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About
Coverage.py is a tool for measuring code coverage of Python programs. It monitors your program, noting which parts of the code have been executed, then analyzes the source to identify code that could have been executed but was not. Coverage measurement is typically used to gauge the effectiveness of tests. It can show which parts of your code are being exercised by tests, and which are not. Use coverage run to run your test suite and gather data. However you normally run your test suite, and you can run your test runner under coverage. If your test runner command starts with “python”, just replace the initial “python” with “coverage run”. To limit coverage measurement to code in the current directory, and also find files that weren’t executed at all, add the source argument to your coverage command line. By default, it will measure line (statement) coverage. It can also measure branch coverage. It can tell you what tests ran which lines.
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About
It works with .NET Framework on Windows and .NET Core on all supported platforms. Coverlet supports coverage for deterministic builds. The solution at the moment is not optimal and need a workaround. If you want to visualize coverlet output inside Visual Studio while you code, you can use the following addins depending on your platform. Coverlet also integrates with the build system to run code coverage after tests. Enabling code coverage is as simple as setting the CollectCoverage property to true. The coverlet tool is invoked by specifying the path to the assembly that contains the unit tests. You also need to specify the test runner and the arguments to pass to the test runner using the --target and --targetargs options respectively. The invocation of the test runner with the supplied arguments must not involve a recompilation of the unit test assembly or no coverage result will be generated.
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About
scikit-image is a collection of algorithms for image processing. It is available free of charge and free of restriction. We pride ourselves on high-quality, peer-reviewed code, written by an active community of volunteers. scikit-image provides a versatile set of image processing routines in Python. This library is developed by its community, and contributions are most welcome! scikit-image aims to be the reference library for scientific image analysis in Python. We accomplish this by being easy to use and install. We are careful in taking on new dependencies, and sometimes cull existing ones, or make them optional. All functions in our API have thorough docstrings clarifying expected inputs and outputs. Conceptually identical arguments have the same name and position in a function signature. Test coverage is close to 100% and code is reviewed by at least two core developers before being included in the library.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Any user looking for a solution to measure line and branch coverage to produce test reports
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Audience
IT teams searching for a cross platform code coverage framework for .NET
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Audience
Developers and professionals requiring a free solution offering algorithms for their image processing projects
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Reviews/
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationCoverage.py
United States
coverage.readthedocs.io/en/7.0.0/
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Company InformationCoverlet
github.com/coverlet-coverage/coverlet
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Company Informationscikit-image
United States
scikit-image.org
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Integrations
Akira AI
C
Codecov
Cython
HTML
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Label Studio
MLReef
Mako
PostgresML
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Integrations
Akira AI
C
Codecov
Cython
HTML
JSON
Label Studio
MLReef
Mako
PostgresML
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Integrations
Akira AI
C
Codecov
Cython
HTML
JSON
Label Studio
MLReef
Mako
PostgresML
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