coveragepy
The code coverage tool for Python (by nedbat)
toml
Python lib for TOML (by uiri)
| coveragepy | toml | |
|---|---|---|
| 7 | 2 | |
| 2,831 | 1,058 | |
| - | - | |
| 9.6 | 5.2 | |
| 5 days ago | 7 months ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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
Posts with mentions or reviews of coveragepy.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-02-14.
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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
toml
Posts with mentions or reviews of toml.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-12-14.
-
Comparison of Python TOML parser libraries
toml This was initially vendored in pip itself to deal with pyproject.toml. Even so pip has since moved to tomli.
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Restore Window Positions on Ubuntu after monitors wake up
TOML - I use TOML as the configuration file format. I like TOML as it makes sense.
What are some alternatives?
When comparing coveragepy and toml you can also consider the following projects:
global-chem - A Knowledge Graph of Common Chemical Names to their Molecular Definition
tomli-w - A lil' TOML writer (counterpart to https://github.com/hukkin/tomli)
slipcover - Near Zero-Overhead Python Code Coverage
tomlplusplus - Header-only TOML config file parser and serializer for C++17.
Zappa - Serverless Python
tomli - A lil' TOML parser
pytomlpp - A python wrapper for tomlplusplus
pytoml - A TOML-0.4.0 parser/writer for Python.
flit - Simplified packaging of Python modules
qtoml - Another Python TOML encoder/decoder