coveragepy
pytest-testinfra
| coveragepy | pytest-testinfra | |
|---|---|---|
| 7 | 2 | |
| 2,838 | 2,321 | |
| - | 0.3% | |
| 9.6 | 7.6 | |
| 1 day ago | 13 days ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
coveragepy
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An Introduction to Testing with Django for Python
Coverage.py is the go-to tool for measuring code coverage of Python programs. Once installed, you can use it with either unittest or pytest.
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The Uncreative Software Engineer's Compendium to Testing
Code Coverage Analysis assess the code portions tested by the current test suites without altering the code.
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Slipcover: Near Zero-Overhead Python Code Coverage
The PLASMA lab @ UMass Amherst (home of the Scalene profiler) has released a new version of Slipcover, a super fast code coverage tool for Python. It is by far the fastest code coverage tool: in our tests, its average slowdown is just 5% (compare to the widely used coverage.py, average slowdown 218%!). The latest release performs both line and branch coverage with virtually no overhead. Use it to dramatically speed up your tests and continuous integration!
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Unit Tests - what’s the point?
Tests ensure the tested behavior is maintained. It's up to the developers to write tests with sufficient coverage. Determining which lines of code on your project are covered by tests is easily quantifiable using tooling. E.g. https://coverage.readthedocs.io/
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How to make Django package smaller for Serverless deployment
Taking the idea further, if you build robust tests for your API, you could use a dynamic code analyzer like coverage or figleaf to identify and delete unused functions.
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Comparison of Python TOML parser libraries
coverage
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New Ways to Be Told That Your Python Code Is Bad
FWIW, ternary expressions aren't properly detected by coverage: https://github.com/nedbat/coveragepy/issues/509
pytest-testinfra
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The Uncreative Software Engineer's Compendium to Testing
Testinfra: is a testing framework for infrastructure used to test system configurations and infrastructure as code.
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Help creating a custom TestInfra module
GitHub: pytest-dev/pytest-testinfra - Issue #660
What are some alternatives?
global-chem - A Knowledge Graph of Common Chemical Names to their Molecular Definition
robotmk - Robotmk - the Robot Framework integration for Checkmk
slipcover - Near Zero-Overhead Python Code Coverage
allure-docker-service - This docker container allows you to see up to date reports simply mounting your "allure-results" directory in the container (for a Single Project) or your "projects" directory (for Multiple Projects). Every time appears new results (generated for your tests), Allure Docker Service will detect those changes and it will generate a new report automatically (optional: send results / generate report through API), what you will see refreshing your browser.
Zappa - Serverless Python
dredd - Language-agnostic HTTP API Testing Tool
pytomlpp - A python wrapper for tomlplusplus
eLog - Log your errors to Notion natively in Python, or externally from any other language. Easy set up, then track of what's occuring and when it's fixed.
flit - Simplified packaging of Python modules
RHCA-study-notes - Red Hat Certified Architect personal study notes.
toml - Python lib for TOML
Puppet-Guide - Puppet Guide