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A small dependency injection container based on Symfony2 Dependency Component

Project description

Python Simple IoC - Dependency Injection Container

CI Python 3.9+ License

A lightweight, Pythonic dependency injection container inspired by Symfony's DependencyInjection component. This library embraces Python's philosophy of simplicity while providing powerful tools for organizing complex applications.

🎯 Why Use Dependency Injection?

Dependency injection isn't just enterprise complexity - it's a Pythonic pattern that promotes:

  • Clear separation of concerns - Each class has a single responsibility
  • Testability - Easy to mock dependencies for unit tests
  • Flexibility - Change implementations without touching existing code
  • Maintainability - Explicit dependencies make code easier to understand

This approach aligns perfectly with Python's zen: "Explicit is better than implicit" and "Readability counts".

🚀 Quick Start

Installation

pip install ioc

Basic Usage

  1. Define your services in a services.yml file:
parameters:
  database_url: "sqlite:///app.db"
  debug_mode: true

services:
  # Database connection
  database:
    class: myapp.database.Database
    arguments: ["%database_url%"]
  
  # User repository with injected database
  user_repository:
    class: myapp.repositories.UserRepository
    arguments: ["@database"]
  
  # User service with injected repository
  user_service:
    class: myapp.services.UserService
    arguments: ["@user_repository"]
    calls:
      - [set_debug, ["%debug_mode%"]]
  1. Use the container in your application:
import ioc

# Build container from configuration
container = ioc.build(['services.yml'])

# Get your services - dependencies are automatically resolved!
user_service = container.get('user_service')

# Your service is ready to use with all dependencies injected
users = user_service.get_all_users()

🏗️ Perfect for Python Projects

This library follows Python best practices:

  • Configuration over code - Define dependencies in YAML, not scattered across your codebase
  • Explicit dependencies - See exactly what each service needs at a glance
  • No magic - Simple, predictable behavior that follows Python conventions
  • Framework agnostic - Works with Flask, Django, FastAPI, or pure Python

📚 Advanced Features

Service Definitions

services:
  # Constructor injection
  email_service:
    class: myapp.EmailService
    arguments: ["@mailer", "%sender_email%"]
  
  # Method calls after construction
  logger:
    class: logging.Logger
    arguments: ["myapp"]
    calls:
      - [setLevel, ["INFO"]]
      - [addHandler, ["@file_handler"]]
  
  # Weak references (lazy loading)
  cache_service:
    class: myapp.CacheService
    arguments: ["#@redis_client"]  # Only loaded when needed

Parameters and Environment

parameters:
  # String interpolation
  log_file: "/var/log/%app_name%.log"
  
  # Environment variables
  secret_key: "%env(SECRET_KEY)%"
  
  # Default values
  redis_url: "%env(REDIS_URL):redis://localhost:6379%"

🧪 Testing Made Easy

With dependency injection, testing becomes straightforward:

import unittest
from unittest.mock import Mock

class TestUserService(unittest.TestCase):
    def test_create_user(self):
        # Mock the repository
        mock_repo = Mock()
        mock_repo.save.return_value = True
        
        # Inject the mock
        user_service = UserService(mock_repo)
        
        # Test with confidence
        result = user_service.create_user("john@example.com")
        self.assertTrue(result)
        mock_repo.save.assert_called_once()

📖 Learn More

🤝 Contributing

Contributions are welcome! This project follows Python community standards:

  • PEP 8 code style
  • Type hints for better IDE support
  • Comprehensive tests
  • Clear documentation

📄 License

Licensed under the Apache License 2.0. See LICENSE for details.


"Beautiful is better than ugly. Explicit is better than implicit. Simple is better than complex." - The Zen of Python

This library embodies these principles while providing the power and flexibility needed for serious Python applications.

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