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pytest plugin for HTTP testing using JSON files

Project description

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pytest-httpchain

A pytest plugin for testing HTTP endpoints.

Overview

pytest-httpchain is an integration testing framework for HTTP APIs based on httpx lib.
It aims at helping with common HTTP API testing scenarios, where user needs to make several calls in specific order using data obtained along the way, like auth tokens or resource ids.

Why pytest-httpchain?

Testing HTTP APIs with plain pytest often leads to these pain points:

  • Boilerplate accumulates — Every test repeats the same setup: create client, set headers, make request, parse response, assert. The actual test intent gets buried.
  • Data threading is manual — When one call returns a token or ID needed by the next, you end up with fragile helper functions passing state around.
  • Common patterns get copy-pasted — Auth flows, base URLs, shared headers end up duplicated across test files. Fixtures might help, but they are not designed for that.
  • Code reviews are noisy — The actual test logic is rarely clear because of all the boilerplate and helpers, following changes gets overwhelming quickly.

pytest-httpchain offers a more structured approach.

Features

Declarative JSON format

Test scenarios are JSON documents that describe what to test, not how. No setup code to scroll through — the request and assertions are right there.

$ref with deep merging

Reuse arbitrary parts of your scenarios with JSONRef. Properties merge with type checking, so you can compose scenarios from shared fragments (auth flows, common headers, base URLs).

Multi-stage execution

Each scenario contains 1+ stages executed in order. One stage failure stops the chain. Use always_run for cleanup stages that should execute regardless.

Common data context

A key-value store persists throughout scenario execution. Variables, fixtures, and saved response data all live here. Use template expressions ({{ var }}) anywhere in your requests — substitution happens dynamically before each stage.

Response processing

  • JMESPath — Extract values from JSON responses directly
  • JSON Schema — Validate response structure against a schema
  • User functions — Call Python functions for custom extraction, verification, or authentication

Full pytest integration

Markers, fixtures, parametrization, and other plugins work as expected. You're not locked into a separate ecosystem.

Quick Start

Create a JSON test file named like test_<name>.<suffix>.json (default suffix is http):

# conftest.py
import pytest
from datetime import datetime

@pytest.fixture
def now_utc():
    return datetime.now()
{
    "substitutions": [
        {
            "vars": {
                "user_id": 1
            }
        }
    ],
    "stages": {
        "get_user": {
            "request": {
                "url": "https://api.example.com/users/{{ user_id }}"
            },
            "response": [
                {
                    "verify": {
                        "status": 200
                    }
                },
                {
                    "save": {
                        "jmespath": {
                            "user_name": "user.name"
                        }
                    }
                }
            ]
        },
        "update_user": {
            "fixtures": ["now_utc"],
            "request": {
                "url": "https://api.example.com/users/{{ user_id }}",
                "method": "PUT",
                "body": {
                    "json": {
                        "user": {
                            "name": "{{ user_name }}_updated",
                            "timestamp": "{{ str(now_utc) }}"
                        }
                    }
                }
            },
            "response": [
                {
                    "verify": {
                        "status": 200
                    }
                }
            ]
        },
        "cleanup": {
            "always_run": true,
            "request": {
                "url": "https://api.example.com/cleanup",
                "method": "POST"
            }
        }
    }
}

Scenario we created:

  • common data context is seeded with the first variable user_id
  • get_user
    url is assembled using user_id variable from common data context
    HTTP GET call is made
    we verify the call returned code 200
    assuming JSON body is returned, we extract a value by JMESPath expression user.name and save it to common data context under user_name key
  • update_user
    now_utc fixture value is injected into common data context
    url is assembled using user_id variable from common data context
    we create JSON body in place using values from common data context, note that now_utc is converted to string in place
    HTTP PUT call with body is made
    we verify the call returned code 200
  • cleanup
    finalizing call meant for graceful exit
    always_run parameter means this stage will be executed regardless of errors in previous stages

For detailed usage guide see the full documentation.

Installation

Install normally via package manager of your choice from PyPi:

pip install pytest-httpchain

or directly from Github, in case you need a particular ref:

pip install 'git+https://github.com/aeresov/pytest-httpchain@main'

Configuration

  • Test file discovery is based on this name pattern: test_<name>.<suffix>.json. The suffix is configurable as pytest ini option, default value is http.
  • $ref instructions can point to other files; absolute and relative paths are supported. You can limit the depth of relative path traversal using ref_parent_traversal_depth ini option, default value is 3.
  • Template expressions support list/dict comprehensions. You can limit the maximum comprehension length using max_comprehension_length ini option, default value is 50000.
  • Parallel stage iterations (repeat/foreach) have a safety limit configurable via max_parallel_iterations ini option, default value is 10000.

MCP Server

pytest-httpchain includes an MCP (Model Context Protocol) server to aid AI code assistants.

Setup

Install the MCP server config and Claude Code skill into your project:

uvx pytest-httpchain install --skill --mcp

Or configure manually in .mcp.json:

{
    "mcpServers": {
        "pytest-httpchain": {
            "command": "uvx",
            "args": ["pytest-httpchain", "mcp"]
        }
    }
}

Features

The MCP server provides:

  • Scenario validation - validate test scenario and scan for possible problems
  • Claude Code skill - authoring guidance for writing test scenarios

Documentation

Thanks

This project was inspired by Tavern and pytest-play.

httpx does comms.
Pydantic keeps structure.
simpleeval powers templates.
pytest-order sorts chain.
pytest-datadir saved me a lot of elbow grease while testing.

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