rapidtest 0.8.0

A lightweight library for REST API testing with HTTP, ASGI, and performance testing

RapidTest

A lightweight library for REST API testing with ASGI/HTTP mode, fake data generation, and performance testing.

Features

• ASGI Testing - Test FastAPI/Starlette apps directly without HTTP server
• HTTP Testing - Test external APIs with GET, POST, PUT, PATCH, DELETE
• Built-in response validation (status, JSON body, required keys)
• Fake data generation with Faker
• Performance testing with concurrent users (threading + requests)
• Test any endpoint with just one line of code

Installation

pip install rapidtest

CLI

Generate a test skeleton file:

rapidtest init

• ASGI Testing - Test FastAPI/Starlette apps directly without HTTP server
• HTTP Testing - Test external APIs with GET, POST, PUT, PATCH, DELETE
• Built-in response validation (status, JSON body, required keys)
• Fake data generation with Faker
• Performance testing with concurrent users (threading + requests)
• Test any endpoint with just one line of code

Installation

pip install rapidtest

CLI

Generate a test skeleton file:

rapidtest init

Quick Start (ASGI mode)

Use this when you want to test your ASGI app directly (for example FastAPI) without network overhead.

from backend.main import app
from rapidtest import ASGITest, StatusCode


tester = ASGITest(app=app)

tester.get(
    path="/ping",
    status=StatusCode.OK_200,
    json={"ok": True}
)

Output:

✅ 1. PASSED
time: 0.01 s

Quick Start (HTTP mode)

from rapidtest import HTTPTest, StatusCode

api = HTTPTest(url="http://localhost:8000")

api.get(
    path="/health",
    status=StatusCode.OK_200,
    keys=["message"]
)

payload = {"username": "hector", "password": "secret"}
api.post(
    path="/login",
    json=payload,
    status=StatusCode.OK_200,
    keys=["token"]
)

Output:

✅ 1. PASSED
✅ 2. PASSED
time: 0.05 s

Data Generation

from rapidtest import Data

auth = Data.generate_auth_user()

print(auth)  # {"username": "...", "password": "..."}

Useful helpers include:

• generate_name()
• generate_email()
• And more...

Performance Testing

from rapidtest import Performance

perf = Performance(
    base_url="http://localhost:8000",
    users=20,
    duration=15,
    timeout=10
)

# Add multiple endpoints with different methods
perf.add_task(endpoint="/health", method="GET")
perf.add_task(endpoint="/login", method="POST", json={"user": "test"})

results = perf.run()

Returned metrics:

• total_requests
• successful_requests
• failed_requests
• success_rate
• avg_response_time
• min_response_time
• max_response_time
• requests_per_second
• duration
• users

Requirements

• Python >=3.10
• requests>=2.25.1
• faker>=13.0.0

Project Info

• Version: 0.7.2
• Author: Hector Rosales
• License: MIT
• Homepage: https://github.com/hector-2710/rapidtest
• Issues: https://github.com/hector-2710/rapidtest/issues