Beginner Tutorial

Preparation

1. Install dependencies and initial the package

make install

If you have multi-version python, use the command like

make install ENVPIP=pip3.9

to specify your pip.

Also, you can use the following command:

pip install -e . --config-settings editable_mode=compat

(Optional)

If you want to include the spider deps, use the following command:

pip install -e .[spider] --config-settings editable_mode=compat

2. Run the demo script to see whether everything has been prepared

cd scripts/beginner
python beginner.py

If you see *** Spark *** in the terminal, then everything goes well.

Then, run the notebook eda.ipynb in scripts/EDA

NOTICE: Download the data before you run the scripts:

data/
├── test_X.xlsx
├── test_y.xlsx
└── train.xlsx

3. The following parts are optional

• Run tests

pip install -e .[test] --config-settings editable_mode=compat
pytest

• Use command line tools to see the feature importance of model

# After you have trained the lgb model
tsl lgb imp scripts/lgb_model/lgb.dill

Troubleshooter

1. For M1/M2/M3 Mac Users: If you encounter issues with installing LightGBM, create a conda virtual environment, and install it using conda:

   conda install -c conda-forge lightgbm

2. File Not Found Error: If you see an error like "No such file or directory: '../../data/train.xlsx'" after placing the files in the data directory, ensure that you are running the script from its directory (e.g., .../spark_learning/scripts/lgb_model) rather than the project root (e.g., .../spark_learning). Note that VSCode's default behavior is to use the project directory, so run the script from the command line instead.