+                                        <label for="stratvars" class="form-label">Transferables</label>							
+                                        <textarea class="form-control" rows="8" id="edittransferables" name="stratvars"></textarea>							
+                                    </div>
                                     <div class="form-group">
                                         <label for="strat_json" class="form-label">Strat JSON</label>							
                                         <textarea class="form-control" rows="6" id="editstratjson" name="stratjson"></textarea>							
@@ -887,39 +1168,43 @@
                 <BR>
             </div>
         </div>
-        <script src="/static/js/config.js?v=1.02"></script>
+        <script src="/static/js/config.js?v=1.04"></script>
         <!-- tady zacina polska docasna lokalizace -->
         <!-- <script type="text/javascript" src="https://unpkg.com/lightweight-charts/dist/lightweight-charts.standalone.production.js"></script> -->
-        <script type="text/javascript" src="/static/js/libs/lightweightcharts/lightweight-charts.standalone.production410.js"></script>
-        <script src="/static/js/dynamicbuttons.js?v=1.03"></script>
+        <script type="text/javascript" src="/static/js/libs/lightweightcharts/lightweight-charts.standalone.production413.js"></script>
+        <script src="/static/js/dynamicbuttons.js?v=1.05"></script>
     
        
         <!-- <script src="/static/js/utils.js?v=1.01"></script> -->
         <!-- new util structure and exports and colors -->
-        <script src="/static/js/utils/utils.js?v=1.02"></script>
-        <script src="/static/js/utils/exports.js?v=1.02"></script>
-        <script src="/static/js/utils/colors.js?v=1.02"></script>
+        <script src="/static/js/utils/utils.js?v=1.06"></script>
+        <script src="/static/js/utils/exports.js?v=1.04"></script>
+        <script src="/static/js/utils/colors.js?v=1.04"></script>
 
 
-        <script src="/static/js/instantindicators.js?v=1.01"></script>
-        <script src="/static/js/archivechart.js?v=1.03"></script>
+        <script src="/static/js/instantindicators.js?v=1.04"></script>
+        <script src="/static/js/archivechart.js?v=1.05"></script>
 
         <!-- <script src="/static/js/archivetables.js?v=1.05"></script> -->
         <!-- archiveTables split into separate files -->
-        <script src="/static/js/tables/archivetable/init.js?v=1.07"></script>
-        <script src="/static/js/tables/archivetable/functions.js?v=1.06"></script>
-        <script src="/static/js/tables/archivetable/modals.js?v=1.05"></script>
-        <script src="/static/js/tables/archivetable/handlers.js?v=1.05"></script>
+        <script src="/static/js/tables/archivetable/init.js?v=1.12"></script>
+        <script src="/static/js/tables/archivetable/functions.js?v=1.11"></script>
+        <script src="/static/js/tables/archivetable/modals.js?v=1.07"></script>
+        <script src="/static/js/tables/archivetable/handlers.js?v=1.11"></script>
 
+        <!-- Runmanager functionality -->
+        <script src="/static/js/tables/runmanager/init.js?v=1.1"></script>
+        <script src="/static/js/tables/runmanager/functions.js?v=1.08"></script>
+        <script src="/static/js/tables/runmanager/modals.js?v=1.07"></script>
+        <script src="/static/js/tables/runmanager/handlers.js?v=1.07"></script>
 
-
-        <script src="/static/js/livewebsocket.js?v=1.01"></script>
-        <script src="/static/js/realtimechart.js?v=1.01"></script>
-        <script src="/static/js/mytables.js?v=1.01"></script>
+        <script src="/static/js/livewebsocket.js?v=1.02"></script>
+        <script src="/static/js/realtimechart.js?v=1.02"></script>
+        <script src="/static/js/mytables.js?v=1.03"></script>
         <script src="/static/js/testlist.js?v=1.01"></script>
         <script src="/static/js/ml.js?v=1.02"></script>
         <script src="/static/js/common.js?v=1.01"></script>
         <script src="/static/js/configform.js?v=1.01"></script>
-
+        <!-- <script src="/static/js/scheduler.js?v=1.01"></script> -->
     </body>
 </html>

v2realbot/static/js/archivetables_firstbatchasheader.js

@@ -638,7 +638,7 @@ $(document).ready(function () {
             else{
                 $('#editstratvars').val(JSON.stringify(row.stratvars,null,2));
             }
-            
+            $('#edittransferables').val(JSON.stringify(row.transferables,null,2));
             
             $('#editstratjson').val(row.strat_json);
         }

v2realbot/static/js/mytables.js

@@ -90,9 +90,55 @@ $(document).ready(function () {
 
         monaco.languages.register({ id: 'python' });
         monaco.languages.register({ id: 'json' });
+        //Register mylogs language
+        monaco.languages.register({ id: 'mylogs' });
         // Register the TOML language
+        monaco.languages.setLanguageConfiguration('mylogs', {
+            comments: {
+                lineComment: '//',  // Adjust if your logs use a different comment symbol
+            },
+            brackets: [['[', ']'], ['{', '}']], // Array and object brackets
+            autoClosingPairs: [
+                { open: '{', close: '}', notIn: ['string'] },
+                { open: '"', close: '"', notIn: ['string', 'comment'] }, 
+                { open: "'", close: "'", notIn: ['string', 'comment'] }, 
+            ],
+        });
+        monaco.languages.setMonarchTokensProvider('mylogs', {
+            tokenizer: {
+                root: [
+                    [/#.*/, 'comment'], // Comments (if applicable)
+        
+                    // Timestamps 
+                    [/\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}\.\d+/, 'timestamp'], 
+        
+                    // Log Levels 
+                    [/\b(INFO|DEBUG|WARNING|ERROR|CRITICAL)\b/, 'log-level'],
+        
+                    // Strings 
+                    [/".*"/, 'string'], 
+                    [/'.*'/, 'string'],
+        
+                    // Key-Value Pairs
+                    [/[A-Za-z_]+\s*:/, 'key'],  
+                    [/-?\d+\.\d+/, 'number.float'], // Floating-point
+                    [/-?\d+/, 'number.integer'],    // Integers 
+                    [/\btrue\b/, 'boolean.true'],
+                    [/\bfalse\b/, 'boolean.false'],
+        
+                    // Other Words and Symbols
+                    [/[A-Za-z_]+/, 'identifier'],
+                    [/[ \t\r\n]+/, 'white'], 
+                    [/[\[\]{}(),]/, 'delimiter'], // Expand if more delimiters exist 
+                ]
+            }
+        });
+        
+        
         monaco.languages.register({ id: 'toml' });
 
+
+
         // Define the TOML language configuration
         monaco.languages.setLanguageConfiguration('toml', {
         comments: {
@@ -621,7 +667,6 @@ $(document).ready(function () {
         })
     });
 
-
     //button run
     $('#button_run').click(function () {
         row = stratinRecords.row('.selected').data();
@@ -953,7 +998,18 @@ var runnerRecords =
                 render: function ( data, type, row ) {
                     return format_date(data)
                 },
+            },
+            {
+                targets: [4], //symbol
+                render: function ( data, type, row ) {
+                    if (type === 'display') {
+                        //console.log("arch")
+                        var color = getColorForId(row.strat_id);
+                        return '<span style="color:' + color + ';">'+data+'</span>';
+                    }
+                    return data;
                 },
+            },
         ],
         // select: {
         //     style: 'multi'

v2realbot/static/js/systeminfo.js

@@ -0,0 +1,31 @@
+    function get_system_info() {
+        console.log('Button get system status clicked')
+        $.ajax({
+            url: '/system-info',
+            type: 'GET',
+            beforeSend: function (xhr) {
+                xhr.setRequestHeader('X-API-Key',
+                API_KEY); },
+            success: function(response) {
+                $.each(response, function(index, item) {
+                    if (index=="disk_space") {
+                        $('#disk-gauge-bar').css('width', response.disk_space.used_percentage + '%');
+                        $('#free-space').text('Free: ' + response.disk_space.free + ' GB');
+                        $('#total-space').text('Total: ' + response.disk_space.total + ' GB');
+                        $('#used-percent').text('Used: ' + response.disk_space.used_percentage + '%');
+                    } else {
+                        var formatted_item = JSON.stringify(item, null, 4)
+                        $('#system-info-output').append('<p>' + index + ': ' + formatted_item + '</p>');
+                    }
+                });            
+            },
+            error: function(xhr, status, error) {
+                $('#disk-gauge-bar').html('An error occurred: ' + error + xhr.responseText + status);
+            }
+        });
+    }
+
+
+$(document).ready(function(){
+  get_system_info()
+});

v2realbot/static/js/tables/archivetable/functions.js

@@ -6,6 +6,7 @@ let editor_diff_arch1
 let editor_diff_arch2
 var archData = null
 var batchHeaders = []
+var editorLog = null
 
 function refresh_arch_and_callback(row, callback) {
     //console.log("entering refresh")
@@ -78,10 +79,11 @@ function get_detail_and_chart(row) {
     })
 }
 
-//rerun stratin
-function run_day_again() {
+//rerun stratin (use to rerun strategy and also to rerun live/paper as bt on same period)
+function run_day_again(turnintobt=false) {
     row = archiveRecords.row('.selected').data();
-    $('#button_runagain_arch').attr('disabled',true);
+    var button_name = turnintobt ? '#button_runbt_arch' : '#button_runagain_arch'
+    $(button_name).attr('disabled',true)
 
     var record1 = new Object()
     //console.log(JSON.stringify(rows))
@@ -142,7 +144,7 @@ function run_day_again() {
         //console.log("Result from second request:", result2);
 
         //console.log("calling compare")
-        rerun_strategy(result1, result2)
+        rerun_strategy(result1, result2, turnintobt)
         // Perform your action with the results from both requests
         // Example:
 
@@ -154,13 +156,22 @@ function run_day_again() {
     });
 
 
-    function rerun_strategy(archRunner, stratData) {
+    function rerun_strategy(archRunner, stratData, turnintobt) {
         record1 = archRunner
         //console.log(record1)
 
+        var note_prefix = "RERUN "
+        if ((turnintobt) && ((record1.mode == 'live') || (record1.mode == 'paper'))) {
+            record1.mode = 'backtest'
+            record1.bt_from = record1.started
+            record1.bt_to = record1.stopped
+            note_prefix = "BT SAME PERIOD "
+        }
+
+        record1.note = note_prefix + record1.note
+        //nebudeme muset odstanovat pri kazdem pridani noveho atributu v budoucnu
         //smazeneme nepotrebne a pridame potrebne
         //do budoucna predelat na vytvoreni noveho objektu
-        //nebudeme muset odstanovat pri kazdem pridani noveho atributu v budoucnu
         delete record1["end_positions"];
         delete record1["end_positions_avgp"];
         delete record1["profit"];
@@ -172,8 +183,6 @@ function run_day_again() {
         delete record1["settings"];
         delete record1["stratvars"];
 
-        record1.note = "RERUN " + record1.note
-
         if (record1.bt_from == "") {delete record1["bt_from"];}
         if (record1.bt_to == "") {delete record1["bt_to"];}
     
@@ -212,7 +221,7 @@ function run_day_again() {
             contentType: "application/json",
             data: jsonString,
             success:function(data){							
-                $('#button_runagain_arch').attr('disabled',false);
+                $(button_name).attr('disabled',false);
                 setTimeout(function () {
                     runnerRecords.ajax.reload();
                     stratinRecords.ajax.reload();
@@ -222,7 +231,7 @@ function run_day_again() {
                 var err = eval("(" + xhr.responseText + ")");
                 window.alert(JSON.stringify(xhr));
                 //console.log(JSON.stringify(xhr));
-                $('#button_runagain_arch').attr('disabled',false);
+                $(button_name).attr('disabled',false);
             }
         })
     }
@@ -453,8 +462,10 @@ function display_batch_report(batch_id) {
 }
 
 function refresh_logfile() {
+    logfile = $("#logFileSelect").val()
+    lines = 1200
     $.ajax({
-        url:"/log?lines=30",
+        url:"/log?lines="+lines+"&logfile="+logfile,
         beforeSend: function (xhr) {
             xhr.setRequestHeader('X-API-Key',
             API_KEY); },
@@ -462,12 +473,34 @@ function refresh_logfile() {
         contentType: "application/json",
         dataType: "json",
         success:function(response){
+            if (editorLog) {
+                editorLog.dispose();
+            }
             if (response.lines.length == 0) {
-                $('#log-content').html("no records");
+                value = "no records";
+                // $('#log-content').html("no records");
             }
             else {
-                $('#log-content').html(response.lines.join('\n'));	
-            }	
+                //console.log(response.lines)
+                //var escapedLines = response.lines.map(line => escapeHtml(line));
+                value = response.lines.join('\n')
+                // $('#log-content').html(escapedLines.join('\n'));  
+            }
+            require(["vs/editor/editor.main"], () => {
+                editorLog = monaco.editor.create(document.getElementById('log-container'), {
+                    value: value,
+                    language: 'mylogs',
+                    theme: 'tomlTheme-dark',
+                    automaticLayout: true,
+                    readOnly: true
+                });
+                });
+                // Focus at the end of the file:
+                const model = editorLog.getModel();
+                const lastLineNumber = model.getLineCount();
+                const lastLineColumn = model.getLineMaxColumn(lastLineNumber);
+                editorLog.setPosition({ lineNumber: lastLineNumber, column: lastLineColumn });
+                editorLog.revealPosition({ lineNumber: lastLineNumber, column: lastLineColumn });
         },
         error: function(xhr, status, error) {
             var err = eval("(" + xhr.responseText + ")");
@@ -476,6 +509,14 @@ function refresh_logfile() {
     })        
 }
 
+function escapeHtml(text) {
+    return text
+        .replace(/&/g, "&")
+        .replace(/</g, "&lt;")
+        .replace(/>/g, "&gt;")
+        .replace(/"/g, "&quot;")
+        .replace(/'/g, "&#039;");
+}
 function delete_arch_rows(ids) {
     $.ajax({
         url:"/archived_runners/",
@@ -530,6 +571,7 @@ function generateStorageKey(batchId) {
 function disable_arch_buttons() {
     //disable buttons (enable on row selection)
     $('#button_runagain_arch').attr('disabled','disabled');
+    $('#button_runbt_arch').attr('disabled','disabled');
     $('#button_show_arch').attr('disabled','disabled');
     $('#button_delete_arch').attr('disabled','disabled');
     $('#button_delete_batch').attr('disabled','disabled');
@@ -552,4 +594,10 @@ function enable_arch_buttons() {
     $('#button_report').attr('disabled',false);
     $('#button_export_xml').attr('disabled',false);
     $('#button_export_csv').attr('disabled',false);
+
+    //Backtest same period button is displayed only when row with mode paper/live is selected
+    row = archiveRecords.row('.selected').data();
+    if ((row.mode == 'paper') || (row.mode == 'live')) {
+        $('#button_runbt_arch').attr('disabled',false);
+    }
 }

v2realbot/static/js/tables/archivetable/handlers.js

@@ -265,8 +265,8 @@ $(document).ready(function () {
 
             $('#diff_first').text(record1.name);
             $('#diff_second').text(record2.name);
-            $('#diff_first_id').text(data1.id);
-            $('#diff_second_id').text(data2.id);
+            $('#diff_first_id').text(data1.id + ' Batch: ' + data1.batch_id);
+            $('#diff_second_id').text(data2.id + ' Batch: ' + data2.batch_id);
 
             //monaco
             require(["vs/editor/editor.main"], () => {
@@ -358,11 +358,20 @@ $(document).ready(function () {
         })
     });
 
+    $('#closeLogModal').click(function () {
+        editorLog.dispose()
+    });
+
     //button to query log
     $('#logRefreshButton').click(function () {
+        editorLog.dispose()
         refresh_logfile()
     });
 
+    $('#logFileSelect').change(function() {
+        refresh_logfile();
+    });
+
     //button to open log modal
     $('#button_show_log').click(function () {
         window.$('#logModal').modal('show');
@@ -441,7 +450,7 @@ $(document).ready(function () {
                 $('#editstratvars').val(JSON.stringify(row.stratvars,null,2));
             }
             
-            
+            $('#edittransferables').val(JSON.stringify(row.transferables,null,2));
             $('#editstratjson').val(row.strat_json);
         }
     });
@@ -458,6 +467,11 @@ $(document).ready(function () {
     //run again button
     $('#button_runagain_arch').click(run_day_again)
 
+    //run in bt mode
+    $('#button_runbt_arch').click(function() {
+        run_day_again(true);
+      });
+
     //workaround pro spatne oznacovani selectu i pro group-headery
     // $('#archiveTable tbody').on('click', 'tr.group-header', function(event) {
     // var $row = $(this);

v2realbot/static/js/tables/archivetable/init.js

@@ -42,6 +42,8 @@ function initialize_archiveRecords() {
                         {data: 'end_positions_avgp', visible: true},
                         {data: 'metrics', visible: true},
                         {data: 'batch_id', visible: true},
+                        {data: 'batch_profit', visible: false},
+                        {data: 'batch_count', visible: false},
                     ],
             paging: true,
             processing: true,
@@ -68,30 +70,32 @@ function initialize_archiveRecords() {
                 {
                     targets: [5],
                     render: function ( data, type, row ) {
-                        now = new Date(data)
                         if (type == "sort") {
                             return new Date(data).getTime();
                         }
+                        //data = "2024-02-26T19:29:13.400621-05:00"
+                        // Create a date object from the string, represents given moment in time in UTC time
                         var date = new Date(data);
+            
                         tit = date.toLocaleString('cs-CZ', {
                                 timeZone: 'America/New_York',
                             })
 
-                        if (isToday(now)) {
+                        if (isToday(date)) {
+                            //console.log("volame isToday s", date)
                             //return local time only
-                            return '<div title="'+tit+'">'+ 'dnes ' + format_date(data,false,true)+'</div>'
+                            return '<div title="'+tit+'">'+ 'dnes ' + format_date(data,true,true)+'</div>'
                         }
                         else
                         {
                             //return  local datetime
-                            return '<div title="'+tit+'">'+ format_date(data,false,false)+'</div>'
+                            return '<div title="'+tit+'">'+ format_date(data,true,false)+'</div>'
                         }
                     },
                     },
                     {
                         targets: [6],
                         render: function ( data, type, row ) {
-                            now = new Date(data)
                             if (type == "sort") {
                                 return new Date(data).getTime();
                             }
@@ -100,14 +104,14 @@ function initialize_archiveRecords() {
                                     timeZone: 'America/New_York',
                                 })
         
-                            if (isToday(now)) {
+                            if (isToday(date)) {
                                 //return local time only
-                                return '<div title="'+tit+'" class="token level comment">'+ 'dnes ' + format_date(data,false,true)+'</div>'
+                                return '<div title="'+tit+'" class="token level comment">'+ 'dnes ' + format_date(data,true,true)+'</div>'
                             }
                             else
                             {
                                 //return  local datetime
-                                return '<div title="'+tit+'" class="token level number">'+ format_date(data,false,false)+'</div>'
+                                return '<div title="'+tit+'" class="token level number">'+ format_date(data,true,false)+'</div>'
                             }
                         },
                         },
@@ -237,6 +241,8 @@ function initialize_archiveRecords() {
                     var groupId = group ? group : 'no-batch-id-' + firstRowData.id;
                     var stateKey = 'dt-group-state-' + groupId;
                     var state = localStorage.getItem(stateKey);
+                    var profit = firstRowData.batch_profit
+                    var itemCount = firstRowData.batch_count
 
                     // Iterate over each row in the group to set the data attribute
                     // zaroven pro kazdy node nastavime viditelnost podle nastaveni
@@ -252,10 +258,10 @@ function initialize_archiveRecords() {
                     });
 
                     // Initialize variables for the group
-                    var itemCount = 0;
+                    //var itemCount = 0;
                     var period = '';
                     var batch_note = '';
-                    var profit = '';
+                    //var profit = '';
                     var started = null;
                     var stratinId = null;
                     var symbol = null;
@@ -284,13 +290,23 @@ function initialize_archiveRecords() {
 
                     //pokud mame batch_id podivame se zda jeho nastaveni uz nema a pokud ano pouzijeme to
                     //pokud nemame tak si ho loadneme
+                    //Tento kod parsuje informace do header hlavicky podle notes, je to relevantni pouze pro
+                    //backtest batche, nikoliv pro paper a live, kde pocet dni je neznamy a poznamka se muze menit
+                    //do budoucna tento parsing na frontendu bude nahrazen batch tabulkou v db, ktera persistuje
+                    //tyto data
                     if (group) {
                         const existingBatch = batchHeaders.find(batch => batch.batch_id == group);
                         //jeste neni v poli batchu - udelame hlavicku
                         if (!existingBatch) {
-                            itemCount = extractNumbersFromString(firstRowData.note);
-                            try {profit = firstRowData.metrics.profit.batch_sum_profit;}
-                            catch (e) {profit = 'NA'}
+                            // itemCount = extractNumbersFromString(firstRowData.note);
+                            // if (!itemCount) {
+                            //     itemCount="NA"
+                            // }
+                
+                            // try { profit = firstRowData.metrics.profit.batch_sum_profit;}
+                            // catch (e) {profit = 'NA'}
+                            
+                            // if (!profit) {profit = 'NA'}
                             period = firstRowData.note ? firstRowData.note.substring(0, 14) : '';
                             try {
                             batch_note = firstRowData.note ? firstRowData.note.split("N:")[1].trim() : ''
@@ -298,15 +314,22 @@ function initialize_archiveRecords() {
                             started = firstRowData.started
                             stratinId = firstRowData.strat_id
                             symbol = firstRowData.symbol
+                            if (period.startsWith("SCHED")) {
+                                period = "SCHEDULER";
+                              }
                             var newBatchHeader = {batch_id:group, batch_note:batch_note, profit:profit, itemCount:itemCount, period:period, started:started, stratinId:stratinId, symbol:symbol};
                             batchHeaders.push(newBatchHeader)
                         }
                         //uz je v poli, ale mame novejsi (pribyl v ramci backtestu napr.) - updatujeme
                         else if (new Date(existingBatch.started) < new Date(firstRowData.started)) {
-                            itemCount = extractNumbersFromString(firstRowData.note);
-                            try {profit = firstRowData.metrics.profit.batch_sum_profit;}
-                            catch (e) {profit = 'NA'}
+                            // try {itemCount = extractNumbersFromString(firstRowData.note);}
+                            // catch (e) {itemCount = 'NA'}
+                            // try {profit = firstRowData.metrics.profit.batch_sum_profit;}
+                            // catch (e) {profit = 'NA'}
                             period = firstRowData.note ? firstRowData.note.substring(0, 14) : '';
+                            if (period.startsWith("SCHED")) {
+                                period = "SCHEDULER";
+                              }
                             try {
                                 batch_note = firstRowData.note ? firstRowData.note.split("N:")[1].trim() : ''
                                 } catch (e) { batch_note = ''}

v2realbot/static/js/tables/runmanager/functions.js

@@ -0,0 +1,100 @@
+function refresh_runmanager_and_callback(row, callback) {
+    //console.log("entering refresh")
+    var request = $.ajax({
+        url: "/run_manager_records/"+row.id,
+        beforeSend: function (xhr) {
+            xhr.setRequestHeader('X-API-Key',
+            API_KEY); },
+        method:"GET",
+        contentType: "application/json",
+        dataType: "json",
+        success:function(data){   
+            //console.log("fetched data ok")                      
+            //console.log(JSON.stringify(data,null,2));
+        },
+        error: function(xhr, status, error) {
+            var err = eval("(" + xhr.responseText + ")");
+            window.alert(JSON.stringify(xhr));
+            console.log(JSON.stringify(xhr));
+        }
+    });
+
+    // Handling the responses of both requests
+    $.when(request).then(function(response) {
+        // Both requests have completed successfully
+        //console.log("Result from  request:", response);
+        //console.log("Response received. calling callback")
+        //call callback function
+        callback(response)
+
+    }, function(error) {
+        // Handle errors from either request here
+        // Example:
+        console.error("Error from first request:", error);
+        console.log("requesting id error")
+    });
+}
+
+function delete_runmanager_row(id) {
+    $.ajax({
+        url:"/run_manager_records/"+id,
+        beforeSend: function (xhr) {
+            xhr.setRequestHeader('X-API-Key',
+                API_KEY); },
+        method:"DELETE",
+        contentType: "application/json",
+        dataType: "json",
+        // data: JSON.stringify(ids),
+        success:function(data){				
+            $('#delFormRunmanager')[0].reset();
+            window.$('#delModalRunmanager').modal('hide');				
+            $('#deleterunmanager').attr('disabled', false);
+            //console.log(data)
+            runmanagerRecords.ajax.reload();
+            disable_runmanager_buttons()
+        },
+        error: function(xhr, status, error) {
+            var err = eval("(" + xhr.responseText + ")");
+            window.alert(JSON.stringify(xhr));
+            console.log(JSON.stringify(xhr));
+            $('#deleterunmanager').attr('disabled', false);
+            //archiveRecords.ajax.reload();
+        }
+    })
+}
+
+//enable/disable based if row(s) selected
+function disable_runmanager_buttons() {
+    //disable buttons (enable on row selection)
+    //$('#button_add_sched').attr('disabled','disabled');
+    $('#button_edit_sched').attr('disabled','disabled');
+    $('#button_delete_sched').attr('disabled','disabled');
+    $('#button_history_sched').attr('disabled','disabled');
+}
+
+function enable_runmanager_buttons() {
+    //enable buttons
+    //$('#button_add_sched').attr('disabled',false);
+    $('#button_edit_sched').attr('disabled',false);
+    $('#button_delete_sched').attr('disabled',false);
+    $('#button_history_sched').attr('disabled',false);
+}
+
+// Function to update options
+function updateSelectOptions(type) {
+    var allOptions = {
+        'paper': '<option value="paper">paper</option>',
+        'live': '<option value="live">live</option>',
+        'backtest': '<option value="backtest">backtest</option>',
+        'prep': '<option value="prep">prep</option>'
+    };
+
+    var allowedOptions = (type === "schedule") ? ['paper', 'live'] : Object.keys(allOptions);
+    
+    var $select = $('#runmanmode');
+    $select.empty(); // Clear current options
+
+    allowedOptions.forEach(function(opt) {
+        $select.append(allOptions[opt]); // Append allowed options
+    });
+}

v2realbot/static/js/tables/runmanager/handlers.js

@@ -0,0 +1,296 @@
+/* <button title="Create new" id="button_add_sched" class="btn btn-outline-success btn-sm">Add</button>
+<button title="Edit selected" id="button_edit_sched" class="btn btn-outline-success btn-sm">Edit</button>
+<button title="Delete selected" id="button_delete_sched" class="btn btn-outline-success btn-sm">Delete</button>
+
+
+id="delModalRunmanager" 
+id="addeditModalRunmanager"   id="runmanagersubmit" == "Add vs Edit"
+ */
+
+// Function to apply filter
+function applyFilter(filter) {
+    switch (filter) {
+        case 'filterSchedule':
+            runmanagerRecords.column(1).search('schedule').draw();
+            break;
+        case 'filterQueue':
+            runmanagerRecords.column(1).search('queue').draw();
+            break;
+        // default:
+        //     runmanagerRecords.search('').columns().search('').draw();
+        //     break;
+    }
+}
+
+// Function to get the ID of current active filter
+function getCurrentFilter() {
+    var activeFilter = $('input[name="filterOptions"]:checked').attr('id');
+    console.log("activeFilter", activeFilter)
+    return activeFilter;
+}
+
+// Function to show/hide input fields based on the current filter
+function updateInputFields() {
+    var activeFilter = getCurrentFilter();
+
+    switch (activeFilter) {
+        case 'filterSchedule':
+            $('#runmantestlist_id_div').hide();
+            $('#runmanbt_from_div').hide();
+            $('#runmanbt_to_div').hide();
+
+            $('#runmanvalid_from_div').show();
+            $('#runmanvalid_to_div').show();
+            $('#runmanstart_time_div').show();
+            $('#runmanstop_time_div').show();
+            break;
+        case 'filterQueue':
+            $('#runmantestlist_id_div').show();
+            $('#runmanbt_from_div').show();
+            $('#runmanbt_to_div').show();
+
+            $('#runmanvalid_from_div').hide();
+            $('#runmanvalid_to_div').hide();
+            $('#runmanstart_time_div').hide();
+            $('#runmanstop_time_div').hide();
+            break;
+        default:
+            //$('#inputForSchedule, #inputForQueue').hide();
+            break;
+    }
+}
+
+
+//event handlers for runmanager table
+$(document).ready(function () {
+    initialize_runmanagerRecords();
+    runmanagerRecords.ajax.reload();
+    disable_runmanager_buttons();
+
+    //on click on #button_refresh_sched call runmanagerRecords.ajax.reload()
+    $('#button_refresh_sched').click(function () {
+        runmanagerRecords.ajax.reload();
+    });
+
+    // Event listener for changes in the radio buttons
+    $('input[name="filterOptions"]').on('change', function() {
+        var selectedFilter = $(this).attr('id');
+        applyFilter(selectedFilter);
+        // Save the selected filter to local storage
+        localStorage.setItem('selectedFilter', selectedFilter);
+    });
+
+
+    // Load the last selected filter from local storage and apply it
+    var lastSelectedFilter = localStorage.getItem('selectedFilter');
+    if (lastSelectedFilter) {
+        $('#' + lastSelectedFilter).prop('checked', true).change();
+    }
+
+    //listen for changes on weekday enabling button
+    $('#runman_enable_weekdays').change(function() {
+        if ($(this).is(':checked')) {
+            $('.weekday-checkboxes').show();
+        } else {
+            $('.weekday-checkboxes').hide();
+        }
+    }); 
+
+    //selectable rows in runmanager table
+    $('#runmanagerTable tbody').on('click', 'tr', function () {
+        if ($(this).hasClass('selected')) {
+            //$(this).removeClass('selected');
+            //aadd here condition that disable is called only when there is no other selected class on tr[data-group-name]
+        // Check if there are no other selected rows before disabling buttons
+            if ($('#runmanagerTable tr.selected').length === 1) {
+                disable_runmanager_buttons();
+            }
+            //disable_arch_buttons()
+        } else {
+            //archiveRecords.$('tr.selected').removeClass('selected');
+            $(this).addClass('selected');
+            enable_runmanager_buttons()
+        }
+    });
+
+
+    //delete button
+    $('#button_delete_sched').click(function () {
+    row = runmanagerRecords.row('.selected').data();
+    window.$('#delModalRunmanager').modal('show');
+    $('#delidrunmanager').val(row.id);
+    // $('#action').val('delRecord');
+    // $('#save').val('Delete');
+    });
+
+    //button add
+    $('#button_add_sched').click(function () {
+        window.$('#addeditModalRunmanager').modal('show');
+        $('#addeditFormRunmanager')[0].reset();
+        //$("#runmanid").prop('readonly', false);
+        if (getCurrentFilter() == 'filterQueue') {
+            mode = 'queue';
+        } else {
+            mode = 'schedule';
+        }
+        //set modus
+        $('#runmanmoddus').val(mode);
+        //updates fields according to selected type
+        updateInputFields();
+        updateSelectOptions(mode);
+        // Initially, check the value of "batch" and enable/disable "btfrom" and "btto" accordingly
+        if ($("#runmantestlist_id").val() !== "") {
+            $("#runmanbt_from, #runmanbt_to").prop("disabled", true);
+        } else {
+            $("#runmanbt_from, #runmanbt_to").prop("disabled", false);
+        }
+
+        // Listen for changes in the "batch" input and diasble/enable "btfrom" and "btto" accordingly
+        $("#runmantestlist_id").on("input", function() {
+            if ($(this).val() !== "") {
+                // If "batch" is not empty, disable "from" and "to"
+                $("#runmanbt_from, #runmanbt_to").prop("disabled", true);
+            } else {
+                // If "batch" is empty, enable "from" and "to"
+                $("#runmanbt_from, #runmanbt_to").prop("disabled", false);
+            }
+        });
+
+        $('.modal-title_run').html("<i class='fa fa-plus'></i> Add Record");
+        $('#runmanagersubmit').val('Add');
+        $('#runmanager_enable_weekdays').prop('checked', false);
+        $('.weekday-checkboxes').hide();
+    });
+
+    //edit button
+    $('#button_edit_sched').click(function () {
+        row = runmanagerRecords.row('.selected').data();
+        if (row == undefined) {
+            return
+        }
+        window.$('#addeditModalRunmanager').modal('show');
+        //set fields as readonly
+        //$("#runmanid").prop('readonly', true); 
+        //$("#runmanmoddus").prop('readonly', true); 
+        console.log("pred editem puvodni row", row)
+        refresh_runmanager_and_callback(row, show_edit_modal)
+
+        function show_edit_modal(row) {
+            console.log("pred editem refreshnuta row", row);
+            $('#addeditFormRunmanager')[0].reset();
+            $('.modal-title_run').html("<i class='fa fa-plus'></i> Edit Record");
+            $('#runmanagersubmit').val('Edit');
+
+            //updates fields according to selected type
+            updateInputFields();
+            // get shared attributess
+            $('#runmanid').val(row.id);
+            $('#runmanhistory').val(row.history);
+            $('#runmanlast_processed').val(row.last_processed);
+            $('#runmanstrat_id').val(row.strat_id);
+            $('#runmanmode').val(row.mode);
+            $('#runmanmoddus').val(row.moddus);
+            $('#runmanaccount').val(row.account);
+            $('#runmanstatus').val(row.status);
+            $('#runmanbatch_id').val(row.batch_id);
+            $('#runmanrunner_id').val(row.runner_id);
+            $("#runmanilog_save").prop("checked", row.ilog_save);
+            $('#runmannote').val(row.note);
+
+            $('#runmantestlist_id').val(row.testlist_id);
+            $('#runmanbt_from').val(row.bt_from);
+            $('#runmanbt_to').val(row.bt_to);
+
+            $('#runmanvalid_from').val(row.valid_from);
+            $('#runmanvalid_to').val(row.valid_to);
+            $('#runmanstart_time').val(row.start_time);				
+            $('#runmanstop_time').val(row.stop_time);
+
+            // Initially, check the value of "batch" and enable/disable "from" and "to" accordingly
+            if ($("#runmantestlist_id").val() !== "") {
+                $("#runmanbt_from, #runmanbt_to").prop("disabled", true);
+            } else {
+                $("#runmanbt_from, #runmanbt_to").prop("disabled", false);
+            }
+
+            // Listen for changes in the "batch" input
+            $("#runmantestlist_id").on("input", function() {
+                if ($(this).val() !== "") {
+                    // If "batch" is not empty, disable "from" and "to"
+                    $("#runmanbt_from, #runmanbt_to").prop("disabled", true);
+                } else {
+                    // If "batch" is empty, enable "from" and "to"
+                    $("#runmanbt_from, #runmanbt_to").prop("disabled", false);
+                }
+            });
+
+            type =   $('#runmanmoddus').val();
+            updateSelectOptions(type);
+
+            //add weekdays_filter transformation from string "1,2,3" to array [1,2,3]
+     
+            // Assuming you have row.weekend_filter available here
+            var weekdayFilter = row.weekdays_filter; 
+
+            //
+
+            if (weekdayFilter) {
+                $('#runman_enable_weekdays').prop('checked', true);
+                $(".weekday-checkboxes").show();
+
+                // Map numbers to weekday names
+                var dayOfWeekMap = {
+                    "0": "monday",
+                    "1": "tuesday",
+                    "2": "wednesday",
+                    "3": "thursday",
+                    "4": "friday",
+                    "5": "saturday", // Adjust if needed for your mapping
+                    "6": "sunday"  // Adjust if needed for your mapping
+                };
+
+                // Iterate through the selected days
+                $.each(weekdayFilter, function(index, dayIndex) {
+                    var dayOfWeek = dayOfWeekMap[dayIndex];
+                    if (dayOfWeek) { // Make sure the day exists in the map
+                        $("#" + dayOfWeek).prop("checked", true);  
+                    }
+                });
+            }
+            else {
+                $('#runman_enable_weekdays').prop('checked', false);
+                $(".weekday-checkboxes").hide();
+            }
+
+        }
+
+    });
+
+    //edit button
+    $('#button_history_sched').click(function () {
+        row = runmanagerRecords.row('.selected').data();
+        if (row == undefined) {
+            return
+        }
+        window.$('#historyModalRunmanager').modal('show');
+        //set fields as readonly
+        //$("#runmanid").prop('readonly', true); 
+        //$("#runmanmoddus").prop('readonly', true); 
+        //console.log("pred editem puvodni row", row)
+        refresh_runmanager_and_callback(row, show_history_modal)
+
+        function show_history_modal(row) {
+            //console.log("pred editem refreshnuta row", row);
+            $('#historyModalRunmanagerForm')[0].reset();
+            // get shared attributess
+            $('#RunmanId').val(row.id);
+            var date = new Date(row.last_processed);
+            formatted = date.toLocaleString('cs-CZ', {
+                    timeZone: 'America/New_York',
+                })
+            $('#Runmanlast_processed').val(formatted);
+            $('#Runmanhistory').val(row.history);
+        }
+    });
+
+});

v2realbot/static/js/tables/runmanager/init.js

@@ -0,0 +1,322 @@
+var runmanagerRecords = null
+
+//ekvivalent to ready
+function initialize_runmanagerRecords() {
+
+    //archive table
+    runmanagerRecords = 
+        $('#runmanagerTable').DataTable( {
+            ajax: { 
+                url: '/run_manager_records/',
+                dataSrc: '',
+                method:"GET",
+                contentType: "application/json",
+                // dataType: "json",
+                beforeSend: function (xhr) {
+                    xhr.setRequestHeader('X-API-Key',
+                        API_KEY); },
+                data: function (d) {
+                            return JSON.stringify(d);
+                        },       
+                error: function(xhr, status, error) {
+                    //var err = eval("(" + xhr.responseText + ")");
+                    //window.alert(JSON.stringify(xhr));
+                    console.log(JSON.stringify(xhr));
+                }
+                },
+            columns: [  { data: 'id' },
+                        { data: 'moddus' },
+                        { data: 'strat_id' },
+                        {data: 'symbol'},
+                        {data: 'account'},
+                        {data: 'mode'},
+                        {data: 'note'},
+                        {data: 'ilog_save'},
+                        {data: 'bt_from'},
+                        {data: 'bt_to'},
+                        {data: 'weekdays_filter', visible: true},
+                        {data: 'batch_id', visible: true},
+                        {data: 'start_time', visible: true},
+                        {data: 'stop_time', visible: true},
+                        {data: 'status'},
+                        {data: 'last_processed', visible: true},
+                        {data: 'history', visible: false},
+                        {data: 'valid_from', visible: true},
+                        {data: 'valid_to', visible: true},
+                        {data: 'testlist_id', visible: true},
+                        {data: 'strat_running', visible: true},
+                        {data: 'runner_id', visible: true},
+                        {data: 'market', visible: true},                  
+                    ],
+            paging: true,
+            processing: true,
+            serverSide: false,
+            columnDefs: [
+                {   //history
+                    targets: [6],
+                    render: function(data, type, row, meta) {
+                        if (!data) return data;
+                        var stateClass = 'truncated-text';
+                        var uniqueId = 'note-' + row.id;
+        
+                        if (localStorage.getItem(uniqueId) === 'expanded') {
+                            stateClass = 'expanded-text';
+                        }
+        
+                        if (type === 'display') {
+                            return '<div class="' + stateClass + '" id="' + uniqueId + '">' + data + '</div>';
+                        }
+                        return data;
+                    },
+                },
+                {   //iloc_save
+                    targets: [7],
+                    render: function ( data, type, row ) {
+                        //if ilog_save true
+                        if (data) {
+                            return '<span class="material-symbols-outlined">done_outline</span>'
+                        }
+                        else {
+                            return null
+                        }
+                    },
+                },
+                {
+                    targets: [10], //weekdays
+                    render: function (data, type, row) {
+                        if (!data) return data;
+                        // Map each number in the array to a weekday
+                        var weekdays = ["monday", "tuesday", "wednesday", "thursday", "friday", "saturday", "sunday"];
+                        return data.map(function(dayNumber) {
+                            return weekdays[dayNumber];
+                        }).join(', ');
+                    },
+                },
+                {
+                    targets: [0, 21], //interni id, runner_id
+                    render: function ( data, type, row ) {
+                        if (!data) return data;
+                        if (type === 'display') {
+                            return '<div class="tdnowrap" data-bs-toggle="tooltip" data-bs-placement="top" title="'+data+'">'+data+'</div>';
+                        }
+                        return data;
+                    },
+                },
+                {
+                    targets: [2], //strat_id
+                    render: function ( data, type, row ) {
+                        if (type === 'display') {
+                            //console.log("arch")
+                            var color = getColorForId(data);
+                            return '<div class="tdnowrap" data-bs-toggle="tooltip" data-bs-placement="top" title="'+data+'"><span class="color-tag" style="background-color:' + color + ';"></span>'+data+'</div>';
+                        }
+                        return data;
+                    },
+                },
+                {
+                    targets: [3,12,13], //symbol, start_time, stop_time
+                    render: function ( data, type, row ) {
+                        if (type === 'display') {
+                            //console.log("arch")
+                            var color = getColorForId(row.strat_id);
+                            return '<span style="color:' + color + ';">'+data+'</span>';
+                        }
+                        return data;
+                    },
+                },
+                {
+                    targets: [16], //history
+                    render: function ( data, type, row ) {
+                        if (type === 'display') {
+                            if (!data) data = "";
+                            return '<div data-bs-toggle="tooltip" data-bs-placement="top" title="'+data+'">'+data+'</div>';
+                        }
+                        return data;
+                    },
+                },
+                {
+                    targets: [14], //status
+                    render: function ( data, type, row ) {
+                        if (type === 'display') {
+                            //console.log("arch")
+                            var color = data == "active" ? "#3f953f" : "#f84c4c";
+                            return '<span style="color:' + color + ';">'+data+'</span>';
+                        }
+                        return data;
+                    },
+                },
+                {
+                    targets: [20], //strat_running
+                    render: function ( data, type, row ) {
+                        if (type === 'display') {
+                            if (!data) data = "";
+                            console.log("running", data)
+                            //var color = data == "active" ? "#3f953f" : "#f84c4c";
+                            data = data ? "running" : ""
+                            return '<div title="' + row.runner_id + '" style="color:#3f953f;">'+data+'</div>';
+                        }
+                        return data;
+                    },
+                },
+                // {
+                // targets: [0,17],
+                // render: function ( data, type, row ) {
+                //     if (!data) return data
+                //     return '<div class="tdnowrap" title="'+data+'">'+data+'</i>'
+                // },
+                // },
+                {   
+                    targets: [15,17, 18, 8, 9], //start, stop, valid_from, valid_to, bt_from, bt_to, last_proccessed
+                    render: function ( data, type, row ) {
+                        if (!data) return data
+                        if (type == "sort") {
+                            return new Date(data).getTime();
+                        }
+                        var date = new Date(data);
+                        tit = date.toLocaleString('cs-CZ', {
+                                timeZone: 'America/New_York',
+                            })
+                        return '<div title="'+tit+'">'+ format_date(data,true,false)+'</div>'
+                        // if (isToday(now)) {
+                        //     //return local time only
+                        //     return '<div title="'+tit+'">'+ 'dnes ' + format_date(data,true,true)+'</div>'
+                        // }
+                        // else
+                        // {
+                        //     //return  local datetime
+                        //     return '<div title="'+tit+'">'+ format_date(data,true,false)+'</div>'
+                        // }
+                    },
+                    },
+                    // {
+                    //     targets: [6],
+                    //     render: function ( data, type, row ) {
+                    //         now = new Date(data)
+                    //         if (type == "sort") {
+                    //             return new Date(data).getTime();
+                    //         }
+                    //         var date = new Date(data);
+                    //         tit = date.toLocaleString('cs-CZ', {
+                    //                 timeZone: 'America/New_York',
+                    //             })
+        
+                    //         if (isToday(now)) {
+                    //             //return local time only
+                    //             return '<div title="'+tit+'" class="token level comment">'+ 'dnes ' + format_date(data,false,true)+'</div>'
+                    //         }
+                    //         else
+                    //         {
+                    //             //return  local datetime
+                    //             return '<div title="'+tit+'" class="token level number">'+ format_date(data,false,false)+'</div>'
+                    //         }
+                    //     },
+                    //     },
+                    // {
+                    // targets: [9,10],
+                    // render: function ( data, type, row ) {
+                    //     if (type == "sort") {
+                    //         return new Date(data).getTime();
+                    //     }
+                    //     //console.log(data)
+                    //     //market datetime
+                    //     return data ? format_date(data, true) : data
+                    // },
+                    // },
+                    // {
+                    //     targets: [2],
+                    //     render: function ( data, type, row ) {
+                    //         return '<div class="tdname tdnowrap" title="'+data+'">'+data+'</div>'
+                    //     },
+                    // },
+                    // // {
+                    // //     targets: [4],
+                    // //     render: function ( data, type, row ) {
+                    // //         return '<div class="tdname tdnowrap" title="'+data+'">'+data+'</div>'
+                    // //     },
+                    // // },
+                    // {
+                    //     targets: [16],
+                    //     render: function ( data, type, row ) {
+                    //         //console.log("metrics", data)
+                    //         try {
+                    //             data = JSON.parse(data)
+                    //         }
+                    //         catch (error) {
+                    //             //console.log(error)
+                    //         }
+                    //         var res = JSON.stringify(data)
+                    //         var unquoted = res.replace(/"([^"]+)":/g, '$1:')
+
+                    //         //zobrazujeme jen kratkou summary pokud mame, jinak davame vse, do titlu davame vzdy vse
+                    //         //console.log(data)
+                    //         short = null
+                    //         if ((data) && (data.profit) && (data.profit.sum)) {
+                    //             short = data.profit.sum
+                    //         }
+                    //         else {
+                    //             short = unquoted
+                    //         }
+                    //         return '<div class="tdmetrics" title="'+unquoted+'">'+short+'</div>'
+                    //     },
+                    // },
+                    // {
+                    //     targets: [4],
+                    //     render: function ( data, type, row ) {
+                    //         return '<div class="tdnote" title="'+data+'">'+data+'</div>'
+                    //     },
+                    // },
+                    // {
+                    //     targets: [13,14,15],
+                    //     render: function ( data, type, row ) {
+                    //         return '<div class="tdsmall">'+data+'</div>'
+                    //     },
+                    // },
+                    // {
+                    //     targets: [11],
+                    //     render: function ( data, type, row ) {
+                    //         //if ilog_save true
+                    //         if (data) {
+                    //             return '<span class="material-symbols-outlined">done_outline</span>'
+                    //         }
+                    //         else {
+                    //             return null
+                    //         }
+                    //     },
+                    // },
+                    {
+                        targets: [4], //account
+                        render: function ( data, type, row ) {
+                            //if ilog_save true
+                            if (data == "ACCOUNT1") {
+                                res="ACC1"
+                            }
+                            else if (data == "ACCOUNT2") {
+                                res="ACC2"
+                            }
+                            else { res=data}
+                            return res
+                        },
+                    },
+                    {
+                        targets: [5], //mode
+                        render: function ( data, type, row ) {
+                            //if ilog_save true
+                            if (data == "backtest") {
+                                res="bt"
+                            }
+                            else { res=data}
+                            return res
+                        },
+                    }
+            ],
+            order: [[1, 'asc']],
+            select: {
+                info: true,
+                style: 'multi',
+                //selector: 'tbody > tr:not(.group-header)'
+                selector: 'tbody > tr:not(.group-header)' 
+            },
+            paging: true
+    });
+
+}

v2realbot/static/js/tables/runmanager/modals.js

@@ -0,0 +1,195 @@
+//delete modal
+$("#delModalRunmanager").on('submit','#delFormRunmanager', function(event){
+    event.preventDefault();
+    $('#deleterunmanager').attr('disabled','disabled');
+
+    //get val from #delidrunmanager
+    id = $('#delidrunmanager').val();
+    delete_runmanager_row(id);
+});
+
+//add api
+// fetch(`/run_manager_records/`, {
+//     method: 'POST',
+//     headers: { 
+//         'Content-Type': 'application/json',
+//         'X-API-Key': API_KEY 
+//     },
+//     body: JSON.stringify(newRecord) 
+// })
+
+// fetch(`/run_manager_records/${recordId}`, {
+//     method: 'PATCH',
+//     headers: { 
+//         'Content-Type': 'application/json',
+//         'X-API-Key': API_KEY 
+//     },
+//     body: JSON.stringify(updatedData)
+// })
+
+function getCheckedWeekdays() {
+    const checkboxes = document.querySelectorAll('input[name="weekdays_filter[]"]:checked');
+    const selectedDays = Array.from(checkboxes).map(checkbox => checkbox.value);
+    return selectedDays;
+}
+
+
+//submit form
+$("#addeditModalRunmanager").on('submit','#addeditFormRunmanager', function(event){
+    //event.preventDefault();
+    //code for add
+    if ($('#runmanagersubmit').val() == "Add") {
+
+        event.preventDefault();
+        //set id as editable
+        $('#runmanagersubmit').attr('disabled','disabled');
+        //trow = runmanagerRecords.row('.selected').data();
+        //note = $('#editnote').val()
+
+        // Handle weekdays functionality
+        var weekdays = [];
+        if ($('#runman_enable_weekdays').is(':checked')) {
+            $('#addeditFormRunmanager input[name="weekdays"]:checked').each(function() {
+                var weekday = $(this).val();
+                switch(weekday) {
+                    case 'monday':    weekdays.push(0); break;
+                    case 'tuesday':   weekdays.push(1); break;
+                    case 'wednesday': weekdays.push(2); break;
+                    case 'thursday':  weekdays.push(3); break;
+                    case 'friday':    weekdays.push(4); break;
+                    // Add cases for Saturday and Sunday if needed
+                }
+            });
+        }
+        console.log("weekdays pole", weekdays)
+
+        var formData = $(this).serializeJSON();
+        console.log("formData", formData)
+
+        delete formData["enable_weekdays"]
+        delete formData["weekdays"]
+
+        //pokud je zatrzeno tak aplikujeme filter, jinak nevyplnujeme
+        if (weekdays.length > 0) {
+            formData.weekdays_filter = weekdays
+        }
+        console.log(formData)
+        if ($('#runmanilog_save').prop('checked')) {
+            formData.ilog_save = true;
+        }
+        else 
+        {
+            formData.ilog_save = false;
+        }
+
+        //if (formData.batch_id == "") {delete formData["batch_id"];}
+
+        //projede vsechny atributy a kdyz jsou "" tak je smaze, default nahradi backend
+        for (let key in formData) {
+            if (formData.hasOwnProperty(key) && formData[key] === "") {
+                delete formData[key];
+            }
+        }
+
+        jsonString = JSON.stringify(formData);
+        console.log("json string pro formData pred odeslanim", jsonString)
+        $.ajax({
+            url:"/run_manager_records/",
+            beforeSend: function (xhr) {
+                xhr.setRequestHeader('X-API-Key',
+                    API_KEY); },
+            method:"POST",
+            contentType: "application/json",
+            // dataType: "json",
+            data: jsonString,
+            success:function(data){				
+                $('#addeditFormRunmanager')[0].reset();
+                window.$('#addeditModalRunmanager').modal('hide');				
+                $('#runmanagersubmit').attr('disabled', false);
+                runmanagerRecords.ajax.reload();
+                disable_runmanager_buttons();
+            },
+            error: function(xhr, status, error) {
+                var err = eval("(" + xhr.responseText + ")");
+                window.alert(JSON.stringify(xhr));
+                console.log(JSON.stringify(xhr));
+                $('#runmanagersubmit').attr('disabled', false);
+            }
+        })
+    }
+    //code for edit
+    else {
+        event.preventDefault();       
+        $('#runmanagersubmit').attr('disabled','disabled');
+        //trow = runmanagerRecords.row('.selected').data();
+        //note = $('#editnote').val()
+
+        // Handle weekdays functionality
+        var weekdays = [];
+        if ($('#runman_enable_weekdays').is(':checked')) {
+            $('#addeditFormRunmanager input[name="weekdays"]:checked').each(function() {
+                var weekday = $(this).val();
+                switch(weekday) {
+                    case 'monday':    weekdays.push(0); break;
+                    case 'tuesday':   weekdays.push(1); break;
+                    case 'wednesday': weekdays.push(2); break;
+                    case 'thursday':  weekdays.push(3); break;
+                    case 'friday':    weekdays.push(4); break;
+                    // Add cases for Saturday and Sunday if needed
+                }
+            });
+        }
+
+        var formData = $(this).serializeJSON();
+        delete formData["enable_weekdays"]
+        delete formData["weekdays"]
+
+        //pokud je zatrzeno tak aplikujeme filter, jinak nevyplnujeme
+        if (weekdays.length > 0) {
+            formData.weekdays_filter = weekdays
+        }
+        console.log(formData)
+        if ($('#runmanilog_save').prop('checked')) {
+            formData.ilog_save = true;
+        }
+        else 
+        {
+            formData.ilog_save = false;
+        }
+
+        //projede formatributy a kdyz jsou "" tak je smaze, default nahradi backend - tzn. smaze se puvodni hodnota
+        for (let key in formData) {
+            if (formData.hasOwnProperty(key) && formData[key] === "") {
+                delete formData[key];
+            }
+        }
+
+        jsonString = JSON.stringify(formData);
+        console.log("EDIT json string pro formData pred odeslanim", jsonString);
+        $.ajax({
+            url:"/run_manager_records/"+formData.id,
+            beforeSend: function (xhr) {
+                xhr.setRequestHeader('X-API-Key',
+                    API_KEY); },
+            method:"PATCH",
+            contentType: "application/json",
+            // dataType: "json",
+            data: jsonString,
+            success:function(data){
+                console.log("EDIT success data", data);				
+                $('#addeditFormRunmanager')[0].reset();
+                window.$('#addeditModalRunmanager').modal('hide');				
+                $('#runmanagersubmit').attr('disabled', false);
+                runmanagerRecords.ajax.reload();
+                disable_runmanager_buttons();
+            },
+            error: function(xhr, status, error) {
+                var err = eval("(" + xhr.responseText + ")");
+                window.alert(JSON.stringify(xhr));
+                console.log(JSON.stringify(xhr));
+                $('#runmanagersubmit').attr('disabled', false);
+            }
+        });  
+    }
+        
+});

v2realbot/static/js/utils/utils.js

@@ -371,9 +371,10 @@ function initialize_chart() {
     }
 
     chart = LightweightCharts.createChart(document.getElementById('chart'), chartOptions);
-    chart.applyOptions({ timeScale: { visible: true, timeVisible: true, secondsVisible: true }, crosshair: {
+    chart.applyOptions({ timeScale: { visible: true, timeVisible: true, secondsVisible: true, minBarSpacing: 0.003}, crosshair: {
         mode: LightweightCharts.CrosshairMode.Normal, labelVisible: true
     }})
+    console.log("chart intiialized")
 }
 
 //mozna atributy last value visible
@@ -990,12 +991,26 @@ JSON.safeStringify = (obj, indent = 2) => {
     return retVal;
   };
 
- function isToday(someDate) {
-    const today = new Date()
-    return someDate.getDate() == today.getDate() &&
-      someDate.getMonth() == today.getMonth() &&
-      someDate.getFullYear() == today.getFullYear()
-  }
+
+function isToday(someDate) {
+  // Convert input date to Eastern Time
+  var dateInEastern = new Date(someDate.toLocaleString('en-US', { timeZone: 'America/New_York' }));
+  //console.log("vstupuje ",someDate)
+  //console.log("americky ",dateInEastern)
+  // Get today's date in Eastern Time
+  var todayInEastern = new Date(new Date().toLocaleString('en-US', { timeZone: 'America/New_York' }));
+
+  return dateInEastern.getDate() === todayInEastern.getDate() &&
+    dateInEastern.getMonth() === todayInEastern.getMonth() &&
+    dateInEastern.getFullYear() === todayInEastern.getFullYear();
+}  
+//  function isToday(someDate) {
+  
+//     const today = new Date()
+//     return someDate.getDate() == today.getDate() &&
+//       someDate.getMonth() == today.getMonth() &&
+//       someDate.getFullYear() == today.getFullYear()
+//   }
 
 //https://www.w3schools.com/jsref/jsref_tolocalestring.asp
 function format_date(datum, markettime = false, timeonly = false) {

v2realbot/static/main.css

@@ -250,6 +250,17 @@ strong {
   --bs-form-invalid-border-color: #ea868f;
 }
 
+.btn-check:checked+.btn, .btn.active, .btn.show, .btn:first-child:active, :not(.btn-check)+.btn:active {
+  color: var(--bs-btn-active-color);
+  background-color: #3a5962;
+  border-color: #3a5962;
+}
+
+.btn-outline-primary {
+  --bs-btn-color: #94b1b3;
+  --bs-btn-border-color: #3a5a62;
+}
+
 .form-label {
   margin-top: 0.5em;
   color: var(--bs-emphasis-color);
@@ -983,3 +994,24 @@ pre {
 #datepicker:disabled {
   background-color: #f2f2f2;
 }
+
+#disk-gauge-container {
+  text-align: center;
+  width: 400px;
+}
+
+
+#disk-gauge {
+  width: 100%;
+  height: 20px;
+  background-color: #ddd;
+  border-radius: 10px;
+  overflow: hidden;
+}
+
+#disk-gauge-bar {
+  height: 100%;
+  background-color: #4285F4;
+  width: 0%; /* Initial state */
+  border-radius: 10px;
+}

v2realbot/strategy/StrategyClassicSL.py

@@ -9,7 +9,7 @@ from alpaca.trading.enums import TradeEvent, OrderStatus
 from v2realbot.indicators.indicators import ema
 import orjson
 from datetime import datetime
-#from rich import print
+from rich import print as printanyway
 from random import randrange
 from alpaca.common.exceptions import APIError
 import numpy as np
@@ -35,36 +35,62 @@ class StrategyClassicSL(Strategy):
 
         max_sum_profit_to_quit_rel = safe_get(self.state.vars, "max_sum_profit_to_quit_rel", None)
         max_sum_loss_to_quit_rel = safe_get(self.state.vars, "max_sum_loss_to_quit_rel", None)
+        #load typ direktivy hard/soft cutoff
+        hard_cutoff = safe_get(self.state.vars, "hard_cutoff", False)
 
         rel_profit  = round(float(np.sum(self.state.rel_profit_cum)),5)
         if max_sum_profit_to_quit_rel is not None:
             if rel_profit >= float(max_sum_profit_to_quit_rel):
-                self.state.ilog(e=f"QUITTING MAX SUM REL PROFIT REACHED {max_sum_profit_to_quit_rel=} {self.state.profit=} {rel_profit=} relprofits:{str(self.state.rel_profit_cum)}")
+                msg = f"QUITTING {hard_cutoff=} MAX SUM REL PROFIT REACHED {max_sum_profit_to_quit_rel=} {self.state.profit=} {rel_profit=} relprofits:{str(self.state.rel_profit_cum)}"
+                printanyway(msg)
+                self.state.ilog(e=msg)
                 self.state.vars.pending = "max_sum_profit_to_quit_rel"
-                send_to_telegram(f"QUITTING MAX SUM REL PROFIT REACHED {max_sum_profit_to_quit_rel=} {self.state.profit=} {rel_profit=} relprofits:{str(self.state.rel_profit_cum)}")
-                self.signal_stop = True
+                if self.mode not in [Mode.BT, Mode.PREP]:
+                    send_to_telegram(msg)
+                if hard_cutoff:
+                    self.hard_stop = True
+                else:
+                    self.soft_stop = True
                 return True
         if max_sum_loss_to_quit_rel is not None:
             if rel_profit < 0 and rel_profit <= float(max_sum_loss_to_quit_rel):
-                self.state.ilog(e=f"QUITTING MAX SUM REL LOSS REACHED {max_sum_loss_to_quit_rel=} {self.state.profit=} {rel_profit=} relprofits:{str(self.state.rel_profit_cum)}")
+                msg=f"QUITTING {hard_cutoff=} MAX SUM REL LOSS REACHED {max_sum_loss_to_quit_rel=} {self.state.profit=} {rel_profit=} relprofits:{str(self.state.rel_profit_cum)}"
+                printanyway(msg)
+                self.state.ilog(e=msg)
                 self.state.vars.pending = "max_sum_loss_to_quit_rel"
-                send_to_telegram(f"QUITTING MAX SUM REL LOSS REACHED {max_sum_loss_to_quit_rel=} {self.state.profit=} {rel_profit=} relprofits:{str(self.state.rel_profit_cum)}")
-                self.signal_stop = True
+                if self.mode not in [Mode.BT, Mode.PREP]:
+                    send_to_telegram(msg)
+                if hard_cutoff:
+                    self.hard_stop = True
+                else:
+                    self.soft_stop = True
                 return True
 
         if max_sum_profit_to_quit is not None:
             if float(self.state.profit) >= float(max_sum_profit_to_quit):
-                self.state.ilog(e=f"QUITTING MAX SUM ABS PROFIT REACHED {max_sum_profit_to_quit=} {self.state.profit=} {rel_profit=} relprofits:{str(self.state.rel_profit_cum)}")
+                msg = f"QUITTING {hard_cutoff=} MAX SUM ABS PROFIT REACHED {max_sum_profit_to_quit=} {self.state.profit=} {rel_profit=} relprofits:{str(self.state.rel_profit_cum)}"
+                printanyway(msg)
+                self.state.ilog(e=msg)
                 self.state.vars.pending = "max_sum_profit_to_quit"
-                send_to_telegram(f"QUITTING MAX SUM ABS PROFIT REACHED {max_sum_profit_to_quit=} {self.state.profit=} {rel_profit=} relprofits:{str(self.state.rel_profit_cum)}")
-                self.signal_stop = True
+                if self.mode not in [Mode.BT, Mode.PREP]:
+                    send_to_telegram(msg)
+                if hard_cutoff:
+                    self.hard_stop = True
+                else:
+                    self.soft_stop = True
                 return True
         if max_sum_loss_to_quit is not None:
             if float(self.state.profit) < 0 and float(self.state.profit) <= float(max_sum_loss_to_quit):
-                self.state.ilog(e=f"QUITTING MAX SUM ABS LOSS REACHED {max_sum_loss_to_quit=} {self.state.profit=} {rel_profit=} relprofits:{str(self.state.rel_profit_cum)}")
+                msg = f"QUITTING {hard_cutoff=} MAX SUM ABS LOSS REACHED {max_sum_loss_to_quit=} {self.state.profit=} {rel_profit=} relprofits:{str(self.state.rel_profit_cum)}"
+                printanyway(msg)
+                self.state.ilog(e=msg)
                 self.state.vars.pending = "max_sum_loss_to_quit"
-                send_to_telegram(f"QUITTING MAX SUM ABS LOSS REACHED {max_sum_loss_to_quit=} {self.state.profit=} {rel_profit=} relprofits:{str(self.state.rel_profit_cum)}")
-                self.signal_stop = True
+                if self.mode not in [Mode.BT, Mode.PREP]:
+                    send_to_telegram(msg)
+                if hard_cutoff:
+                    self.hard_stop = True
+                else:
+                    self.soft_stop = True
                 return True
 
         return False
@@ -149,6 +175,10 @@ class StrategyClassicSL(Strategy):
                         self.state.rel_profit_cum.append(rel_profit)
                         rel_profit_cum_calculated = round(np.sum(self.state.rel_profit_cum),5)
 
+                        #pro martingale updatujeme loss_series_cnt
+                        self.state.vars["transferables"]["martingale"]["cont_loss_series_cnt"] = 0 if rel_profit > 0 else self.state.vars["transferables"]["martingale"]["cont_loss_series_cnt"]+1
+                        self.state.ilog(lvl=1, e=f"update cont_loss_series_cnt na {self.state.vars['transferables']['martingale']['cont_loss_series_cnt']}")
+
                 self.state.ilog(e=f"BUY notif - SHORT PROFIT: {partial_exit=} {partial_last=} {round(float(trade_profit),3)} celkem:{round(float(self.state.profit),3)} rel:{float(rel_profit)} rel_cum:{round(rel_profit_cum_calculated,7)}", msg=str(data.event), rel_profit_cum=str(self.state.rel_profit_cum), bought_amount=bought_amount, avg_costs=avg_costs, trade_qty=data.qty, trade_price=data.price, orderid=str(data.order.id))
 
                 #zapsat profit do prescr.trades
@@ -185,7 +215,8 @@ class StrategyClassicSL(Strategy):
                             setattr(tradeData, "rel_profit_cum", rel_profit_cum_calculated)
 
                 #test na maximalni profit/loss, pokud vypiname pak uz nedelame pripdany reverzal
-                if await self.stop_when_max_profit_loss() is False:
+                #kontrolu na max loss provadime az u FILLu, kdy je znama celkova castka
+                if data.event == TradeEvent.FILL and await self.stop_when_max_profit_loss() is False:
 
                     #pIF REVERSAL REQUIRED - reverse position is added to prescr.Trades with same signal name
                     #jen při celém FILLU
@@ -293,6 +324,10 @@ class StrategyClassicSL(Strategy):
                         self.state.rel_profit_cum.append(rel_profit)
                         rel_profit_cum_calculated = round(np.sum(self.state.rel_profit_cum),5)
 
+                        #pro martingale updatujeme loss_series_cnt
+                        self.state.vars["transferables"]["martingale"]["cont_loss_series_cnt"] = 0 if rel_profit > 0 else self.state.vars["transferables"]["martingale"]["cont_loss_series_cnt"]+1
+                        self.state.ilog(lvl=1, e=f"update cont_loss_series_cnt na {self.state.vars['transferables']['martingale']['cont_loss_series_cnt']}")
+
                 self.state.ilog(e=f"SELL notif - LONG PROFIT {partial_exit=} {partial_last=}:{round(float(trade_profit),3)} celkem:{round(float(self.state.profit),3)} rel:{float(rel_profit)} rel_cum:{round(rel_profit_cum_calculated,7)}", msg=str(data.event), rel_profit_cum = str(self.state.rel_profit_cum), sold_amount=sold_amount, avg_costs=avg_costs, trade_qty=data.qty, trade_price=data.price, orderid=str(data.order.id))
 
                 #zapsat profit do prescr.trades
@@ -328,7 +363,8 @@ class StrategyClassicSL(Strategy):
                             setattr(tradeData, "rel_profit_cum", rel_profit_cum_calculated)
                             #sem nejspis update skutecne vstupni ceny (celk.mnozstvi(order.qty) a avg_costs), to same i druhy smer
 
-                if await self.stop_when_max_profit_loss() is False:
+                #kontrolu na max loss provadime az u FILLu, kdy je znama celkova castka
+                if data.event == TradeEvent.FILL and await self.stop_when_max_profit_loss() is False:
 
                     #IF REVERSAL REQUIRED - reverse position is added to prescr.Trades with same signal name
                     if data.event == TradeEvent.FILL and self.state.vars.requested_followup is not None:
@@ -400,7 +436,7 @@ class StrategyClassicSL(Strategy):
         populate_all_indicators(item, self.state)
         
         #pro přípravu dat next nevoláme
-        if self.mode == Mode.PREP:
+        if self.mode == Mode.PREP or self.soft_stop:
             return
         else:
             self.next(item, self.state)
@@ -417,12 +453,12 @@ class StrategyClassicSL(Strategy):
         #jde o uzavreni short pozice
         if int(self.state.positions) < 0 and (int(self.state.positions) + int(sizer)) > 0:
             self.state.ilog(e="buy nelze nakoupit vic nez shortuji", positions=self.state.positions, size=size)
-            print("buy nelze nakoupit vic nez shortuji") 
+            printanyway("buy nelze nakoupit vic nez shortuji") 
             return -2
 
         if int(self.state.positions) >= self.state.vars.maxpozic:
             self.state.ilog(e="buy Maxim mnozstvi naplneno", positions=self.state.positions)
-            print("max mnostvi naplneno")
+            printanyway("max mnostvi naplneno")
             return 0
 
         self.state.blockbuy = 1
@@ -441,13 +477,13 @@ class StrategyClassicSL(Strategy):
         #jde o uzavreni long pozice
         if int(self.state.positions) > 0 and (int(self.state.positions) - int(size)) < 0:
             self.state.ilog(e="nelze prodat vic nez longuji", positions=self.state.positions, size=size)
-            print("nelze prodat vic nez longuji") 
+            printanyway("nelze prodat vic nez longuji") 
             return -2
 
         #pokud shortuji a mam max pozic
         if int(self.state.positions) < 0 and abs(int(self.state.positions)) >= self.state.vars.maxpozic:
             self.state.ilog(e="short - Maxim mnozstvi naplneno", positions=self.state.positions, size=size)
-            print("max mnostvi naplneno")
+            printanyway("short - Maxim mnozstvi naplneno") 
             return 0
 
         #self.state.blocksell = 1

v2realbot/strategy/base.py

@@ -6,7 +6,7 @@ from v2realbot.utils.utils import AttributeDict, zoneNY, is_open_rush, is_close_
 from v2realbot.utils.tlog import tlog
 from v2realbot.utils.ilog import insert_log, insert_log_multiple_queue
 from v2realbot.enums.enums import RecordType, StartBarAlign, Mode, Order, Account
-from v2realbot.config import BT_DELAYS, get_key, HEARTBEAT_TIMEOUT, QUIET_MODE, LOG_RUNNER_EVENTS, ILOG_SAVE_LEVEL_FROM,PROFILING_NEXT_ENABLED, PROFILING_OUTPUT_DIR, AGG_EXCLUDED_TRADES
+from v2realbot.config import get_key, HEARTBEAT_TIMEOUT, PROFILING_NEXT_ENABLED, PROFILING_OUTPUT_DIR
 import queue
 #from rich import print
 from v2realbot.loader.aggregator import TradeAggregator2Queue, TradeAggregator2List, TradeAggregator
@@ -29,6 +29,7 @@ from rich import print as printnow
 from collections import defaultdict
 import v2realbot.strategyblocks.activetrade.sl.optimsl as optimsl
 from tqdm import tqdm
+import v2realbot.utils.config_handler as cfh
 
 if PROFILING_NEXT_ENABLED:
     from pyinstrument import Profiler
@@ -79,7 +80,8 @@ class Strategy:
         self.pe = pe
         self.se = se
         #signal stop - internal
-        self.signal_stop = False
+        self.hard_stop = False #indikuje hard stop, tedy vypnuti strategie
+        self.soft_stop = False #indikuje soft stop (napr. při dosažení max zisku/ztráty), tedy pokracovani strategie, vytvareni dat, jen bez obchodu
 
     #prdelat queue na dynamic - podle toho jak bud uchtit pracovat s multiresolutions
     #zatim jen jedna q1
@@ -93,7 +95,7 @@ class Strategy:
             align: StartBarAlign = StartBarAlign.ROUND,
             mintick: int = 0,
             exthours: bool = False,
-            excludes: list = AGG_EXCLUDED_TRADES):
+            excludes: list = cfh.config_handler.get_val('AGG_EXCLUDED_TRADES')):
         
         ##TODO vytvorit self.datas_here containing dict - queue - SYMBOL - RecType - 
         ##zatim natvrdo
@@ -327,8 +329,8 @@ class Strategy:
         elif self.rectype == RecordType.TRADE:
             self.state.last_trade_time = item['t']
         if self.mode == Mode.BT or self.mode == Mode.PREP:
-            self.bt.time = self.state.last_trade_time + BT_DELAYS.trigger_to_strat
-            self.state.time = self.state.last_trade_time + BT_DELAYS.trigger_to_strat
+            self.bt.time = self.state.last_trade_time + cfh.config_handler.get_val('BT_DELAYS','trigger_to_strat')
+            self.state.time = self.state.last_trade_time + cfh.config_handler.get_val('BT_DELAYS','trigger_to_strat')
         elif self.mode == Mode.LIVE or self.mode == Mode.PAPER:
             self.state.time = datetime.now().timestamp()
         #ic('time updated')
@@ -424,7 +426,7 @@ class Strategy:
         
         #main strat loop
         print(self.name, "Waiting for DATA",self.q1.qsize())
-        with tqdm(total=self.q1.qsize()) as pbar:
+        with tqdm(total=self.q1.qsize(), desc=self.name + "-Ingesting Aggregated") as pbar:
             while True:
                 try:
                     #block 5s, after that check signals
@@ -432,7 +434,7 @@ class Strategy:
                     #printnow(current_thread().name, "Items waiting in queue:", self.q1.qsize())
                 except queue.Empty:
                     #check internal signals - for profit/loss optim etc - valid for runner
-                    if self.signal_stop:
+                    if self.hard_stop:
                         print(current_thread().name, "Stopping signal - internal")
                         break     
                     
@@ -453,7 +455,7 @@ class Strategy:
                 if item == "last" or self.se.is_set():
                     print(current_thread().name, "stopping")
                     break
-                elif self.signal_stop:
+                elif self.hard_stop:
                     print(current_thread().name, "Stopping signal - internal")
                     break                     
                 elif self.pe.is_set():
@@ -655,7 +657,7 @@ class Strategy:
             if len(self.state.iter_log_list) > 0:
                 rt_out["iter_log"] = self.state.iter_log_list
 
-            #print(rt_out)
+            printnow(rt_out)
 
             print("RTQUEUE INSERT")
             #send current values to Realtime display on frontend
@@ -805,7 +807,7 @@ class StrategyState:
         self.iter_log_list = None
   
     def ilog(self, e: str = None, msg: str = None, lvl: int = 1, **kwargs):
-        if lvl < ILOG_SAVE_LEVEL_FROM:
+        if lvl < cfh.config_handler.get_val('ILOG_SAVE_LEVEL_FROM'):
             return
         
         if self.mode == Mode.LIVE or self.mode == Mode.PAPER:
@@ -829,6 +831,4 @@ class StrategyState:
                 row = dict(time=time, event=e, message=msg, details=kwargs)
         self.iter_log_list.append(row)
         row["name"] = self.name
-        print(row)
-        #zatim obecny parametr -predelat per RUN?
-        #if LOG_RUNNER_EVENTS: insert_log(self.runner_id, time=self.time, logdict=row)
+        print(row)

v2realbot/strategyblocks/indicators/custom/classes/DWT.py

@@ -0,0 +1,26 @@
+from v2realbot.strategyblocks.indicators.custom.classes.indicatorbase import IndicatorBase
+import pywt
+import numpy as np
+
+class DWT(IndicatorBase):
+    def __init__(self, state=None, wavelet='db1', levels=2):
+        super().__init__(state)
+        self.wavelet = wavelet
+        self.levels = levels
+
+    def next(self, close):
+        coeffs = pywt.wavedec(close, self.wavelet, level=self.levels)
+        # Zeroing out all detail coefficients
+        coeffs = [coeffs[0]] + [np.zeros_like(c) for c in coeffs[1:]]
+
+        # Reconstruct the signal using only the approximation coefficients
+        reconstructed_signal = pywt.waverec(coeffs, self.wavelet)
+
+        # Handle length difference
+        length_difference = len(close) - len(reconstructed_signal)
+        if length_difference > 0:
+            reconstructed_signal = np.pad(reconstructed_signal, (0, length_difference), 'constant', constant_values=(0, 0))
+
+        self.state.indicators["MultiLevelDWT"] = reconstructed_signal.tolist()
+
+        return float(reconstructed_signal[-1])

v2realbot/strategyblocks/indicators/custom/classes/SuperTrendTV.py

@@ -10,6 +10,7 @@ class SuperTrendTV(IndicatorBase):
     See conversation: [Indicator Plugin Builder](https://chat.openai.com/g/g-aCKuSmbIe-indicator-plugin-builder/c/1ad650dc-05f1-4cf6-b936-772c0ea86ffa)
     inspirace https://www.tradingview.com/script/r6dAP7yi/
     """
+    
     def __init__(self, atr_period=10, atr_multiplier=3.0, state=None):
         super().__init__(state)
         self.atr_period = atr_period
@@ -19,7 +20,7 @@ class SuperTrendTV(IndicatorBase):
         self.closes = deque(maxlen=atr_period)
         self.up = None
         self.down = None
-        self.trend = 1
+        self.trend = 0
 
     def next(self, high, low, close):
         self.highs.append(high[-1])
@@ -44,7 +45,14 @@ class SuperTrendTV(IndicatorBase):
             self.up = max(up, self.up) if close[-2] > self.up else up
             self.down = min(dn, self.down) if close[-2] < self.down else dn
 
-        previous_trend = self.trend
-        self.trend = 1 if (self.trend == -1 and close[-1] > self.down) else -1 if (self.trend == 1 and close[-1] < self.up) else self.trend
+        # Update trend for the first time if it's still at initial state
+        if self.trend == 0:
+            self.trend = 1 if close[-1] > self.down else -1 if close[-1] < self.up else 0
+        else:
+            # Update trend based on previous values if it's not at initial state
+            self.trend = 1 if (self.trend == -1 and close[-1] > self.down) else -1 if (self.trend == 1 and close[-1] < self.up) else self.trend
+
+        #previous_trend = self.trend
+        #self.trend = 1 if (self.trend == -1 and close[-1] > self.down) else -1 if (self.trend == 1 and close[-1] < self.up) else self.trend
 
         return [self.up, self.down, self.trend]

v2realbot/strategyblocks/inits/init_attached_data.py

@@ -0,0 +1,112 @@
+
+from v2realbot.common.model import RunDay, StrategyInstance, Runner, RunRequest, RunArchive, RunArchiveView, RunArchiveViewPagination, RunArchiveDetail, RunArchiveChange, Bar, TradeEvent, TestList, Intervals, ConfigItem, InstantIndicator, DataTablesRequest
+import v2realbot.controller.services as cs
+from v2realbot.utils.utils import slice_dict_lists,zoneUTC,safe_get, AttributeDict, filter_timeseries_by_timestamp
+#id = "b11c66d9-a9b6-475a-9ac1-28b11e1b4edf"
+#state = AttributeDict(vars={})
+from rich import print
+from traceback import format_exc
+
+def attach_previous_data(state):
+    """""
+    Attaches data from previous runner of the same batch.
+    """""
+    print("ATTACHING PREVIOUS DATA")
+    try:
+        runner : Runner
+        #get batch_id of current runer
+        res, runner = cs.get_runner(state.runner_id)
+        if res < 0:
+            if runner.batch_id is None:
+                print(f"No batch_id found for runner {runner.id}")
+            else:
+                print(f"Couldnt get previous runner {state.runner_id} error: {runner}")
+            return None
+        
+        batch_id = runner.batch_id
+        #batch_id = "6a6b0bcf"
+        res, runner_ids =cs.get_archived_runnerslist_byBatchID(batch_id, "desc")
+        if res < 0:
+            msg = f"error whne fetching runners of batch {batch_id} {runner_ids}"
+            print(msg)
+            return None
+        
+        if runner_ids is None or len(runner_ids) == 0:
+            print(f"NO runners found for batch {batch_id} {runner_ids}")
+            return None
+        
+        last_runner = runner_ids[0]
+        print("Previous runner identified:", last_runner)
+
+        #get archived header - to get transferables
+        runner_header : RunArchive = None
+        res, runner_header = cs.get_archived_runner_header_byID(last_runner)
+        if res < 0:
+            print(f"Error when fetching runner header {last_runner}")
+            return None
+
+        state.vars["transferables"] = runner_header.transferables
+        print("INITIALIZED transferables", state.vars["transferables"])
+
+
+        #get details from the runner
+        print(f"Fetching runner details of {last_runner}")
+        res, val = cs.get_archived_runner_details_byID(last_runner)
+        if res < 0:
+            print(f"no archived runner {last_runner}")
+            return None
+
+        detail = RunArchiveDetail(**val)
+        #print("toto jsme si dotahnuli", detail.bars)
+
+        if len(detail.bars["time"]) == 0:
+            print(f"no bars for runner {last_runner}")
+            return None
+
+        # from stratvars directives 
+        attach_previous_bar_data = safe_get(state.vars, "attach_previous_bar_data", 50)
+        attach_previous_tick_data = safe_get(state.vars, "attach_previous_tick_data", None)
+        
+        #indicators datetime utc
+        indicators = slice_dict_lists(d=detail.indicators[0],last_item=attach_previous_bar_data, time_to_datetime=True)
+
+        #time -datetime utc, updated - timestamp float
+        bars = slice_dict_lists(d=detail.bars, last_item=attach_previous_bar_data, time_to_datetime=True)
+
+        cbar_ids = {}
+        #zarovname tick spolu s bar daty
+        if attach_previous_tick_data is None:
+            oldest_timestamp = bars["updated"][0]
+
+            #returns only values older that oldest_timestamp
+            cbar_inds = filter_timeseries_by_timestamp(detail.indicators[1], oldest_timestamp)
+        else:
+            cbar_inds = slice_dict_lists(d=detail.indicators[1],last_item=attach_previous_tick_data)
+
+        #USE these as INITs - TADY SI TO JESTE ZASTAVIT a POROVNAT
+        #print("state.indicatorsL", state.indicators, "NEW:", indicators)
+        state.indicators = AttributeDict(**indicators)
+        print("transfered indicators:", len(state.indicators["time"]))
+        #print("state.bars", state.bars, "NEW:", bars)
+        state.bars = AttributeDict(bars)
+        print("transfered bars:", len(state.bars["time"]))
+        #print("state.cbar_indicators", state.cbar_indicators, "NEW:", cbar_inds)
+        state.cbar_indicators = AttributeDict(cbar_inds)
+        print("transfered ticks:", len(state.cbar_indicators["time"]))
+
+        print("TRANSFERABLEs INITIALIZED")
+        #bars
+        #transferable_state_vars = ["martingale", "batch_profit"]
+        #1. pri initu se tyto klice v state vars se namapuji do ext_data ext_data["transferrables"]["martingale"] = state.vars["martingale"]
+        #2. pri transferu se vse z ext_data["trasferrables"] dá do stejnénné state.vars["martingale"]
+        #3. na konci dne se uloží do sloupce transferables v RunArchive
+
+        #pridavame dailyBars z extData
+        # if hasattr(detail, "ext_data") and "dailyBars" in detail.ext_data:
+        #     state.dailyBars = detail.ext_data["dailyBars"]
+        return
+    except Exception as e:
+        print(str(e)+format_exc())
+        return None
+# if __name__ == "__main__":
+#     attach_previous_data(state)

v2realbot/strategyblocks/inits/init_indicators.py

@@ -4,9 +4,9 @@ from v2realbot.enums.enums import RecordType, StartBarAlign, Mode, Account, Foll
 from v2realbot.common.PrescribedTradeModel import Trade, TradeDirection, TradeStatus
 from v2realbot.utils.utils import isrising, isfalling,zoneNY, price2dec, print, safe_get, is_still, is_window_open, eval_cond_dict, crossed_down, crossed_up, crossed, is_pivot, json_serial, pct_diff, create_new_bars, slice_dict_lists
 from v2realbot.utils.directive_utils import get_conditions_from_configuration
-import mlroom.utils.mlutils as ml
+#import mlroom.utils.mlutils as ml
 from v2realbot.common.model import SLHistory
-from v2realbot.config import KW, MODEL_DIR
+from v2realbot.config import KW, MODEL_DIR, _ml_module_loaded
 from uuid import uuid4
 from datetime import datetime
 #import random
@@ -17,8 +17,14 @@ from rich import print as printanyway
 from threading import Event
 from traceback import format_exc
 
+def load_ml_model(modelname, modelversion, MODEL_DIR):
+    global ml
+    import mlroom.utils.mlutils as ml
+    return ml.load_model(modelname, modelversion, None, MODEL_DIR)
+
 def initialize_dynamic_indicators(state):
     #pro vsechny indikatory, ktere maji ve svych stratvars TYPE inicializujeme
+    
     ##ßprintanyway(state.vars, state)
     dict_copy = state.vars.indicators.copy()
     for indname, indsettings in dict_copy.items():
@@ -68,7 +74,8 @@ def initialize_dynamic_indicators(state):
                     modelname = safe_get(indsettings["cp"], 'name', None)
                     modelversion = safe_get(indsettings["cp"], 'version', "1")
                     if modelname is not None:
-                        state.vars.loaded_models[modelname] =  ml.load_model(modelname, modelversion, None, MODEL_DIR)
+                        state.vars.loaded_models[modelname] =  load_ml_model(modelname, modelversion, MODEL_DIR)
+                        # state.vars.loaded_models[modelname] =  ml.load_model(modelname, modelversion, None, MODEL_DIR)
                         if state.vars.loaded_models[modelname] is not None:
                             printanyway(f"model {modelname} loaded")
                         else:

v2realbot/strategyblocks/newtrade/prescribedtrades.py

@@ -78,6 +78,7 @@ def execute_prescribed_trades(state: StrategyState, data):
                 size = state.vars.chunk
             res = state.sell(size=size)
             if isinstance(res, int) and res < 0:
+                print(f"error in required operation SHORT {res}")
                 raise Exception(f"error in required operation SHORT {res}")
             #defaultní goalprice nastavujeme az v notifikaci
 

v2realbot/strategyblocks/newtrade/signals.py

@@ -78,7 +78,7 @@ def execute_signal_generator(state, data, name):
                                     last_update=datetime.fromtimestamp(state.time).astimezone(zoneNY),
                                     status=TradeStatus.READY,
                                     generated_by=name,
-                                    size=multiplier*state.vars.chunk,
+                                    size=int(multiplier*state.vars.chunk),
                                     size_multiplier = multiplier,
                                     direction=TradeDirection.LONG,
                                     entry_price=None,
@@ -90,7 +90,7 @@ def execute_signal_generator(state, data, name):
                     last_update=datetime.fromtimestamp(state.time).astimezone(zoneNY),
                     status=TradeStatus.READY,
                     generated_by=name,
-                    size=multiplier*state.vars.chunk,
+                    size=int(multiplier*state.vars.chunk),
                     size_multiplier = multiplier,
                     direction=TradeDirection.SHORT,
                     entry_price=None,

v2realbot/strategyblocks/newtrade/sizing.py

@@ -9,6 +9,7 @@ from traceback import format_exc
 from v2realbot.strategyblocks.newtrade.conditions import go_conditions_met, common_go_preconditions_check
 from v2realbot.strategyblocks.indicators.helpers import get_source_series
 import numpy as np
+from scipy.interpolate import interp1d
 
 def get_size(state: StrategyState, data, signaloptions: dict, direction: TradeDirection):
     return state.vars.chunk * get_multiplier(state, signaloptions, direction)
@@ -133,11 +134,35 @@ def get_multiplier(state: StrategyState, data, signaloptions: dict, direction: T
             state.ilog(lvl=1,e=f"SIZER - Pattern source  and size axis must be set", options=str(options))
             return multiplier
 
-        state.ilog(lvl=1,e=f"SIZER - Input value of {pattern_source} value {input_value}", options=options, time=state.time)
-        multiplier = np.interp(input_value, pattern_source_axis, pattern_size_axis)
+        state.ilog(lvl=1,e=f"SIZER - Input value of {pattern_source} value {input_value}", options=options, time=state.time)   
+
+        #puvodni jednoducha interpolace
+        #multiplier = np.interp(input_value, pattern_source_axis, pattern_size_axis)
+
+        # Updated interpolation function for smoother results
+        # Create the interpolation function
+        f = interp1d(pattern_source_axis, pattern_size_axis, kind='cubic')
+
+        # Interpolate the input value using the interpolation function
+        multiplier = f(input_value)
         state.ilog(lvl=1,e=f"SIZER - Interpolated value  {multiplier}", input_value=input_value, pattern_source_axis=pattern_source_axis, pattern_size_axis=pattern_size_axis, options=options, time=state.time)
     
-    if multiplier > 1 or multiplier <= 0:
+    martingale_enabled = utls.safe_get(options, "martingale_enabled", False)    
+
+    #pocet ztrátových obchodů v řadě mi udává multiplikátor (0 - 1, 1 ztráta 2x, 3 v řadě - 4x atp.)
+    if martingale_enabled:
+
+        #martingale base - základ umocňování - klasicky 2
+        base = float(utls.safe_get(options, "martingale_base", 2))
+        #pocet aktuálních konsekutivních ztrát
+        cont_loss_series_cnt = state.vars["transferables"]["martingale"]["cont_loss_series_cnt"]
+        if cont_loss_series_cnt == 0:
+            multiplier = 1
+        else:
+            multiplier = base ** cont_loss_series_cnt
+        state.ilog(lvl=1,e=f"SIZER - MARTINGALE {multiplier}", options=options, time=state.time, cont_loss_series_cnt=cont_loss_series_cnt)
+        
+    if (martingale_enabled is False and multiplier > 1) or multiplier <= 0:
         state.ilog(lvl=1,e=f"SIZER - Mame nekde problem MULTIPLIER mimo RANGE ERROR {multiplier}", options=options, time=state.time)
         multiplier = 1
     return multiplier

v2realbot/tools/createbatchimage.py

@@ -0,0 +1,585 @@
+import argparse
+#import v2realbot.reporting.metricstoolsimage as mt
+import matplotlib
+import matplotlib.dates as mdates
+matplotlib.use('Agg')  # Set the Matplotlib backend to 'Agg'
+import matplotlib.pyplot as plt
+import seaborn as sns
+import pandas as pd
+from datetime import datetime
+from typing import List
+from enum import Enum
+import numpy as np
+import v2realbot.controller.services as cs
+#from rich import print
+from v2realbot.common.PrescribedTradeModel import TradeDirection, TradeStatus, Trade, TradeStoplossType
+from v2realbot.utils.utils import isrising, isfalling,zoneNY, price2dec, safe_get
+from pathlib import Path
+from v2realbot.config import WEB_API_KEY, DATA_DIR, MEDIA_DIRECTORY
+from v2realbot.enums.enums import RecordType, StartBarAlign, Mode, Account, OrderSide
+from io import BytesIO
+from v2realbot.utils.historicals import get_historical_bars
+from alpaca.data.timeframe import TimeFrame, TimeFrameUnit
+import mlroom.utils.ext_services as es
+from v2realbot.common.db import pool, execute_with_retry
+from v2realbot.utils.utils import ltp, isrising, isfalling,trunc,AttributeDict
+import tqdm
+
+# start_date = datetime(2020, 1, 1, 0, 0, 0, 0, zoneNY)
+# end_date = datetime(2024, 1, 2, 0, 0, 0, 0, zoneNY)
+# bars= get_historical_bars("BLK", start_date, end_date, TimeFrame.Hour)
+# print("bars for given period",bars)
+
+#upload image to the remote server scp 4bea3a54.png david@142.132.188.109:/home/david/media/basic/ 
+
+#zkopirovany a upravena funkce, ktera umi vybrat cilovy server
+def generate_trading_report_image(runner_ids: list = None, batch_id: str = None, stream: bool = False, server: str = None):
+    
+    #TODO dopracovat drawdown a minimalni a maximalni profity nikoliv cumulovane, zamyslet se
+    #TODO list of runner_ids
+    #TODO pridelat na vytvoreni runnera a batche, samostatne REST API + na remove archrunnera
+    
+    if runner_ids is None and batch_id is None:
+        return -2, f"runner_id or batch_id must be present"
+
+    if batch_id is not None:
+        res, runner_ids = es.get_archived_runners_list_by_batch_id(batch_id, server)
+        if res != 0:
+            print(f"no batch {batch_id} found")
+            return -1, f"no batch {batch_id} found"
+        
+    trades = []
+    symbol = None
+    mode = None
+    sada_list = []
+    for id in tqdm.tqdm(runner_ids):
+        #get runner
+        res, sada =es.get_archived_runner_header_by_id(id, server)
+        if res != 0:
+            print(f"no runner {id} found")
+            return -1, f"no runner {id} found"
+        
+        #sada = AttributeDict(**sada)
+
+        print("archrunner")
+        print(sada)
+
+        sada["started"]=datetime.fromisoformat(sada['started'])  if sada['started'] else None
+        sada["stopped"]=datetime.fromisoformat(sada['stopped']) if sada['stopped'] else None
+        sada["bt_from"]=datetime.fromisoformat(sada['bt_from']) if sada['bt_from'] else None
+        sada["bt_to"]=datetime.fromisoformat(sada['bt_to']) if sada['bt_to'] else None
+
+        sada_list.append(sada)
+    
+        symbol = sada["symbol"]
+        mode = sada["mode"]
+        # Parse trades
+
+        trades_dicts =  sada["metrics"]["prescr_trades"]
+
+        for trade_dict in trades_dicts:
+            trade_dict['last_update'] = datetime.fromtimestamp(trade_dict.get('last_update')).astimezone(zoneNY) if trade_dict['last_update'] is not None else None
+            trade_dict['entry_time'] = datetime.fromtimestamp(trade_dict.get('entry_time')).astimezone(zoneNY) if trade_dict['entry_time'] is not None else None
+            trade_dict['exit_time'] = datetime.fromtimestamp(trade_dict.get('exit_time')).astimezone(zoneNY) if trade_dict['exit_time'] is not None else None
+            trades.append(Trade(**trade_dict))
+
+        #print(trades)
+
+    #get from to dates
+    #calculate start a end z min a max dni - jelikoz muze byt i seznam runner_ids a nejenom batch, pripadne testovaci sady
+    if mode in [Mode.BT,Mode.PREP]:
+        start_date = min(runner["bt_from"] for runner in sada_list)
+        end_date = max(runner["bt_to"] for runner in sada_list)
+    else:
+        start_date = min(runner["started"] for runner in sada_list)
+        end_date = max(runner["stopped"] for runner in sada_list) 
+
+    #hour bars for backtested period
+    print(start_date,end_date)
+    bars= get_historical_bars(symbol, start_date, end_date, TimeFrame.Hour)
+    print("bars for given period",bars)
+    """Bars a dictionary with the following keys:
+        * high: A list of high prices
+        * low: A list of low prices
+        * volume: A list of volumes
+        * close: A list of close prices
+        * hlcc4: A list of HLCC4 indicators
+        * open: A list of open prices
+        * time: A list of times in UTC (ISO 8601 format)
+        * trades: A list of number of trades
+        * resolution: A list of resolutions (all set to 'D')
+        * confirmed: A list of booleans (all set to True)
+        * vwap: A list of VWAP indicator
+        * updated: A list of booleans (all set to True)
+        * index: A list of integers (from 0 to the length of the list of daily bars)
+    """
+
+    # Filter to only use trades with status 'CLOSED'
+    closed_trades = [trade for trade in trades if trade.status == TradeStatus.CLOSED]
+
+    if len(closed_trades) == 0:
+        return -1, "image generation no closed trades"
+    
+    # Data extraction for the plots
+    exit_times = [trade.exit_time for trade in closed_trades if trade.exit_time is not None]
+    ##cumulative_profits = [trade.profit_sum for trade in closed_trades if trade.profit_sum is not None]
+
+    profits = [trade.profit for trade in closed_trades if trade.profit is not None]
+    cumulative_profits = np.cumsum(profits)
+    wins = [trade.profit for trade in closed_trades if trade.profit > 0]
+    losses = [trade.profit for trade in closed_trades if trade.profit < 0]
+
+    wins_long = [trade.profit for trade in closed_trades if trade.profit > 0 and trade.direction == TradeDirection.LONG]
+    losses_long = [trade.profit for trade in closed_trades if trade.profit < 0 and trade.direction == TradeDirection.LONG]    
+    wins_short = [trade.profit for trade in closed_trades if trade.profit > 0 and trade.direction == TradeDirection.SHORT]
+    losses_short = [trade.profit for trade in closed_trades if trade.profit < 0 and trade.direction == TradeDirection.SHORT]    
+
+    directions = [trade.direction for trade in closed_trades]
+
+    long_profits = [trade.profit for trade in closed_trades if trade.direction == TradeDirection.LONG and trade.profit is not None]
+    short_profits = [trade.profit for trade in closed_trades if trade.direction == TradeDirection.SHORT and trade.profit is not None]
+
+    # Setting up dark mode for the plots
+    plt.style.use('dark_background')
+
+    # Optionally, you can further customize colors, labels, and axes
+    params = {
+        'axes.titlesize': 9,
+        'axes.labelsize': 8,
+        'xtick.labelsize': 9,
+        'ytick.labelsize': 9,
+        'axes.labelcolor': '#a9a9a9', #a1a3aa',
+        'axes.facecolor': '#121722', #'#0e0e0e', #202020',  # Dark background for plot area
+        'axes.grid': False,  # Turn off the grid globally
+        'grid.color': 'gray',  # If the grid is on, set grid line color
+        'grid.linestyle': '--',  # Grid line style        
+        'grid.linewidth': 1,
+        'xtick.color': '#a9a9a9',
+        'ytick.color': '#a9a9a9',
+        'axes.edgecolor': '#a9a9a9'
+    }
+    plt.rcParams.update(params)
+
+
+    #Custom dark theme similar to the provided image
+    # dark_finance_theme = {
+    #     'background': '#1a1a1a',  # Very dark (almost black) background
+    #     'text': '#eaeaea',       # Light grey text for readability
+    #     'grid': '#333333',       # Dark grey grid lines
+    #     'accent': '#2e91e5',     # Bright blue accent for main elements
+    #     'secondary': '#e15f99',  # Secondary pink/magenta color for highlights
+    #     'highlight': '#fcba03',  # Gold-like color for special highlights
+    # }
+
+    # # Apply the theme settings
+    # plt.style.use('dark_background')
+    # plt.rcParams.update({
+    #     'figure.facecolor': dark_finance_theme['background'],
+    #     'axes.facecolor': dark_finance_theme['background'],
+    #     'axes.edgecolor': dark_finance_theme['text'],
+    #     'axes.labelcolor': dark_finance_theme['text'],
+    #     'axes.titlesize': 12,
+    #     'axes.labelsize': 10,
+    #     'xtick.color': dark_finance_theme['text'],
+    #     'xtick.labelsize': 8,
+    #     'ytick.color': dark_finance_theme['text'],
+    #     'ytick.labelsize': 8,
+    #     'grid.color': dark_finance_theme['grid'],
+    #     'grid.linestyle': '-',
+    #     'grid.linewidth': 0.6,
+    #     'legend.facecolor': dark_finance_theme['background'],
+    #     'legend.edgecolor': dark_finance_theme['background'],
+    #     'legend.fontsize': 10,
+    #     'text.color': dark_finance_theme['text'],
+    #     'lines.color': dark_finance_theme['accent'],
+    #     'patch.edgecolor': dark_finance_theme['accent'],
+    # })
+
+    if len(closed_trades) > 100:
+        fig, axs = plt.subplots(3, 4, figsize=(15, 10))        
+    else:
+        # Create a combined figure for all plots 11,7 ideal na 3,4
+        fig, axs = plt.subplots(3, 4, figsize=(12, 7))
+
+    #TITLE
+    title = ""
+    cnt_ids = len(runner_ids)
+    if batch_id is not None:
+        title = "Batch: "+str(batch_id)+ " "
+
+    title += "Days: " + str(cnt_ids)
+    if cnt_ids == 1:
+        title += " ("+str(runner_ids[0])[0:14]+") "
+       
+        if sada["mode"] == Mode.BT:
+            datum = sada["bt_from"]
+        else:
+            datum = sada["started"]
+
+        title += datum.strftime("%d.%m.%Y %H:%M")
+
+
+    # Add a title to the figure
+    fig.suptitle(title, fontsize=15, color='white')
+
+    # Plot 1: Overall Profit Summary Chart
+    total_wins = int(sum(wins))
+    total_losses = int(sum(losses))
+    net_profit = int(sum(profits))
+    sns.barplot(x=['Total', 'Wins','Losses'],
+                y=[net_profit, total_wins, total_losses],
+                ax=axs[0, 0])
+    axs[0, 0].set_title('Overall Profit Summary')
+    # Define the offset for placing text inside the bars
+    offset = max(total_wins, abs(total_losses), net_profit) * 0.05  # 5% of the highest (or lowest) bar value
+
+    # Function to place text annotation
+    def place_annotation(ax, x, value, offset):
+        va = 'top' if value >= 0 else 'bottom'
+        y = value - offset if value >= 0 else value + offset
+        ax.text(x, y, f'{value}', ha='center', va=va, color='black', fontsize=12)
+
+    # Annotate the Total Wins, Losses, and Net Profit bars
+    place_annotation(axs[0, 0], 0, net_profit, offset)
+    place_annotation(axs[0, 0], 1, total_wins, offset)
+    place_annotation(axs[0, 0], 2, total_losses, offset)
+
+    # Plot 2: LONG - profit summary
+    total_wins_long = int(sum(wins_long))
+    total_losses_long = int(sum(losses_long))
+    total_long = total_wins_long + total_losses_long
+    sns.barplot(x=['Total', 'Wins','Losses'],
+                y=[total_long, total_wins_long, total_losses_long],
+                ax=axs[0, 1])
+    axs[0, 1].set_title('LONG Profit Summary')
+    # Define the offset for placing text inside the bars
+    offset = max(total_wins_long, abs(total_losses_long)) * 0.05  # 5% of the highest (or lowest) bar value
+
+    place_annotation(axs[0, 1], 0, total_long, offset)
+    place_annotation(axs[0, 1], 1, total_wins_long, offset)
+    place_annotation(axs[0, 1], 2, total_losses_long, offset)
+
+
+    # Plot 3: SHORT - profit summary
+    total_wins_short =int(sum(wins_short))
+    total_losses_short = int(sum(losses_short))  
+    total_short = total_wins_short + total_losses_short
+    sns.barplot(x=['Total', 'Wins', 'Losses'],
+                y=[total_short, total_wins_short,
+                   total_losses_short],
+                ax=axs[0, 2])
+    axs[0, 2].set_title('SHORT Profit Summary')
+    # Define the offset for placing text inside the bars
+    offset = max(total_wins_short, abs(total_losses_short)) * 0.05  # 5% of the highest (or lowest) bar value
+
+    place_annotation(axs[0, 2], 0, total_short, offset)
+    place_annotation(axs[0, 2], 1, total_wins_short, offset)
+    place_annotation(axs[0, 2], 2, total_losses_short, offset)
+
+    # Plot 4: Trade Counts Bar Chart
+    long_count = len([trade for trade in closed_trades if trade.direction == TradeDirection.LONG])
+    short_count = len([trade for trade in closed_trades if trade.direction == TradeDirection.SHORT])
+    sns.barplot(x=['Long Trades', 'Short Trades'], y=[long_count, short_count], ax=axs[0, 3])
+    axs[0, 3].set_title('Trade Counts')
+    offset = max(long_count, short_count) * 0.05  # 5% of the highest (or lowest) bar value
+
+    place_annotation(axs[0, 3], 0, long_count, offset)
+    place_annotation(axs[0, 3], 1, short_count, offset)
+
+    #PLOT 5 - Heatman (exit time)
+    # Creating a DataFrame for the heatmap
+    heatmap_data_list = []
+    for trade in trades:
+        if trade.status == TradeStatus.CLOSED:
+            day = trade.exit_time.strftime('%m-%d')  # Format date as 'MM-DD'
+            #day = trade.exit_time.date()
+            hour = trade.exit_time.hour
+            profit = trade.profit
+            heatmap_data_list.append({'Day': day, 'Hour': hour, 'Profit': profit})
+
+    try:
+        heatmap_data = pd.DataFrame(heatmap_data_list)
+        heatmap_data = heatmap_data.groupby(['Day', 'Hour']).sum().reset_index()
+        heatmap_pivot = heatmap_data.pivot(index='Day', columns='Hour', values='Profit')
+
+        # Heatmap of Profits
+        sns.heatmap(heatmap_pivot, cmap='viridis', ax=axs[1, 0])
+        axs[1, 0].set_title('Heatmap of Profits (based on Exit time)')
+        axs[1, 0].set_xlabel('Hour of Day')
+        axs[1, 0].set_ylabel('Day')
+    except KeyError:
+             # Handle the case where there is no data
+            axs[1, 0].text(0.5, 0.5, 'No data available', 
+                            horizontalalignment='center', 
+                            verticalalignment='center', 
+                            transform=axs[1, 0].transAxes)
+            axs[1, 0].set_title('Heatmap of Profits (based on Exit time)')       
+    
+    # Plot 6: Profit/Loss Distribution Histogram
+    sns.histplot(profits, bins=30, ax=axs[1, 1], kde=True, color='skyblue')
+    axs[1, 1].set_title('Profit/Loss Distribution')
+    axs[1, 1].set_xlabel('Profit/Loss')
+    axs[1, 1].set_ylabel('Frequency')
+
+    # Plot 7
+    #    - for 1 den: Position Size Distribution   
+    #    - for more days:  Trade Duration vs. Profit/Loss
+    if len(runner_ids) == 1:
+        
+        sizes = [trade.size for trade in closed_trades if trade.size is not None]
+        if sizes:
+            size_counts = {size: sizes.count(size) for size in set(sizes)}
+            sns.barplot(x=list(size_counts.keys()), y=list(size_counts.values()), ax=axs[1, 2])
+            axs[1, 2].set_title('Position Size Distribution')
+        else:
+             # Handle the case where there is no data
+            axs[1, 2].text(0.5, 0.5, 'No data available', 
+                            horizontalalignment='center', 
+                            verticalalignment='center', 
+                            transform=axs[1, 2].transAxes)
+            axs[1, 2].set_title('Position Size Distribution')   
+    else:
+        trade_durations = []
+        trade_profits = []
+        #trade_volumes = []  # Assuming you have a way to measure the size/volume of each trade
+        trade_types = []  # 'Long' or 'Short'
+
+        for trade in trades:
+            if trade.status == TradeStatus.CLOSED:
+                duration = (trade.exit_time - trade.entry_time).total_seconds() / 60  # Duration in minutes  (3600 for hours)
+                trade_durations.append(duration)
+                trade_profits.append(trade.profit)
+                ##trade_volumes.append(trade.size)  # or any other measure of trade size
+                trade_types.append('Long' if trade.direction == TradeDirection.LONG else 'Short')
+
+        # Trade Duration vs. Profit/Loss
+        scatter_data = pd.DataFrame({
+            'Duration': trade_durations,
+            'Profit': trade_profits,
+            #'Volume': trade_volumes,
+            'Type': trade_types
+        })
+        #sns.scatterplot(data=scatter_data, x='Duration', y='Profit', size='Volume', hue='Type', ax=axs[1, 2])
+        sns.scatterplot(data=scatter_data, x='Duration', y='Profit', hue='Type', ax=axs[1, 2])
+        axs[1, 2].set_title('Trade Duration vs. Profit/Loss')
+        axs[1, 2].set_xlabel('Duration (Minutes)')
+        axs[1, 2].set_ylabel('Profit/Loss')
+
+
+    #Plot 8 Cumulative profit - bud 1 den nebo vice dni + pridame pod to vyvoj ceny
+    # Extract the closing prices and times
+    closing_prices = bars.get('close',[]) if bars is not None else [] 
+    #times = bars['time']  # Assuming this is a list of pandas Timestamp objects
+    times = pd.to_datetime(bars['time']) if bars is not None else []  # Ensure this is a Pandas datetime series
+    # # Plot the closing prices over time
+    # axs[0, 4].plot(times, closing_prices, color='blue')
+    # axs[0, 4].tick_params(axis='x', rotation=45)  # Rotate date labels if necessar
+    # axs[0, 4].xaxis.set_major_formatter(mdates.DateFormatter('%H', tz=zoneNY))
+
+    if len(runner_ids)== 1:
+        if cumulative_profits.size > 0:
+            # Plot 3: Cumulative Profit Over Time with Max Profit Point
+            max_profit_time = exit_times[np.argmax(cumulative_profits)]
+            max_profit = max(cumulative_profits)
+            min_profit_time = exit_times[np.argmin(cumulative_profits)]
+            min_profit = min(cumulative_profits)
+
+            #Plot Cumulative Profit Over Time with Max Profit Point on the primary y-axis
+            # Create a secondary y-axis for the closing prices
+            ax2 = axs[1, 3].twinx()
+            ax2.plot(times, closing_prices, label='Closing Price', color='orange')
+            ax2.set_ylabel('Closing Price', color='orange')
+            ax2.tick_params(axis='y', labelcolor='orange')
+            
+            # Set the limits for the x-axis to cover the full range of 'times'
+            if isinstance(times, pd.DatetimeIndex):
+                axs[1, 3].set_xlim(times.min(), times.max())
+            sns.lineplot(x=exit_times, y=cumulative_profits, ax=axs[1, 3], color='limegreen')
+            axs[1, 3].scatter(max_profit_time, max_profit, color='green', label='Max Profit')
+            axs[1, 3].scatter(min_profit_time, min_profit, color='red', label='Min Profit')
+            axs[1, 3].set_xlabel('Time')
+            axs[1, 3].set_ylabel('Cumulative Profit', color='limegreen')
+            axs[1, 3].tick_params(axis='y', labelcolor='limegreen')
+            axs[1, 3].xaxis.set_major_formatter(mdates.DateFormatter('%H', tz=zoneNY))
+            # Add legends to the plot
+            # lines, labels = axs[1, 3].get_legend_handles_labels()
+            # lines2, labels2 = ax2.get_legend_handles_labels()
+            # axs[1, 3].legend(lines + lines2, labels + labels2, loc='upper left')
+        else:
+            # Handle the case where cumulative_profits is empty
+            axs[1, 3].text(0.5, 0.5, 'No profit data available', 
+                            horizontalalignment='center', 
+                            verticalalignment='center', 
+                            transform=axs[1, 3].transAxes)
+            axs[1, 3].set_title('Cumulative Profit Over Time')
+    else:
+        # Calculate cumulative profit
+        # Additional Plot: Cumulative Profit Over Time
+        # Sort trades by exit time
+
+        # # Set the limits for the x-axis to cover the full range of 'times'
+        # axs[1, 3].set_xlim(times.min(), times.max())
+
+        sorted_trades = sorted([trade for trade in trades if trade.status == TradeStatus.CLOSED], 
+                            key=lambda x: x.exit_time)
+        cumulative_profits_sorted = np.cumsum([trade.profit for trade in sorted_trades])
+        exit_times_sorted = [trade.exit_time for trade in sorted_trades if trade.exit_time is not None]
+
+        # Create a secondary y-axis for the closing prices
+        ax2 = axs[1, 3].twinx()
+        ax2.plot(times, closing_prices, label='Closing Price', color='orange')
+        ax2.set_ylabel('Closing Price', color='orange')
+        ax2.tick_params(axis='y', labelcolor='orange')
+
+        axs[1, 3].set_xlim(times.min(), times.max())
+        # Plot Cumulative Profit Over Time on the primary y-axis
+        axs[1, 3].plot(exit_times_sorted, cumulative_profits_sorted, label='Cumulative Profit', color='blue')
+        axs[1, 3].set_xlabel('Time')
+        axs[1, 3].set_ylabel('Cumulative Profit', color='blue')
+        axs[1, 3].tick_params(axis='y', labelcolor='blue')
+
+        # Format dates on the x-axis
+        axs[1, 3].xaxis.set_major_formatter(mdates.DateFormatter('%d.%m.', tz=zoneNY))
+        axs[1, 3].tick_params(axis='x', rotation=45)  # Rotate date labels if necessary
+
+        # Set the title
+        axs[1, 3].set_title('Cumulative Profit and Closing Price Over Time')
+
+        # Add legends to the plot
+        # axs[1, 3].legend(loc='upper left')
+        # ax2.legend(loc='upper right')
+
+    # Plot 9
+    # - for 1 day: Daily Relative Profit Chart
+    # - for more days: Heatmap of Profits (based on Entry time)
+    if len(runner_ids) == 1:
+        daily_rel_profits = [trade.rel_profit for trade in closed_trades if trade.rel_profit is not None]
+        sns.lineplot(x=range(len(daily_rel_profits)), y=daily_rel_profits, ax=axs[2, 0])
+        axs[2, 0].set_title('Daily Relative Profit')
+    else:
+        # Creating a DataFrame for the heatmap
+        heatmap_data_list = []
+        for trade in trades:
+            if trade.status == TradeStatus.CLOSED:
+                day = trade.entry_time.strftime('%m-%d')  # Format date as 'MM-DD'
+                #day = trade.entry_time.date()
+                hour = trade.entry_time.hour
+                profit = trade.profit
+                heatmap_data_list.append({'Day': day, 'Hour': hour, 'Profit': profit})
+
+        heatmap_data = pd.DataFrame(heatmap_data_list)
+        heatmap_data = heatmap_data.groupby(['Day', 'Hour']).sum().reset_index()
+        heatmap_pivot = heatmap_data.pivot(index='Day', columns='Hour', values='Profit')
+
+        # Heatmap of Profits
+        sns.heatmap(heatmap_pivot, cmap='viridis', ax=axs[2, 0])
+        axs[2, 0].set_title('Heatmap of Profits (based on Entry time)')
+        axs[2, 0].set_xlabel('Hour of Day')
+        axs[2, 0].set_ylabel('Day')
+
+    # Plot 10: Profits Based on Hour of the Day (Entry)
+    entry_hours = [trade.entry_time.hour for trade in closed_trades if trade.entry_time is not None]
+    profits_by_hour = {}
+    for hour, trade in zip(entry_hours, closed_trades):
+        if hour not in profits_by_hour:
+            profits_by_hour[hour] = 0
+        profits_by_hour[hour] += trade.profit
+
+    # Sorting by hour for plotting
+    sorted_hours = sorted(profits_by_hour.keys())
+    sorted_profits = [profits_by_hour[hour] for hour in sorted_hours]
+
+    if sorted_profits:
+        sns.barplot(x=sorted_hours, y=sorted_profits, ax=axs[2, 1])
+        axs[2, 1].set_title('Profits by Hour of Day (Entry)')
+        axs[2, 1].set_xlabel('Hour of Day')
+        axs[2, 1].set_ylabel('Profit')
+    else:
+        # Handle the case where sorted_profits is empty
+        axs[2, 1].text(0.5, 0.5, 'No data available', 
+                        horizontalalignment='center', 
+                        verticalalignment='center', 
+                        transform=axs[2, 1].transAxes)
+        axs[2, 1].set_title('Profits by Hour of Day (Entry)')
+
+    # Plot 11: Profits Based on Hour of the Day - based on Exit
+    exit_hours = [trade.exit_time.hour for trade in closed_trades if trade.exit_time is not None]
+    profits_by_hour = {}
+    for hour, trade in zip(exit_hours, closed_trades):
+        if hour not in profits_by_hour:
+            profits_by_hour[hour] = 0
+        profits_by_hour[hour] += trade.profit
+
+    # Sorting by hour for plotting
+    sorted_hours = sorted(profits_by_hour.keys())
+    sorted_profits = [profits_by_hour[hour] for hour in sorted_hours]
+
+    if sorted_profits:
+        sns.barplot(x=sorted_hours, y=sorted_profits, ax=axs[2, 2])
+        axs[2, 2].set_title('Profits by Hour of Day (Exit)')
+        axs[2, 2].set_xlabel('Hour of Day')
+        axs[2, 2].set_ylabel('Profit')
+    else:
+        # Handle the case where sorted_profits is empty
+        axs[2, 2].text(0.5, 0.5, 'No data available', 
+                        horizontalalignment='center', 
+                        verticalalignment='center', 
+                        transform=axs[2, 2].transAxes)
+        axs[2, 2].set_title('Profits by Hour of Day (Exit)')
+
+    # Plot 12: Calculate profits by day of the week
+    day_of_week_profits = {i: 0 for i in range(7)}  # Dictionary to store profits for each day of the week
+
+    for trade in trades:
+        if trade.status == TradeStatus.CLOSED:
+            day_of_week = trade.exit_time.weekday()  # Monday is 0 and Sunday is 6
+            day_of_week_profits[day_of_week] += trade.profit
+
+    days = ['Mo', 'Tue', 'Wed', 'Thu', 'Fri']
+    # Additional Plot: Strategy Performance by Day of the Week
+    axs[2, 3].bar(days, [day_of_week_profits[i] for i in range(5)])
+    axs[2, 3].set_title('Profit by Day of the Week')
+    axs[2, 3].set_xlabel('Day of the Week')
+    axs[2, 3].set_ylabel('Cumulative Profit')    
+
+    #filename 
+    file = batch_id if batch_id is not None else runner_ids[0]
+    image_file_name = f"{file}.png"
+    image_path = str(MEDIA_DIRECTORY / "basic" / image_file_name)
+
+    # Adjust layout and save the combined plot as an image
+    plt.tight_layout()
+
+    if stream is False:
+        plt.savefig(image_path)
+        plt.close()
+        return 0, None
+    else:
+        # Return the image as a BytesIO stream
+        img_stream = BytesIO()
+        plt.savefig(img_stream, format='png')
+        plt.close()
+        img_stream.seek(0)  # Rewind the stream to the beginning
+        return 0, img_stream        
+
+##Generates BATCH REPORT again for the given batch_id
+##USAGE: python createbatchimage.py <batch_id>
+#Parse the command-line arguments
+#parser = argparse.ArgumentParser(description="Generate trading report image with batch ID")
+# parser.add_argument("server", type=str, help="The server IP for the report")
+# parser.add_argument("batch_id", type=str, help="The batch ID for the report")
+# args = parser.parse_args()
+
+# batch_id = args.batch_id
+# server = args.server
+
+# Generate the report image, using local copy, which will replace the current e0639b45  4bea3a54
+res, val = generate_trading_report_image(batch_id="4bea3a54", server="142.132.188.109")
+
+# Print the result
+if res == 0:
+    print("BATCH REPORT CREATED")
+else:
+    print(f"BATCH REPORT ERROR - {val}")
+
+

v2realbot/tools/loadbatch.py

@@ -0,0 +1,320 @@
+import matplotlib
+import matplotlib.dates as mdates
+#matplotlib.use('Agg')  # Set the Matplotlib backend to 'Agg'
+import matplotlib.pyplot as plt
+import seaborn as sns
+import pandas as pd
+from datetime import datetime
+from typing import List
+from enum import Enum
+import numpy as np
+import v2realbot.controller.services as cs
+from rich import print as richprint
+from v2realbot.common.model import AnalyzerInputs
+from v2realbot.common.PrescribedTradeModel import TradeDirection, TradeStatus, Trade, TradeStoplossType
+from v2realbot.utils.utils import isrising, isfalling,zoneNY, price2dec, safe_get#, print
+from pathlib import Path
+from v2realbot.config import WEB_API_KEY, DATA_DIR, MEDIA_DIRECTORY
+from v2realbot.enums.enums import RecordType, StartBarAlign, Mode, Account, OrderSide
+from io import BytesIO
+from v2realbot.utils.historicals import get_historical_bars
+from alpaca.data.timeframe import TimeFrame, TimeFrameUnit
+from collections import defaultdict
+from scipy.stats import zscore
+from io import BytesIO
+from typing import Tuple, Optional, List
+from v2realbot.common.PrescribedTradeModel import TradeDirection, TradeStatus, Trade, TradeStoplossType
+from collections import Counter
+import vectorbtpro as vbt
+
+    # Function to add 23 seconds to the last datetime (if it exists and is the same day)
+def adjust_datetime_iteratively(df, resolution):
+    adjusted_times = []
+    for i, current_time in enumerate(df.index):
+        if i == 0:
+            # The first entry is unchanged
+            adjusted_times.append(current_time)
+            continue
+        
+        previous_time = adjusted_times[-1]
+        # Check if it's the same day
+        if previous_time.date() == current_time.date():
+            # Add resolution to the previous datetime
+            adjusted_time = previous_time + pd.Timedelta(seconds=resolution)
+        else:
+            # Different day, leave it as is
+            adjusted_time = current_time
+        
+        adjusted_times.append(adjusted_time)
+    
+    # Update DataFrame index
+    df.index = pd.DatetimeIndex(adjusted_times)
+    return df
+
+def convert_to_dataframe(ohlcv):
+    """
+    Convert a dictionary containing OHLCV data into a pandas DataFrame.
+    
+    Parameters:
+        ohlcv (dict): Dictionary containing OHLCV data.
+                      It should have keys 'time', 'open', 'high', 'low', 'close', 'volume', 'updated'.
+                      'time' should be a list of float timestamps.
+                      'updated' should be a list of Python datetimes in UTC time zone.
+    
+    Returns:
+        pd.DataFrame: DataFrame containing the OHLCV data with the index converted to East coast US time.
+    """
+
+    #pokud existuje key index, tak menime na custom_index, aby nedelal neplechu v pd
+    try:
+        if ohlcv.get('index', False):
+            ohlcv['custom_index'] = ohlcv.pop('index')
+    except Exception as e:
+        pass
+
+    #keys that should not go uppercase letter first 
+    keys_not_to_upper = ["time", "updated"]
+
+    # Update keys not in the exclusion list
+    for key in list(ohlcv.keys()):  # Iterate over a copy of the keys
+        if key not in keys_not_to_upper:
+            ohlcv[key.title()] = ohlcv.pop(key) 
+
+    # Create DataFrame from the dictionary
+    df = pd.DataFrame(ohlcv)
+    
+    # Convert 'time' to datetime and set as index
+    df['time'] = pd.to_datetime(df['time'], unit='s', utc=True)
+    df.set_index('time', inplace=True)
+    # Convert index to East coast US time zone
+    df.index = df.index.tz_convert('US/Eastern')
+    if 'updated' in df.columns:
+        df['updated'] = pd.to_datetime(df['updated'], unit='s', utc=True)
+        df['updated'] = df['updated'].dt.tz_convert('US/Eastern')
+    
+    return df
+
+def print(v, *args, **kwargs):
+    if v:
+        richprint(*args, **kwargs)
+
+def load_batch(runner_ids: List = None, batch_id: str = None, space_resolution_evenly = False, main_session_only = True, merge_ind2bars = True, bars_columns = ['Open', 'High', 'Low', 'Close', 'Volume', 'Vwap'], indicators_columns = [], verbose = False) -> Tuple[int, dict]:
+    """Load batches (all runners from single batch) into pandas dataframes
+
+    Args:
+        runner_ids (List, optional): A list of runner identifiers (e.g., stock tickers). Defaults to None.
+        batch_id (str, optional): The ID of a specific batch to retrieve. Defaults to None.
+        merge_ind2bars (bool, optional): merge indicator into bars dataframe. Defaults to True.
+        bars_columns (list, optional):  List of columns to keep in bars df. Defaults to ['Open', 'High', 'Low', 'Close', 'Volume', 'Vwap'].
+        indicators_columns (list, optional): List of columns to keep in indicators df. Defaults to an empty list.
+        space_resoution_evenly: If True then, it alters index so it is spaced evenly in given resolution in ['resooution']
+    Returns:
+        Tuple[int, dict]: A tuple containing:
+            * An integer potentially representing a status code or data count.
+            * A dictionary with keys bars, indicators and cbar_indicators - with pandas dataframe
+    """
+
+    if runner_ids is None and batch_id is None:
+        return -2, f"runner_id or batch_id must be present", 0
+
+    if batch_id is not None:
+        res, runner_ids =cs.get_archived_runnerslist_byBatchID(batch_id)
+
+        if res != 0:
+            print(f"no batch {batch_id} found")
+            return -1, f"no batch {batch_id} found", 0
+
+    #DATA PREPARATION
+    bars = None
+    indicators = None
+    cnt = 0
+    dfs = dict(bars=[], indicators=[],cbar_indicators=[])
+    resolution = None
+    for id in runner_ids:
+        cnt += 1
+        #get runner detail
+        res, sada =cs.get_archived_runner_details_byID(id)
+        if res != 0:
+            print(f"no runner {id} found")
+            return -1, f"no runner {id} found", 0
+        
+        if resolution is None:
+            resolution  = sada["bars"]["resolution"][0]
+            print(verbose, f"Resolution : {resolution}")
+
+        #add daily bars limited to required columns, we keep updated as its mapping column to indicators
+        bars = convert_to_dataframe(sada["bars"])[bars_columns + ["updated"]]
+        #bars = bars.loc[:, bars_columns]
+
+        indicators = convert_to_dataframe(sada["indicators"][0])[indicators_columns]
+
+        #join indicators to bars dataframe
+        if merge_ind2bars:
+            #merge, time v indicators odpovida udpated v bars
+            bars = bars.reset_index()
+            bars = pd.merge(bars, indicators, left_on="updated", right_on="time", how="left")
+            bars = bars.set_index("time")
+        else:
+            dfs["indicators"].append(indicators)
+
+        #drop updated as mapping column
+        #bars = bars.drop("updated", axis=1)
+        dfs["bars"].append(bars)
+
+        #indicators = sada["indicators"][0]
+        #cbar_indicators = sada["indicators"][1]
+    #merge all days into single df
+    for key in dfs:
+        if len(dfs[key])>0:
+            concat_df = pd.concat(dfs[key], axis=0)
+            concat_df = concat_df.between_time('9:30', '16:00') if main_session_only else concat_df
+
+            # Count the number of duplicates (excluding the first occurrence)
+            num_duplicates = concat_df.index.duplicated().sum()
+
+            if num_duplicates > 0:
+                print(verbose, f"NOTE: DUPLICATES {num_duplicates}/{len(concat_df)} in {key}. REMOVING.")
+                concat_df = concat_df[~concat_df.index.duplicated()]
+
+                num_duplicates = concat_df.index.duplicated().sum()
+                print(verbose, f"Now there are {num_duplicates}/{len(concat_df)}")
+
+            if space_resolution_evenly and key != "cbar_indicators":
+                # Apply rounding to the datetime index according to resolution (in seconds)
+                concat_df = adjust_datetime_iteratively(concat_df, resolution)
+
+            dfs[key] = concat_df
+    return 0, dfs
+
+if __name__ == "__main__":
+    res, df = load_batch(batch_id="e44a5075", space_resolution_evenly=True, indicators_columns=["Rsi14"], main_session_only=False)
+    if res < 0:
+        print("Error" + str(res) + str(df))
+    print(df)
+    df = df["bars"]
+    print(df.info(), df.head())
+    #filter columns
+    #columns_to_keep = ['Open', 'High', 'Low', 'Close', 'Volume', 'Vwap']
+    #df = df.loc[:, columns_to_keep]
+    #df = df.rename(columns={'index': 'custom_index'})
+    print(df.info(), df.head(), df.describe())
+    #filter times
+    #df = df.between_time('9:30', '16:00')
+    print(df.info())
+    # Set the frequency to 23 seconds
+    #df.index.freq = pd.tseries.offsets.Second(23)
+    # Check the frequency of the index
+
+    # Resample and aggregate the data
+    # resampled_df = df.resample('23S').agg({
+    #         'open': 'first',
+    #         'high': 'max',
+    #         'low': 'min',
+    #         'close': 'last',
+    #         'volume': 'sum'
+    #     })
+
+    #df.index.freq = pd.infer_freq(df.index)
+    #print(df.index.freq)
+
+
+    # Set the frequency of the index explicitly - if it exists like 1T etc, if doesnt exists then custom_frequency will be used
+    #df.index.freq = pd.date_range(start=df.index[0], periods=len(df), freq='23S')
+
+    print(df.info())
+
+    vbt.settings.set_theme("dark")
+    vbt.settings['plotting']['layout']['width'] = 1280
+    vbt.settings.plotting.auto_rangebreaks = True
+
+    #naloadujeme do vbt symbol as column
+    bar_data = vbt.Data.from_data({"BAC": df}, tz_convert="US/Eastern")
+    print(bar_data)
+    print(bar_data.close)
+    
+    print(bar_data.data["BAC"]["Rsi14"])
+    bar_data.data["BAC"]["Rsi14"].vbt.plot().show()
+    print(bar_data["Rsi14"])
+    
+    
+    #ohlcv plot (sublot 2x1)
+    bar_data.data["BAC"].vbt.ohlcv.plot().show()
+
+    #create two subplots 3x1 (ohlcv + RSI)
+    # fig = vbt.make_subplots(rows=3, cols=1)
+    # bar_data.data["BAC"].vbt.ohlcv.plot(add_trace_kwargs=dict(row=1, col=1),fig=fig)
+    # bar_data.data["BAC"]["Rsi14"].vbt.plot(add_trace_kwargs=dict(row=3, col=1),fig=fig)
+    # fig.show()
+
+    #create subplots with alternate Y axis - RSI overlay
+    fig1 = vbt.make_subplots(specs=[[{"secondary_y": True}]])
+    bar_data.data["BAC"]["Close"].vbt.plot(add_trace_kwargs=dict(secondary_y=False),fig=fig1)
+    bar_data.data["BAC"].vbt.plot(add_trace_kwargs=dict(secondary_y=True),fig=fig1)
+    fig1.show()
+
+    puv_df = bar_data.data["BAC"]
+
+    bar_data23s = bar_data[["Open", "High", "Low", "Close", "Volume"]]
+    print(bar_data23s)
+    #resample by vbt
+    bar_data46s = bar_data23s.get().resample("46s").agg({
+        "Open": "first",
+        "High": "max",
+        "Low": "min",
+        "Close": "last",
+        "Volume": "sum"
+    })
+
+    print(bar_data46s)
+    res_data = bar_data46s.data["BAC"]
+    #bar_data23s.data["BAC"].ptable()
+    #bar_data23s = bar_data.resample("23S")
+    print(bar_data46s)
+    print(bar_data46s.close)
+    vbt.settings.plotting.auto_rangebreaks = True
+    bar_data46s.data["BAC"].vbt.ohlcv.plot().show()
+
+    #TARGET DAYS - only one day or range
+    # Target Date
+    #target_date = pd.to_datetime('2023-10-12', tz='US/Eastern')
+
+    # Date Range
+    start_date = pd.to_datetime('2024-03-12')
+    #end_date = pd.to_datetime('2023-10-14')
+
+    new_data = bar_data.transform(lambda df: df[df.index.date == start_date.date()])
+    #range filtered_data = data[(data.index >= start_date) & (data.index <= end_date)
+
+    print(new_data)
+    new_data.data["BAC"].vbt.ohlcv.plot().show()
+
+
+    # Filtering RANGE or DAY
+    # filtered_data = data[(data.index >= start_date) & (data.index <= end_date)]g
+    # filtered_data = data[data.index.date == target_date.date()]
+
+
+
+    #custom aggregagation
+    # ohlcv_agg = pd.DataFrame({
+    #     'Open': df.resample('1T')['Open'].first(),
+    #     'High': df.resample('1T')['High'].max(),
+    #     'Low': df.resample('1T')['Low'].min(),
+    #     'Close': df.resample('1T')['Close'].last(),
+    #     'Volume': df.resample('1T')['Volume'].sum()
+    # })
+
+    #Define a custom frequency with a timedelta of 23 seconds
+    # custom_frequency = pd.tseries.offsets.DateOffset(seconds=23)
+
+    # # Create a new DataFrame with the desired frequency
+    # new_index = pd.date_range(start=df.index[0], end=df.index[-1], freq=custom_frequency)
+    # new_df = pd.DataFrame(index=new_index)
+
+    # # Reindex the DataFrame
+    # df = df.reindex(new_df.index)
+
+    # # Now you can check the frequency of the index
+    # print(df.index.freq)
+
+

v2realbot/tools/sizingpattervisual.py

@@ -1,6 +1,6 @@
 import numpy as np
+from scipy.interpolate import interp1d
 import matplotlib.pyplot as plt
-
 # Sem zadat pattern X a Y pro VIZUALIZACI
 
 #minutes
@@ -14,16 +14,34 @@ pattern_y = [0.1, 0.5, 0.8, 1, 0.6, 0.1]
 #celkový profit
 
 # Generating a range of input values for interpolation
-input_values = np.linspace(min(pattern_x), max(pattern_x), 500)
-multipliers = np.interp(input_values, pattern_x, pattern_y)
+input_values = np.linspace(min(pattern_x), max(pattern_x), 1000)  # Increase the number of points
 
-# Plotting
+# Bezier interpolation
+interp_func = interp1d(pattern_x, pattern_y, kind='cubic')
+multipliers_cubic = interp_func(input_values)
+
+multipliers_linear = np.interp(input_values, pattern_x, pattern_y)
+
+
+# Plotting multipliers_linear and multipliers_cubic on the same canvas
 plt.figure(figsize=(10, 6))
 plt.plot(pattern_x, pattern_y, 'o', label='Original Points')
-plt.plot(input_values, multipliers, label='Interpolated Values')
+plt.plot(input_values, multipliers_linear, label='Linear Interpolation')
+plt.plot(input_values, multipliers_cubic, label='Cubic Interpolation')
 plt.xlabel('X values')
 plt.ylabel('Interpolated Multipliers')
-plt.title('Interpolation Chart')
+plt.title('Interpolation Comparison')
 plt.legend()
 plt.grid(True)
 plt.show()
+
+# # Plotting multipliers_cubic
+# plt.figure(figsize=(10, 6))
+# plt.plot(pattern_x, pattern_y, 'o', label='Original Points')
+# plt.plot(input_values, multipliers_cubic, label='Cubic Interpolation')
+# plt.xlabel('X values')
+# plt.ylabel('Interpolated Multipliers')
+# plt.title('Cubic Interpolation Chart')
+# plt.legend()
+# plt.grid(True)
+# plt.show()

v2realbot/utils/config_defaults.py

@@ -0,0 +1,64 @@
+from alpaca.data.enums import DataFeed
+from v2realbot.enums.enums import FillCondition
+
+#Separate file that contains default values for all config variables
+#they are loaded by the config_handler and then can be overriden on the fly 
+#by configuration profiles
+
+#note if the type is not simple (enum etc.) dont forget to add it to config_handler get_val function to transform
+
+#PREMIUM pro MARKET order, if positive it means absolute value (0.005), if negative it means pct (0.0167)  #0.005 is approximately 0.0167% of base price 30.
+BT_FILL_PRICE_MARKET_ORDER_PREMIUM=0.005
+#no dense print in the console
+QUIET_MODE=True
+BT_FILL_CONS_TRADES_REQUIRED=2
+BT_FILL_LOG_SURROUNDING_TRADES= 10
+LIVE_DATA_FEED=DataFeed.IEX
+OFFLINE_MODE = False
+#minimalni vzdalenost mezi trady, kterou agregator pousti pro CBAR(0.001 - blokuje mensi nez 1ms)
+GROUP_TRADES_WITH_TIMESTAMP_LESS_THAN = 0.003
+#normalized price for tick 0.01
+NORMALIZED_TICK_BASE_PRICE = 30.00
+
+#DEFAULT AGGREGATOR filter trades
+#NOTE pridana F - Inter Market Sweep Order - obcas vytvarela spajky
+AGG_EXCLUDED_TRADES = ['C','O','4','B','7','V','P','W','U','Z','F']
+#how many consecutive trades with the fill price are necessary for LIMIT fill to happen in backtesting
+#0 - optimistic, every knot high will fill the order
+#N - N consecutive trades required
+#not impl.yet
+#minimum is 1, na alpace live to vetsinou vychazi 7-8 u BAC, je to hodne podobne tomu, nez je cena překonaná pul centu. tzn. 7-8 a nebo FillCondition.SLOW
+BT_FILL_CONS_TRADES_REQUIRED = 2
+#during bt trade execution logs X-surrounding trades of the one that triggers the fill
+BT_FILL_LOG_SURROUNDING_TRADES = 10
+#fill condition for limit order in bt
+# fast - price has to be equal or bigger <=
+# slow - price has to be bigger <
+BT_FILL_CONDITION_BUY_LIMIT = FillCondition.SLOW
+BT_FILL_CONDITION_SELL_LIMIT = FillCondition.SLOW
+#backend counter of api requests
+COUNT_API_REQUESTS = False
+# ilog lvls = 0,1 - 0 debug, 1 info
+ILOG_SAVE_LEVEL_FROM  = 1
+#currently only prod server has acces to LIVE
+PROD_SERVER_HOSTNAMES = ['tradingeastcoast','David-MacBook-Pro.local'] #,'David-MacBook-Pro.local'
+TEST_SERVER_HOSTNAMES = ['tradingtest'] 
+
+""""
+LATENCY DELAYS for LIVE eastcoast
+.000 trigger - last_trade_time (.4246266)
++.020 vstup do strategie a BUY (.444606)
++.023 submitted (.469198)
++.008    filled (.476695552)
++.023   fill not(.499888)
+"""
+BT_DELAYS = {
+    "trigger_to_strat": 0.020,
+    "strat_to_sub": 0.023,
+    "sub_to_fill": 0.008,
+    "fill_to_not": 0.023,
+    #doplnit dle live
+    "limit_order_offset": 0,
+}
+
+#cfh.config_handler.get_val('BT_DELAYS','trigger_to_strat')

v2realbot/utils/config_handler.py

@@ -0,0 +1,121 @@
+import v2realbot.controller.configs as cfgservices
+import orjson
+from traceback import format_exc
+from alpaca.data.enums import DataFeed
+import v2realbot.utils.config_defaults as config_defaults
+from v2realbot.enums.enums import FillCondition
+from rich import print
+# from v2realbot.utils.utils import print
+
+def aggregate_configurations(module):
+    return {key: getattr(module, key) for key in dir(module) if key.isupper()}
+
+#config handler - signleton pattern
+#details https://chat.openai.com/share/e056af70-76da-4dbe-93a1-ecf99f0b0f29
+#it is initialized on app start, loading default and updating based on active_profile settings
+#also there is handler for updating active_profile which changes it immediately (in controller.config.update_config_item)
+class ConfigHandler:
+    _instance = None
+
+    #this ensure that it is created only once
+    def __new__(cls):
+        if cls._instance is None:
+            cls._instance = super(ConfigHandler, cls).__new__(cls)
+            # Initialize your default config here in __new__, since it's only done once
+            # Default configuration
+            # Dynamically create the configuration dictionary
+            cls.default_config = aggregate_configurations(config_defaults)
+            cls._instance.active_config = cls._instance.default_config.copy()
+            cls._instance.active_profile = "default"
+            #if there is profile to be activated, it is loaded overriding default
+            cls._instance.activate_profile()
+        return cls._instance
+
+    def load_profile(self, profile_name):
+        """
+        Load configuration profiles, JSON with all profiles is stored in config item 'profiles'
+        """
+        try:
+            config_directive = "profiles"
+            ret, res = cfgservices.get_config_item_by_name(config_directive)
+            if ret < 0:
+                print(f"CONFIG OVERRIDE {config_directive} Error {res}")
+                return
+            else:
+                fetched_dict = orjson.loads(res["json_data"])
+                override_configuration = fetched_dict.get(profile_name, None)
+                if override_configuration is not None:
+                    #first reset to default then override profile on top of them
+                    self.active_config = self.default_config.copy() 
+                    self.active_config.update(override_configuration)
+                    self.active_profile = profile_name
+                    #print(f"Profile {profile_name} loaded successfully.")
+                    #print("Current values:", self.active_config)
+                else:
+                    print(f"Profile {profile_name} does not exist in config item: {config_directive}")
+        except Exception as e:
+            print(f"Error while fetching {profile_name} error:" + str(e) + format_exc())
+
+    def activate_profile(self):
+        """
+        Activates the profiles which is stored in configuration as currently active.
+        """
+        try:
+            config_directive = "active_profile"
+            ret, res = cfgservices.get_config_item_by_name(config_directive)
+            if ret < 0:
+                print(f"ERROR fetching item {config_directive} Error {res}")
+                return
+            else:
+                fetched_dict = orjson.loads(res["json_data"])
+                active_profile = fetched_dict.get("ACTIVE_PROFILE", None)
+                if active_profile is not None:
+                    print("Activating profile", active_profile)
+                    self.load_profile(active_profile)
+                else:
+                    print("No ACTIVE_PROFILE element in config item: " + config_directive)
+
+        except Exception as e:
+            print(f"Error while activating profile:" + str(e) + format_exc())    
+
+    def get_val(self, key, subkey=None):
+        """
+        Retrieve a configuration value by key and optionally transforms to appropriate type
+        
+        Also supports nested dictionaries - with subkeys
+        """
+        value = self.active_config.get(key, None)
+        if subkey and isinstance(value, dict):
+            return value.get(subkey, None)        
+        match key:
+            case "LIVE_DATA_FEED":
+                return DataFeed(value)  # Convert to DataFeed enum
+            case "BT_FILL_CONDITION_BUY_LIMIT":
+                return FillCondition(value)
+            case "BT_FILL_CONDITION_SELL_LIMIT":
+                return FillCondition(value)
+            case "AGG_EXCLUDED_TRADES":
+                return sorted(value)  # Convert to sorted
+            # Add cases for other enumeration conversions or transformations as needed
+            case _:
+                return value
+
+    def print_current_config(self):
+        print(f"Active profile {self.active_profile} conf_values: {str(self.active_config)}")
+
+# Global configuratio - it is imported by modules that need it. In the future can be changed to Dependency Ingestion (each service will have the config instance  as input parameter)
+config_handler = ConfigHandler()
+#print(f"{config_handler.active_profile=}")
+#print("config handler initialized")
+
+#this is how to get value
+#config_handler.get_val('BT_FILL_PRICE_MARKET_ORDER_PREMIUM')
+
+# config_handler.load_profile('profile1')  # Assuming 'profile1.json' exists
+# print(f"{config_handler.active_profile=}")
+
+# config_handler.load_profile('profile2')  # Assuming 'profile1.json' exists
+# print(f"{config_handler.active_profile=}")
+
+# config_handler.activate_profile()  # Switch to profile according to active_profile directive
+

v2realbot/utils/historicals.py

@@ -3,8 +3,8 @@ from alpaca.data.requests import StockLatestQuoteRequest, StockBarsRequest, Stoc
 from alpaca.data import Quote, Trade, Snapshot, Bar
 from alpaca.data.models import BarSet, QuoteSet, TradeSet
 from alpaca.data.timeframe import TimeFrame, TimeFrameUnit
-from v2realbot.utils.utils import zoneNY
-from v2realbot.config import ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY
+from v2realbot.utils.utils import zoneNY, send_to_telegram
+from v2realbot.config import ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, ACCOUNT1_PAPER_FEED
 from alpaca.data.enums import DataFeed
 from datetime import datetime, timedelta
 import pandas as pd
@@ -12,6 +12,8 @@ from rich import print
 from collections import defaultdict
 from pandas import to_datetime
 from msgpack.ext import Timestamp
+import time
+from traceback import format_exc
 
 def convert_historical_bars(daily_bars):
   """Converts a list of daily bars into a dictionary with the specified keys.
@@ -49,6 +51,9 @@ def convert_historical_bars(daily_bars):
   for i in range(len(daily_bars)):
     bar = daily_bars[i]
 
+    if bar is None:
+       continue
+
     # Calculate the HLCC4 indicator
     hlcc4 = (bar['h'] + bar['l'] + bar['c'] + bar['o']) / 4
     datum = to_datetime(bar['t'], utc=True)
@@ -80,15 +85,48 @@ def get_todays_open():
     pass
 
 ##vrati historicke bary v nasem formatu
-def get_historical_bars(symbol: str, time_from: datetime, time_to: datetime, timeframe: TimeFrame):
-    stock_client = StockHistoricalDataClient(ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, raw_data=True)
-    # snapshotRequest = StockSnapshotRequest(symbol_or_symbols=[symbol], feed=DataFeed.SIP)
-    # snapshotResponse = stock_client.get_stock_snapshot(snapshotRequest)
-    # print("snapshot", snapshotResponse)
+# def get_historical_bars(symbol: str, time_from: datetime, time_to: datetime, timeframe: TimeFrame):
+#     stock_client = StockHistoricalDataClient(ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, raw_data=True)
+#     # snapshotRequest = StockSnapshotRequest(symbol_or_symbols=[symbol], feed=DataFeed.SIP)
+#     # snapshotResponse = stock_client.get_stock_snapshot(snapshotRequest)
+#     # print("snapshot", snapshotResponse)
 
-    bar_request = StockBarsRequest(symbol_or_symbols=symbol,timeframe=timeframe, start=time_from, end=time_to, feed=DataFeed.SIP)
-    bars: BarSet = stock_client.get_stock_bars(bar_request)
-    #print("puvodni bars", bars["BAC"])
-    if bars[symbol][0] is None:
-       return None
-    return convert_historical_bars(bars[symbol])
+#     bar_request = StockBarsRequest(symbol_or_symbols=symbol,timeframe=timeframe, start=time_from, end=time_to, feed=DataFeed.SIP)
+#     bars: BarSet = stock_client.get_stock_bars(bar_request)
+#     #print("puvodni bars", bars["BAC"])
+#     if bars[symbol][0] is None:
+#        return None
+#     return convert_historical_bars(bars[symbol])
+
+def get_historical_bars(symbol: str, time_from: datetime, time_to: datetime, timeframe: TimeFrame, max_retries=5, backoff_factor=1):
+    """
+    Fetches historical bar data with retries on failure.
+
+    :param symbol: Stock symbol.
+    :param time_from: Start time for the data.
+    :param time_to: End time for the data.
+    :param timeframe: Timeframe for the data.
+    :param max_retries: Maximum number of retries.
+    :param backoff_factor: Factor to determine the next sleep time.
+    :return: Converted historical bar data.
+    :raises: Exception if all retries fail.
+    """
+    stock_client = StockHistoricalDataClient(ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, raw_data=True)
+    bar_request = StockBarsRequest(symbol_or_symbols=symbol, timeframe=timeframe, start=time_from, end=time_to, feed=ACCOUNT1_PAPER_FEED)
+    
+    last_exception = None
+
+    for attempt in range(max_retries):
+        try:
+            bars = stock_client.get_stock_bars(bar_request)
+            if bars[symbol][0] is None:
+                return None
+            return convert_historical_bars(bars[symbol])
+        except Exception as e:
+            print(f"Load historical bars Attempt {attempt + 1} failed: {str(e)} and {format_exc()}")
+            last_exception = e
+            time.sleep(backoff_factor * (2 ** attempt))
+
+    print("All attempts to fetch historical bar data failed.")
+    send_to_telegram(f"Failed to fetch historical bar data after {max_retries} retries. Last exception: {str(last_exception)} and {format_exc()}")
+    raise Exception(f"Failed to fetch historical bar data after {max_retries} retries. Last exception: {str(last_exception)} and {format_exc()}")

v2realbot/utils/ilog.py

@@ -6,7 +6,7 @@ import json
 from datetime import datetime
 from v2realbot.enums.enums import RecordType, StartBarAlign, Mode, Account
 from v2realbot.common.db import pool, insert_queue
-import sqlite3
+
 
 
 #standardne vraci pole tuplů, kde clen tuplu jsou sloupce

v2realbot/utils/sysutils.py

@@ -1,11 +1,11 @@
 import socket
 from v2realbot.enums.enums import Env
-from v2realbot.config import PROD_SERVER_HOSTNAMES, TEST_SERVER_HOSTNAMES
+import v2realbot.utils.config_handler as cfh
 
 def get_environment():
     """Determine if the current server is production or test based on hostname."""
     hostname = socket.gethostname()
-    if hostname in PROD_SERVER_HOSTNAMES:
+    if hostname in cfh.config_handler.get_val('PROD_SERVER_HOSTNAMES'):
         return Env.PROD
     else:
         return Env.TEST

v2realbot/utils/utils.py

@@ -13,19 +13,119 @@ from v2realbot.common.model import StrategyInstance, Runner, RunArchive, RunArch
 from v2realbot.common.PrescribedTradeModel import Trade, TradeDirection, TradeStatus, TradeStoplossType
 from typing import List
 import tomli
-from v2realbot.config import DATA_DIR, QUIET_MODE,NORMALIZED_TICK_BASE_PRICE
+from v2realbot.config import DATA_DIR, ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY
 import requests
 from uuid import UUID
 #from decimal import Decimal
 from enum import Enum
 #from v2realbot.enums.enums import Order
 from v2realbot.common.model import Order as btOrder, TradeUpdate as btTradeUpdate
-from alpaca.trading.models import Order, TradeUpdate
+from alpaca.trading.models import Order, TradeUpdate, Calendar
 import numpy as np
 import pandas as pd
 from collections import deque
 import socket
 import numpy as np
+from alpaca.trading.requests import GetCalendarRequest
+from alpaca.trading.client import TradingClient
+import time as timepkg
+from traceback import format_exc
+import re
+import tempfile
+import shutil
+from filelock import FileLock
+import v2realbot.utils.config_handler as cfh
+import pandas_market_calendars as mcal
+
+def validate_and_format_time(time_string):
+    """
+    Validates if the given time string is in the format HH:MM or H:MM. 
+    If valid, returns the standardized time string in HH:MM format.
+
+    Args:
+        time_string (str): The time string to validate.
+
+    Returns:
+        str or None: Standardized time string in HH:MM format if valid, 
+                     None otherwise.
+    """
+    # Regular expression for matching the time format H:MM or HH:MM
+    time_pattern = re.compile(r'^([0-1]?[0-9]|2[0-3]):([0-5][0-9])$')
+
+    # Checking if the time string matches the pattern
+    if time_pattern.match(time_string):
+        # Standardize the time format to HH:MM
+        standardized_time = datetime.strptime(time_string, '%H:%M').strftime('%H:%M')
+        return standardized_time
+    else:
+        return None
+
+def fetch_calendar_data(start: datetime, end: datetime) -> List[Calendar]:
+    """
+    Fetches the trading schedule for the NYSE (New York Stock Exchange) between the specified start and end dates.
+    Args:
+        start (datetime): The start date for the trading schedule.
+        end (datetime): The end date for the trading schedule.
+    Returns:
+        List[Calendar]: A list of Calendar objects containing the trading dates and market open/close times. 
+                        Returns an empty list if no trading days are found within the specified range.
+    """ 
+    nyse = mcal.get_calendar('NYSE')
+    schedule = nyse.schedule(start_date=start, end_date=end, tz='America/New_York')
+    if not schedule.empty: 
+        schedule = (schedule.reset_index()
+                        .rename(columns={"index": "date", "market_open": "open", "market_close": "close"})
+                        .assign(date=lambda day: day['date'].dt.date.astype(str),
+                                open=lambda day: day['open'].dt.strftime('%H:%M'), 
+                                close=lambda day: day['close'].dt.strftime('%H:%M'))
+                        .to_dict(orient="records"))
+        cal_dates = [Calendar(**record) for record in schedule]
+        return cal_dates
+    else:
+        return []
+
+#Alpaca Calendar wrapper with retry
+def fetch_calendar_data_from_alpaca(start, end, max_retries=5, backoff_factor=1):
+    """
+    Attempts to fetch calendar data with exponential backoff. Raises an exception if all retries fail.
+
+    TODO sem pridat local caching mechanism
+
+    :param client: Alpaca API client instance.
+    :param start: The start date for the calendar data.
+    :param end: The end date for the calendar data.
+    :param max_retries: Maximum number of retries.
+    :param backoff_factor: Factor to determine the next sleep time.
+    :return: Calendar data.
+    :raises: ConnectionError if all retries fail.
+    """
+    # Ensure start and end are of type datetime.date
+    if isinstance(start, datetime):
+        start = start.date()
+    if isinstance(end, datetime):
+        end = end.date()
+
+    # Verify that start and end are datetime.date objects after conversion
+    if not all([isinstance(start, date), isinstance(end, date)]):
+        raise ValueError("start and end must be datetime.date objects")
+    
+    clientTrading = TradingClient(ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, raw_data=False)
+    calendar_request = GetCalendarRequest(start=start, end=end)
+    last_exception = None
+
+    for attempt in range(max_retries):
+        try:
+            cal_dates = clientTrading.get_calendar(calendar_request)
+            richprint("Calendar data fetch successful", start, end)
+            return cal_dates
+        except Exception as e:
+            richprint(f"Attempt {attempt + 1} failed: {e}")
+            last_exception = e
+            timepkg.sleep(backoff_factor * (2 ** attempt))
+
+    richprint("****All attempts to fetch calendar data failed.****")
+    send_to_telegram(f"FETCH_CALENDER_DATA_FAILED. {str(last_exception)} and {format_exc()} BACKEST STOPPED" )
+    raise ConnectionError(f"Failed to fetch calendar data after {max_retries} retries. Last exception: {str(last_exception)} and {format_exc()}")
 
 def concatenate_weekdays(weekday_filter):
     # Mapping of weekdays where 0 is Monday and 6 is Sunday
@@ -37,21 +137,45 @@ def concatenate_weekdays(weekday_filter):
     # Concatenate the weekday strings
     return ','.join(weekday_strings)
 
-def slice_dict_lists(d, last_item, to_tmstp = False):
+def filter_timeseries_by_timestamp(timeseries, timestamp):
+    """
+    Filter a timeseries dictionary, returning a new dictionary with entries
+    where the time value is greater than the provided timestamp.
+
+    Parameters:
+    - timeseries (dict): The original timeseries dictionary.
+    - timestamp (float): The timestamp to filter the timeseries by.
+
+    Returns:
+    - dict: A new timeseries dictionary filtered based on the provided timestamp.
+    """
+    # Find indices where time values are greater than the provided timestamp
+    indices = [i for i, time in enumerate(timeseries['time']) if time > timestamp]
+
+    # Create a new dictionary with values filtered by the indices
+    filtered_timeseries = {key: [value[i] for i in indices] for key, value in timeseries.items()}
+
+    return filtered_timeseries
+
+def slice_dict_lists(d, last_item, to_tmstp = False, time_to_datetime = False):
   """Slices every list in the dictionary to the last last_item items.
   
   Args:
     d: A dictionary.
     last_item: The number of items to keep at the end of each list.
-    to_tmstp: For "time" elements change it to timestamp from datetime if required.
-
+    to_tmstp: For "time" elements change it from datetime to timestamp from datetime if required.
+    time_to_datetime: For "time" elements change it from timestamp to datetime UTC if required.
   Returns:
     A new dictionary with the sliced lists.
+
+    datetime.fromtimestamp(data['updated']).astimezone(zoneUTC)
   """
   sliced_d = {}
   for key in d.keys():
     if key == "time" and to_tmstp:
         sliced_d[key] = [datetime.timestamp(t) for t in d[key][-last_item:]]
+    elif key == "time" and time_to_datetime:
+        sliced_d[key] = [datetime.fromtimestamp(t).astimezone(zoneUTC) for t in d[key][-last_item:]]
     else:
         sliced_d[key] = d[key][-last_item:]
   return sliced_d
@@ -392,11 +516,11 @@ def get_tick(price: float, normalized_ticks: float = 0.01):
     u cen pod 30, vrací 0.01. U cen nad 30 vrací pomerne zvetsene, 
 
     """
-    if price<NORMALIZED_TICK_BASE_PRICE:
+    if price<cfh.config_handler.get_val('NORMALIZED_TICK_BASE_PRICE'):
         return normalized_ticks
     else:
         #ratio of price vs base price
-        ratio = price/NORMALIZED_TICK_BASE_PRICE
+        ratio = price/cfh.config_handler.get_val('NORMALIZED_TICK_BASE_PRICE')
         return price2dec(ratio*normalized_ticks)
 
 def eval_cond_dict(cond: dict) -> tuple[bool, str]:
@@ -550,6 +674,7 @@ def json_serial(obj):
         Intervals: lambda obj: obj.__dict__,
         SLHistory: lambda obj: obj.__dict__,
         InstantIndicator: lambda obj: obj.__dict__,
+        StrategyInstance: lambda obj: obj.__dict__,
     }
 
     serializer = type_map.get(type(obj))
@@ -578,23 +703,36 @@ def parse_toml_string(tomlst: str):
     try:
         tomlst = tomli.loads(tomlst)
     except tomli.TOMLDecodeError as e:
-        print("Not valid TOML.", str(e))
-        return (-1, None)
+        msg = f"Not valid TOML: " + str(e)
+        richprint(msg)
+        return (-1, msg)
     return (0, dict_replace_value(tomlst,"None",None))
 
 #class to persist
+
+# A FileLock is used to prevent concurrent access to the cache file.
+# The __init__ method reads the existing cache file within the lock to ensure it's not being written to simultaneously by another process.
+# The save method writes to a temporary file first and then atomically moves it to the desired file location. This prevents the issue of partial file writes in case the process is interrupted during the write.
+#Zatim temporary fix, aby nezapisoval jiny process
+#predtim nez bude implementovano ukladani do db
+#pro ostatni processy je dostupne rest api get stratin
 class Store:
-    stratins : List[StrategyInstance]  = []
+    stratins: List[StrategyInstance] = []
     runners: List[Runner] = []
+    
     def __init__(self) -> None:
+        self.lock = FileLock(DATA_DIR + "/strategyinstances.lock")
         self.db_file = DATA_DIR + "/strategyinstances.cache"
         if os.path.exists(self.db_file):
-            with open (self.db_file, 'rb') as fp:
+            with self.lock, open(self.db_file, 'rb') as fp:
                 self.stratins = pickle.load(fp)
 
     def save(self):
-        with open(self.db_file, 'wb') as fp:
-            pickle.dump(self.stratins, fp)
+        with self.lock:
+            temp_fd, temp_path = tempfile.mkstemp(dir=DATA_DIR)
+            with os.fdopen(temp_fd, 'wb') as temp_file:
+                pickle.dump(self.stratins, temp_file)
+            shutil.move(temp_path, self.db_file)
 
 qu = Queue()
 
@@ -604,7 +742,7 @@ zoneUTC = pytz.utc
 zonePRG = pytz.timezone('Europe/Amsterdam')
 
 def print(*args, **kwargs):
-    if QUIET_MODE:
+    if cfh.config_handler.get_val('QUIET_MODE'):
         pass
     else:
         ####ic(*args, **kwargs)

v2trading_create_db.sql

@@ -0,0 +1,97 @@
+BEGIN TRANSACTION;
+CREATE TABLE IF NOT EXISTS "test_list" (
+	"id"	varchar(32) NOT NULL,
+	"name"	varchar(255) NOT NULL,
+	"dates"	json NOT NULL
+);
+CREATE TABLE IF NOT EXISTS "runner_detail" (
+	"runner_id"	varchar(32) NOT NULL,
+	"data"	json NOT NULL,
+	PRIMARY KEY("runner_id")
+);
+CREATE TABLE IF NOT EXISTS "runner_header" (
+	"runner_id"	varchar(32) NOT NULL,
+	"strat_id"	TEXT,
+	"batch_id"	TEXT,
+	"symbol"	TEXT,
+	"name"	TEXT,
+	"note"	TEXT,
+	"started"	TEXT,
+	"stopped"	TEXT,
+	"mode"	TEXT,
+	"account"	TEXT,
+	"bt_from"	TEXT,
+	"bt_to"	TEXT,
+	"strat_json"	TEXT,
+	"settings"	TEXT,
+	"ilog_save"	INTEGER,
+	"profit"	NUMERIC,
+	"trade_count"	INTEGER,
+	"end_positions"	INTEGER,
+	"end_positions_avgp"	NUMERIC,
+	"metrics"	TEXT,
+	"stratvars_toml"	TEXT,
+	"transferables"        TEXT,
+	PRIMARY KEY("runner_id")
+);
+CREATE TABLE IF NOT EXISTS "config_table" (
+	"id"	INTEGER,
+	"item_name"	TEXT NOT NULL,
+	"json_data"	JSON NOT NULL,
+	"item_lang"	TEXT,
+	PRIMARY KEY("id" AUTOINCREMENT)
+);
+CREATE TABLE IF NOT EXISTS "runner_logs" (
+	"runner_id"	varchar(32) NOT NULL,
+	"time"	real NOT NULL,
+	"data"	json NOT NULL
+);
+CREATE TABLE "run_manager" (
+    "moddus"    TEXT NOT NULL,
+    "id"    varchar(32),
+    "strat_id"  varchar(32) NOT NULL,
+    "symbol"    TEXT,
+    "account"   TEXT NOT NULL,
+    "mode"  TEXT NOT NULL,
+    "note"  TEXT,
+    "ilog_save" BOOLEAN,
+    "bt_from"   TEXT,
+    "bt_to" TEXT,
+    "weekdays_filter"   TEXT,
+    "batch_id"  TEXT,
+    "start_time"    TEXT NOT NULL,
+    "stop_time" TEXT NOT NULL,
+    "status"    TEXT NOT NULL,
+    "last_processed"    TEXT,
+    "history"   TEXT,
+    "valid_from"    TEXT,
+    "valid_to"  TEXT,
+    "testlist_id"   TEXT,
+    "runner_id" varchar2(32),
+    "market" TEXT,
+    PRIMARY KEY("id")
+);
+CREATE INDEX idx_moddus ON run_manager (moddus);
+CREATE INDEX idx_status ON run_manager (status);
+CREATE INDEX idx_status_moddus ON run_manager (status, moddus);
+CREATE INDEX idx_valid_from_to ON run_manager (valid_from, valid_to);
+CREATE INDEX idx_stopped_batch_id ON runner_header (stopped, batch_id);
+CREATE INDEX idx_search_value ON runner_header (strat_id, batch_id);
+CREATE INDEX IF NOT EXISTS "index_runner_header_pk" ON "runner_header" (
+	"runner_id"
+);
+CREATE INDEX IF NOT EXISTS "index_runner_header_strat" ON "runner_header" (
+	"strat_id"
+);
+CREATE INDEX IF NOT EXISTS "index_runner_header_batch" ON "runner_header" (
+	"batch_id"
+);
+CREATE UNIQUE INDEX IF NOT EXISTS "index_runner_detail_pk" ON "runner_detail" (
+	"runner_id"
+);
+CREATE INDEX IF NOT EXISTS "index_runner_logs" ON "runner_logs" (
+	"runner_id",
+	"time"
+);
+INSERT INTO config_table VALUES (1, "test", "{}", "json");
+COMMIT;