Does this skill support older Python versions?

This skill specifically targets Python 3.12+ features to utilize modern syntax improvements like PEP 604 union types and optimized performance.

How does it handle external system connections?

It implements a 'no side effects in constructor' rule, utilizing @cached_property to lazily evaluate properties that require IO, ensuring faster and safer object instantiation.

Why are dataclasses used for arguments and responses?

Dataclasses provide a structured, type-safe way to define the data contracts between different parts of your service, making the code more readable and easier to test.

Can this be used for internal system logic?

Yes, while it excels at interfacing with external systems like APIs, the patterns of encapsulation and lazy evaluation are highly beneficial for any internal Python service module.

Python Service Engineering

Name: Python Service Engineering
Author: jack-michaud

byjack-michaud

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API Development

Standardizes the development of robust Python services using modern 3.12+ syntax and clean architectural patterns.

About

This skill enhances Claude's ability to architect and implement production-grade Python services by enforcing modern development standards. It focuses on creating maintainable classes that encapsulate logic for external systems—such as APIs and logging frameworks—while ensuring performance through lazy evaluation. By mandating Python 3.12+ type syntax and the use of dataclasses for method interfaces, it ensures that your backend services are type-safe, side-effect-free at instantiation, and consistent across your entire codebase.

Key Features

Prevents constructor side effects by implementing lazy evaluation via @cached_property
Standardizes service communication using dataclasses for method arguments and responses
Encapsulates complex logic for interfacing with external APIs and logging systems
Enforces Python 3.12+ modern type hinting syntax (e.g., using | for unions)
Promotes clean, modular backend architecture and domain-specific implementation patterns
3 GitHub stars

Use Cases

Developing structured API clients that interface with external third-party services
Building robust logging and monitoring wrappers with deferred resource initialization
Creating maintainable backend business logic modules with strict type safety

About

Key Features

Prevents constructor side effects by implementing lazy evaluation via @cached_property
Standardizes service communication using dataclasses for method arguments and responses
Encapsulates complex logic for interfacing with external APIs and logging systems
Enforces Python 3.12+ modern type hinting syntax (e.g., using | for unions)
Promotes clean, modular backend architecture and domain-specific implementation patterns
3 GitHub stars

Use Cases

Developing structured API clients that interface with external third-party services
Building robust logging and monitoring wrappers with deferred resource initialization
Creating maintainable backend business logic modules with strict type safety