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A hands-on Python DevOps toolkit built for automation, cloud workflows, and CI/CD pipelines. From shell scripting to API integration, this repo demonstrates real-world use cases for platform engineers and full-stack developers.

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PYTHON FOR DEVOPS 🐍🛠️

Welcome to PYTHON FOR DEVOPS 💻 repository!

This comprehensive course is designed to equip you with essential Python skills tailored for DevOps practices. Whether you're a beginner or looking to enhance your automation skills, this repository provides structured learning materials with practical examples.

Follow along and level up your DevOps game! 🚀

📚 Repository Structure

python-for-devops/
├── Fundamental/           # Core Python concepts
├── Intermediate/          # Advanced topics and integrations
├── examples/              # Practical code examples and exercises
│   └── testing/          # Testing examples and sample code
├── .github/workflows/     # GitHub Actions for Jekyll deployment
├── README.md             # This file
├── PythonJourney.md      # Introduction and Python overview
└── .gitattributes        # Git configuration

🎯 Features

Fundamental Concepts

Intermediate Topics

Testing & Quality Assurance

Practical Examples

  • Email automation with SMTP
  • Web scraping and data extraction
  • File system operations and automation
  • Network device management
  • Database interactions
  • API consumption and data processing
  • System monitoring and maintenance scripts
  • Unit and integration testing examples
  • Test automation and CI/CD pipeline integration
  • Mocking and stubbing for external dependencies

📖 Course Contents

Python Basics 🔄

Exercise: Write a Python script showcasing the use of python datatypes, handling files, control flow loops, functions & modules.

Networking and Automation 🌐

Exercise: Develop a Python script to automate port scanning for a list of IP addresses.

Databases and Integration 🗃️

  • 📋 Database Basics - Understanding databases and relational models
  • 🐘 Connecting to PostgreSQL - Interacting with PostgreSQL databases using Python (Coming Soon)
  • 🔍 SQL Queries with Python - Executing SQL queries and managing data with Python (Coming Soon)
  • 🐍 ORM with SQLAlchemy - Exploring Object-Relational Mapping using SQLAlchemy (Coming Soon)
  • 📡 Integrating Python with Web Services - Interacting with web services using Python (Coming Soon)

Exercise: Build a Python script that interacts with a database to manage user information.

Testing and Quality Assurance 🧪

  • 🧪 Testing Fundamentals - Unit testing with unittest and pytest frameworks
  • 🔍 Advanced Testing - Integration testing, mocking, and API testing strategies
  • 🚀 CI/CD Testing - Automated testing in CI/CD pipelines and GitHub Actions
  • 📊 Test Coverage and Reporting - Measuring code coverage and generating test reports (Coming Soon)
  • 🐳 Docker Testing Strategies - Testing containerized applications and services (Coming Soon)

Exercise: Develop a comprehensive test suite for a Python automation script with unit tests, integration tests, and CI/CD integration.

DevOps Tools with Python 🛠️

  • 🐬 Introduction to Docker - Getting started with Docker and containerization (Coming Soon)
  • 🚀 Docker Automation with Python - Automating Docker tasks using Python (Coming Soon)
  • ⚙️ Ansible and Python - Using Python with Ansible for configuration management (Coming Soon)
  • 🚢 Kubernetes and Python - Interacting with Kubernetes clusters using Python (Coming Soon)
  • 🛡️ CI/CD Automation - Automating CI/CD pipelines with Python (Coming Soon)

Exercise: Create a Python script to automate the deployment of a multi-container application.

Monitoring and Scaling 📊

  • 📊 Monitoring with Prometheus - Introduction to Prometheus for system monitoring (Coming Soon)
  • 📜 Log Management with ELK Stack - Centralized log management with Elasticsearch, Logstash, and Kibana (Coming Soon)
  • ⚙️ Infrastructure Scaling - Strategies for scaling infrastructure and applications (Coming Soon)
  • ☁️ Cloud Services Integration - Integrating Python with cloud services for automation (Coming Soon)
  • 🚦 CI/CD Best Practices - Exploring best practices for CI/CD pipelines (Coming Soon)

Exercise: Configure Prometheus to monitor a sample application and visualize the data in Grafana.

DevOps Culture and Case Studies 🏢

  • 👥 DevOps Culture and Collaboration - Emphasizing collaboration, communication, and shared responsibility within DevOps teams (Coming Soon)
  • 🔄 Continuous Improvement - Implementing continuous improvement practices in DevOps (Coming Soon)
  • 🌐 Case Studies - Examining real-world DevOps success stories and lessons learned (Coming Soon)
  • 🚀 Final Project - Design and implement a complete DevOps pipeline for a sample application using Python (Coming Soon)

Final Exercise: Present and demonstrate your final project, explaining how each component works together in the DevOps pipeline.

🚀 How to Use This Repository

Getting Started

  1. Clone the repository:

    git clone https://github.com/karadHub/python-for-devops.git
    cd python-for-devops
  2. Start with the basics: Begin with the Introduction to Python to understand Python's role in DevOps.

  3. Follow the structured path:

  4. Progress to intermediate topics:

Prerequisites

  • Basic understanding of programming concepts
  • Python 3.x installed on your system
  • Text editor or IDE (VS Code, PyCharm, etc.)
  • Internet connection for API examples and package installations

Required Python Libraries

Install the following packages as you progress through the course:

# Core libraries (install as needed)
pip install requests          # For API interactions
pip install beautifulsoup4    # For web scraping
pip install schedule         # For task scheduling
pip install psutil           # For system monitoring
pip install netmiko          # For network device management
pip install scapy            # For packet manipulation
pip install twisted          # For networking framework
pip install selenium         # For web automation
pip install PyPDF2           # For PDF operations
pip install pandas           # For data analysis
pip install matplotlib       # For visualizations

# Testing libraries
pip install pytest           # Modern testing framework
pip install pytest-cov       # Coverage plugin for pytest
pip install pytest-mock      # Mocking plugin for pytest
pip install tox              # Testing across multiple Python versions
pip install coverage         # Code coverage measurement
pip install unittest-xml-reporting  # XML test reports

Learning Path

  1. Week 1-2: Complete all Fundamental topics
  2. Week 3-4: Work through Intermediate file handling, JSON, and APIs
  3. Week 5-6: Focus on automation and networking topics
  4. Week 7-8: Learn testing fundamentals and advanced testing techniques
  5. Week 9-10: Practice with real-world scenarios, projects, and CI/CD integration

🛠️ Examples and Practical Applications

Each module includes practical examples such as:

  • Automation Scripts: Email sending, file management, system tasks
  • Network Tools: Port scanners, device management, packet analysis
  • Data Processing: JSON parsing, API consumption, file operations
  • System Integration: Database connections, web scraping, monitoring
  • Testing Examples: Unit tests, integration tests, mocking, CI/CD pipelines

🤝 Contributing

Contributions are welcome! Please feel free to:

  • Report bugs or issues
  • Suggest new topics or improvements
  • Submit pull requests with enhancements
  • Share your own DevOps Python scripts and examples

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

📞 Support

If you have questions or need help:

  • Open an issue in this repository
  • Check existing documentation and examples
  • Refer to the official Python documentation

Note: This repository is continuously updated with new content and examples. Some advanced topics are marked as "Coming Soon" and will be added in future updates.

Happy coding! 🚀🐍

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A hands-on Python DevOps toolkit built for automation, cloud workflows, and CI/CD pipelines. From shell scripting to API integration, this repo demonstrates real-world use cases for platform engineers and full-stack developers.

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