E2E Testing Framework for Microservices
Project description
Testing Engine Core
A reusable E2E testing framework for microservices architectures.
Features
- 🎯 Universal: Works with any REST API microservices
- 🔧 Flexible: Dynamic service registration - no hardcoded dependencies
- 🧪 Complete: HTTP requests, database assertions, message queue monitoring
- 📝 Declarative: Clean DSL for defining test scenarios
- 🔌 Extensible: Custom clients and step handlers
- ✅ Production-Ready: Battle-tested in real-world microservices environments
Installation
From PyPI (Recommended)
pip install testing-engine-core
From Source (Development)
git clone https://github.com/MysticAladin/testing-engine-core.git
cd testing-engine-core
pip install -e .
Quick Start
Basic Usage
from engine.orchestrator import TestOrchestrator
from engine.scenario import TestScenario
from engine.config import EngineConfig, ServiceConfig
# Configure for your services
config = EngineConfig()
config.services = ServiceConfig.from_dict({
"api": "http://localhost:8000"
})
orchestrator = TestOrchestrator(config)
# Create test scenario
scenario = TestScenario("User Registration")
scenario.http_request(
service="api",
method="POST",
endpoint="/api/users/register",
json_data={
"username": "testuser",
"email": "test@example.com",
"password": "SecurePass123!"
},
expected_status=201
)
# Execute
result = orchestrator.execute_scenario(scenario)
print(f"Test status: {result['status']}")
orchestrator.close()
Custom Services (Any Architecture)
from engine.config import EngineConfig, ServiceConfig
# Configure for your services
config = EngineConfig()
config.services = ServiceConfig.from_dict({
"order": "http://order-api:8001",
"payment": "http://payment-api:8002",
"inventory": "http://inventory-api:8003"
})
orchestrator = TestOrchestrator(config)
# Use your service names
scenario = TestScenario("Order Flow")
scenario.http_request("order", "POST", "/api/orders", json_data=order_data)
scenario.http_request("payment", "POST", "/api/charge", json_data=payment_data)
orchestrator.execute_scenario(scenario)
Environment-Agnostic Configuration
Use the built-in config loader to write tests that work across dev/staging/prod:
from engine import get_test_config, get_service_url
from engine.clients import GenericServiceClient
# Load config from environment variables or config files
config = get_test_config() # Auto-loads from TEST_ENV or config files
# Get service URLs
api_url = get_service_url('api')
client = GenericServiceClient(api_url)
# Or use with orchestrator
from engine.config import EngineConfig, ServiceConfig
engine_config = EngineConfig()
engine_config.services = ServiceConfig.from_dict(config['services'])
orchestrator = TestOrchestrator(engine_config)
See Configuration Guide for details.
Custom Authentication
from engine.clients import GenericServiceClient
class AuthClient(GenericServiceClient):
def __init__(self, base_url, api_key):
super().__init__(
base_url,
default_headers={"Authorization": f"Bearer {api_key}"}
)
# Register custom client
orchestrator.register_service("secure_api", AuthClient(url, "your-api-key"))
Core Components
TestOrchestrator
Coordinates test execution across multiple services:
- HTTP client management
- Database inspection
- Message queue monitoring
- Test scenario execution
TestScenario
Declarative test definition:
http_request()- Make HTTP callswait_for_message()- Wait for RabbitMQ messagesassert_database()- Verify database statecustom_step()- Add custom logic
GenericServiceClient
Universal HTTP client for any REST API:
- Automatic retries
- Timeout handling
- Convenience methods (
get_json,post_json, etc.) - Custom headers support
Configuration
Environment Variables
# Services
export USER_SERVICE_URL=http://localhost:8001
export NOTIFICATION_SERVICE_URL=http://localhost:8002
export ADMIN_SERVICE_URL=http://localhost:8003
# Database
export DB_HOST=localhost
export DB_PORT=5432
export DB_NAME=testdb
export DB_USER=testuser
export DB_PASSWORD=testpass
# RabbitMQ
export RABBITMQ_HOST=localhost
export RABBITMQ_PORT=5672
export RABBITMQ_USER=testuser
export RABBITMQ_PASSWORD=testpass
Programmatic Configuration
config = EngineConfig()
config.services = ServiceConfig.from_dict({"api": "http://api:8080"})
config.database = DatabaseConfig(host="db.example.com", port=5432)
config.rabbitmq = RabbitMQConfig(host="mq.example.com", port=5672)
Advanced Features
Custom Step Handlers
def kafka_handler(step):
kafka.publish(step.params['topic'], step.params['message'])
orchestrator.register_step_handler("kafka_publish", kafka_handler)
# Use in scenarios
scenario.custom_step(
custom_type="kafka_publish",
params={"topic": "events", "message": {...}}
)
Context Manager
with TestOrchestrator(config) as orchestrator:
# Test code
orchestrator.execute_scenario(scenario)
# Automatically cleaned up
Architecture Support
Works with any microservices architecture:
- ✅ E-Commerce (order, payment, inventory, shipping)
- ✅ IoT (device, telemetry, alerts)
- ✅ Banking (account, transaction, fraud detection)
- ✅ SaaS (user, subscription, billing)
- ✅ And more...
Documentation
- Reusability Guide - Complete guide for using with any services
- Examples - 6 complete usage examples
- How-to Guide - Practical usage patterns
Requirements
- Python 3.8+
- PostgreSQL (for database assertions)
- RabbitMQ (for message queue monitoring)
- Your microservices
Testing
Run API tests (no infrastructure needed):
python test_api_only.py
Run full integration tests (requires running services):
python test_refactored_engine.py
## Real-World Usage
This library is being used in production for:
- ✅ Event enrollment systems
- ✅ E-commerce platforms
- ✅ Microservices architectures
**Proven reusability:** Successfully integrated into multiple projects with different architectures, databases, and endpoints.
## Links
- **PyPI:** https://pypi.org/project/testing-engine-core/
- **GitHub:** https://github.com/MysticAladin/testing-engine-core
- **Issues:** https://github.com/MysticAladin/testing-engine-core/issues
## License
MIT License
## Contributing
Contributions welcome! This engine is designed to be universal and extensible.
1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request
Contributions welcome! This engine is designed to be universal and extensible.
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