Ramil Individual Project 1

CI/CD Badges:

• Test Status:
• Code Formatting:
• Linting:

Project Overview

This project demonstrates the setup of continuous integration for a Python data science project using Github CI/CD pipelines. It includes a Jupyter Notebook performing descriptive statistics with Pandas, test scripts and jupyter notebook, a shared library, and a Makefile to automate tasks such as formatting, linting, and testing. Github Actions run these tasks, with badges reflecting their status.

YouTube video

Link to the YouTube video

1. Jupyter Notebook

• The notebook performs descriptive statistics using Pandas.
• It is tested using the nbval plugin for pytest to validate the correctness of the results.

2. Python Scripts

• test_script.py: Contains tests for a standalone script.
• test_lib.py: Tests the shared code in lib.py.
• lib.py: Shared utility code used in both the notebook and scripts.
• main.py: More advanced code built on the top of lib.py

3. Makefile

The Makefile includes the following commands:

• Run all tests: Executes tests on the notebook, script, and library.
• Code formatting: Formats the Python code using black.
• Linting: Lints the code using Ruff.
• Install dependencies: Installs all required packages listed in requirements.txt.

4. requirements.txt

A pinned list of dependencies for the project to ensure consistent environments across systems.

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Github Actions

Tasks from the Makefile are automated using Github CI/CD pipelines. The github worflows have following jobs that:

• Run tests on the Jupyter Notebook, scripts, and library.
• Format the code using black.
• Lint the code using Ruff.
• Install the dependencies via pip.

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Setup and Usage Instructions

1. Clone the repository:

git https://github.com/nogibjj/Ramil-Individual-Project-1.git
cd Ramil-Individual-Project-1

2. Install the dependencies:

make install

3. Run the Makefile commands:

• Run all tests:

  make test_code

• Format code with black:

  make format

• Lint code with Ruff:

  make lint