/python-simple-ioc

A simple Python IOC based on Symfony2 Dependency Component

Primary LanguagePythonApache License 2.0Apache-2.0

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.

๐ŸŽฏ 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".

๐Ÿš€ 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()

๐Ÿ—๏ธ 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

๐Ÿ“š 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%"

๐Ÿงช 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()

๐Ÿ“– Learn More

๐Ÿค Contributing

Contributions are welcome! This project follows Python community standards:

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

๐Ÿ“„ 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.