### Install PyLingual from Source

Source: https://github.com/syssec-utd/pylingual/blob/main/README.md

Install PyLingual locally using Poetry. Ensure you have Python 3.12 or later and Poetry version 2.0 or higher.

```sh
git clone https://github.com/syssec-utd/pylingual
cd pylingual
python -m venv venv
source venv/bin/activate
pip install poetry>=2.0
poetry lock
poetry install
```

--------------------------------

### Generate Dataset

Source: https://github.com/syssec-utd/pylingual/blob/main/dev_scripts/README.md

Use this command to create a dataset for PyLingual. Ensure you have a JSON configuration file and the dataset directory is structured correctly.

```bash
python prepare_dataset.py <path to JSON>
```

--------------------------------

### PyLingual Command-Line Usage

Source: https://github.com/syssec-utd/pylingual/blob/main/README.md

The main command-line interface for PyLingual. Use options to specify output directory, configuration file, Python version, and other parameters.

```sh
Usage: pylingual [OPTIONS] [FILES]...

  End to end pipeline to decompile Python bytecode into source code.

Options:
  -o, --out-dir PATH      The directory to export results to.
  -c, --config-file PATH  Config file for model information.
  -v, --version VERSION   Python version of the .pyc, default is auto
                          detection.
  -k, --top-k INT         Maximum number of additional segmentations to
                          consider.
  -q, --quiet             Suppress console output.
  --trust-lnotab          Use the lnotab for segmentation instead of the
                          segmentation model.
  --init-pyenv            Install pyenv before decompiling.
  -h, --help              Show this message and exit.
```

--------------------------------

### Train Segmentation Model

Source: https://github.com/syssec-utd/pylingual/blob/main/dev_scripts/README.md

Train the segmentation model using a specified JSON configuration file. This model is crucial for dividing bytecode instructions.

```bash
python train_models.py --segmentation <path to JSON>
```

--------------------------------

### Train Statement Model

Source: https://github.com/syssec-utd/pylingual/blob/main/dev_scripts/README.md

Train the statement model with a provided JSON configuration. This model is responsible for transforming instruction groups into source code.

```bash
python train_models.py --statement <path to JSON>
```

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