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

NCover Desktop is a Windows application that helps you collect code coverage statistics for .NET applications and services. After coverage is collected, Desktop displays charts and coverage metrics in a browser-based GUI that allows you to drill all the way down to your individual lines of source code. Desktop also allows you the option to install a Visual Studio extension called Bolt. Bolt offers built-in code coverage that displays unit test results, timings, branch visualization and source code highlighting right in the Visual Studio IDE. NCover Desktop is a major leap forward in the ease and flexibility of code coverage tools. Code coverage, gathered while testing your .NET code, shows the NCover user what code was exercised during the test and gives a specific measurement of unit test coverage. By tracking these statistics over time, you gain a concrete measurement of code quality during the development cycle.

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

ScienceDesk data automation demystifies the use of artificial intelligence in materials sciences. A practical tool for your team to add and apply the newest AI algorithms on an everyday basis. Customizable properties, universal identifiers, QR-codes and a powerful textual-numeric search engine that links sample and experimental data. ScienceDesk is an innovative platform for scientists and engineers to interact with, collaborate on and obtain insights into their experimental data. Unfortunately, the potential of this asset is not fully exploited due to the variety of data formats and the strong dependence on experts to manually extract specific information. The ScienceDesk research data management system solves this problem by combining documentation and data analysis in a cleverly-engineered data structure. Researchers and scientists are empowered by our algorithms to gain total control of their data. They can not only share datasets, but even the analysis know-how.

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

Development teams searching for a powerful .NET Code Coverage solution

Audience

Developers interested in a beautiful but advanced programming language

Audience

Researchers requiring a solution to improve material characterization and optimize experimental parameters

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

No information available.
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

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Reviews/Ratings

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

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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 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

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

NCover
www.ncover.com

Company Information

Python
Founded: 1991
www.python.org

Company Information

ScienceDesk
Germany
sciencedesk.net

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Alternatives

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Blanket.js
Devel::Cover

Devel::Cover

metacpan
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Devel::Cover

metacpan
Albert

Albert

Albert Invent

Categories

Categories

Categories

Categories

Integrations

Agent Builder
Base64.ai
CodeRunner
CotEditor
DeepSeek-V3
Einblick
GPT-5.1
Grok 3 mini
IpnProxy
Lexalytics
Navie AI
Parallel Domain Replica Sim
Rainforest
Relevance Lab SPECTRA
Restack
TF-Agents
Ubivox
Ultralytics
Zenserp
scikit-learn

Integrations

Agent Builder
Base64.ai
CodeRunner
CotEditor
DeepSeek-V3
Einblick
GPT-5.1
Grok 3 mini
IpnProxy
Lexalytics
Navie AI
Parallel Domain Replica Sim
Rainforest
Relevance Lab SPECTRA
Restack
TF-Agents
Ubivox
Ultralytics
Zenserp
scikit-learn

Integrations

Agent Builder
Base64.ai
CodeRunner
CotEditor
DeepSeek-V3
Einblick
GPT-5.1
Grok 3 mini
IpnProxy
Lexalytics
Navie AI
Parallel Domain Replica Sim
Rainforest
Relevance Lab SPECTRA
Restack
TF-Agents
Ubivox
Ultralytics
Zenserp
scikit-learn

Integrations

Agent Builder
Base64.ai
CodeRunner
CotEditor
DeepSeek-V3
Einblick
GPT-5.1
Grok 3 mini
IpnProxy
Lexalytics
Navie AI
Parallel Domain Replica Sim
Rainforest
Relevance Lab SPECTRA
Restack
TF-Agents
Ubivox
Ultralytics
Zenserp
scikit-learn
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