nose2 VS callee

Compare nose2 vs callee and see what are their differences.

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nose2 callee
2 -
771 86
0.1% -
7.1 0.0
9 days ago over 3 years ago
Python Python
GNU General Public License v3.0 or later BSD 3-clause "New" or "Revised" License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

nose2

Posts with mentions or reviews of nose2. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-08-10.

callee

Posts with mentions or reviews of callee. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning callee yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing nose2 and callee you can also consider the following projects:

pytest - The pytest framework makes it easy to write small tests, yet scales to support complex functional testing

tox - Command line driven CI frontend and development task automation tool.

nose - nose is nicer testing for python

factory_boy - A test fixtures replacement for Python

aiounittest - Test python asyncio-based code with ease.

coverage

Robot Framework - Generic automation framework for acceptance testing and RPA

Selenium WebDriver - A browser automation framework and ecosystem.

Behave - BDD, Python style.

green - Green is a clean, colorful, fast python test runner.

hypothesis - Hypothesis is a powerful, flexible, and easy to use library for property-based testing.

Mimesis - Mimesis is a powerful Python library that empowers developers to generate massive amounts of synthetic data efficiently.