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AI-powered Locust load test generator from API documentation

Project description

DevDox AI Locust

License: Apache 2.0 Python 3.12+ Code style: black Quality Gate Status

AI-powered Locust load test generator from API documentation

DevDox AI Locust automatically generates comprehensive Locust load testing scripts from your API documentation (OpenAPI/Swagger specs). Using advanced AI capabilities, it creates realistic test scenarios, handles complex authentication flows, and generates production-ready performance tests.

[0.1.8] - 2025-11-18

๐Ÿ†• What's New in 0.1.8

๐Ÿ” Smart Authentication Integration:

  • Seamless integration with existing base_workflow.py authentication patterns
  • Automatic detection and reuse of existing authentication methods
  • Zero duplication of authentication logic across test files
  • Smart 401 response handling with automatic re-authentication
  • Configurable authentication retry mechanisms

๐Ÿ“Š Comprehensive Test Scenario Framework:

  • Weighted scenario distribution for realistic load patterns:
    • 60% Positive scenarios (happy path, valid data)
    • 25% Negative scenarios (validation errors, missing fields)
    • 10% Edge cases (boundary testing, unicode characters)
    • 4% State-dependent scenarios (concurrent operations, duplicates)
    • 1% Security scenarios (injection attacks, vulnerability detection)
  • Enhanced test data generators supporting all scenario types
  • Security vulnerability detection with immediate alerting for critical issues

โœจ Features

  • ๐Ÿค– AI-Enhanced Generation: Uses Together AI to create intelligent, realistic load test scenarios
  • ๐Ÿ“š OpenAPI/Swagger Support: Automatically parses OpenAPI 3.0 and Swagger 2.0 specifications
  • ๐Ÿ”ง Production-Ready Code: Generates clean, maintainable Locust test files
  • ๐ŸŽฏ Smart Test Scenarios: Creates CRUD workflows, authentication flows, and error handling
  • ๐Ÿ“Š Realistic Data: Generates appropriate test data using Faker
  • ๐Ÿ› ๏ธ Template-Based: Highly customizable Jinja2 templates for different testing needs
  • ๐Ÿ”„ Hybrid Approach: Combines rule-based generation with AI enhancement
  • ๐Ÿ“ˆ Comprehensive Coverage: Handles various HTTP methods, content types, and response scenarios
  • โšก Asynchronous Processing: Fast, non-blocking test generation with async/await

๐Ÿš€ Quick Start

Installation

# Install from PyPI (when published)
pip install devdox-ai-locust

# Or install from source
git clone https://github.com/montymobile1/devdox-ai-locust.git
cd devdox-ai-locust
pip install -e .

Prerequisites

  1. Python 3.12+ - Required for modern async/await syntax and type hints
  2. Together AI API Key - For AI-enhanced generation capabilities

Configuration

  1. Get your Together AI API key from Together AI
  2. Set up your environment:
# Copy example environment file
cp .env.example .env

# Edit .env and add your API key
echo "API_KEY=your_together_ai_api_key_here" > .env

Basic Usage

# Generate from OpenAPI URL
devdox_ai_locust generate --openapi-url https://api.example.com/openapi.json --output ./tests

# Generate with custom configuration
devdox_ai_locust generate \
   https://petstore3.swagger.io/api/v3/openapi.json \
  --output ./petstore-tests \
  --together-api-key your_api_key \
  
 # Generate with db integration 
devdox_ai_locust generate \
  https://petstore3.swagger.io/api/v3/openapi.json \
  --output ./petstore-tests \
  --db-type mongo \

๐Ÿš€ Installation with Inputs

Add this step to your GitHub Actions workflow:

- name: DevDox Locust Test Generator
  uses: montymobile1/devdox-ai-locust@v0.1.6
  with:
    swagger_url: "https://portal-api.devdox.ai/openapi.json"
    output: "generated_tests"
    users: "15"
    spawn_rate: "3"
    run_time: "10m"
    together_api_key: ${{ secrets.TOGETHER_API_KEY }}


## ๐Ÿ“– Documentation

### Command Line Interface

```bash
devdox_ai_locust generate [OPTIONS] SWAGGER_URL
Option Short Type Description Default
--output -o Path Output directory for generated tests output
--users -u Integer Number of simulated users 10
--spawn-rate -r Float User spawn rate (users/second) 2
--run-time -t String Test duration (e.g., 5m, 1h) 5m
--host -H String Target host URL None
--auth/--no-auth Boolean Include authentication True
--dry-run Flag Generate without running False
--custom-requirement String Custom AI instructions None
--together-api-key String Together AI API key From env

Generated Test Structure

locust_tests/
โ”œโ”€โ”€ locust.py              # Main Locust test file
โ”œโ”€โ”€ config.py              # Test configuration
โ”œโ”€โ”€ test_data.py           # Test data generators
โ”œโ”€โ”€ utils.py               # Utility functions
โ”œโ”€โ”€ requirements.txt       # Python dependencies
โ”œโ”€โ”€ .env.example          # Environment variables template
โ”œโ”€โ”€ README.md             # Test documentation
โ”œโ”€โ”€ workflows/
โ”‚   โ”œโ”€โ”€ user_workflow.py   # User-related test scenarios
โ”‚   โ”œโ”€โ”€ auth_workflow.py   # Authentication workflows
โ”‚   โ””โ”€โ”€ crud_workflow.py   # CRUD operation workflows
โ””โ”€โ”€ data/
    โ”œโ”€โ”€ users.json         # Sample user data
    โ””โ”€โ”€ test_cases.json    # Predefined test cases

๐Ÿ”ง Advanced Usage

Custom Templates

Create custom Jinja2 templates for specialized test generation:

# custom_template.py.j2
from locust import HttpUser, task, between

class {{ class_name }}User(HttpUser):
    wait_time = between(1, 3)
    
    def on_start(self):
        """Setup method called before tasks"""
        self.token = self.login()
    
    {% for endpoint in endpoints %}
    @task({{ endpoint.weight | default(1) }})
    def {{ endpoint.method_name }}(self):
        """{{ endpoint.description }}"""
        # Custom task implementation
        {{ endpoint.ai_generated_code | indent(8) }}
    {% endfor %}

Programmatic Usage

from devdox_ai_locust import HybridLocustGenerator
from devdox_ai_locust.config import Settings

# Initialize generator
config = Settings()
generator = HybridLocustGenerator(config)

# Generate from OpenAPI spec
async def generate_tests():
    files, workflows = await generator.generate_from_url(
        "https://api.example.com/openapi.json",
        output_dir="./tests",
        ai_enhanced=True
    )
    
    print(f"Generated {len(files)} test files")
    print(f"Created {len(workflows)} workflows")

# Run generation
import asyncio
asyncio.run(generate_tests())

๐Ÿงช Development

Setup Development Environment

# Clone repository
git clone https://github.com/montymobile1/devdox-ai-locust.git
cd devdox-ai-locust

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install in development mode
pip install -e ".[dev,test,ai]"

# Install pre-commit hooks
pre-commit install

Running Tests

# Use the test runner script
coverage run -m pytest tests/

Project Structure

src/devdox_ai_locust/
โ”œโ”€โ”€ __init__.py
โ”œโ”€โ”€ cli.py                      # Command line interface
โ”œโ”€โ”€ config.py                   # Configuration management
โ”œโ”€โ”€ locust_generator.py         # Basic test generation
โ”œโ”€โ”€ hybrid_loctus_generator.py  # AI-enhanced generation
โ”œโ”€โ”€ templates/                  # Jinja2 templates
โ”‚   โ”œโ”€โ”€ locust.py.j2
โ”‚   โ”œโ”€โ”€ config.py.j2
โ”‚   โ””โ”€โ”€ workflow.py.j2
โ”œโ”€โ”€ schemas/                    # Data models and validation
โ”‚   โ”œโ”€โ”€ processing_result.py
โ”‚   โ””โ”€โ”€ endpoint_schema.py
โ”œโ”€โ”€ utils/                      # Utility modules
โ”‚   โ”œโ”€โ”€ swagger_utils.py
โ”‚   โ”œโ”€โ”€ open_ai_parser.py
โ”‚   โ””โ”€โ”€ file_creation.py
โ””โ”€โ”€ prompt/                     # AI prompt templates
    โ”œโ”€โ”€ system_prompts.py
    โ””โ”€โ”€ enhancement_prompts.py

Development Workflow

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Make your changes
  4. Add tests for new functionality
  5. Run the test suite (make test)
  6. Commit your changes (git commit -m 'Add amazing feature')
  7. Push to the branch (git push origin feature/amazing-feature)
  8. Open a Pull Request

Code Standards

  • Python 3.12+ with type hints
  • Black for code formatting
  • isort for import sorting
  • pytest for testing
  • mypy for type checking
  • Pre-commit hooks for quality gates

๐Ÿ“‹ Requirements

System Requirements

  • Python: 3.12 or higher
  • Memory: 512MB RAM minimum, 1GB recommended
  • Storage: 100MB for installation, additional space for generated tests

Dependencies

Core Dependencies

  • locust - Load testing framework
  • click - CLI framework
  • pyyaml - YAML parsing
  • requests - HTTP client
  • pydantic - Data validation
  • jinja2 - Template engine
  • rich - Rich text output
  • faker - Test data generation

AI Dependencies

  • langchain-together - Together AI integration
  • together - Together AI Python client

Development Dependencies

  • pytest - Testing framework
  • black - Code formatter
  • mypy - Type checker
  • pre-commit - Git hooks

๐Ÿ” Examples

Example 1: E-commerce API

# Generate tests for an e-commerce API
devdox_ai_locust generate \
   https://api.shop.example.com/v1/openapi.json \
  --output ./ecommerce-tests 

# The generator will create:
# - Product browsing scenarios
# - Shopping cart workflows  
# - Checkout and payment flows
# - User registration and login
# - Order management tests

โ“ FAQ

Q: What API specification formats are supported? A: We support OpenAPI 3.0+ and Swagger 2.0 specifications in JSON and YAML formats.

Q: Do I need an AI API key? A: Yes, for AI-enhanced generation you need a Together AI API key. Basic generation works without AI.

Q: Can I customize the generated test templates? A: Absolutely! You can provide custom Jinja2 templates using the --template-dir option.

Q: How do I handle authentication in generated tests? A: The generator automatically detects authentication schemes from your OpenAPI spec and creates appropriate test flows.

Q: Can I run tests against different environments? A: Yes, use environment variables or configuration files to specify different target hosts and settings.

Q: What if my API has complex business logic? A: The AI enhancement feature analyzes your API patterns and generates realistic business workflows, not just individual endpoint tests.

๐Ÿ› Troubleshooting

Common Issues

Import Errors

# Ensure proper installation
pip install -e .

# Check Python path
python -c "import devdox_ai_locust; print('OK')"

API Key Issues

# Verify API key is set
echo $API_KEY

# Test API connectivity
python -c "from together import Together; print(Together(api_key='your_key').models.list())"

Template Errors

# Validate your OpenAPI spec
# Use online validators like swagger.io/tools/swagger-editor/

# Check template syntax
# Ensure custom templates use valid Jinja2 syntax

๐Ÿ“„ License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

๐Ÿ™ Acknowledgments

  • Locust - The amazing load testing framework that powers our generated tests
  • Together AI - Providing the AI capabilities for intelligent test generation
  • OpenAPI Initiative - For standardizing API documentation
  • Python Community - For the excellent libraries and tools

Made with โค๏ธ by the DevDox team

Transform your API documentation into powerful load tests with the magic of AI! ๐Ÿš€

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