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Found 1,737 Skills
Python code refactoring skills, covering code smell identification, design pattern application, readability improvement, and practical experience. This skill is applicable when users request "refactor code", "refactor", "code optimization", "improve code quality", "code smell review", "apply design patterns", "enhance readability", or submit code review requests. It supports generating structured refactoring documents after refactoring completion ("output refactoring document", "generate refactoring report"). It includes practical patterns extracted from 20+ real refactoring PRs in the vllm-ascend repository.
Python SDK for the iii engine. Use when building workers, registering functions, or invoking triggers in Python.
Python development principles and decision-making. Framework selection, async patterns, type hints, project structure. Teaches thinking, not copying.
Master Python 3.12+ with modern features, async programming, performance optimization, and production-ready practices. Expert in the latest Python ecosystem including uv, ruff, pydantic, and FastAPI. Use PROACTIVELY for Python development, optimization, or advanced Python patterns.
MLflow experiment tracking via Python API. TRIGGERS - MLflow metrics, log backtest, experiment tracking, search runs.
Python backend implementation patterns for FastAPI applications with SQLAlchemy 2.0, Pydantic v2, and async patterns. Use during the implementation phase when creating or modifying FastAPI endpoints, Pydantic models, SQLAlchemy models, service layers, or repository classes. Covers async session management, dependency injection via Depends(), layered error handling, and Alembic migrations. Does NOT cover testing (use pytest-patterns), deployment (use deployment-pipeline), or FastAPI framework mechanics like middleware and WebSockets (use fastapi-patterns).
Python error handling patterns for FastAPI, Pydantic, and asyncio. Follows "Let it crash" philosophy - raise exceptions, catch at boundaries. Covers HTTPException, global exception handlers, validation errors, background task failures. Use when: (1) Designing API error responses, (2) Handling RequestValidationError, (3) Managing async exceptions, (4) Preventing stack trace leakage, (5) Designing custom exception hierarchies.
pytest testing patterns for Python. Triggers on: pytest, fixture, mark, parametrize, mock, conftest, test coverage, unit test, integration test, pytest.raises.
Modern Python project architecture guide for 2025. Use when creating Python projects (APIs, CLI, data pipelines). Covers uv, Ruff, Pydantic, FastAPI, and async patterns.
Improves Python library code quality through ruff linting, mypy type checking, Pythonic idioms, and refactoring. Use when reviewing code for quality issues, adding type hints, configuring static analysis tools, or refactoring Python library code.
Python performance optimization patterns using profiling, algorithmic improvements, and acceleration techniques. Use when optimizing slow Python code, reducing memory usage, or improving application throughput and latency.
Python Coding Standards, including type hints, logging specifications, naming conventions, code structure, etc. Applicable to all Python code files.