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python-programming

Python development guidance for creating, modifying, reviewing, testing, packaging, and debugging Python code. Use when tasks involve .py files, pyproject.toml, requirements files, pytest, ruff, mypy, FastAPI, Django, Flask, CLIs, scripts, type hints, virtual environments, or Python dependency management.

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更新日2026年5月1日 19:23

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devalexandre

devalexandre/Agno-Deep-Agents

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ソフトウェア開発者コンピュータ・数学職15-1252L4

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SKILL.md

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name	python-programming
description	Python development guidance for creating, modifying, reviewing, testing, packaging, and debugging Python code. Use when tasks involve .py files, pyproject.toml, requirements files, pytest, ruff, mypy, FastAPI, Django, Flask, CLIs, scripts, type hints, virtual environments, or Python dependency management.

Python Programming

Goal

Produce Python changes that fit the local project style, remain easy to test, and avoid surprising runtime behavior.

Discovery

Identify the Python version, package manager, and tooling from pyproject.toml, setup.cfg, setup.py, requirements*.txt, lockfiles, tox/nox config, and CI.
Check existing module layout before adding files.
Read nearby tests, fixtures, factories, and public API docs before changing behavior.
Preserve the project's existing framework choices, import style, typing level, and error handling conventions.

Implementation

Prefer straightforward functions and small classes over new abstractions.
Use pathlib, context managers, dataclasses, enums, and type hints when they match the surrounding code.
Keep import-time side effects out of modules; put executable script entry points behind if __name__ == "__main__":.
For async code, preserve the current event-loop model and avoid blocking calls inside coroutines.
For web apps, update schemas, route handlers, services, and tests together so request and response contracts stay aligned.
For packaging changes, keep dependencies minimal and update the right manifest or lockfile for the repo's chosen tool.

Verification

Prefer the narrowest relevant checks first: targeted pytest, then broader test suites when the change crosses modules.
Run configured formatters and linters such as ruff, black, isort, and mypy only when they are already part of the project.
When dependencies are unavailable, run syntax checks such as python -m py_compile <files> and explain the remaining gap.

Review Focus

Import cycles, hidden global state, mutable defaults, broad exception catches, sync/async mismatches, unclosed files, and compatibility with the configured Python version.

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Python Programming

Goal

Produce Python changes that fit the local project style, remain easy to test, and avoid surprising runtime behavior.

Discovery

Identify the Python version, package manager, and tooling from pyproject.toml, setup.cfg, setup.py, requirements*.txt, lockfiles, tox/nox config, and CI.

Check existing module layout before adding files.

Read nearby tests, fixtures, factories, and public API docs before changing behavior.

Preserve the project's existing framework choices, import style, typing level, and error handling conventions.

Implementation

Prefer straightforward functions and small classes over new abstractions.

Use pathlib, context managers, dataclasses, enums, and type hints when they match the surrounding code.

Keep import-time side effects out of modules; put executable script entry points behind if __name__ == "__main__":.

For async code, preserve the current event-loop model and avoid blocking calls inside coroutines.

For web apps, update schemas, route handlers, services, and tests together so request and response contracts stay aligned.

For packaging changes, keep dependencies minimal and update the right manifest or lockfile for the repo's chosen tool.

Verification

Prefer the narrowest relevant checks first: targeted pytest, then broader test suites when the change crosses modules.

Run configured formatters and linters such as ruff, black, isort, and mypy only when they are already part of the project.

When dependencies are unavailable, run syntax checks such as python -m py_compile <files> and explain the remaining gap.

Review Focus

Import cycles, hidden global state, mutable defaults, broad exception catches, sync/async mismatches, unclosed files, and compatibility with the configured Python version.