68 lines
2.6 KiB
Python
68 lines
2.6 KiB
Python
from alpaca.data.historical import CryptoHistoricalDataClient, StockHistoricalDataClient
|
|
from alpaca.data.requests import CryptoLatestTradeRequest, StockLatestTradeRequest, StockLatestBarRequest, StockTradesRequest, StockBarsRequest
|
|
from alpaca.data.enums import DataFeed
|
|
from config import API_KEY, SECRET_KEY, MAX_BATCH_SIZE
|
|
import datetime
|
|
import time
|
|
from alpaca.data import Quote, Trade, Snapshot, Bar
|
|
from alpaca.data.models import BarSet, QuoteSet, TradeSet
|
|
from alpaca.data.timeframe import TimeFrame
|
|
# import mplfinance as mpf
|
|
import pandas as pd
|
|
from rich import print
|
|
from v2realbot.utils.utils import zoneNY
|
|
from v2realbot.config import ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY
|
|
from alpaca.trading.requests import GetCalendarRequest
|
|
from alpaca.trading.client import TradingClient
|
|
parametry = {}
|
|
|
|
# no keys required
|
|
#client = CryptoHistoricalDataClient()
|
|
client = StockHistoricalDataClient(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 previous days bar
|
|
|
|
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
|
|
|
|
bars: BarSet = client.get_stock_bars(bar_request)
|
|
#bars = bars.drop(['symbol'])
|
|
|
|
#print(bars.df.close)
|
|
#bars = bars.tz_convert('America/New_York')
|
|
#print(len(bars))
|
|
print(bars)
|
|
#print(bars.data["BAC"][0])
|
|
#print(bars.df.columns)
|
|
#Index(['open', 'high', 'low', 'close', 'volume', 'trade_count', 'vwap'], dtype='object')
|
|
# bars.df.set_index('timestamp', inplace=True)
|
|
|
|
# mpf.plot(bars.df, # the dataframe containing the OHLC (Open, High, Low and Close) data
|
|
# type='candle', # use candlesticks
|
|
# volume=True, # also show the volume
|
|
# mav=(3,6,9), # use three different moving averages
|
|
# figratio=(3,1), # set the ratio of the figure
|
|
# style='yahoo', # choose the yahoo style
|
|
# title='Prvni chart');
|
|
|
|
# #vrací se list od dict
|
|
# print(bars["BAC"])
|
|
|
|
# # k nemu muzeme pristupovat s
|
|
# dict = bars["BAC"]
|
|
# print(type(dict))
|
|
# print(dict[2].timestamp)
|
|
|
|
# print(dict[2].close)
|
|
|
|
# print(dict[].close)
|
|
|
|
|