CQRS

CQRS Pattern ⚙️

Overview 🌐

The Command Query Responsibility Segregation (CQRS) pattern separates the responsibilities of handling command (write) operations from query (read) operations, allowing them to scale independently and embrace different optimization strategies. This approach enhances performance, scalability, and security, providing a clear structure that can handle complex business scenarios.

Use Cases 🔍

• Complex systems where the difference in behavior between commands (modifying data) and queries (reading data) requires distinctly different handling and scalability considerations.
• Applications requiring high performance and scalability for read operations without compromising write operation integrity.
• Systems where read and write operations evolve at different speeds and require different models to manage changes effectively.

Implementation 🛠️

The cqrs.py file contains implementations for separating read and write responsibilities. The architecture typically involves:

• Command Model - Handles create, update, and delete operations that might involve domain logic and business rules.
• Query Model - Provides multiple views of data that are optimized for specific use cases, often updated asynchronously.

Example Usage 📝

# Command Usage
command_service = CommandService()
command_service.create_item("Item1")
command_service.update_item("Item1", "Updated Description")

# Query Usage
query_service = QueryService()
print(query_service.get_item("Item1"))

# Handling different aspects separately
print(query_service.list_all_items())

Output 📊

Item created: Item1
Item updated: Item1
Item1: Updated Description
All items: ['Item1']

This output demonstrates how the CQRS pattern separates the handling of creating and updating data (commands) from the retrieval of data (queries).

Business Logic Method 🧠

Here's how you might utilize CQRS in your business logic:

# Initialize services
command_service = CommandService()
query_service = QueryService()

# Business logic to handle a transaction
command_service.create_item("Item2")
query_service.get_item("Item2")  # Immediate consistency is not guaranteed

# Ensuring eventual consistency
import time
time.sleep(1)  # Simulate delay for data synchronization
print(query_service.get_item("Item2"))

Testing 🧪

The test_cqrs.py file includes tests to ensure that commands and queries are handled correctly within their respective models. It checks for:

• Correct execution of write operations without impacting read models.
• Accurate and efficient query operations that reflect the state changes made by commands, respecting eventual consistency.