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.

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.

About

The core of extensible programming is defining functions. Python allows mandatory and optional arguments, keyword arguments, and even arbitrary argument lists. Whether you're new to programming or an experienced developer, it's easy to learn and use Python. Python can be easy to pick up whether you're a first-time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way to writing programs with Python! The community hosts conferences and meetups to collaborate on code, and much more. Python's documentation will help you along the way, and the mailing lists will keep you in touch. The Python Package Index (PyPI) hosts thousands of third-party modules for Python. Both Python's standard library and the community-contributed modules allow for endless possibilities.

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.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Any user looking for a solution to measure line and branch coverage to produce test reports

Audience

IT teams searching for a cross platform code coverage framework for .NET

Audience

Developers interested in a beautiful but advanced programming language

Audience

Developers and professionals requiring a free solution offering algorithms for their image processing projects

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

Reviews/Ratings

Overall 5.0 / 5
ease 3.0 / 5
features 5.0 / 5
design 5.0 / 5
support 3.0 / 5

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Coverage.py
United States
coverage.readthedocs.io/en/7.0.0/

Company Information

Coverlet
github.com/coverlet-coverage/coverlet

Company Information

Python
Founded: 1991
www.python.org

Company Information

scikit-image
United States
scikit-image.org

Alternatives

Alternatives

Alternatives

Alternatives

JCov

JCov

OpenJDK
dotCover

dotCover

JetBrains
blanket.js

blanket.js

Blanket.js
CodeRush

CodeRush

DevExpress
Devel::Cover

Devel::Cover

metacpan

Categories

Categories

Categories

Categories

Integrations

Akira AI
Allure Report
BBEdit
CodePeer
CodeQwen
Codoki
EditRocket
Fabi.ai
Kite
Kontra
LLM Guard
LanceDB
NextCaptcha
PDFmyURL
RepoFlow
SikuliX
Unify AI
c/ua
luminoth
{CodeWhizz}

Integrations

Akira AI
Allure Report
BBEdit
CodePeer
CodeQwen
Codoki
EditRocket
Fabi.ai
Kite
Kontra
LLM Guard
LanceDB
NextCaptcha
PDFmyURL
RepoFlow
SikuliX
Unify AI
c/ua
luminoth
{CodeWhizz}

Integrations

Akira AI
Allure Report
BBEdit
CodePeer
CodeQwen
Codoki
EditRocket
Fabi.ai
Kite
Kontra
LLM Guard
LanceDB
NextCaptcha
PDFmyURL
RepoFlow
SikuliX
Unify AI
c/ua
luminoth
{CodeWhizz}

Integrations

Akira AI
Allure Report
BBEdit
CodePeer
CodeQwen
Codoki
EditRocket
Fabi.ai
Kite
Kontra
LLM Guard
LanceDB
NextCaptcha
PDFmyURL
RepoFlow
SikuliX
Unify AI
c/ua
luminoth
{CodeWhizz}
Claim Coverage.py and update features and information
Claim Coverage.py and update features and information
Claim Coverlet and update features and information
Claim Coverlet and update features and information
Claim Python and update features and information
Claim Python and update features and information
Claim scikit-image and update features and information
Claim scikit-image and update features and information