Learn Pytest Framework: Python Automation Testing, Unit Testing, API Testing & Test Automation with GitHub Actions CI/CD
👉 Enroll Now: https://www.udemy.com/course/pytest-course-python ✨
✓ Learn Pytest framework for Python automation testing, from basic software testing to advanced level
✓ Write unit, integration, and API tests in Python - from 0% to 100% test automation coverage
✓ Implement CI/CD pipelines using GitHub Actions to run automated tests on every code change
✓ Test-Driven Development (TDD), Fixtures, Mocking, Monkeypatch, Parameterize, FastAPI testing, API testing
✓ Debug efficiently using Python software testing best practices with real-world examples
Cas Teeuwen (Data Engineer at Xomnia) - 5/5 rating feedback
It was very well made and I learned a lot!
Tomer Kotek (R&D Team Lead at NextSilicon) - 5/5 rating feedback
Even after many years of using pytest, I learned many new ways to use pytest better. Very helpful overall, and it took my understanding to the next level. I am going to recommend that all the engineers in my team take this course.
Dino Bavaro (Python Backend Engineer) - 5/5 rating feedback
Excellent Real-world Code examples
Bilal Samee (Python & Embedded Systems Engineer) - 5/5 rating feedback
Great course on pytest. Straight to the point. Touches on all important points. Starts by showing a scenario, then leads the student into why a test concept (e.g. fixture, mock) is needed and what it solves. Gives real life examples and problems the student can hack at. Includes a review at the end of every module, bringing together everything the student has learnt in that module.
Armand Borel (Python Data & Automation Engineer) - 5/5 rating feedback
This course has been great. It explains pytest and testing very clearly, starting from the basics and quickly moving into real world usage. The real code examples are very helpful, and mocking is covered in clear detail, which makes complex topics much easier to understand.
👉 Enroll Now: https://www.udemy.com/course/pytest-course-python ✨
- Introduction
- Course Roadmap
- Real World Example: New Scikit Feature
- Real World Example: Testing New Feature
- Why Testing: From Theory to Practice
- Virtual Environments & pytest Installation
- Pytest: Run & Debug
- Test Discovery
- Test Execution Status
- Hands-On Practice
- TDD and BDD: Testing Approaches
- Module Summary
- Module Introduction
- Writing Test Classes
- Descriptive Test Failure
- Asserting Exceptions
- Given-When-Then Structure
- Selective Tests Running
- Challenge: more-itertools
- Challenge: Solution
- Module Summary
- Module Introduction
- What is @pytest.fixture
- Setup and Teardown
- Fixture Scope
- Reusable Fixtures via conftest.py
- Temporary Directories & Output Capture
- Mocking with monkeypatch
- Fixtures with autouse
- Testing Logs
- Challenge: Finance Tracker
- Challenge: Solution
- Module Summary
- Module Introduction
- Problem: Almost Identical Tests
- Parametrizing Tests
- Parametrizing Fixtures
- Dynamic Parametrization
- Factories as Fixtures
- Finance Tracker: Parametrized Tests
- Module Summary
- Module Introduction
- Advanced Mocking
- Mocking with mocker
- Mocking Classes
- Too Much Mocking vs Too Little
- Patching Target
- Patching Decorators
- Markers
- Marker-Aware Fixture
- Configuration Files
- Coverage: Part 1
- Coverage: Part 2
- Hypothesis and Faker
- Testing Levels
- Testing Levels in Action
- Test File Name Collision
- Module Summary
- Module Introduction
- CI/CD Explained
- CI with GitHub Actions: Part 1
- CI with GitHub Actions: Part 2
- Matrix Testing with pytest
- Parallel Testing & Coverage Gates
- Module Summary
- Course Roundup