Does it support the latest Python 3.10+ features?

Yes, it specifically includes patterns for Python 3.10+ union syntax, built-in generics, and modern typing features like ParamSpec.

Can this skill help with performance optimization?

Yes, it includes advanced patterns for memory-efficient dataclasses using slots and high-performance data processing using generators and itertools.

How does this skill improve Python code generation?

It provides Claude with specific architectural patterns and modern syntax rules, ensuring generated code is idiomatic, type-safe, and follows current industry standards.

Is this skill useful for data science projects?

Absolutely. It includes triggers for popular data libraries like Pandas and NumPy, helping structure data analysis scripts more effectively.

Modern Python Development

Name: Modern Python Development
Author: miles990

bymiles990

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API Development

Implements high-quality Python code using modern type hints, asynchronous patterns, and idiomatic best practices.

About

This skill equips Claude with specialized knowledge for modern Python development, emphasizing type safety, performance, and maintainability. It provides robust implementation patterns for complex type hinting (including Protocols and Generics), advanced use of dataclasses for structured data, and production-grade asynchronous programming. By leveraging these patterns, developers can ensure their codebases follow PEP 8 standards and utilize the latest features found in Python 3.10 and beyond.

Key Features

Advanced Type Hinting including Protocols, Generics, and TypedDict
Asynchronous programming templates for concurrency and rate limiting
Production-grade error handling using the Result type pattern
1 GitHub stars
Modern Dataclass patterns with memory-efficient slots and frozen states
High-performance data iteration using itertools and generators

Use Cases

Optimizing data processing scripts with async/await and memory-efficient iterators
Refactoring legacy Python code to modern 3.10+ standards and type safety
Building type-safe backend services and robust APIs

About

Key Features

Advanced Type Hinting including Protocols, Generics, and TypedDict
Asynchronous programming templates for concurrency and rate limiting
Production-grade error handling using the Result type pattern
1 GitHub stars
Modern Dataclass patterns with memory-efficient slots and frozen states
High-performance data iteration using itertools and generators

Use Cases

Optimizing data processing scripts with async/await and memory-efficient iterators
Refactoring legacy Python code to modern 3.10+ standards and type safety
Building type-safe backend services and robust APIs