Datasets

Follow these steps to test if your demonstration algorithm will run in production with the processed data:

1. Open the Lean.DataSource.<vendorNameDatasetName> / QuantConnect.DataSource.csproj file in Visual Studio.
2. In the top menu bar of Visual Studio, click Build > Build Solution.

The Output panel displays the build status of the project.

3. Close Visual Studio.
4. If you have a local copy of LEAN, pull the latest changes.

$ git pull upstream master

5. If you don't have a local copy of LEAN, fork the LEAN repository and then clone it.

$ git clone https://github.com/<username>/Lean.git

6. Copy the contents of the Lean.DataSource.<vendorNameDatasetName> / output directory and paste them into the Lean / Data directory.
7. Open the Lean / QuantConnect.Lean.sln file in Visual Studio.
8. In the Solution Explorer panel of Visual Studio, right-click QuantConnect.Algorithm.CSharp and then click Add > Existing Item….
9. In the Add Existing Item window, click the Lean.DataSource.<vendorNameDatasetName> / <vendorNameDatasetName>Algorithm.cs file and then click Add.
10. In the Solution Explorer panel, right-click QuantConnect.Algorithm.CSharp and then click Add > Project Reference....
11. In the Reference Manager window, click Browse….
12. In the Select the files to reference… window, click the Lean.DataSource.<vendorNameDatasetName> / bin / Debug / net9.0 / QuantConnect.DataSource.<vendorNameDatasetName>.dll file and then click Add.

The Reference Manager window displays the QuantConnect.DataSource.<vendorNameDatasetName>.dll file with the check box beside it enabled.

13. Click OK.

The Solution Explorer panel adds the QuantConnect.DataSource.<vendorNameDatasetName>.dll file under QuantConnect.Algorithm.CSharp > Dependencies > Assemblies.

14. In the Lean / Algorithm.CSharp / <vendorNameDatasetName>Algorithm.cs file, write an algorithm that uses your new dataset.
15. In the Solution Explorer panel, click QuantConnect.Lean.Launcher > config.json.
16. In the config.json file, set the following keys:

"algorithm-type-name": "<vendorNameDatasetName>Algorithm",
"algorithm-location": "QuantConnect.Algorithm.CSharp.dll",

17. Press Ctrl+F5 to backtest your demonstration algorithm.
18. Copy the Lean.DataSource.<vendorNameDatasetName> / <vendorNameDatasetName>Algorithm.py file and paste it in Lean / Algorithm.Python directory.
19. In the Lean / Algorithm.Python / <vendorNameDatasetName>Algorithm.py file, write an algorithm that uses your new dataset.
20. In the Solution Explorer panel, click QuantConnect.Lean.Launcher > config.json.
21. In the config.json file, set the following keys:

"algorithm-type-name": "<vendorNameDatasetName>Algorithm",
"algorithm-location": "../../../Algorithm.Python/<vendorNameDatasetName>Algorithm.py",

22. Press Ctrl+F5 to backtest your demonstration algorithm.

Important: Your backtests must run without error. If your backtests produce errors, correct them and then run the backtest again.

23. Copy the Lean / Algorithm.CSharp / <vendorNameDatasetName>Algorithm.cs file to Lean.DataSource.<vendorNameDatasetName> / <vendorNameDatasetName>Algorithm.cs.
24. Copy the Lean / Algorithm.Python / <vendorNameDatasetName>Algorithm.py file to Lean.DataSource.<vendorNameDatasetName> / <vendorNameDatasetName>Algorithm.py.

You must run your demonstration algorithms without error before you set up unit tests.

In the Lean.DataSource.<vendorNameDatasetName> / <vendorNameDatasetName>Tests.cs file, define the CreateNewInstance method to return an instance of your DataSource class and then execute the following commands to run the unit tests:

$ dotnet build tests/Tests.csproj
$ dotnet test tests/bin/Debug/net9.0/Tests.dll