UnitaryIron/Jam-backend

AI Summary: Write unit tests using pytest for the `jam_to_js` function, covering basic math, variable declarations, and simple control flow (if, repeat) statements. The tests should be placed in a new `tests/test_transpiler.py` file.

AI Summary: Create a Dockerfile and optionally a docker-compose.yml file to containerize the Jam backend application, simplifying deployment and onboarding. The Dockerfile should use a Python 3.10+ base image, install dependencies from requirements.txt, and run the backend server (app.py).

AI Summary: Create a GitHub Actions workflow to automate testing (using pytest and optionally flake8/black) for the Jam programming language transpiler and interpreter project on every pull request, ensuring code quality and preventing regressions.

AI Summary: Create a new directory named `examples/` within the Jam-backend repository. Populate this directory with several example Jam programs demonstrating basic features like math operations, variable assignments, control flow (if/repeat statements), and functions. Include a README file within the `examples/` directory explaining how to run these Jam programs using the provided Jam backend.

AI Summary: Add comprehensive docstrings to all public functions within the `jam.py` and `app.py` files of a Jam-to-JavaScript transpiler and interpreter project. Docstrings should follow a standard style guide (like Google or NumPy) and clearly describe the function's purpose, parameters, and return values.

AI Summary: Improve the Jam interpreter's error handling to provide more informative error messages including error type, line number (if possible), and a descriptive explanation. This involves reviewing existing exception handling, adding try/except blocks with detailed messages, and standardizing error output. Bonus points for adding unit tests to verify the improved error messages.

AI Summary: Refactor the Jam interpreter's core logic (currently in `jam.py`) into a well-structured Python package, improving organization and maintainability. This involves creating a new package directory, moving the code, adding an `__init__.py`, and updating import statements in other parts of the project to reflect the new structure. The goal is to prepare the codebase for easier expansion and future development.

AI Summary: Add Python type hints to all functions within the `jam.py` file of a Jam-to-JavaScript transpiler and interpreter project. This involves reviewing each function, adding type annotations for parameters and return values using Python's `typing` module, and validating the changes with a type checker like `mypy`. The goal is to improve code readability, enhance IDE support, and facilitate early detection of type-related errors.