getsentry/responses
Responses
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 of connection timeouts, network errors, and HTTP redirections.
The library provides capabilities for dynamic API simulation using callback-driven responses and sequential response queues to test state changes. It includes tools for request data verification and attribute validation to ensure that outgoing headers, bodies, and query parameters meet expected criteria.
Mock configurations and registries are managed through decorators and context managers to isolate behaviors between test cases.
Features
- API Request Mocking - Intercepts outgoing HTTP calls made with the Python Requests library to return predefined simulated responses.
- HTTP Mock Servers - Intercepts outgoing requests to specific URLs and returns predefined status codes, headers, and bodies to simulate a server.
- Traffic Serialization - Persists captured network responses to structured files on disk for offline playback.
- Request Matching Engines - Uses a lookup table of URL patterns and HTTP methods to resolve incoming requests to simulated responses.
- Module Monkey Patching - Replaces the internal request methods of the Requests library to divert traffic to a mock registry.
- Python HTTP Mocking Libraries - Provides a specialized library for intercepting and mocking HTTP calls within Python applications using the Requests library.
- API Response Recordings - Captures real API responses from a server and saves them to files for deterministic replay in tests.
- API Integration Testing - Provides tools to verify that applications correctly send requests and handle various server responses using mock data.
- API Simulation and Mocking - Implements flexible mock servers that generate different responses based on request bodies, headers, or sequences.
- Request Verification - Includes a framework for asserting that outgoing requests contain the expected headers, bodies, and query parameters.
- Mock Registry Management - Add, replace, or remove registered mock data dynamically during test execution to simulate different server scenarios.
- Network Failure Simulations - Simulates network-level errors such as connection timeouts and failures to verify application resilience.
- Sequential Response Queues - Maintains an ordered queue of responses for a single endpoint to simulate evolving server states.
- Exception Simulation Utilities - Triggers specific Python exceptions instead of standard HTTP responses to test application error handling.
- Predicate-Based Validations - Matches requests using custom logic and predicates applied to headers, bodies, and query parameters.
- Context Managers - Implements Python decorators and context managers to isolate mock configurations and reset the registry between tests.
- Dynamic Response Callbacks - Provides callback functions that generate mock HTTP responses based on incoming request data.
- Response Sequencing - Returns a sequence of different responses for the same URL to test state changes and retry logic.
- HTTP Traffic Recording - Captures real network interactions and saves them to files for deterministic replay in test suites.
- Lifecycle Management - Provides automated handling of mock setup, teardown, and state resetting using decorators and context managers.
- Network Request Assertions - Verifies that specific network requests were executed and tracks the number of times they were called.
- Outgoing Request Validation - Validates that outgoing HTTP request bodies and headers match expected schemas or criteria.
- Mocking and Fixtures - Utility for mocking the requests library.
- Mocking Libraries - Utility for mocking network requests.
- Testing Tools - Listed in the “Testing Tools” section of the Awesome Python awesome list.
