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What is pytest-cov?

This plugin produces comprehensive coverage reports that surpass the basic capabilities of using coverage run alone. It offers subprocess execution support, enabling users to fork or run tasks in a separate subprocess while still collecting coverage data effortlessly. Furthermore, it seamlessly integrates with xdist, allowing users to access all features of pytest-xdist without compromising coverage reporting. The plugin ensures compatibility with pytest, providing consistent access to all functionalities of the coverage package, whether through pytest-cov's command line options or the coverage configuration file. Occasionally, a stray .pth file may linger in the site packages post-execution. To ensure a fresh start for each test run, the data file is cleared before testing begins. If you need to merge coverage results from different test runs, you can utilize the --cov-append option to incorporate this information into previous results. At the end of testing, the data file is preserved, enabling users to make use of standard coverage tools for additional analysis of their findings. This extra functionality not only improves the overall user experience but also provides enhanced control over coverage data management throughout the testing lifecycle, ultimately leading to more efficient testing practices.

What is JCov?

The JCov open-source project was established to gather quality metrics pertinent to the creation of test suites. By making JCov readily available, the initiative seeks to improve the verification process of regression test executions in the development of OpenJDK. The main objective of JCov is to provide clarity regarding test coverage metrics. Advocating for a standardized coverage tool such as JCov offers advantages to OpenJDK developers by delivering a code coverage solution that progresses alongside developments in the Java language and virtual machine. Completely developed in Java, JCov functions as a tool for evaluating and analyzing dynamic code coverage in Java applications. It encompasses features that assess method coverage, linear block coverage, and branch coverage, while also pinpointing execution paths that go untested. Furthermore, JCov has the capability to annotate the source code of the program with coverage information. This tool is particularly significant from a testing perspective, as it aids in uncovering execution paths and provides insights into how various code segments are utilized during testing. Such comprehensive understanding empowers developers to refine their testing methodologies and elevate the overall quality of their code, ultimately contributing to more robust software development practices.

Media

Media

Integrations Supported

XML
Codecov
Coverage.py
HTML
Python
pytest

Integrations Supported

XML
AWS Marketplace
Amazon Corretto
Apache NetBeans
Azure Marketplace
Helidon
Java
Red Hat Runtimes

API Availability

API Availability

Has API

Pricing Information

Free
Free Version

Pricing Information

Free
Free Version

Supported Platforms

Windows
Mac
Linux

Supported Platforms

Windows
Mac
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Python

Company Location

United States

Company Website

pypi.org/project/pytest-cov/

Company Facts

Organization Name

OpenJDK

Company Location

United States

Company Website

wiki.openjdk.org/display/CodeTools/jcov

Categories and Features

Code Coverage

Not specified

Categories and Features

Code Coverage

Not specified

Regression Testing

Not specified

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