This repository is dedicated to a CI/CD challenge in analytical architecture, focusing on building a robust and automated data ingestion pipeline. The goal is to develop a data ingestion platform in a development environment and establish a deployment process to move pipelines to production efficiently.
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Automated Data Pipeline Deployment: Set up CI/CD workflows to deploy ingestion pipelines.
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Reliable Data Processing: Ensure clean and structured data flows into analytical environments.
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Unit Testing with Pytest: Implement automated tests to validate pipeline transformations.
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Programming Language: Python ๐
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Testing Framework: Pytest
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CI/CD Tools: GitHub Actions
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Containerization: Docker
- Clone the Repository:
git clone https://github.com/yourusername/cicd-data-pipeline.git
cd cicd-data-pipeline
- Set Up Virtual Environment & Dependencies:
python -m venv venv
source venv/bin/activate # Windows: venv\Scripts\activate
pip install -r requirements.txt
- Running Unit Tests:
Run tests to validate transformations and pipeline integrity:
pytest tests/
- Push changes to trigger the CI/CD workflow and deploy the pipeline:
The workflow will try to deploy the new docker image in render.
git add .
git commit -m "Deploying ingestion pipeline"
git push origin main
- Don't stray from the path to the dark side:
We welcome contributions! Follow these steps:
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Fork the repository.
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Create a branch (git checkout -b feature-branch).
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Implement changes and commit with meaningful messages (git commit -m 'Feature update').
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Push your branch (git push origin feature-branch).
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Open a pull request for review.
If you have any questions or issues, feel free to contact:
๐ง Email: davicc@outlook.com.br
- Darth Davi โ๏ธ๐ก
๐ฉโ๐ป Mentorโs GitHub: https://github.com/arteweyl
Through victory, my chains are broken.
The Force shall free me.