Cannot run locally my personnal datas

To help you run your personal forex data locally on QuantConnect, follow these steps:

1. Verify Data Format: Ensure your data is in a CSV format with headers like date, open, high, low, close, and volume.

2. Create a Custom Data Class: Define a custom data class by extending the PythonData class. This class will handle the parsing and loading of your data.

3. Implement GetSource and Reader Methods:

   • GetSource: Specify the data source. For local data, you can use a local file path.
   • Reader: Parse each line of your data file into a format that QuantConnect can understand.

   Here's a basic example:

   import datetime
   from QuantConnect.Data import SubscriptionDataSource, SubscriptionTransportMedium
   from QuantConnect.Python import PythonData
   from QuantConnect import BaseData, SubscriptionDataConfig
   
   class ForexData(PythonData):
       def get_source(self, config: SubscriptionDataConfig, date: datetime.datetime, is_live_mode: bool) -> SubscriptionDataSource:
           # Use local file path
           path = f"/path/to/your/data/{config.symbol}.csv"
           return SubscriptionDataSource(path, SubscriptionTransportMedium.LOCAL_FILE)
   
       def reader(self, config: SubscriptionDataConfig, line: str, date: datetime.datetime, is_live_mode: bool) -> BaseData:
           if not (line.strip() and line[0].isdigit()):
               return None
           data = line.split(',')
           forex_data = ForexData()
           forex_data.symbol = config.symbol
           try:
               forex_data.time = datetime.datetime.strptime(data[0], "%Y-%m-%d %H:%M:%S")
               forex_data.value = float(data[4])  # Close price
               forex_data["Open"] = float(data[1])
               forex_data["High"] = float(data[2])
               forex_data["Low"] = float(data[3])
               forex_data["Close"] = float(data[4])
           except ValueError:
               return None
           return forex_data
   
   class MyAlgorithm(QCAlgorithm):
       def initialize(self):
           self.set_start_date(2020, 1, 1)
           self.set_end_date(2020, 12, 31)
           self.set_cash(100000)
           self.add_data(ForexData, "EURUSD", Resolution.DAILY)
   

4. Add Custom Data to Algorithm: In your algorithm's Initialize method, use AddData to include your custom data class.

5. Check Data Path: Ensure the file path to your data is correct and accessible.

6. Debugging: Use logging to identify issues. Check for common errors like file not found or parsing errors.

7. Test with Sample Data: Start with a small sample to ensure everything is set up correctly.

By following these steps, you should be able to run your personal forex data locally on QuantConnect. If you encounter specific errors, let me know, and I can help troubleshoot further.

Sources: Custom Data - QuantConnect.com, CSV Format Example - QuantConnect.com, Key Concepts - QuantConnect.com, Custom Data - QuantConnect.com, Key Concepts - QuantConnect.com

Here is the code I use to test:


from AlgorithmImports import *

class HourlyForexStrategy(QCAlgorithm):
   def Initialize(self):
       self.SetStartDate(2022, 1, 1)
       self.SetEndDate(2023, 1, 1)
       self.SetCash(100000)

       # Ajouter les paires Forex EURUSD et AUDCAD en résolution horaire
       self.eurusd = self.AddForex("EURUSD", Resolution.Hour).Symbol
       self.audcad = self.AddForex("AUDCAD", Resolution.Hour).Symbol

       # Initialiser les indicateurs de moyennes mobiles
       self.sma_fast_eurusd = self.SMA(self.eurusd, 50, Resolution.Hour)
       self.sma_slow_eurusd = self.SMA(self.eurusd, 200, Resolution.Hour)
       
       self.sma_fast_audcad = self.SMA(self.audcad, 50, Resolution.Hour)
       self.sma_slow_audcad = self.SMA(self.audcad, 200, Resolution.Hour)

   def OnData(self, data):
       # EURUSD: Achat si la SMA rapide croise au-dessus de la SMA lente
       if self.sma_fast_eurusd.Current.Value > self.sma_slow_eurusd.Current.Value and not self.Portfolio[self.eurusd].Invested:
           self.SetHoldings(self.eurusd, 0.5)
       elif self.sma_fast_eurusd.Current.Value < self.sma_slow_eurusd.Current.Value and self.Portfolio[self.eurusd].Invested:
           self.Liquidate(self.eurusd)

       # AUDCAD: Achat si la SMA rapide croise au-dessus de la SMA lente
       if self.sma_fast_audcad.Current.Value > self.sma_slow_audcad.Current.Value and not self.Portfolio[self.audcad].Invested:
           self.SetHoldings(self.audcad, 0.5)
       elif self.sma_fast_audcad.Current.Value < self.sma_slow_audcad.Current.Value and self.Portfolio[self.audcad].Invested:
           self.Liquidate(self.audcad)



How can I update it to use my own personnal data files?

Hi Adrien

For custom-imported data, please follow here for instructions. I believe Mia's example is a valid one if you adapt and modify it for your case. Have you tried that?

Best
Louis