What goes into creating automated tests for your Python code? Should you focus on testing the individual code sections or on how the entire system runs? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder's Weekly articles and projects.
👉 Links from the show: https://realpython.com/podcasts/rpp/237/
We discuss a recent article from Semaphore about unit testing vs. integration testing. Christopher shares his experiences setting up automated tests for his own smaller projects. He also answers questions about building tests in an existing codebase and integrating tests across systems.
We also share several other articles and projects from the Python community, including a news roundup, improving default line charts to journal-quality infographics, why `hash(-1) == hash(-2)` in Python, data cleaning in data science, ways to work with large files in Python, a lightweight CLI viewer for log files, and a tool for mocking the `datetime` module for testing.
This episode is sponsored by Postman.
Topics:
00:00:00 -- Introduction
00:02:28 -- Python news and releases
00:04:02 -- From Default Line Charts to Journal-Quality Infographics
00:07:25 -- PyViz: Python Tools for Data Visualization
00:09:25 -- Why Is hash(-1) == hash(-2) in Python?
00:12:40 -- Sponsor: Postman
00:13:32 -- Data Cleaning in Data Science
00:19:29 -- 10 Ways to Work With Large Files in Python
00:23:40 -- Unit Testing vs. Integration Testing
00:29:17 -- Does university curriculum cover this?
00:31:22 -- Building tests into smaller projects
00:36:04 -- Video Course Spotlight
00:37:30 -- How does the approach differ with clients or larger-scale projects?
00:40:45 -- How do tests act as documentation?
00:42:02 -- Difficulties in building integration tests
00:45:24 -- How do you limit the results of tests?
00:47:52 -- klp: Lightweight CLI Viewer for Log Files
00:50:54 -- freezegun: Mocks the datetime Module for Testing
00:53:11 -- Thanks and goodbye
👉 Links from the show: https://realpython.com/podcasts/rpp/237/
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