rapidtest 0.3.2

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, and with clear colorized reports - no heavy dependencies!

✨ 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.
• Fast & Lightweight: Minimal dependencies, maximum speed!
• 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)

PATCH / PUT / DELETE

# Update data
tester.patch(endpoint="/user/hector", json={"password": "new_password"}, expected_status=200)

# Delete resource  
tester.delete(endpoint="/user/hector", expected_status=204)

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)

# Test user retrieval 
tester.get(endpoint=f"/users/{user['email']}", expected_status=200)

# Test user update
tester.put(endpoint=f"/user/{user['id']}", json=user, expected_status=200)

# Test user deletion
tester.delete(endpoint=f"/user/{user['id']}", expected_status=202)

3. Generate Random Data

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

from rapidtest import data

# Generate a complete user with all fields
user = data.generate_user(id=True, name=True, email=True, age=True, password=True, username=True)
print(user) # {'id': '...', 'name': '...', 'email': '...', 'age': '25', 'password': '...', 'username': '...'}

# 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"})

# Form data
tester.post(endpoint="/upload", data={"file": "content"})

# Additional requests arguments
tester.get(endpoint="/secure", timeout=30, verify=False)

🚀 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()

Simple Performance Testing Features

• No external dependencies: Uses only requests and threading
• Real-time terminal output: See results as they happen
• Basic load simulation: Multiple concurrent users
• Essential metrics: Response times, success rates, RPS

Performance Test Output

See real results in action:

📊 Reports

See how your tests look with real colorized output:

✅ Successful Test

❌ Failed Test

Colors:

• ✅ Green for PASSED tests
• ❌ Red for FAILED tests
• 🔵 Blue for labels and info
• 🟡 Yellow for warnings

📁 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: 0.3.2
• 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! 🛠️✨