This course aims to help learners master testing in Python using Pytest, covering topics such as setting up CI/CD pipelines, using cloud-based development environments, creating local test environments, and utilizing advanced Pytest functions. The course teaches skills like Pytest test selection, debugging with pdb, and building command-line tools and web frameworks. The teaching method includes hands-on demonstrations and practical examples. This course is intended for Python developers looking to enhance their testing and DevOps skills.
Overview
Syllabus
* Introduction
* What is DevOps?
* Github CodeSpaces
* Create Python Project Structure: Makefile, requirements.txt, test file and virtualenv
* Importing code with IPython
* Writing tests with Pytest
* Using Pylint
* Verifying Pylint bad syntax catch
* Formatting code with Black
* Pinning requirements to a specific version
* Setup Github Actions
* Matrix Testing multiple versions of a Python 3.6, 3.7, 3.8, 3.9 with Github Actions
* Using AWS CloudShell
* Using AWS Cloud9
* Adding virtualenv to ~/.bashrc
* Using AWS CodeBuild
* Testing Google Colab Notebooks and Jupyter Notebooks with nbval and Pytest
* Using pdb;pdb.set_trace and ipdb;ipdb.set_trace
* Using pytest-cov
* Using pytest with --pdb pdb debbuging during tests
* Using pytest with --pdb --maxfailures 1 to stop after first failure
* Using pytest to test a single test
* Using Pytest with fixtures
* Using Pytest setup_function and teardown_function to setup and teardown of tests
* Using flask web framework
* Testing flask web framework with pytest
* Extending flask with a greedy coin change machine
* Using click to create a command line interface
* Using Pytest to test click command line interfaces
* Matrix testing entire project with click, pytest, and nbval using Github Actions and multiple versions of Python 3.6, 3.7, 3.8, 3.9
Taught by
Pragmatic AI Labs
