Related Products
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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
Enjoy the highest performance and unlimited possibilities when working with SQLite. SQLite Data Access Components (LiteDAC) is a library of components that provides native connectivity to SQLite from Delphi and C++Builder including Community Edition, as well as Lazarus (and Free Pascal) on Windows, Linux, macOS, iOS, and Android for both 32-bit and 64-bit platforms. LiteDAC is designed for programmers to develop truly cross-platform desktop and mobile SQLite database applications with no need to deploy any additional libraries. LiteDAC-based DB applications are easy to deploy and do not require the installation of other data provider layers (such as BDE or ODBC), and that's why they can work faster than the ones based on standard Delphi data connectivity solutions. Moreover, LiteDAC provides an additional opportunity to work with SQLite in Delphi and C++Builder directly by linking the client library statically in your application.
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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
|
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
Developer teams and anyone seeking a solution providing a library of components to build cross-platform databases
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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
$169.95 per year
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 InformationDevart
Founded: 1997
Czech Republic
www.devart.com/litedac/
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Company Informationscikit-image
United States
scikit-image.org
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Categories |
Categories |
Categories |
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Integrations
Akira AI
C
C++Builder
Codecov
Cython
Delphi
Django
FreeBSD
JSON
Label Studio
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Integrations
Akira AI
C
C++Builder
Codecov
Cython
Delphi
Django
FreeBSD
JSON
Label Studio
|
Integrations
Akira AI
C
C++Builder
Codecov
Cython
Delphi
Django
FreeBSD
JSON
Label Studio
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