Overview

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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this course, you will gain the skills to integrate Python into DevOps practices by mastering best practices for automation, API interaction, static typing, testing, and CI/CD pipelines. You’ll explore using Python to interact with APIs, automate DevOps tasks, and implement best practices for writing robust code. You'll also dive deep into testing using Pytest and configuring a full CI/CD pipeline to automate development workflows and streamline deployments. The course begins by introducing API interaction using the requests library, where you’ll learn how to send GET and POST requests, handle authentication, and manage HTTP errors. Then, you'll master static typing in Python, applying type hints to ensure cleaner and more maintainable code. This section also includes techniques for flexible typing with Python's type system and best practices for using generics and type hints in decorators and generators. You will then learn how to implement robust testing practices with Pytest, including writing assertions, handling test failures, mocking external dependencies, and creating reusable fixtures. The course also provides a comprehensive guide to building a CI/CD pipeline, showing how to automate testing, versioning, deployment, and more with tools like GitHub Actions, Pytest, and Semantic Release. This course is intended for intermediate Python developers looking to streamline their DevOps practices. Familiarity with Python basics and DevOps concepts is required. By the end of the course, you'll have the knowledge and hands-on experience to automate processes, ensure code quality, and integrate DevOps best practices into your Python projects. By the end of the course, you will be able to build robust Python applications, automate DevOps workflows, write efficient and maintainable code, and create end-to-end automated CI/CD pipelines.

Syllabus

API Interaction with the Requests Library

In this module, we will explore API interaction using Python's requests library. You will learn how to make GET and POST requests, handle authentication, interpret HTTP status codes, and implement best practices like retries and timeouts to ensure smooth API communication.

Writing Robust Code with Static Typing

In this module, we will dive into Python's static typing system, learning to apply type hints for better code clarity and error prevention. You will explore advanced typing concepts and configure your development environment for optimal type checking to write more robust and maintainable code.

Mastering Automated Testing with Pytest

In this module, we will master automated testing using the Pytest framework. You'll learn to write assertions, handle test failures, and implement features like fixtures and parametrization. We’ll also cover mocking techniques for simulating external dependencies and improving test flexibility.

Best Practices for Structuring Python Projects

In this module, we will focus on best practices for structuring Python projects. You will learn how to organize code using modules and packages, manage project configurations with pyproject.toml, and resolve common import issues, setting the foundation for scalable and maintainable projects.

Building a Full CI/CD Pipeline for Python Projects

In this module, we will guide you through building a full CI/CD pipeline for Python projects. You’ll learn how to automate the build, test, and deployment processes using GitHub Actions, Pytest, and Semantic Release, culminating in packaging and securely publishing your project to PyPI for easy distribution.