Responses is a Python mocking library designed to intercept outgoing HTTP calls made with the Requests library to return predefined simulated responses. It functions as a request verification framework and a network simulation tool, allowing for the verification of application behavior against various API response patterns without making real network calls. The project distinguishes itself through a traffic recorder that captures real network interactions and saves them to files for deterministic replay. It further enables the simulation of complex network scenarios, including the triggering
Faker is a Python library designed to generate realistic synthetic data for software testing, database prototyping, and privacy-preserving anonymization. It provides a comprehensive suite of tools to create diverse information types, including personal identities, financial records, geographic locations, and technical system metadata, allowing developers to populate environments with mock data that mimics real-world structures. The library is built on a modular provider architecture that supports dynamic method dispatch, enabling users to extend functionality by registering custom data genera
The code coverage tool for Python
Automatically mock your HTTP interactions to simplify and speed up testing
Mock HTTPX with awesome request patterns and response side effects π¦
The main features of lundberg/respx are: Mocking and Fixtures, Testing Tools.
Open-source alternatives to lundberg/respx include: joke2k/faker β Faker is a Python library designed to generate realistic synthetic data for software testing, database prototyping,β¦ litestar-org/polyfactory. coveragepy/coveragepy β The code coverage tool for Python. getsentry/responses β Responses is a Python mocking library designed to intercept outgoing HTTP calls made with the Requests library toβ¦ kevin1024/vcrpy β Automatically mock your HTTP interactions to simplify and speed up testing. lk-geimfari/mimesis β Mimesis is a Python synthetic data generator used to create realistic fake datasets and mock data for software testingβ¦