This package contains hypothesis strategies for generating Python programs, something like CSmith, a random generator of C programs.

This package provides a plugin for Pytest which adds the ability to retry flaky tests, thereby improving the consistency of the test suite results.

green is a Python test runner that describes itself as:

Clean

Low redundancy in output. Result statistics for each test is vertically aligned.

Colorful

Terminal output makes good use of color when the terminal supports it.

Fast

Tests run in independent processes (one per processor by default).

Powerful

Multi-target and auto-discovery support.

Traditional

It uses the normal unittest classes and methods.

Descriptive

Multiple verbosity levels, from just dots to full docstring output.

Convenient

Bash-completion and ZSH-completion of options and test targets.

Thorough

Built-in integration with coverage.

This Pytest plugin adds a cookies fixture, which is a wrapper for the Cookiecutter API. This fixture helps you verify that your template is working as expected and takes care of cleaning up after running the tests.

Sure is a python library that leverages a DSL for writing assertions. Sure is heavily inspired by RSpec Expectations and should.js.

This Python module adds a @public decorator and function which populates a module's __all__ and optionally the module globals. With it, the declaration of a name's public export semantics are not separated from the implementation of that name.

This package enables dynamic orchestration of Celery environments for testing tasks in isolated conditions, leveraging Docker & pytest-docker-tools for environment simulation.

This package implements a functionality to store data created during your pytest tests execution, and retrieve it at the end of the session, e.g. for applicative benchmarking purposes.

re-assert provides a helper class to make assertions of regexes simpler.

This is a Pytest plugin to randomly order tests and control Python's random.seed.

This package provides a utility for mocking out the Python libraries HTTPX and HTTPCore.

Avocado is a set of tools and libraries to help with automated testing, i.e. a test framework. Native tests are written in Python and they follow the unittest pattern, but any executable can serve as a test. The following output formats are supported:

xUnit

an XML format that contains test results in a structured form, and are used by other test automation projects, such as Jenkins.

JSON

a widely used data exchange format. The JSON Avocado plugin outputs job information, similarly to the xunit output plugin.

TAP

Provides the basic TAP (Test Anything Protocol) results. Unlike most existing Avocado machine readable outputs this one is streamlined (per test results).

This package provides utilities for production code that work well with python-approvaltests.

This package provides a plugin for the Pytest framework that allows developers to control unit tests that require access to data from the internet.

Cram is a functional testing framework for command line applications. Cram tests look like snippets of interactive shell sessions. Cram runs each command and compares the command output in the test with the command’s actual output.

Testfixtures is a collection of helpers and mock objects that are useful when writing automated tests in Python.

Tappy is a set of tools for working with the Test Anything Protocol (TAP) in Python. TAP is a line based test protocol for recording test data in a standard way.

Validation library and CLI tool for checking on pyproject.toml files using JSON Schema.

This plugin adds functionality to Pytest to recognise and collect Jupyter notebooks. The intended purpose of the tests is to determine whether execution of the stored inputs match the stored outputs of the .ipynb file. Whilst also ensuring that the notebooks are running without errors.

This flake8 plugin helps you keep up with method deprecations by providing hints about what deprecated methods should be replaced with.

This package provides a collection of utility functions and classes which make writing and running functional and integration tests easier.

This package provides a pytest plugin to show failures instantly.

This plugin makes it simple to test general data, images, files, and numeric tables by saving expected data in a data directory (courtesy of pytest-datadir) that can be used to verify that future runs produce the same data.

Aiounittest is a library that helps write tests using asynchronous code in Python (asyncio).