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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.

About

Visual Studio Code (VS Code) is Microsoft’s open-source AI code editor designed to make coding faster, smarter, and more collaborative. It supports thousands of extensions and nearly every programming language, offering developers a lightweight yet powerful environment for writing, testing, and debugging code. With AI-powered features like GitHub Copilot, Next Edit Suggestions, and Agent Mode, VS Code helps you code with precision, automate complex tasks, and streamline development workflows. It integrates seamlessly with cloud services, remote repositories, and tools like Git, Docker, and Azure. The editor is fully customizable, allowing you to personalize your layout, color themes, and keyboard shortcuts. Whether coding locally or in the browser, VS Code delivers a complete development experience for individuals and teams alike.

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

Audience

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

Audience

Developers, data scientists, and engineering teams seeking a customizable, AI-powered code editor that enhances productivity, supports all major languages, and integrates seamlessly with cloud and collaboration tools

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

API

Offers API

API

Offers API

API

Offers API

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

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 4.8 / 5
ease 4.8 / 5
features 4.8 / 5
design 4.9 / 5
support 4.8 / 5

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

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

Microsoft
Founded: 1975
United States
code.visualstudio.com

Company Information

scikit-image
United States
scikit-image.org

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Atom

Atom

GitHub

Categories

Categories

Categories

Software Documentation Features

Access Roles / User Permissions
Automatic Documentation Generation
Collaboration Tools
Docs Web Hosting
Feedback Capture
Markdown Support
Multiple Formats Support
Multiple Versions Support
reStructured Text Support
Version Control
Webhooks
WYSIWIG Editor

Source Code Management Features

Access Controls/Permissions
Bug Tracking
Build Automation
Change Management
Code Review
Collaboration
Continuous Integration
Repository Management
Version Control

Text Editors Features

API
Auto-Complete
Code Folding
Column Editing
Customizable Themes
Debugging
Formatting / Table Editing
Keyboard Shortcuts
Multi-Monitor Editing
Syntax Highlighting
WYSIWYG

Integrations

Python
Archipelo
Capacitor
Dart
DevCycle
F#
GPT-5.2
Grit
JFrog
JuliaHub
Kropply
Magier
Mailtrap
Mermaid Chart
Monica Code
OpenContext
Roo Code
Snyk
Sourcetrail
Tabnine

Integrations

Python
Archipelo
Capacitor
Dart
DevCycle
F#
GPT-5.2
Grit
JFrog
JuliaHub
Kropply
Magier
Mailtrap
Mermaid Chart
Monica Code
OpenContext
Roo Code
Snyk
Sourcetrail
Tabnine

Integrations

Python
Archipelo
Capacitor
Dart
DevCycle
F#
GPT-5.2
Grit
JFrog
JuliaHub
Kropply
Magier
Mailtrap
Mermaid Chart
Monica Code
OpenContext
Roo Code
Snyk
Sourcetrail
Tabnine
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