What is the main benefit of using this CQRS skill?

It helps you separate read and write concerns, allowing you to optimize and scale each model independently for better performance.

When should I use CQRS instead of a standard CRUD pattern?

CQRS is recommended for complex domains where the read and write logic differs significantly, or when you need to optimize query performance across multiple data sources.

Does this skill support event sourcing?

Yes, the skill includes patterns for event stores, uncommitted events, and projectors which form the foundation of event-sourced systems.

Can this skill be used with frameworks other than FastAPI?

Yes. While the included templates feature FastAPI integration, the core Command and Query bus logic is framework-agnostic and can be applied to any Python backend.

CQRS Implementation Patterns

Name: CQRS Implementation Patterns
Author: drgaciw

bydrgaciw

API 개발

Implements Command Query Responsibility Segregation (CQRS) to build highly scalable, performant, and maintainable backend architectures.

소개

This skill provides a comprehensive framework for implementing CQRS patterns within your applications, enabling the clean separation of data modification (Commands) from data retrieval (Queries). It offers standardized Python templates for command buses, query handlers, and event-sourced system foundations, making it ideal for developers building complex systems that require independent scaling of read and write workloads or high-performance reporting capabilities. By decoupling these concerns, the skill helps reduce system complexity in large-scale applications and facilitates more flexible data modeling.

주요 기능

Support for event-driven and event-sourced architectures
Ready-to-use FastAPI integration patterns
0 GitHub stars
Read model synchronization and projection templates
Decoupled handlers for improved code maintainability
Standardized Command and Query bus infrastructure

사용 사례

Scaling read-heavy applications independently from write operations
Implementing domain-driven design (DDD) with clear architectural boundaries
Optimizing complex reporting queries without impacting transactional performance

소개

주요 기능

Support for event-driven and event-sourced architectures
Ready-to-use FastAPI integration patterns
0 GitHub stars
Read model synchronization and projection templates
Decoupled handlers for improved code maintainability
Standardized Command and Query bus infrastructure

사용 사례

Scaling read-heavy applications independently from write operations
Implementing domain-driven design (DDD) with clear architectural boundaries
Optimizing complex reporting queries without impacting transactional performance