rapidtest 0.3.3

A comprehensive testing framework for REST APIs with functional and performance testing capabilities

RapidTest 🚀

A super lightweight and blazingly fast library to simplify REST API testing. Designed to be intuitive, fast to implement.

✨ Features

• Simplicity: Perform HTTP requests (GET, POST, PUT, PATCH, DELETE) in a single line with comprehensive response validation.
• Automatic Validation: Automatically compare status codes and response bodies with detailed error reporting.
• Data Generator: Integrated random data generator (using Faker) for dynamic testing with flexible user creation.
• Performance Testing: Built-in load testing with threading - no external tools needed!

🛠️ Installation

Install the required dependencies:

pip install rapidtest

🚀 Quick Start

1. Initialize RapidTest

from rapidtest import Test

# Configure your API's base URL
tester = Test(url="http://localhost:8000")

2. Run Tests

GET

tester.get(endpoint="/users", expected_status=200)

POST with Body Validation

user_data = {"username": "Uziel", "password": "Mypass123"}
tester.post(endpoint="/user", json=user_data, expected_status=201, expected_json=user_data)

Advanced Example with Dynamic Data

from rapidtest import Test, data

# Initialize tester
tester = Test(url="http://127.0.0.1:8000")

# Generate dynamic test data
user = data.generate_user(id=True, name=True, email=True, age=True, password=True, username=True)

# Test user creation
tester.post(endpoint="/user", json=user, expected_status=201)

3. Generate Random Data

Use the data class to create test data on the fly:

from rapidtest import data

# Generate specific data types
auth_user = data.generate_auth_user()
email = data.generate_email()
name = data.generate_name()
phone = data.generate_phone()

print(auth_user) # {'username': '...', 'password': '...'}

Additional Parameters

All HTTP methods support additional parameters:

# Query parameters
tester.get(endpoint="/users", params={"page": 1, "limit": 10})

# Custom headers
tester.post(endpoint="/auth", json=user_data, headers={"Content-Type": "application/json"})

⚡ RapidTest vs FastAPI TestClient

See the difference yourself! RapidTest dramatically simplifies your testing code:

📋 FastAPI's TestClient Approach

# Traditional FastAPI TestClient - More verbose
from fastapi.testclient import TestClient
from api import app

client = TestClient(app)

def test_read_item():
    response = client.get("/items/foo")
    assert response.status_code == 200
    assert response.json() == {"id": "foo", "title": "Foo"}

# Result: 4 lines for the test

🚀 RapidTest Approach

# RapidTest - Clean and concise
from rapidtest import Test

fastTest = Test(url="http://localhost:8000")
fastTest.get(endpoint="/items/foo", expected_status=200, expected_json={"id": "foo", "title": "Foo"})

# Result: 2 lines for the test

🎯 Key Advantages

Feature	FastAPI TestClient	RapidTest
Lines of code	4+ lines	2 lines
Assertions	Manual assert statements	Built-in validation
Setup complexity	Import app, create client	Simple URL configuration
Error reporting	Basic assertion errors	Detailed, colored output
Data generation	Manual or external tools	Built-in data class
Performance testing	Requires additional tools	Built-in Performance class

Result: 50% less code, 100% more clarity! ✨

🚀 Performance Testing

Use the Performance class to run simple load tests on your APIs: Beta*

from rapidtest import Performance

# Initialize performance test
perf = Performance(
    base_url="http://localhost:8000",
    users=10,       # Number of concurrent users
    duration=30,    # Test duration in seconds  
    timeout=10      # Request timeout
)

# Add endpoint to test
perf.add_get_task(endpoint="/api/users")

# Run the test and shown results in terminal)
perf.run()

Performance Test Output

See real results in action:

📊 Reports

See how your tests look with real colorized output:

✅ Successful Test

❌ Failed Test

📁 Project Structure

• rapidtest/
  • RapidTest.py: Core library logic with comprehensive API testing methods and detailed response handling
  • RapidData.py: Random data generator with flexible user creation and comprehensive fake data
  • Performance.py: Simple performance testing (no external deps)
  • Utils.py: Formatting and reporting utilities
  • __init__.py: Module configuration

🔧 Dependencies

• requests>=2.25.1: For making HTTP requests
• faker>=13.0.0: For generating fake data

📋 Requirements

• Python >=3.7

📖 Project Information

• Version: 0.3.3
• Author: Hector Rosales
• License: MIT
• Homepage: https://github.com/hector-dev/rapidtest

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⚡ Built for speed and simplicity - because testing should be fast and fun! 🛠️✨