balik zmen uff

v2realbot/utils/historicals.py

@@ -0,0 +1,92 @@
+from alpaca.data.historical import StockHistoricalDataClient, CryptoHistoricalDataClient
+from alpaca.data.requests import StockLatestQuoteRequest, StockBarsRequest, StockTradesRequest, StockSnapshotRequest
+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 alpaca.data.enums import DataFeed
+from datetime import datetime, timedelta
+import pandas as pd
+from rich import print
+from collections import defaultdict
+from pandas import to_datetime
+from msgpack.ext import Timestamp
+
+def convert_daily_bars(daily_bars):
+  """Converts a list of daily bars into a dictionary with the specified keys.
+
+  Args:
+    daily_bars: A list of daily bars, where each bar is a dictionary with the
+      following keys:
+        * c: Close price
+        * h: High price
+        * l: Low price
+        * n: Number of trades
+        * o: Open price
+        * t: Time in UTC (ISO 8601 format)
+        * v: Volume
+        * vw: VWAP
+
+  Returns:
+    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)
+  """
+
+  bars = defaultdict(list)
+  for i in range(len(daily_bars)):
+    bar = daily_bars[i]
+
+    # Calculate the HLCC4 indicator
+    hlcc4 = (bar['h'] + bar['l'] + bar['c'] + bar['o']) / 4
+    datum = to_datetime(bar['t'], utc=True)
+
+    #nebo pripadna homogenizace s online streamem
+    #datum = Timestamp.from_unix(datum.timestamp())
+
+    # Add the bar to the dictionary
+    bars['high'].append(bar['h'])
+    bars['low'].append(bar['l'])
+    bars['volume'].append(bar['v'])
+    bars['close'].append(bar['c'])
+    bars['hlcc4'].append(hlcc4)
+    bars['open'].append(bar['o'])
+    bars['time'].append(datum)
+    bars['trades'].append(bar['n'])
+    bars['resolution'].append('D')
+    bars['confirmed'].append(1)
+    bars['vwap'].append(bar['vw'])
+    bars['updated'].append(datum)
+    bars['index'].append(i)
+
+  return bars
+
+def get_last_close():
+   pass
+
+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)
+
+    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"])
+    return convert_daily_bars(bars[symbol])

v2realbot/utils/profitloss.py

@@ -0,0 +1,16 @@
+
+
+def calculate_relative_profit_loss(entry_price, exit_price):
+  """Calculates the relative profit/loss in percents.
+
+  Args:
+    entry_price: The entry price.
+    exit_price: The exit price.
+
+  Returns:
+    The relative profit/loss in percents.
+  """
+
+  relative_profit_loss = (exit_price - entry_price) / entry_price * 100
+  return relative_profit_loss
+

v2realbot/utils/utils.py

@@ -152,18 +152,19 @@ def is_pivot(source: list, leg_number: int, type: str = "A"):
     right_leg = source[-leg_number:]
     
     if type == "A":
-        if isrising(left_leg) and isfalling(right_leg):
+        if isrisingc(left_leg) and isfallingc(right_leg):
             return True
         else:
             return False
     elif type == "V":
-        if isfalling(left_leg) and isrising(right_leg):
+        if isfallingc(left_leg) and isrisingc(right_leg):
             return True
         else:
             return False
     else:
         print("Unknown type")
         return False
+    
 
 def crossed_up(threshold, list):
     """check if threshold has crossed up last thresholdue in list"""
@@ -324,6 +325,7 @@ def json_serial(obj):
     """
 
     type_map = {
+        pd.Timestamp: lambda obj: obj.timestamp(),
         datetime: lambda obj: obj.timestamp(),
         UUID: lambda obj: str(obj),
         Enum: lambda obj: str(obj),