+

Related Products

  • Parasoft
    132 Ratings
    Visit Website
  • MuukTest
    31 Ratings
    Visit Website
  • Boozang
    15 Ratings
    Visit Website
  • TrustInSoft Analyzer
    6 Ratings
    Visit Website
  • Orca Security
    481 Ratings
    Visit Website
  • Wiz
    1,062 Ratings
    Visit Website
  • ZeroPath
    2 Ratings
    Visit Website
  • Windsurf Editor
    148 Ratings
    Visit Website
  • QuantaStor
    6 Ratings
    Visit Website
  • ERA EHS Software
    27 Ratings
    Visit Website

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

Pexpect makes Python a better tool for controlling other applications. Pexpect is a pure Python module for spawning child applications; controlling them, and responding to expected patterns in their output. Pexpect works like Don Libes’ Expect. Pexpect allows your script to spawn a child application and control it as if a human were typing commands. Pexpect can be used for automating interactive applications such as ssh, FTP, passwd, telnet, etc. It can be used to automate setup scripts for duplicating software package installations on different servers. It can be used for automated software testing. Pexpect is in the spirit of Don Libes’ Expect, but Pexpect is pure Python. Unlike other Expect-like modules for Python, Pexpect does not require TCL or Expect nor does it require C extensions to be compiled. It should work on any platform that supports the standard Python pty module. The Pexpect interface was designed to be easy to use.

About

Scikit-learn provides simple and efficient tools for predictive data analysis. Scikit-learn is a robust, open source machine learning library for the Python programming language, designed to provide simple and efficient tools for data analysis and modeling. Built on the foundations of popular scientific libraries like NumPy, SciPy, and Matplotlib, scikit-learn offers a wide range of supervised and unsupervised learning algorithms, making it an essential toolkit for data scientists, machine learning engineers, and researchers. The library is organized into a consistent and flexible framework, where various components can be combined and customized to suit specific needs. This modularity makes it easy for users to build complex pipelines, automate repetitive tasks, and integrate scikit-learn into larger machine-learning workflows. Additionally, the library’s emphasis on interoperability ensures that it works seamlessly with other Python libraries, facilitating smooth data processing.

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

Professional teams and individuals seeking a tool for managing and controlling other applications

Audience

Engineers and data scientists requiring a solution to manage and improve their machine learning research

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

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

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

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

Company Information

Coverage.py
United States
coverage.readthedocs.io/en/7.0.0/

Company Information

pexpect
pexpect.readthedocs.io/en/stable/

Company Information

scikit-learn
United States
scikit-learn.org/stable/

Alternatives

Alternatives

Alternatives

Gensim

Gensim

Radim Řehůřek
JCov

JCov

OpenJDK
yarl

yarl

Python Software Foundation
ML.NET

ML.NET

Microsoft
MLlib

MLlib

Apache Software Foundation
blanket.js

blanket.js

Blanket.js
Devel::Cover

Devel::Cover

metacpan
Keepsake

Keepsake

Replicate

Categories

Categories

Categories

Integrations

Python
C
Codecov
DagsHub
Databricks Data Intelligence Platform
Flower
Guild AI
JSON
Keepsake
MLJAR Studio
Mako
Matplotlib
ModelOp
NumPy
SQLite
Tidelift
Train in Data
XML
pytest
pytest-cov

Integrations

Python
C
Codecov
DagsHub
Databricks Data Intelligence Platform
Flower
Guild AI
JSON
Keepsake
MLJAR Studio
Mako
Matplotlib
ModelOp
NumPy
SQLite
Tidelift
Train in Data
XML
pytest
pytest-cov

Integrations

Python
C
Codecov
DagsHub
Databricks Data Intelligence Platform
Flower
Guild AI
JSON
Keepsake
MLJAR Studio
Mako
Matplotlib
ModelOp
NumPy
SQLite
Tidelift
Train in Data
XML
pytest
pytest-cov
Claim Coverage.py and update features and information
Claim Coverage.py and update features and information
Claim pexpect and update features and information
Claim pexpect and update features and information
Claim scikit-learn and update features and information
Claim scikit-learn and update features and information