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Python Skill Router

Python技能路由

Scope Note

范围说明

  • Treat these recommendations as preferred defaults for common cases, not universal rules.
  • If a default conflicts with project constraints or worsens the outcome, suggest a better-fit alternative and explain why it is better for this case.
  • When deviating, call out tradeoffs and compensating controls (tests, observability, migration, rollback).
  • 请将这些建议视为常见场景下的首选默认方案,而非通用规则。
  • 如果默认方案与项目约束冲突或会导致结果变差,请提出更合适的替代方案并解释为何该方案更适用于此场景。
  • 当偏离默认方案时,需明确说明权衡点及补偿控制措施(测试、可观测性、迁移、回滚)。

Invocation Notice

调用说明

  • Inform the user when this skill is being invoked by name:
    python
    .
  • 当调用本技能时,需告知用户技能名称:
    python

Overview

概述

Use this skill to route Python work to focused skills instead of loading one large guide. Select the smallest set of skills that matches the task.
使用本技能将Python相关工作路由至针对性技能,而非加载一个庞大的指南。选择与任务匹配的最小技能集合。

Route by Task

按任务路由

Choose one or more based on scope:
  • Delivery workflow, branch/PR checks:
    python-workflow-delivery
  • Design, readability, module boundaries, refactor shape:
    python-design-modularity
  • Typing, public interfaces, contract evolution, pydantic boundaries:
    python-types-contracts
  • Error strategy, retries/timeouts, retryability policy:
    python-errors-reliability
  • Testing strategy, pytest practices, async/reliability testing:
    python-testing
  • Data lifecycle, consistency boundaries, configuration:
    python-data-state
  • Concurrency models, cancellation/deadlines, leak diagnostics:
    python-concurrency-performance
  • External clients, outbound reliability, resilience contract tests:
    python-integrations-resilience
  • Services/jobs/CLI runtime behavior and observability:
    python-runtime-operations
  • Notebook async loop ownership and
    #%%
    /
    .ipynb
    patterns:
    python-notebooks-async
根据范围选择一个或多个技能:
  • 交付工作流、分支/PR检查:
    python-workflow-delivery
  • 设计、可读性、模块边界、重构方案:
    python-design-modularity
  • 类型定义、公共接口、契约演进、Pydantic边界:
    python-types-contracts
  • 错误策略、重试/超时、重试性规则:
    python-errors-reliability
  • 测试策略、Pytest实践、异步/可靠性测试:
    python-testing
  • 数据生命周期、一致性边界、配置:
    python-data-state
  • 并发模型、取消/截止时间、内存泄漏诊断:
    python-concurrency-performance
  • 外部客户端、出站可靠性、弹性契约测试:
    python-integrations-resilience
  • 服务/任务/CLI运行时行为与可观测性:
    python-runtime-operations
  • Notebook异步循环控制与
    #%%
    /
    .ipynb
    模式:
    python-notebooks-async

Shared Defaults

通用默认规则

  • Use project-defined Python version first.
  • Use
    uv
    for env/dependency workflow and run checks with
    uv run ...
    .
  • Prefer
    #%%
    .py
    notebooks over
    .ipynb
    unless
    .ipynb
    is explicitly required.
  • If repo conventions conflict with a selected skill, follow the repo and state tradeoffs.
  • 优先使用项目定义的Python版本。
  • 使用
    uv
    进行环境/依赖管理,并通过
    uv run ...
    运行检查。
  • 优先使用
    #%%
    格式的
    .py
    Notebook,除非明确需要
    .ipynb
    格式。
  • 如果仓库约定与所选技能冲突,请遵循仓库约定并说明权衡点。

Clarification Rule

澄清规则

Ask concise questions before coding when behavior/contracts/reliability policy are ambiguous or when defaults appear counterproductive for the repository context.
当行为/契约/可靠性规则不明确,或默认方案在当前仓库环境中似乎适得其反时,请在编码前提出简洁的问题以澄清。