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python-packaging

Create distributable Python packages with proper project structure, setup.py/pyproject.toml, and publishing to PyPI. Use when packaging Python libraries, creating CLI tools, or distributing Python code.

DeepseekModel 官方收录技能 质量 优秀 · 90 v1.0.0

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https://deepseekmodel.com/api/download.php?id=wshobson-agents-plugins-python-development-skills-python-packaging-skill-md&format=skill
下载 .skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用
.skill 文件中 system_prompt 字段的实际内容。
name python-packaging description Create distributable Python packages with proper project structure, setup.py/pyproject.toml, and publishing to PyPI. Use when packaging Python libraries, creating CLI tools, or distributing Python code. Python Packaging Comprehensive guide to creating, structuring, and distributing Python packages using modern packaging tools, pyproject.toml, and publishing to PyPI. When to Use This Skill Creating Python libraries for distribution Building command-line tools with entry points Publishing packages to PyPI or private repositories Setting up Python project structure Creating installable packages with dependencies Building wheels and source distributions Versioning and releasing Python packages Creating namespace packages Implementing package metadata and classifiers Core Concepts 1. Package Structure Source layout : src/package_name/ (recommended) Flat layout : package_name/ (simpler but less flexible) Package metadata : pyproject.toml, setup.py, or setup.cfg Distribution formats : wheel (.whl) and source distribution (.tar.gz) 2. Modern Packaging Standards PEP 517/518 : Build system requirements PEP 621 : Metadata in pyproject.toml PEP 660 : Editable installs pyproject.toml : Single source of configuration 3. Build Backends setuptools : Traditional, widely used hatchling : Modern, opinionated flit : Lightweight, for pure Python poetry : Dependency management + packaging 4. Distribution PyPI : Python Package Index (public) TestPyPI : Testing before production Private repositories : JFrog, AWS CodeArtifact, etc. Quick Start Minimal Package Structure my-package/ ├── pyproject.toml ├── README.md ├── LICENSE ├── src/ │ └── my_package/ │ ├── __init__.py │ └── module.py └── tests/ └── test_module.py Minimal pyproject.toml [build-system] requires = [ "setuptools>=61.0" ] build-backend = "setuptools.build_meta" [project] name = "my-package" version = "0.1.0" description = "A short description" authors = [{name = "Your Name" , email = "you@example.com" }] readme = "README.md" requires-python = ">=3.8" dependencies = [ "requests>=2.28.0" , ] [project.optional-dependencies] dev = [ "pytest>=7.0" , "black>=22.0" , ] Package Structure Patterns Pattern 1: Source Layout (Recommended) my-package/ ├── pyproject.toml ├── README.md ├── LICENSE ├── .gitignore ├── src/ │ └── my_package/ │ ├── __init__.py │ ├── core.py │ ├── utils.py │ └── py.typed # For type hints ├── tests/ │ ├── __init__.py │ ├── test_core.py │ └── test_utils.py └── docs/ └── index.md Advantages: Prevents accidentally importing from source Cleaner test imports Better isolation pyproject.toml for source layout: [tool.setuptools.packages.find] where = [ "src" ] Pattern 2: Flat Layout my-package/ ├── pyproject.toml ├── README.md ├── my_package/ │ ├── __init__.py │ └── module.py └── tests/ └── test_module.py Simpler but: Can import package without installing Less professional for libraries Pattern 3: Multi-Package Project project/ ├── pyproject.toml ├── packages/ │ ├── package-a/ │ │ └── src/ │ │ └── package_a/ │ └── package-b/ │ └── src/ │ └── package_b/ └── tests/ Detailed patterns and worked examples Detailed pattern documentation lives in references/details.md . Read that file when the navigation tier above is insufficient.
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下载的 .skill 包内含以下字段。
字段 说明
format格式标识(skill/v1)
skill_id技能唯一 ID
name技能名称
version版本号
description技能描述
category所属分类(数组)
trigger_words触发词列表
tags标签列表
source来源标识
source_url来源链接(本页地址)
exported_at导出时间(每次下载生成)
system_prompt系统提示词正文
model_config模型参数:provider / model / temperature / max_tokens / top_p
examples示例
install_guide各平台导入说明(Coze / Dify / Claude / 自定义框架)
同一份技能可按不同平台格式导出。
.skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用 下载
.skillpro 增强格式,额外含脚本 / 工具 / 依赖 / 钩子占位 下载
.json 纯 JSON 导出,只含 system_prompt 与模型参数 下载
Coze 带 frontmatter 的 Markdown,Coze 平台导入用 下载
Dify Dify DSL,创建应用后直接导入 下载

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