newellp88
58 lines
1.9 KiB
Python
58 lines
1.9 KiB
Python
# price history or stream functions
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from .config import token, accountID, env
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from oandapyV20 import API
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from oandapyV20.endpoints.instruments import InstrumentsCandles
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from oandapyV20.endpoints.pricing import PricingStream
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import pandas as pd
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import time
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api = API(token)
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# returns the last 500 OHLCV candles for an instrument
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# maximum count is 500
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# window: M1, M5, M15, H, H4, D, etc.
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def history(instrument, window, collection=False):
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instrument = instrument
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data = list()
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client = API(token)
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params = {"count": 500, "granularity": window}
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r = InstrumentsCandles(instrument, params)
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client.request(r)
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resp = r.response
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for candle in resp.get('candles'):
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dt = candle['time']
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Open = candle['mid']['o']
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High = candle['mid']['h']
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Low = candle['mid']['l']
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Close = candle['mid']['c']
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Volume = candle['volume']
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update = [dt, Open, High, Low, Close, Volume]
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data.append(update)
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df = pd.DataFrame(data, columns=['dt','Open','High','Low','Close','Volume'])
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# collect data, useful for research and weekends/holidays when the market isn't open
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if collection == True:
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title = 'data/%s_%s_history.csv' % (instrument, window)
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df.to_csv(title)
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return df
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# creates a pricing stream,
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def stream(instrument, window):
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request_params = {"timeout":100}
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params = {"instruments":instrument, "granularity":window}
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api = API(access_token=token,environment=env, request_params=request_params)
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r = PricingStream(accountID=accountID, params=params)
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while True:
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try:
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api.request(r)
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for R in r.response:
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time = R['time']
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ask = R['asks'][0]['price']
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bid = R['bids'][0]['price']
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return time, ask, bid
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except Exception as e:
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print(e)
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continue
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