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awesome-python-testing
Collection of awesome ποΈ Python resources for testing
https://github.com/cleder/awesome-python-testing
Last synced: about 12 hours ago
JSON representation
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Behavior-driven Development
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Fake Data
- radar - Generate random datetime / time.
- autofaker - designed to minimize the setup/arrange phase of your unit tests by removing the need to manually write code to create anonymous variables as part of a test cases setup/arrange phase.
- faker - A Python package that generates fake data.
- fake2db - Fake database generator.
- genuine-fake - Genuine Fake means an imitation of a (usually) valuable object that is so good that it is, to all intents and purposes, identical.
- mimesis - A Python library that helps you generate fake data.
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Memory Management
- tracemalloc - is a debug tool to trace memory blocks allocated by Python.
- filprofiler - A Python memory profiler for data processing and scientific computing applications.
- Guppy 3 - a Python programming environment & heap analysis toolset.
- mem_top - shows top suspects for memory leaks in your Python program.
- Pympler - is a development tool to measure, monitor and analyze the memory behavior of Python objects in a running Python application.
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Mock and Stub
- doublex - Powerful test doubles framework for Python.
- mock - (Python standard library) A mocking and patching library.
- Mockintosh - aims to provide usual HTTP mock service functionality with small resource footprint, making it friendly for microservice applications.
- moto - allows you to easily mock out tests based on AWS infrastructure.
- Flexmock - is a testing library for Python that makes it easy to create mocks, stubs and fakes.
- freezegun - Travel through time by mocking the datetime module.
- httmock - A mocking library for requests for Python 2.6+ and 3.2+.
- Aioresponses - is a helper for mock/fake web requests in python aiohttp package.
- Cornell - record & replay mock server.
- httpretty - HTTP request mock tool for Python.
- Kesha - A web service with a user interface for testing http requests and web hooks.
- Mockafka - Python library designed for mocking Kafka in a testing environment. It simplifies testing Kafka-integrated applications by providing an in-memory mock for aiokafka and confluent-kafka-python.
- mocket - A socket mock framework with gevent/asyncio/SSL support.
- Mockintosh - aims to provide usual HTTP mock service functionality with small resource footprint, making it friendly for microservice applications.
- Pretend - is a library to make stubbing with Python easier.
- responses - A utility library for mocking out the requests Python library.
- time-machine - Travel through time in your tests.
- trustme - gives you a fake certificate authority (CA) that you can use to generate fake TLS certs to use in your tests.
- moto - allows you to easily mock out tests based on AWS infrastructure.
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Rest API Testing
- Schemathesis - A tool for automatic property-based testing of web applications built with Open API / Swagger specifications.
- Dredd - is a language-agnostic command-line tool for validating API description document against backend implementation of the API.
- HttpRunner - is a simple & elegant, yet powerful HTTP(S) testing framework.
- hypothesis-graphql - Hypothesis strategies for GraphQL schemas, queries and data.
- playback - A Python decorator-based framework that lets you "record" and "replay" operations (e.g. API requests, workers consuming jobs from queues).
- RESTler - is the first stateful REST API fuzzing tool for automatically testing cloud services through their REST APIs and finding security and reliability bugs in these services.
- Tavern - is a pytest plugin, command-line tool and Python library for automated testing of APIs, with a simple, concise and flexible YAML-based syntax.
- behave-restful - BDD Framework to Test REST Services and APIs.
- cherrybomb - CLI tool that helps you avoid undefined user behaviour by auditing your API specifications, validating them and running API security tests.
- Zato API Test - API testing in pure English. No programming needed. Implemented and extendable in Python.
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Static Checks
- awesome-python-typing - Collection of awesome Python types, stubs, plugins, and tools to work with them.
- flake8 - is a python tool that glues together pep8, pyflakes, mccabe, and third-party plugins to check the style and quality of python code.
- Pylint - A Python static code analysis tool which looks for programming errors, helps enforcing a coding standard, sniffs for code smells and offers simple refactoring suggestions.
- ruff - An extremely fast Python linter, written in Rust.
- awesome-flake8-extensions - A curated list of awesome flake8 extensions.
- Bandit - is a tool designed to find common security issues in Python code.
- pyanalyze - A tool for programmatically detecting common mistakes in Python code, such as references to undefined variables and some categories of type mismatches.
- pyflakes - A simple program which checks Python source files for errors.
- Pylint - A Python static code analysis tool which looks for programming errors, helps enforcing a coding standard, sniffs for code smells and offers simple refactoring suggestions.
- Refurb - A tool for refurbishing and modernizing Python codebases.
- slotscheck - Find mistakes in your `__slots__` definitions.
- Typecheckers - A list of Python type checkers.
- ruff - An extremely fast Python linter, written in Rust.
- typos - A Source code spell checker that finds and corrects spelling mistakes in source code.
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Resources
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Books
- Crafting Test-Driven Software with Python
- pytest Quick Start Guide
- Python Testing with Selenium
- Architecture Patterns with Python
- Crafting Test-Driven Software with Python
- Python Testing with pytest
- Python Testing with Selenium
- Python Unit Test Automation
- Testing In Python
- Testing Python
- Test-Driven Development with Python
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Test-Driven Development with Python
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
- Python Testing with Selenium
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Articles
- Anna-Lena Popkes: "Mocking in Python" - Mocking might seem confusing in the beginning but once you understand the basics it can be very helpful.
- async test patterns for Pytest - Learn some handy async examples and patterns for testing in Pytest.
- Getting Started With Property-Based Testing in Python With Hypothesis and Pytest
- How not to footgun yourself when writing tests - a showcase of flaky tests
- Stargirl Flowers: βMy Python testing style guideβ - An attempt to catalog some practices around testing Python projects. It's not meant to be treated as dogma.
- Test & Code: Python Testing - Test & Code is a weekly podcast hosted by Brian Okken. The show covers a wide array of topics including software engineering, development, testing, Python programming, and many related topics.
- Testing your Python Code with Hypothesis - A look at how Hypothesis can help you discover errors in your code.
- Patterns of flakey Python tests - This post details several patterns that cause flakey Python tests. Being aware of these common causes can help when investigating your own flakey tests.
- Unit testing Python code in Jupyter notebooks - This article covers several options for unit testing Python code in a Jupyter notebook.
- 30 best practices for software development and testing - These software engineering rules and testing best practices might help save you time and headaches.
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Videos
- PyCascades 2023 - Talk - Brian Okken: "Sharing is Caring - Sharing pytest Fixtures"
- PyCon US 2023 - Talk - Dan Craig: Testing Spacecraft with Pytest
- PyCon US 2023 - Talk - Dave Aronson: Kill All Mutants! (Intro to Mutation Testing)
- PyCon US 2023 - Talk - Shai Geva: 10 Ways To Shoot Yourself In The Foot With Tests
- PyCon US 2023 - Tutorial - Zac Hatfield-Dodds, Ryan Soklaski: Introduction to Property-Based Testing
- PyCascades 2023 - Talk - Brian Okken: "Sharing is Caring - Sharing pytest Fixtures"
- PyCon US 2023 - Talk - Dan Craig: Testing Spacecraft with Pytest
- PyCon US 2023 - Talk - Dave Aronson: Kill All Mutants! (Intro to Mutation Testing)
- PyCon US 2023 - Talk - Shai Geva: 10 Ways To Shoot Yourself In The Foot With Tests
- PyCon US 2023 - Tutorial - Zac Hatfield-Dodds, Ryan Soklaski: Introduction to Property-Based Testing
- PyCascades 2023 - Talk - Brian Okken: "Sharing is Caring - Sharing pytest Fixtures"
- PyCon US 2023 - Talk - Dan Craig: Testing Spacecraft with Pytest
- PyCon US 2023 - Talk - Dave Aronson: Kill All Mutants! (Intro to Mutation Testing)
- PyCon US 2023 - Talk - Shai Geva: 10 Ways To Shoot Yourself In The Foot With Tests
- PyCon US 2023 - Tutorial - Zac Hatfield-Dodds, Ryan Soklaski: Introduction to Property-Based Testing
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Related
- Awesome Python - A curated list of awesome Python frameworks, libraries, software and resources.
- Python test automation - A comprehensive curated list of python test automation frameworks, tools, libraries and software to help software engineers easily bootstrap test automation on python.
- commit-check - Check commit message formatting, branch naming, commit author, email, and more.
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Testing Frameworks
- doctest - (Python standard library) The doctest module searches for pieces of text that look like interactive Python sessions, and then executes those sessions to verify that they work exactly as shown.
- unittest - (Python standard library) Unit testing framework.
- awesome-pytest - A curated list of awesome pytest resources.
- hammett - Fast python test runner, compatible with a subset of pytest.
- maelstrom - Maelstrom is a fast Rust and Python test runner that runs every test in its own container. Tests are either run locally or distributed to a clustered job runner.
- async-asgi-testclient - A framework-agnostic library for testing ASGI web applications.
- nose2 - The successor to `nose`, based on `unittest2`.
- perftester - A lightweight framework for performance testing of Python functions; allows for testing of performance in terms of execution time and memory usage.
- promptimize - a prompt engineering evaluation and testing toolkit. It accelerates and provides structure around prompt engineering at scale with confidence, bringing some of the ideas behind test-driven development (TDD) to engineering prompts.
- sundew - Sundew is a testing framework for Python, implementing a new approach to testing. One that combines functional programming concepts and the general best practices for writing tests that we already know, and enforces them in a way that enables some really powerful features that make testing easier, enjoyable, and more effective.
- Robot Framework - A generic test automation framework.
- testbook - A unit testing framework extension for testing code in Jupyter Notebooks.
- vedro - Pragmatic testing framework for Python
- Ward - is a modern test framework for Python with a focus on productivity and readability.
- xdoctest - A rewrite of Python's builtin doctest module (with pytest plugin integration) with AST instead of REGEX.
- awesome-robotframework - A curated list of awesome Robot Framework resources and libraries.
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Tools
- ghostwriter - Writing tests with Hypothesis frees you from the tedium of deciding on and writing out specific inputs to test.
- Klara - Static analysis tools to automatic generate test case, based on SMT (z3) solver, with a powerful ast level inference system.
- logot - Test whether your code is logging correctly.
- Auger - Project to automatically generate unit tests for Python code.
- CrossHair - An analysis tool for Python that blurs the line between testing and type systems.
- importlab - A library that automatically infers dependencies for Python files. Importlab's main use case is to work with static analysis tools that process one file at a time, ensuring that a file's dependencies are analysed before it is.
- Pifpaf - A suite of fixtures and a command-line tool that allows to start and stop daemons for a quick throw-away usage. This is typically useful when needing these daemons to run integration testing.
- Pynguin - A tool that allows developers to generate unit tests automatically.
- pytest-codegen - Pytest-codgen will statically analyze your code to create pytest function stubs.
- pytestify - Automatically convert unittests to pytest.
- pytest-mock-generator - A pytest fixture wrapper for `mock_autogen`.
- teyit - A static analyzer and a refactoring tool to rewrite your unittest assertions in the right way.
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Assertions
- believe - A python package for json/dictionary validation.
- easycheck - A collection of assertion-like functions to be used in code, where assertion themselves should be avoided; `easycheck` includes also function aliases to be used in unit testing.
- expects - Expects is an expressive and extensible TDD/BDD assertion library for Python.
- expycted - Another Python expect pattern implementation. Simple, intuitive and approachable, with ability to plug in to any testing framework that relies on assertions.
- dirty-equals - A python library that (mis)uses the `__eq__` method to make python code (generally unit tests) more declarative and therefore easier to read and write.
- Precisely - Write precise assertions so you only test the behaviour you're really interested in.
- PyHamcrest - A framework for writing matcher objects, allowing you to declaratively define "match" rules.
- pytest_cache_assert - Cache assertion data to simplify regression testing of complex serializable data.
- sure - An idiomatic assertion toolkit with human-friendly failure messages, inspired by RSpec Expectations and should.js.
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Design by Contract
- icontract - Design-by-contract in Python3 with informative violation messages and inheritance.
- pact-python - Python version of Pact. Enables consumer driven contract testing, providing a mock service and DSL for the consumer project, and interaction playback and verification for the service provider project.
- deal - Design by contract for Python with static checker and test generation.
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Code Coverage
- Coverage.py - is a tool for measuring code coverage of Python programs.
- coverage-conditional-plugin - Conditional coverage based on any rules you define.
- diff_cover - Automatically find diff lines that need test coverage.
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Load Testing
- Dynamic Workload Model - Code to generate dynamic workload model. Useful for testing autoscaling in cloud or mimicking different load profile for different scenario.
- Grasshopper - A lightweight framework for performing load tests against an environment, primarily against an API. Grasshopper glues Locust, Pytest, some plugins (namely Locust InfluxDBListener ) and some custom code to provide a package that makes authoring load tests simple with very little boilerplate needed.
- Grizzly - is a framework to be able to easily define load scenarios, and is mainly built on-top of Locust and Behave.
- Locust - Scalable user load testing tool written in Python.
- pynonymizer - is a universal tool for translating sensitive production database dumps into anonymized copies.
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Mutation Testing
- Cosmic Ray - makes small changes to your source code, running your test suite for each one.
- Mutatest - Python mutation testing.
- Mutmut - is a mutation testing system for Python, with a strong focus on ease of use.
- MutPy - MutPy is a mutation testing tool for Python 3.x source code
- xmutant.py - Python 3.6 bytecode based mutation analysis framework
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Object Factories
- factory_boy - A test fixtures replacement for Python.
- mixer - Another fixtures replacement. Supports Django, Flask, SQLAlchemy, Peewee and etc.
- Model Bakery - offers you a smart way to create fixtures for testing in Django.
- polyfactory - A simple and powerful mock data generation library, based around type hints and supporting dataclasses, typed-dicts, pydantic models, msgspec structs and more.
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Penetration Testing
- fsociety - A Modular Penetration Testing Framework.
- python-pentest-tools - Python tools for penetration testers.
- fencer - Fencer is an automated API security testing tool. It's an experimental project to see how much of the API security testing process can be automated.
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Property Based Testing
- Atheris - is a coverage-guided Python fuzzing engine. It supports fuzzing of Python code, but also native extensions written for CPython.
- hypofuzz - Adaptive fuzzing of Hypothesis tests.
- Hypothesis - is an advanced Quickcheck style property based testing library.
- hypothesis-crosshair - Add the power of solver-based symbolic execution to your Hypothesis tests with CrossHair.
- icontract-hypothesis - Instead of writing manually the Hypothesis search strategies for a function, `icontract-hypothesis` infers them based on the function's precondition.
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Snapshot Tests
- ApprovalTests - work by comparing the test results to a golden master.
- SnapshotTest - is a way to test your APIs without writing actual test cases.
- syrupy - is a zero-dependency pytest snapshot plugin. It enables developers to write tests which assert immutability of computed results.
- VCR.py - Record and replay HTTP interactions on your tests.
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Speed
- Partial Testing - Run only the tests that are relevant for your changes.
- Pytest-incremental - analyses your project structure and file modifications between test-runs to modify the order tests are executed and de-select tests.
- pytest-testmon - Selects tests affected by changed files. Continuous test runner when used with pytest-watch.
- Awesome pytest speedup - A checklist of best practices to speed up your pytest suite.
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Test Runners
- green - A clean, colorful test runner.
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UI Testing
- Flybirds - is a front-end UI automation test framework based on BDD mode, providing a series of out-of-the-box tools and complete documentation.
- Golem - is a test framework and a complete tool for browser automation. Tests can be written with code in Python, codeless using the web IDE, or both.
- Lost Pixel - is an open source visual regression testing tool. Run visual regression tests on your Storybook and Ladle stories and on your application pages.
- LuluTest - is an open source browser automation framework using Python and Selenium.
- PyAutoGUI - is a cross-platform GUI automation Python module for human beings.
- pytest-ui-automatic - Playwright Python tool practice pytest pytest-bdd screen-play page-object allure cucumber-report.
- selene - User-oriented Web UI browser tests in Python (Selenide port).
- SeleniumBase - is an all-in-one Python framework for automated browser testing. Tests are run with "pytest", and use WebDriver APIs for web-page interaction.
- splinter - Open source tool for testing web applications.
- squape - is a package that extends Squish API providing convenience tools for everyday automated test cases development.
- helium - is great for web automation. Helium makes it easier to use.
- sixpack - A language-agnostic A/B Testing framework.
Programming Languages
Categories
Resources
106
Mock and Stub
19
Testing Frameworks
16
Static Checks
14
UI Testing
12
Tools
12
Rest API Testing
10
Assertions
9
Fake Data
6
Mutation Testing
5
Memory Management
5
Load Testing
5
Property Based Testing
5
Object Factories
4
Speed
4
Snapshot Tests
4
Behavior-driven Development
3
Penetration Testing
3
Code Coverage
3
Design by Contract
3
Test Runners
1
Sub Categories
Keywords
python
64
testing
46
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11
pytest
10
http
10
python3
10
test-automation
8
testing-framework
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mock
8
pytest-plugin
7
linter
6
unit-testing
6
webdriver
5
performance-testing
5
bdd
5
selenium
5
automation
5
mocking
5
static-analysis
5
cli
4
static-code-analysis
4
api
4
mutation-testing
4
fixtures
4
e2e-testing
3
gherkin
3
load-testing
3
performance
3
locust
3
benchmarking
3
testing-library
3
requests
3
code-quality
3
unit-test
3
django
3
test-runner
3
fuzzing
3
security
3
openapi
3
behavior-driven-development
3
awesome
3
tdd
3
test
3
mypy
3
typing
2
validation
2
openapi3
2
fake
2
security-tools
2
faker
2