Update projects/forex_algo_trading.md
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@@ -55,55 +55,64 @@ swing_trading_project/
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```python
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import os
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import pandas as pd
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from oandapyV20 import API
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from oandapyV20 import API # Import the Oanda API client
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import oandapyV20.endpoints.instruments as instruments
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# Configuration
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# Set your Oanda API credentials and configuration for data fetching
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ACCOUNT_ID = 'your_account_id_here'
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ACCESS_TOKEN = 'your_access_token_here'
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INSTRUMENTS = ['EUR_USD', 'USD_JPY', 'GBP_USD', 'AUD_USD', 'USD_CAD'] # Extendable to more pairs
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GRANULARITY = 'H4' # Can be parameterized as needed
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DATA_DIR = 'data'
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# List of currency pairs to fetch. Add or remove pairs as needed.
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CURRENCY_PAIRS = ['EUR_USD', 'USD_JPY', 'GBP_USD', 'AUD_USD', 'USD_CAD']
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TIME_FRAME = 'H4' # 4-hour candles, change as per your analysis needs
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DATA_DIRECTORY = 'data' # Directory where fetched data will be saved
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def fetch_and_save_data(account_id, access_token, instruments, granularity, data_dir):
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"""Fetch historical forex data for specified instruments and save to CSV."""
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client = API(access_token=access_token)
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# Ensure the data directory exists, create it if it doesn't
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if not os.path.exists(DATA_DIRECTORY):
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os.makedirs(DATA_DIRECTORY)
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def fetch_and_save_forex_data(account_id, access_token, currency_pairs, time_frame, data_dir):
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"""Fetch historical forex data for specified currency pairs and save it to CSV files."""
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# Initialize the Oanda API client with your access token
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api_client = API(access_token=access_token)
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if not os.path.exists(data_dir):
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os.makedirs(data_dir)
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for instrument in instruments:
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params = {
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"granularity": granularity,
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"count": 5000 # Adjust based on needs
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}
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for pair in currency_pairs:
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# Define the parameters for the data request: time frame and number of data points
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request_params = {"granularity": time_frame, "count": 5000}
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data_request = instruments.InstrumentsCandles(instrument=instrument, params=params)
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data = client.request(data_request)
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candles = data.get('candles', [])
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# Prepare the data request for fetching candle data for the current currency pair
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data_request = instruments.InstrumentsCandles(instrument=pair, params=request_params)
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# Fetch the data
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response = api_client.request(data_request)
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# Extract the candle data from the response
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candle_data = response.get('candles', [])
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if candles:
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df = pd.DataFrame([{
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# If data was fetched, proceed to save it
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if candle_data:
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# Convert the candle data into a pandas DataFrame
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forex_data_df = pd.DataFrame([{
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'Time': 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': candle['volume']
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} for candle in candles])
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} for candle in candle_data])
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# Save to CSV
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output_filename = f"{instrument.lower()}_data.csv"
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df.to_csv(os.path.join(data_dir, output_filename), index=False)
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print(f"Data saved for {instrument} to {output_filename}")
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# Construct the filename for the CSV file
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csv_filename = f"{pair.lower()}_data.csv"
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# Save the DataFrame to a CSV file in the specified data directory
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forex_data_df.to_csv(os.path.join(data_dir, csv_filename), index=False)
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print(f"Data for {pair} saved to {csv_filename}")
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def main():
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"""Main function to orchestrate data fetching and saving."""
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print("Fetching data for instruments...")
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fetch_and_save_data(ACCOUNT_ID, ACCESS_TOKEN, INSTRUMENTS, GRANULARITY, DATA_DIR)
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print("Data fetching and saving complete.")
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"""Orchestrates the data fetching and saving process."""
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print("Starting data fetching process...")
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# Call the function to fetch and save data for the configured currency pairs
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fetch_and_save_forex_data(ACCOUNT_ID, ACCESS_TOKEN, CURRENCY_PAIRS, TIME_FRAME, DATA_DIRECTORY)
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print("Data fetching process completed.")
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if __name__ == '__main__':
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# Execute the script
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main()
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```
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