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dwker/v2realbot:master dwker/v2realbot:feature/multiaccount227 dwker/v2realbot:feature/multisymbol223 dwker/v2realbot:vbtnewvers dwker/v2realbot:init-fixes2 dwker/v2realbot:researchadded dwker/v2realbot:feature/aggregachanges dwker/v2realbot:feature/vectorizedaggregator dwker/v2realbot:sitemap dwker/v2realbot:bug/attachdataoutindex dwker/v2realbot:feature/softstopmartingalebase dwker/v2realbot:feature/archrunnerdbsearch dwker/v2realbot:feature/tomlvalidation dwker/v2realbot:feature/transferables dwker/v2realbot:feature/martingale-alpaca-pyupgrade dwker/v2realbot:feature-actionbutton dwker/v2realbot:js-refactor dwker/v2realbot:feature-gui-resizing
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pull from: dwker/v2realbot:feature/tomlvalidation
Branches Tags
dwker/v2realbot:master dwker/v2realbot:feature/multiaccount227 dwker/v2realbot:feature/multisymbol223 dwker/v2realbot:vbtnewvers dwker/v2realbot:init-fixes2 dwker/v2realbot:researchadded dwker/v2realbot:feature/aggregachanges dwker/v2realbot:feature/vectorizedaggregator dwker/v2realbot:sitemap dwker/v2realbot:bug/attachdataoutindex dwker/v2realbot:feature/softstopmartingalebase dwker/v2realbot:feature/archrunnerdbsearch dwker/v2realbot:feature/tomlvalidation dwker/v2realbot:feature/transferables dwker/v2realbot:feature/martingale-alpaca-pyupgrade dwker/v2realbot:feature-actionbutton dwker/v2realbot:js-refactor dwker/v2realbot:feature-gui-resizing

1 Commits
sitemap .. feature/tomlvalidation

Author SHA1 Message Date
David Brazda 1e5e6a311f toml validation to frontend 2024-03-14 17:36:48 +01:00
1119 changed files with 160 additions and 266711 deletions
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{
"cells": [
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import pyarrow\n",
"import numpy as np\n",
"from numba import jit\n",
"import v2realbot.utils.config_handler as cfh"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Další info k pokračování je zde https://blog.quantinsti.com/tick-tick-ohlc-data-pandas-tutorial/"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"DatetimeIndex: 190261 entries, 2024-04-22 13:30:00.267711+00:00 to 2024-04-22 19:59:59.987614+00:00\n",
"Data columns (total 6 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 exchange 190261 non-null object \n",
" 1 price 190261 non-null float64\n",
" 2 size 190261 non-null float64\n",
" 3 id 190261 non-null int64 \n",
" 4 conditions 190261 non-null object \n",
" 5 tape 190261 non-null object \n",
"dtypes: float64(2), int64(1), object(3)\n",
"memory usage: 10.2+ MB\n"
]
},
{
"data": {
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" <th></th>\n",
" <th>exchange</th>\n",
" <th>price</th>\n",
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" <th>2024-04-22 19:59:59.977134+00:00</th>\n",
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"</div>"
],
"text/plain": [
" exchange price size id \\\n",
"timestamp \n",
"2024-04-22 13:30:00.267711+00:00 K 36.890 5.0 52983525037630 \n",
"2024-04-22 13:30:00.300501+00:00 D 37.005 1.0 71675241117014 \n",
"2024-04-22 13:30:00.305439+00:00 D 37.005 1.0 71675241117496 \n",
"2024-04-22 13:30:00.314520+00:00 D 37.005 1.0 71675241118034 \n",
"2024-04-22 13:30:00.335201+00:00 D 37.005 1.0 71675241121369 \n",
"... ... ... ... ... \n",
"2024-04-22 19:59:59.902614+00:00 V 37.750 1100.0 56480705310575 \n",
"2024-04-22 19:59:59.977134+00:00 N 37.745 300.0 52983559963478 \n",
"2024-04-22 19:59:59.977137+00:00 N 37.740 7300.0 52983559963696 \n",
"2024-04-22 19:59:59.978626+00:00 V 37.750 16.0 56480706886228 \n",
"2024-04-22 19:59:59.987614+00:00 N 37.745 30.0 52983559963958 \n",
"\n",
" conditions tape \n",
"timestamp \n",
"2024-04-22 13:30:00.267711+00:00 [ , F, I] A \n",
"2024-04-22 13:30:00.300501+00:00 [ , I] A \n",
"2024-04-22 13:30:00.305439+00:00 [ , I] A \n",
"2024-04-22 13:30:00.314520+00:00 [ , I] A \n",
"2024-04-22 13:30:00.335201+00:00 [ , I] A \n",
"... ... ... \n",
"2024-04-22 19:59:59.902614+00:00 [ ] A \n",
"2024-04-22 19:59:59.977134+00:00 [ ] A \n",
"2024-04-22 19:59:59.977137+00:00 [ ] A \n",
"2024-04-22 19:59:59.978626+00:00 [ , I] A \n",
"2024-04-22 19:59:59.987614+00:00 [ , I] A \n",
"\n",
"[190261 rows x 6 columns]"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tdf=pd.read_parquet('trades_bac.parquet',engine='pyarrow')\n",
"#print(df)\n",
"df = tdf.loc['BAC']\n",
"df.info()\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [],
"source": [
"@jit(nopython=True)\n",
"def ohlcv_bars(ticks, start_time, end_time, resolution):\n",
" \"\"\"\n",
" Generate OHLCV bars from tick data, skipping intervals without trading activity.\n",
" \n",
" Parameters:\n",
" - ticks: numpy array with columns [timestamp, price, size]\n",
" - start_time: the start timestamp for bars (Unix timestamp)\n",
" - end_time: the end timestamp for bars (Unix timestamp)\n",
" - resolution: time resolution in seconds\n",
" \n",
" Returns:\n",
" - OHLCV bars as a numpy array\n",
" \"\"\"\n",
" num_bars = (end_time - start_time) // resolution + 1\n",
" bar_list = []\n",
"\n",
" for i in range(num_bars):\n",
" bar_start_time = start_time + i * resolution\n",
" bar_end_time = bar_start_time + resolution\n",
" bar_ticks = ticks[(ticks[:, 0] >= bar_start_time) & (ticks[:, 0] < bar_end_time)]\n",
" \n",
" if bar_ticks.shape[0] == 0:\n",
" continue # Skip this bar as there are no ticks\n",
"\n",
" # Calculate OHLCV values\n",
" open_price = bar_ticks[0, 1] # open\n",
" high_price = np.max(bar_ticks[:, 1]) # high\n",
" low_price = np.min(bar_ticks[:, 1]) # low\n",
" close_price = bar_ticks[-1, 1] # close\n",
" volume = np.sum(bar_ticks[:, 2]) # volume\n",
" bar_time = bar_start_time # timestamp for the bar\n",
"\n",
" bar_list.append([open_price, high_price, low_price, close_price, volume, bar_time])\n",
"\n",
" # Convert list to numpy array\n",
" if bar_list:\n",
" ohlcv = np.array(bar_list)\n",
" else:\n",
" ohlcv = np.empty((0, 6)) # return an empty array if no bars were created\n",
"\n",
" return ohlcv\n"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"DatetimeIndex: 190261 entries, 2024-04-22 13:30:00.267711+00:00 to 2024-04-22 19:59:59.987614+00:00\n",
"Data columns (total 6 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 exchange 190261 non-null object \n",
" 1 price 190261 non-null float64\n",
" 2 size 190261 non-null float64\n",
" 3 id 190261 non-null int64 \n",
" 4 conditions 190261 non-null object \n",
" 5 tape 190261 non-null object \n",
"dtypes: float64(2), int64(1), object(3)\n",
"memory usage: 10.2+ MB\n"
]
}
],
"source": [
"df.info()"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['C', 'O', '4', 'B', '7', 'V', 'P', 'W', 'U', 'Z', 'F']\n",
"<class 'pandas.core.frame.DataFrame'>\n",
"DatetimeIndex: 143751 entries, 2024-04-22 13:30:00.300501+00:00 to 2024-04-22 19:59:59.987614+00:00\n",
"Data columns (total 6 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 exchange 143751 non-null object \n",
" 1 price 143751 non-null float64\n",
" 2 size 143751 non-null float64\n",
" 3 id 143751 non-null int64 \n",
" 4 conditions 143751 non-null object \n",
" 5 tape 143751 non-null object \n",
"dtypes: float64(2), int64(1), object(3)\n",
"memory usage: 7.7+ MB\n"
]
},
{
"data": {
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" <td>37.750</td>\n",
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" <th>2024-04-22 19:59:59.977134+00:00</th>\n",
" <td>N</td>\n",
" <td>37.745</td>\n",
" <td>300.0</td>\n",
" <td>52983559963478</td>\n",
" <td>[ ]</td>\n",
" <td>A</td>\n",
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" <th>2024-04-22 19:59:59.977137+00:00</th>\n",
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" <td>37.740</td>\n",
" <td>7300.0</td>\n",
" <td>52983559963696</td>\n",
" <td>[ ]</td>\n",
" <td>A</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2024-04-22 19:59:59.978626+00:00</th>\n",
" <td>V</td>\n",
" <td>37.750</td>\n",
" <td>16.0</td>\n",
" <td>56480706886228</td>\n",
" <td>[ , I]</td>\n",
" <td>A</td>\n",
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" <th>2024-04-22 19:59:59.987614+00:00</th>\n",
" <td>N</td>\n",
" <td>37.745</td>\n",
" <td>30.0</td>\n",
" <td>52983559963958</td>\n",
" <td>[ , I]</td>\n",
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"</div>"
],
"text/plain": [
" exchange price size id \\\n",
"timestamp \n",
"2024-04-22 13:30:00.300501+00:00 D 37.005 1.0 71675241117014 \n",
"2024-04-22 13:30:00.305439+00:00 D 37.005 1.0 71675241117496 \n",
"2024-04-22 13:30:00.314520+00:00 D 37.005 1.0 71675241118034 \n",
"2024-04-22 13:30:00.335201+00:00 D 37.005 1.0 71675241121369 \n",
"2024-04-22 13:30:00.346219+00:00 D 37.005 1.0 71675241122389 \n",
"... ... ... ... ... \n",
"2024-04-22 19:59:59.902614+00:00 V 37.750 1100.0 56480705310575 \n",
"2024-04-22 19:59:59.977134+00:00 N 37.745 300.0 52983559963478 \n",
"2024-04-22 19:59:59.977137+00:00 N 37.740 7300.0 52983559963696 \n",
"2024-04-22 19:59:59.978626+00:00 V 37.750 16.0 56480706886228 \n",
"2024-04-22 19:59:59.987614+00:00 N 37.745 30.0 52983559963958 \n",
"\n",
" conditions tape \n",
"timestamp \n",
"2024-04-22 13:30:00.300501+00:00 [ , I] A \n",
"2024-04-22 13:30:00.305439+00:00 [ , I] A \n",
"2024-04-22 13:30:00.314520+00:00 [ , I] A \n",
"2024-04-22 13:30:00.335201+00:00 [ , I] A \n",
"2024-04-22 13:30:00.346219+00:00 [ , I] A \n",
"... ... ... \n",
"2024-04-22 19:59:59.902614+00:00 [ ] A \n",
"2024-04-22 19:59:59.977134+00:00 [ ] A \n",
"2024-04-22 19:59:59.977137+00:00 [ ] A \n",
"2024-04-22 19:59:59.978626+00:00 [ , I] A \n",
"2024-04-22 19:59:59.987614+00:00 [ , I] A \n",
"\n",
"[143751 rows x 6 columns]"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"excludes = cfh.config_handler.get_val('AGG_EXCLUDED_TRADES')\n",
"print(excludes)\n",
"#excludes = [\"F\", \"I\"]\n",
"# FILTER EXCLUDED TRADES\n",
"# Filter rows to exclude those where 'conditions' contains 'F' or 'I'\n",
"# This simplifies the logic by directly using ~ (bitwise not operator) with np.isin\n",
"df = df[~df['conditions'].apply(lambda x: np.isin(x, excludes).any())]"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/8p/dwqnp65s0s77jdbm4_6z4vp80000gn/T/ipykernel_52602/3341929382.py:2: DeprecationWarning: parsing timezone aware datetimes is deprecated; this will raise an error in the future\n",
" structured_array = np.array(list(zip(df.index, df['price'], df['size'])),\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[('2024-04-22T13:30:00.300501000', 37.005, 1.0e+00)\n",
" ('2024-04-22T13:30:00.305439000', 37.005, 1.0e+00)\n",
" ('2024-04-22T13:30:00.314520000', 37.005, 1.0e+00) ...\n",
" ('2024-04-22T19:59:59.977137000', 37.74 , 7.3e+03)\n",
" ('2024-04-22T19:59:59.978626000', 37.75 , 1.6e+01)\n",
" ('2024-04-22T19:59:59.987614000', 37.745, 3.0e+01)]\n"
]
},
{
"data": {
"text/plain": [
"array([('2024-04-22T13:30:00.300501000', 37.005, 1.0e+00),\n",
" ('2024-04-22T13:30:00.305439000', 37.005, 1.0e+00),\n",
" ('2024-04-22T13:30:00.314520000', 37.005, 1.0e+00), ...,\n",
" ('2024-04-22T19:59:59.977137000', 37.74 , 7.3e+03),\n",
" ('2024-04-22T19:59:59.978626000', 37.75 , 1.6e+01),\n",
" ('2024-04-22T19:59:59.987614000', 37.745, 3.0e+01)],\n",
" dtype=[('timestamp', '<M8[ns]'), ('price', '<f8'), ('size', '<f8')])"
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Creating a structured array with the timestamp as the first element\n",
"structured_array = np.array(list(zip(df.index, df['price'], df['size'])),\n",
" dtype=[('timestamp', 'datetime64[ns]'), ('price', 'float'), ('size', 'float')])\n",
"\n",
"print(structured_array)\n",
"structured_array\n",
"\n",
"# ticks = df[['index', 'price', 'size']].to_numpy()\n",
"# # ticks[:, 0] = pd.to_datetime(ticks[:, 0]).astype('int64') // 1_000_000_000 # \n",
"# ticks"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"resolution_seconds = 1 # 1 second resolution\n",
"ohlcv_data = ohlcv_bars(structured_array, resolution_seconds)\n",
"\n",
"# Converting the result back to DataFrame for better usability\n",
"ohlcv_df = pd.DataFrame(ohlcv_data, columns=['Open', 'High', 'Low', 'Close', 'Volume', 'Time'])\n",
"ohlcv_df['Time'] = pd.to_datetime(ohlcv_df['Time'], unit='s') # Convert timestamps back to datetime\n"
]
}
],
"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
}
v2realbot/backtesting/backtester.py
+2 -2
View File
@@ -524,7 +524,7 @@ class Backtester:
if actual_minus_reserved <= 0: if actual_minus_reserved <= 0:
cena = price if price else self.get_last_price(time, self.symbol) cena = price if price else self.get_last_price(time, self.symbol)
if (self.cash - reserved_price - float(int(size)*float(cena))) < 0: if (self.cash - reserved_price - float(int(size)*float(cena))) < 0:
printanyway("ERROR: not enough cash for shorting. cash",self.cash,"reserved",reserved,"available",self.cash-reserved,"needed",float(int(size)*float(cena))) printanyway("not enough cash for shorting. cash",self.cash,"reserved",reserved,"available",self.cash-reserved,"needed",float(int(size)*float(cena)))
return -1 return -1
#check for available cash #check for available cash
@@ -550,7 +550,7 @@ class Backtester:
if actual_plus_reserved_qty >= 0: if actual_plus_reserved_qty >= 0:
cena = price if price else self.get_last_price(time, self.symbol) cena = price if price else self.get_last_price(time, self.symbol)
if (self.cash - reserved_price - float(int(size)*float(cena))) < 0: if (self.cash - reserved_price - float(int(size)*float(cena))) < 0:
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))) printanyway("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 return -1
id = str(uuid4()) id = str(uuid4())
v2realbot/common/model.py
+1 -2
View File
@@ -5,7 +5,7 @@ from rich import print
from typing import Any, Optional, List, Union from typing import Any, Optional, List, Union
from datetime import datetime, date from datetime import datetime, date
from pydantic import BaseModel, Field from pydantic import BaseModel, Field
from v2realbot.enums.enums import Mode, Account, SchedulerStatus, Moddus, Market from v2realbot.enums.enums import Mode, Account, SchedulerStatus, Moddus
from alpaca.data.enums import Exchange from alpaca.data.enums import Exchange
@@ -159,7 +159,6 @@ class RunManagerRecord(BaseModel):
mode: Mode mode: Mode
note: Optional[str] = None note: Optional[str] = None
ilog_save: bool = False ilog_save: bool = False
market: Optional[Market] = Market.US
bt_from: Optional[datetime] = None bt_from: Optional[datetime] = None
bt_to: Optional[datetime] = None bt_to: Optional[datetime] = None
#weekdays filter #weekdays filter
v2realbot/common/transform.py
+2 -1
View File
@@ -5,7 +5,9 @@ import v2realbot.controller.services as cs
#prevede dict radku zpatky na objekt vcetme retypizace #prevede dict radku zpatky na objekt vcetme retypizace
def row_to_runmanager(row: dict) -> RunManagerRecord: def row_to_runmanager(row: dict) -> RunManagerRecord:
is_running = cs.is_runner_running(row['runner_id']) if row['runner_id'] else False is_running = cs.is_runner_running(row['runner_id']) if row['runner_id'] else False
res = RunManagerRecord( res = RunManagerRecord(
moddus=row['moddus'], moddus=row['moddus'],
id=row['id'], id=row['id'],
@@ -15,7 +17,6 @@ def row_to_runmanager(row: dict) -> RunManagerRecord:
account=row['account'], account=row['account'],
note=row['note'], note=row['note'],
ilog_save=bool(row['ilog_save']), 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_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, 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 [], weekdays_filter=[int(x) for x in row['weekdays_filter'].split(',')] if row['weekdays_filter'] else [],
v2realbot/controller/run_manager.py
+3 -3
View File
@@ -172,14 +172,14 @@ def add_run_manager_record(new_record: RunManagerRecord):
# Construct a suitable INSERT query based on your RunManagerRecord fields # Construct a suitable INSERT query based on your RunManagerRecord fields
insert_query = """ insert_query = """
INSERT INTO run_manager (moddus, id, strat_id, symbol,account, mode, note,ilog_save, INSERT INTO run_manager (moddus, id, strat_id, symbol,account, mode, note,ilog_save,
market, bt_from, bt_to, weekdays_filter, batch_id, bt_from, bt_to, weekdays_filter, batch_id,
start_time, stop_time, status, last_processed, start_time, stop_time, status, last_processed,
history, valid_from, valid_to, testlist_id) history, valid_from, valid_to, testlist_id)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?,?) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
""" """
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, 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, int(new_record.ilog_save),
new_record.bt_from.isoformat() if new_record.bt_from is not None else None, 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, 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, ",".join(str(x) for x in new_record.weekdays_filter) if new_record.weekdays_filter else None,
v2realbot/controller/services.py
+3 -3
View File
@@ -1114,7 +1114,7 @@ def get_all_archived_runners_p(request: DataTablesRequest) -> Tuple[int, RunArch
# Total count query # Total count query
total_count_query = """ total_count_query = """
SELECT COUNT(*) FROM runner_header 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) WHERE (:search_value = '' OR strat_id LIKE :search_value OR batch_id LIKE :search_value)
""" """
c.execute(total_count_query, {'search_value': f'%{search_value}%'}) c.execute(total_count_query, {'search_value': f'%{search_value}%'})
total_count = c.fetchone()[0] total_count = c.fetchone()[0]
@@ -1129,7 +1129,7 @@ def get_all_archived_runners_p(request: DataTablesRequest) -> Tuple[int, RunArch
SUM(profit) OVER (PARTITION BY batch_id) AS batch_profit, SUM(profit) OVER (PARTITION BY batch_id) AS batch_profit,
COUNT(*) OVER (PARTITION BY batch_id) AS batch_count COUNT(*) OVER (PARTITION BY batch_id) AS batch_count
FROM runner_header 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) WHERE (:search_value = '' OR strat_id LIKE :search_value OR batch_id LIKE :search_value)
), ),
InterleavedGroups AS ( InterleavedGroups AS (
SELECT *, SELECT *,
@@ -1156,7 +1156,7 @@ def get_all_archived_runners_p(request: DataTablesRequest) -> Tuple[int, RunArch
# Filtered count query # Filtered count query
filtered_count_query = """ filtered_count_query = """
SELECT COUNT(*) FROM runner_header 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) WHERE (:search_value = '' OR strat_id LIKE :search_value OR batch_id LIKE :search_value)
""" """
c.execute(filtered_count_query, {'search_value': f'%{search_value}%'}) c.execute(filtered_count_query, {'search_value': f'%{search_value}%'})
filtered_count = c.fetchone()[0] filtered_count = c.fetchone()[0]
v2realbot/enums/enums.py
-6
View File
@@ -104,9 +104,3 @@ class StartBarAlign(str, Enum):
""" """
ROUND = "round" ROUND = "round"
RANDOM = "random" RANDOM = "random"
class Market(str, Enum):
US = "US"
CRYPTO = "CRYPTO"
v2realbot/loader/aggregator_vectorized.py
-122
View File
@@ -1,122 +0,0 @@
import pandas as pd
import numpy as np
from numba import jit
from alpaca.data.historical import StockHistoricalDataClient
from v2realbot.config import ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, DATA_DIR
from alpaca.data.requests import StockTradesRequest
import time
from datetime import datetime
from v2realbot.utils.utils import parse_alpaca_timestamp, ltp, zoneNY, send_to_telegram, fetch_calendar_data
import pyarrow
""""
WIP - for later use
"""""
def fetch_stock_trades(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.
"""
client = StockHistoricalDataClient(ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY)
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)
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.")
raise ConnectionError(f"Failed to fetch stock trades after {max_retries} retries. Last exception: {str(last_exception)} and {format_exc()}")
@jit(nopython=True)
def ohlcv_bars(ticks, start_time, end_time, resolution):
"""
Generate OHLCV bars from tick data, skipping intervals without trading activity.
Parameters:
- ticks: numpy array with columns [timestamp, price, size]
- start_time: the start timestamp for bars (Unix timestamp)
- end_time: the end timestamp for bars (Unix timestamp)
- resolution: time resolution in seconds
Returns:
- OHLCV bars as a numpy array
"""
num_bars = (end_time - start_time) // resolution + 1
bar_list = []
for i in range(num_bars):
bar_start_time = start_time + i * resolution
bar_end_time = bar_start_time + resolution
bar_ticks = ticks[(ticks[:, 0] >= bar_start_time) & (ticks[:, 0] < bar_end_time)]
if bar_ticks.shape[0] == 0:
continue # Skip this bar as there are no ticks
# Calculate OHLCV values
open_price = bar_ticks[0, 1] # open
high_price = np.max(bar_ticks[:, 1]) # high
low_price = np.min(bar_ticks[:, 1]) # low
close_price = bar_ticks[-1, 1] # close
volume = np.sum(bar_ticks[:, 2]) # volume
bar_time = bar_start_time # timestamp for the bar
bar_list.append([open_price, high_price, low_price, close_price, volume, bar_time])
# Convert list to numpy array
if bar_list:
ohlcv = np.array(bar_list)
else:
ohlcv = np.empty((0, 6)) # return an empty array if no bars were created
return ohlcv
# Example usage
if __name__ == '__main__':
# symbol = ["BAC"]
# #datetime in zoneNY
# day_start = datetime(2024, 4, 22, 9, 30, 0)
# day_stop = datetime(2024, 4, 22, 16, 00, 0)
# day_start = zoneNY.localize(day_start)
# day_stop = zoneNY.localize(day_stop)
# tradesResponse = fetch_stock_trades(symbol, day_start, day_stop)
# df = tradesResponse.df
# df.to_parquet('trades_bac.parquet', engine='pyarrow')
df=pd.read_parquet('trades_bac.parquet',engine='pyarrow')
print(df)
#df = pd.read_csv('tick_data.csv') # DF with tick data
# Assuming 'df' is your DataFrame with columns 'time', 'price', 'size', 'condition'
exclude_conditions = ['ConditionA', 'ConditionB'] # Conditions to exclude
df_filtered = df[~df['condition'].isin(exclude_conditions)]
# Define your start and end times based on your trading session, ensure these are Unix timestamps
start_time = pd.to_datetime('2023-01-01 09:30:00').timestamp()
end_time = pd.to_datetime('2023-01-01 16:00:00').timestamp()
ticks = df[['time', 'price', 'size']].to_numpy()
ticks[:, 0] = pd.to_datetime(ticks[:, 0]).astype('int64') // 1_000_000_000 # Convert to Unix timestamp
resolution_seconds = 1 # 1 second resolution
ohlcv_data = ohlcv_bars(ticks, start_time, end_time, resolution_seconds)
# Converting the result back to DataFrame for better usability
ohlcv_df = pd.DataFrame(ohlcv_data, columns=['Open', 'High', 'Low', 'Close', 'Volume', 'Time'])
ohlcv_df['Time'] = pd.to_datetime(ohlcv_df['Time'], unit='s') # Convert timestamps back to datetime
v2realbot/scheduler/ap_scheduler.py
+13 -15
View File
@@ -2,7 +2,7 @@ from uuid import UUID
from typing import Any, List, Tuple from typing import Any, List, Tuple
from uuid import UUID, uuid4 from uuid import UUID, uuid4
from v2realbot.enums.enums import Moddus, SchedulerStatus, RecordType, StartBarAlign, Mode, Account, OrderSide 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.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.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 v2realbot.common.PrescribedTradeModel import Trade, TradeDirection, TradeStatus, TradeStoplossType
from datetime import datetime from datetime import datetime
@@ -116,8 +116,7 @@ def initialize_jobs(run_manager_records: RunManagerRecord = None):
scheduler.add_job(start_runman_record, start_trigger, id=f"scheduler_start_{record.id}", args=[record.id]) 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(stop_runman_record, stop_trigger, id=f"scheduler_stop_{record.id}", args=[record.id])
#scheduler.add_job(print_hello, 'interval', seconds=10, id= #scheduler.add_job(print_hello, 'interval', seconds=10, id=f"scheduler_testinterval")
# f"scheduler_testinterval")
scheduled_jobs = scheduler.get_jobs() scheduled_jobs = scheduler.get_jobs()
print(f"APS jobs refreshed ({len(scheduled_jobs)})") print(f"APS jobs refreshed ({len(scheduled_jobs)})")
current_jobs_dict = format_apscheduler_jobs(scheduled_jobs) current_jobs_dict = format_apscheduler_jobs(scheduled_jobs)
@@ -125,9 +124,9 @@ def initialize_jobs(run_manager_records: RunManagerRecord = None):
return 0, current_jobs_dict return 0, current_jobs_dict
#zastresovaci funkce resici error handling a printing #zastresovaci funkce resici error handling a printing
def start_runman_record(id: UUID, debug_date = None): def start_runman_record(id: UUID, market = "US", debug_date = None):
record = None record = None
res, record, msg = _start_runman_record(id=id, debug_date=debug_date) res, record, msg = _start_runman_record(id=id, market=market, debug_date=debug_date)
if record is not None: if record is not None:
market_time_now = datetime.now().astimezone(zoneNY) if debug_date is None else debug_date market_time_now = datetime.now().astimezone(zoneNY) if debug_date is None else debug_date
@@ -166,8 +165,8 @@ def update_runman_record(record: RunManagerRecord):
err_msg= f"STOP: Error updating {record.id} errir {set} with values {record}" 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 return -2, err_msg#toto stopne zpracovani dalsich zaznamu pri chybe, zvazit continue
def stop_runman_record(id: UUID, debug_date = None): def stop_runman_record(id: UUID, market = "US", debug_date = None):
res, record, msg = _stop_runman_record(id=id, debug_date=debug_date) res, record, msg = _stop_runman_record(id=id, market=market, debug_date=debug_date)
#results : 0 - ok, -1 not running/already running/not specific, -2 error #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 #report vzdy zapiseme do history, pokud je record not None, pripadna chyba se stala po dotazeni recordu
@@ -197,7 +196,7 @@ def stop_runman_record(id: UUID, debug_date = None):
print(f"STOP JOB: {id} FINISHED") print(f"STOP JOB: {id} FINISHED")
#start function that is called from the job #start function that is called from the job
def _start_runman_record(id: UUID, debug_date = None): def _start_runman_record(id: UUID, market = "US", debug_date = None):
print(f"Start scheduled record {id}") print(f"Start scheduled record {id}")
record : RunManagerRecord = None record : RunManagerRecord = None
@@ -208,16 +207,15 @@ def _start_runman_record(id: UUID, debug_date = None):
record = result record = result
if record.market == Market.US or record.market == Market.CRYPTO: if market is not None and market == "US":
res, sada = sch.get_todays_market_times(market=record.market, debug_date=debug_date) res, sada = sch.get_todays_market_times(market=market, debug_date=debug_date)
if res == 0: if res == 0:
market_time_now, market_open_datetime, market_close_datetime = sada market_time_now, market_open_datetime, market_close_datetime = sada
print(f"OPEN:{market_open_datetime} CLOSE:{market_close_datetime}") print(f"OPEN:{market_open_datetime} CLOSE:{market_close_datetime}")
else: else:
sada = f"Market {record.market} Error getting market times (CLOSED): " + str(sada) sada = f"Market {market} Error getting market times (CLOSED): " + str(sada)
return res, record, sada return res, record, sada
else:
print("Market type is unknown.")
if cs.is_stratin_running(record.strat_id): if cs.is_stratin_running(record.strat_id):
return -1, record, f"Stratin {record.strat_id} is already running" return -1, record, f"Stratin {record.strat_id} is already running"
@@ -231,7 +229,7 @@ def _start_runman_record(id: UUID, debug_date = None):
return 0, record, record.runner_id return 0, record, record.runner_id
#stop function that is called from the job #stop function that is called from the job
def _stop_runman_record(id: UUID, debug_date = None): def _stop_runman_record(id: UUID, market = "US", debug_date = None):
record = None record = None
#get all records #get all records
print(f"Stopping record {id}") print(f"Stopping record {id}")
@@ -306,5 +304,5 @@ if __name__ == "__main__":
# print(f"CALL FINISHED, with {debug_date} RESULT: {res}, {result}") # print(f"CALL FINISHED, with {debug_date} RESULT: {res}, {result}")
res, result = stop_runman_record(id=id, debug_date = debug_date) res, result = stop_runman_record(id=id, market = "US", debug_date = debug_date)
print(f"CALL FINISHED, with {debug_date} RESULT: {res}, {result}") print(f"CALL FINISHED, with {debug_date} RESULT: {res}, {result}")
v2realbot/scheduler/scheduler.py
+14 -26
View File
@@ -2,10 +2,10 @@ import json
import datetime import datetime
import v2realbot.controller.services as cs import v2realbot.controller.services as cs
import v2realbot.controller.run_manager as rm 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 v2realbot.common.model import RunnerView, RunManagerRecord, StrategyInstance, Runner, RunRequest, Trade, RunArchive, RunArchiveView, RunArchiveViewPagination, RunArchiveDetail, Bar, RunArchiveChange, TestList, ConfigItem, InstantIndicator, DataTablesRequest, AnalyzerInputs
from uuid import uuid4, UUID from uuid import uuid4, UUID
from v2realbot.utils.utils import json_serial, send_to_telegram, zoneNY, zonePRG, zoneUTC, fetch_calendar_data from v2realbot.utils.utils import json_serial, send_to_telegram, zoneNY, zonePRG, fetch_calendar_data
from datetime import datetime, timedelta, time from datetime import datetime, timedelta
from traceback import format_exc from traceback import format_exc
from rich import print from rich import print
import requests import requests
@@ -18,18 +18,9 @@ from v2realbot.config import WEB_API_KEY
#naplanovany jako samostatni job a triggerován pouze jednou v daný čas pro start a stop #naplanovany jako samostatni job a triggerován pouze jednou v daný čas pro start a stop
#novy kod v aps_scheduler.py #novy kod v aps_scheduler.py
def is_US_market_day(date): def get_todays_market_times(market = "US", debug_date = None):
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: try:
if market == Market.US: if market == "US":
#zjistit vsechny podminky - mozna loopovat - podminky jsou vlevo #zjistit vsechny podminky - mozna loopovat - podminky jsou vlevo
if debug_date is not None: if debug_date is not None:
nowNY = debug_date nowNY = debug_date
@@ -37,20 +28,17 @@ def get_todays_market_times(market, debug_date = None):
nowNY = datetime.now().astimezone(zoneNY) nowNY = datetime.now().astimezone(zoneNY)
nowNY_date = nowNY.date() nowNY_date = nowNY.date()
#is market open - nyni pouze US #is market open - nyni pouze US
stat, calendar_dates = is_US_market_day(nowNY_date) cal_dates = fetch_calendar_data(nowNY_date, nowNY_date)
if stat:
if len(cal_dates) == 0:
print("No Market Day today")
return -1, "Market Closed"
#zatim podpora pouze main session #zatim podpora pouze main session
#pouze main session #pouze main session
market_open_datetime = zoneNY.localize(calendar_dates[0].open) market_open_datetime = zoneNY.localize(cal_dates[0].open)
market_close_datetime = zoneNY.localize(calendar_dates[0].close) market_close_datetime = zoneNY.localize(cal_dates[0].close)
return 0, (nowNY, market_open_datetime, market_close_datetime) 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: else:
return -1, "Market not supported" return -1, "Market not supported"
except Exception as e: except Exception as e:
v2realbot/static/index.html
+6 -7
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@@ -347,7 +347,6 @@
<th>testlist_id</th> <th>testlist_id</th>
<th>Running</th> <th>Running</th>
<th>RunnerId</th> <th>RunnerId</th>
<th>Market</th>
</tr> </tr>
</thead> </thead>
<tbody></tbody> <tbody></tbody>
@@ -668,14 +667,14 @@
</div> </div>
<div class="form-group mt-3"> <div class="form-group mt-3">
<label for="logHere" class="form-label">Log</label> <label for="logHere" class="form-label">Log</label>
<div id="log-container"style="height:700px;border:1px solid black;"> <div id="log-container">
<!-- <pre id="log-content"></pre> --> <pre id="log-content"></pre>
</div> </div>
</div> </div>
</div> </div>
<div class="modal-footer"> <div class="modal-footer">
<button type="button" class="btn btn-primary" id="logRefreshButton" value="Refresh">Refresh</button> <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> <button type="button" class="btn btn-secondary" data-bs-dismiss="modal">Close</button>
</div> </div>
</div> </div>
</div> </div>
@@ -1167,9 +1166,9 @@
<!-- <script src="/static/js/archivetables.js?v=1.05"></script> --> <!-- <script src="/static/js/archivetables.js?v=1.05"></script> -->
<!-- archiveTables split into separate files --> <!-- archiveTables split into separate files -->
<script src="/static/js/tables/archivetable/init.js?v=1.12"></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/functions.js?v=1.10"></script>
<script src="/static/js/tables/archivetable/modals.js?v=1.07"></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> <script src="/static/js/tables/archivetable/handlers.js?v=1.09"></script>
<!-- Runmanager functionality --> <!-- Runmanager functionality -->
<script src="/static/js/tables/runmanager/init.js?v=1.1"></script> <script src="/static/js/tables/runmanager/init.js?v=1.1"></script>
@@ -1179,7 +1178,7 @@
<script src="/static/js/livewebsocket.js?v=1.02"></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/realtimechart.js?v=1.02"></script>
<script src="/static/js/mytables.js?v=1.03"></script> <script src="/static/js/mytables.js?v=1.02"></script>
<script src="/static/js/testlist.js?v=1.01"></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/ml.js?v=1.02"></script>
<script src="/static/js/common.js?v=1.01"></script> <script src="/static/js/common.js?v=1.01"></script>
v2realbot/static/js/mytables.js
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@@ -90,55 +90,9 @@ $(document).ready(function () {
monaco.languages.register({ id: 'python' }); monaco.languages.register({ id: 'python' });
monaco.languages.register({ id: 'json' }); monaco.languages.register({ id: 'json' });
//Register mylogs language
monaco.languages.register({ id: 'mylogs' });
// Register the TOML language // 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' }); monaco.languages.register({ id: 'toml' });
// Define the TOML language configuration // Define the TOML language configuration
monaco.languages.setLanguageConfiguration('toml', { monaco.languages.setLanguageConfiguration('toml', {
comments: { comments: {
v2realbot/static/js/tables/archivetable/functions.js
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@@ -6,7 +6,6 @@ let editor_diff_arch1
let editor_diff_arch2 let editor_diff_arch2
var archData = null var archData = null
var batchHeaders = [] var batchHeaders = []
var editorLog = null
function refresh_arch_and_callback(row, callback) { function refresh_arch_and_callback(row, callback) {
//console.log("entering refresh") //console.log("entering refresh")
@@ -473,34 +472,13 @@ function refresh_logfile() {
contentType: "application/json", contentType: "application/json",
dataType: "json", dataType: "json",
success:function(response){ success:function(response){
if (editorLog) {
editorLog.dispose();
}
if (response.lines.length == 0) { if (response.lines.length == 0) {
value = "no records"; $('#log-content').html("no records");
// $('#log-content').html("no records");
} }
else { else {
//console.log(response.lines) var escapedLines = response.lines.map(line => escapeHtml(line));
//var escapedLines = response.lines.map(line => escapeHtml(line)); $('#log-content').html(escapedLines.join('\n'));
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) { error: function(xhr, status, error) {
var err = eval("(" + xhr.responseText + ")"); var err = eval("(" + xhr.responseText + ")");
v2realbot/static/js/tables/archivetable/handlers.js
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@@ -265,8 +265,8 @@ $(document).ready(function () {
$('#diff_first').text(record1.name); $('#diff_first').text(record1.name);
$('#diff_second').text(record2.name); $('#diff_second').text(record2.name);
$('#diff_first_id').text(data1.id + ' Batch: ' + data1.batch_id); $('#diff_first_id').text(data1.id);
$('#diff_second_id').text(data2.id + ' Batch: ' + data2.batch_id); $('#diff_second_id').text(data2.id);
//monaco //monaco
require(["vs/editor/editor.main"], () => { require(["vs/editor/editor.main"], () => {
@@ -358,13 +358,8 @@ $(document).ready(function () {
}) })
}); });
$('#closeLogModal').click(function () {
editorLog.dispose()
});
//button to query log //button to query log
$('#logRefreshButton').click(function () { $('#logRefreshButton').click(function () {
editorLog.dispose()
refresh_logfile() refresh_logfile()
}); });
v2realbot/static/js/tables/runmanager/init.js
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@@ -46,7 +46,6 @@ function initialize_runmanagerRecords() {
{data: 'testlist_id', visible: true}, {data: 'testlist_id', visible: true},
{data: 'strat_running', visible: true}, {data: 'strat_running', visible: true},
{data: 'runner_id', visible: true}, {data: 'runner_id', visible: true},
{data: 'market', visible: true},
], ],
paging: true, paging: true,
processing: true, processing: true,
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