Name: Python Assistant
Author: jvy

据 AlphaMoat 统计,截至 2026-09,Python Assistant 累计下载 4,574 次、获 3 个星标,在全部 5,078 个 AI 技能中排名第 2,090 位,在「开发编程」分类(577 个)中排名第 268 位。

累计安装

547

累计下载

4,574

星标

全站排名

#2,090

全站前 42% · 「开发编程」前 47%

平台	累计安装	累计下载	星标	评论
ClawHub ↗	69	2,390	-	-
SkillHub ↗	547	4,574	3	—

各平台的计数口径不同,统计时间不一致。

这个技能是做什么的

覆盖项目初始化、依赖安装、脚本执行与环境排障，主张用项目内的虚拟环境而不是全局安装，用模块方式调用 pip 以避免解释器不匹配。安装前先看依赖清单文件，遇到不认识的安装钩子或随机脚本要先征得同意再执行。目标是让本地与开发环境可复现、风险低。若 --venv 路径设错，recreate 流程可能删除任意可写目录。使用明确位于项目内的 .venv，避免绝对路径或父目录，并在删除/重建前验证目标。

资料发布于 2026-10-27

可以用来做什么

给新项目搭一套可复现的环境
排查依赖装不上或版本冲突

什么时候用

要初始化 Python 项目时
环境报错想按稳妥步骤排查时

示例提示词

以下是根据技能文档生成的示例,不代表实际运行结果。

帮我给这个项目建虚拟环境并装依赖

这个依赖冲突该怎么排查

月度数据趋势

累计下载4,574

星标3

2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。

月份	累计下载	环比	星标
2026-09	4,574	—	3
2026-08	3,813	+75.2%	3
2026-07	2,176	—	-
2026-05	2,785	—	2
2026-03	1,577	—	-

SKILL.md 原文

以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。

2.7 KB · ClawHub v1.0.0

---
name: python
description: Use Python for practical project setup, dependency install, script execution, and environment troubleshooting with safe defaults. Use when tasks involve pyproject.toml or requirements.txt, virtual environment setup, running Python scripts/tests, packaging basics, or fixing common Python errors (interpreter mismatch, pip resolver conflicts, missing modules, build failures).
metadata:
  openclaw:
    emoji: "🐍"
    requires:
      bins: ["python3"]
      anyBins: ["pip", "pip3"]
    install:

展开全部(共 91 行)

      - id: "brew"
        kind: "brew"
        formula: "python"
        bins: ["python3"]
        label: "Install Python + pip (brew)"
      - id: "apt"
        kind: "apt"
        package: "python3-pip"
        bins: ["pip3"]
        label: "Install pip (apt)"
---

# Python

Use this skill to keep Python workflows reproducible and low-risk across local/dev shells.

## Safety Defaults

- Prefer project-local virtual environments (`.venv`) over global installs.
- Prefer `python3 -m pip ...` to avoid interpreter and pip mismatch.
- Inspect dependency files before install (`requirements*.txt`, `pyproject.toml`).
- Avoid executing unknown setup hooks or random install scripts without user approval.

## Standard Workflow

1. Detect current environment:

```bash
python3 --version
python3 -c "import sys; print(sys.executable)"
{baseDir}/scripts/python_env_tool.py doctor
```

2. Create or refresh a venv:

```bash
{baseDir}/scripts/python_env_tool.py bootstrap --venv .venv --requirements requirements.txt
```

3. Install project package (if `pyproject.toml` exists):

```bash
{baseDir}/scripts/python_env_tool.py install --venv .venv --editable
```

4. Run tests/tools from the venv interpreter:

```bash
.venv/bin/python -m pytest -q
.venv/bin/python -m pip list --outdated
```

## Task Recipes

```bash
# Install specific packages into venv
{baseDir}/scripts/python_env_tool.py install --venv .venv --package requests --package pydantic

# Install from requirements file
{baseDir}/scripts/python_env_tool.py install --venv .venv --requirements requirements-dev.txt

# Recreate corrupted venv from scratch
{baseDir}/scripts/python_env_tool.py bootstrap --venv .venv --recreate --requirements requirements.txt
```

## Troubleshooting Rules

- `ModuleNotFoundError`: verify command is run via `.venv/bin/python`, then reinstall deps.
- `externally-managed-environment`: stop global install attempts; use venv.
- Build failures on native deps: upgrade `pip setuptools wheel`, then retry.
- Multiple Python versions: always print and confirm `sys.executable` before fixes.

## Bundled Helper

Use the helper for repeatable environment setup and diagnosis:

```bash
{baseDir}/scripts/python_env_tool.py --help
{baseDir}/scripts/python_env_tool.py doctor
```