Example for creating a simple CI/CD pipeline for a Python Project using GitHub Actions.

⚙️ A DevOps project demonstrating a complete CI/CD pipeline for backend microservices. The pipeline automates testing, building, and deployment of Python and Java microservices using GitHub Actions and Jenkins, with Docker and Kubernetes for containerized deployment. Prometheus and Grafana provide monitoring and observability for reliability.

Project showing a CI CD pipeline for Dataflow Python with Flex Template and Cloud Build

This is an example GitLab CI/CD pipeline configuration file (gitlab-ci.yml) for a Python project.

A ready-to-use CI/CD Pipeline for your Python projects

The reference implementation of CI/CD pipeline for Python/Django based projects

Creating a simple CI/CD Pipeline using GitHub Actions for a Python Project.

End-to-end MLOps project for sentiment analysis on YouTube comments using Python, FastAPI, Docker, and CI/CD pipelines.

In this project, I implemented a Machine Learning Microservice API with CI/CD using Python, GitHub Actions, Azure Pipelines and Terraform for infrastructure provisioning.

🚀 Learn CI/CD the easy way! A beginner-friendly GitHub Actions pipeline that automatically runs a Python script on every push. Perfect for DevOps portfolio projects!

This project offers a complete MLOps workflow for predicting rain in Australia. It uses Python, Flask, and Scikit-learn for model development and provides a web interface for predictions. The repository includes CI/CD pipelines and containerization with Docker.

This project is a full-featured Accounting Management Application developed using the MERN stack (MongoDB, Express.js, React 18, Node.js), with integrated AI modules (Python + XGBoost) for fraud detection and predictive analytics. It also includes CI/CD pipelines with Docker and GitHub Actions.

This repository contains the source code for a simple web application built with Python and Flask. The primary purpose of this project is to serve as a practical, hands-on demonstration of a complete, end-to-end Continuous Integration and Continuous Deployment (CI/CD) pipeline built with Jenkins, Docker, and AWS.

In this project, we have created a CI/CD Pipeline for the Python Flask application along with the Pytest functionality

python demo app was deployed using GitLab cicd pipelines. This was uploaded here to make it publicly accessible.

Creating CI/CD-pipeline for simple python project using Github-Actions Ddemo-1

A simple Python Flask application used as the target for a full CI/CD pipeline project."

This project uses GitHub actions to automate the complete CI/CD software pipeline for Python code.

A repository showcasing multi-stage Docker builds for optimizing CI/CD pipelines. Includes examples for Node.js, Python, and Java projects with a focus on reducing image size and improving build efficiency.

# Step-by-Step Guide for CI/CD Pipeline Demo ## Project: Calculator Microservice (Simple Demo) **Tech Stack**: Python (Flask) **Pipeline Stages**: 1. Build 2. Test 3. Containerize 4. Push Docker Image 5. Deploy using Kubernetes 6. Configure with Ansible 7. Monitor with Prometheus

Hello Trading is a Python-based trading simulation project that demonstrates basic trading strategies. It includes a Dockerized environment for easy deployment and a CI/CD pipeline for automated testing and builds. Perfect for learning and experimenting with trading algorithms!

This project demonstrates a two-tier application architecture by deploying a Flask-based web application connected to a MySQL database, using Docker for containerization and Jenkins for CI/CD pipeline automation. Technologies Used :Python + Flask, MySQL, Docker, Docker Compose , Jenkins ,Git.

The Astronomy Shop project is a microservices-based e-commerce site using GoLang, Python, Java, and more. A GitOps CI/CD pipeline is being designed with GitHub Actions/Jenkins, Docker, LKE(Linode), SonarQube, Helm, and Istio for secure, reliable deployment.

This project automates a CI/CD pipeline for a simple Python Flask application using GitHub Actions and Docker, with deployment to AWS Elastic Beanstalk. The pipeline builds a Docker image, runs unit tests with pytest, and deploys the app to AWS, showcasing DevOps practices like automation, containerization, and cloud infrastructure management.

This project showcases the deployment of a Python Flask-based microservice on AWS ECS Fargate using Terraform for infrastructure automation. Leveraging Docker for containerization and automated CI/CD pipelines, it delivers a secure, scalable, and highly available cloud architecture aligned with Well-Architected Framework principles.

This project serves as a comprehensive example for setting up a Continuous Integration and Continuous Deployment (CI/CD) pipeline for a Python application using GitHub Actions. It includes a simple source code structure, unit tests, and a pre-configured workflow to automate linting and testing.

This project involves the creation and configuration of a Continuous Integration and Continuous Deployment (CI/CD) pipeline for a Python web application built with Flask. The objectives are to automate the testing and deployment processes using GitHub Actions and deploy to AWS Elastic Beanstalk.

This project demonstrates a full CI/CD pipeline for a simple Python FastAPI application using Jenkins, Docker, and Kubernetes (Minikube or Kind). It's built to help you understand and simulate the real-world flow of building, testing, and deploying applications in a containerized and orchestrated environment.

A Python-based prime number checker that efficiently determines whether a given number is prime using optimized algorithms. The project features comprehensive test coverage, automated CI/CD pipeline with GitLab, and code quality analysis through SonarQube, making it a robust and maintainable solution for prime number validation.

This project demonstrates Dockerizing a Django app with PostgreSQL using Docker, Nginx, and Gunicorn. Its structured setup includes Django app, Nginx config, Dockerfiles, and env files. The Jenkinsfile establishes a CI/CD pipeline for flexible branch-based builds. Explore efficient Python and Django app management with Docker containers.