mirror of
https://github.com/Arianhgh/fx-quant-research.git
synced 2026-08-08 08:27:45 +00:00
Arian Haghparast
114 lines
3.8 KiB
Python
114 lines
3.8 KiB
Python
"""OANDA v20 historical candle downloader.
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The access token is read from configuration (the ``OANDA_ACCESS_TOKEN``
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environment variable) rather than being hard-coded.
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"""
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import time
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from datetime import datetime, timedelta
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import pandas as pd
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import oandapyV20
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import oandapyV20.endpoints.instruments as instruments
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from oandapyV20.exceptions import V20Error
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from tradingbot.config import OANDA_ACCESS_TOKEN
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class OandaDataConnector:
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def __init__(self, access_token):
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self.client = oandapyV20.API(access_token=access_token)
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self.last_request_time = 0
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self.request_limit_delay = 0.01 # 100 requests per second max
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def _respect_rate_limit(self):
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current_time = time.time()
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time_passed = current_time - self.last_request_time
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if time_passed < self.request_limit_delay:
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time.sleep(self.request_limit_delay - time_passed)
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self.last_request_time = time.time()
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def get_historical_data_chunked(self, instrument, timeframe, start_date, end_date=None, chunk_days=5):
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if end_date is None:
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end_date = datetime.now()
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all_candles = []
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current_date = start_date
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while current_date < end_date:
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self._respect_rate_limit()
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chunk_end = min(current_date + timedelta(days=chunk_days), end_date)
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params = {
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"from": current_date.strftime('%Y-%m-%dT%H:%M:%SZ'),
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"to": chunk_end.strftime('%Y-%m-%dT%H:%M:%SZ'),
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"granularity": timeframe,
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"price": "MBA" # Mid, Bid, Ask prices
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}
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try:
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r = instruments.InstrumentsCandles(instrument=instrument, params=params)
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self.client.request(r)
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for candle in r.response['candles']:
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if candle['complete']:
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all_candles.append({
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'timestamp': candle['time'],
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'open': float(candle['mid']['o']),
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'high': float(candle['mid']['h']),
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'low': float(candle['mid']['l']),
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'close': float(candle['mid']['c']),
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'volume': float(candle['volume'])
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})
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print(f"Downloaded data from {current_date.date()} to {chunk_end.date()}")
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current_date = chunk_end
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except V20Error as e:
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print(f"Error fetching data: {e}")
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return None
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df = pd.DataFrame(all_candles)
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if not df.empty:
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df['timestamp'] = pd.to_datetime(df['timestamp'])
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df.set_index('timestamp', inplace=True)
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df = df.sort_index()
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return df
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def download(instrument="EUR_USD", timeframe="M5", lookback_days=1825,
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access_token=None, out_dir="."):
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"""Download ``lookback_days`` of candles and save them to a CSV.
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Returns the downloaded DataFrame (or ``None`` on failure).
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"""
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token = access_token or OANDA_ACCESS_TOKEN
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if not token:
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raise ValueError(
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"No OANDA access token. Set the OANDA_ACCESS_TOKEN environment "
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"variable or pass access_token=..."
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)
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connector = OandaDataConnector(token)
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start_date = datetime.now() - timedelta(days=lookback_days)
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data = connector.get_historical_data_chunked(
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instrument=instrument,
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timeframe=timeframe,
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start_date=start_date,
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)
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if data is not None:
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name = instrument.replace("_", "")
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filename = (
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f"{out_dir}/{name}_{timeframe}_"
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f"{start_date.strftime('%Y%m%d')}_to_{datetime.now().strftime('%Y%m%d')}.csv"
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)
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data.to_csv(filename)
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print(f"Data saved to {filename}")
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print(f"Total candles downloaded: {len(data)}")
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return data
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if __name__ == "__main__":
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download()
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