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Description
Coverage.py serves as a powerful utility for assessing the code coverage of Python applications. It tracks the execution of your program, recording which segments of the code have been activated, and subsequently reviews the source to pinpoint areas that could have been executed yet remained inactive. This measurement of coverage is primarily utilized to evaluate the efficacy of testing efforts. It provides insights into which portions of your code are being tested and which are left untested. To collect data, you can use the command `coverage run` to execute your test suite. Regardless of how you typically run your tests, you can incorporate coverage by executing your test runner with the coverage tool. If the command for your test runner begins with "python," simply substitute the initial "python" with "coverage run." To restrict coverage evaluation to only the code within the current directory and to identify files that have not been executed at all, include the source parameter in your coverage command. By default, Coverage.py measures line coverage, but it is also capable of assessing branch coverage. Additionally, it provides information on which specific tests executed particular lines of code, enhancing your understanding of test effectiveness. This comprehensive approach to coverage analysis can significantly improve the quality and reliability of your codebase.
Description
This module offers metrics for code coverage specifically tailored for Perl, highlighting the extent to which tests engage with the code. By utilizing Devel::Cover, users can identify sections of their code that remain untested and decide on additional tests necessary to enhance coverage. Essentially, code coverage serves as a proxy indicator of software quality. Devel::Cover has reached a commendable level of stability, incorporating an array of features typical of effective coverage tools. It provides detailed reports on statement, branch, condition, subroutine, and pod coverage. Generally, the data on statement and subroutine coverage is reliable, while branch and condition coverage may not always align with expectations. For pod coverage, it leverages Pod::Coverage, and if Pod::Coverage::CountParents is accessible, it will utilize that for more comprehensive insights. Overall, Devel::Cover stands out as an essential tool for Perl developers seeking to improve their code's robustness through better testing practices.
API Access
Has API
API Access
Has API
Integrations
C
Codecov
HTML
JSON
Django
GitHub
Go
Mako
Perl
Python
Integrations
C
Codecov
HTML
JSON
Django
GitHub
Go
Mako
Perl
Python
Pricing Details
Free
Free Trial
Free Version
Pricing Details
Free
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Coverage.py
Country
United States
Website
coverage.readthedocs.io/en/7.0.0/
Vendor Details
Company Name
metacpan
Website
metacpan.org/pod/Devel::Cover