大家都知道Python库很强大，却不知道还有强大工具包 poet

前言

Python有很多很强大的库，因此而闻名天下，却不知道还有不少的工具包，今天为大家一款包管理和打包的工具poetry

在Python中，对于初学者来说，打包系统和依赖管理是非常复杂和难懂的。即使对于经验丰富的开发者，一个项目总是要同时创建多个文件： setup.py ,requirements.txt,setup.cfg , MANIFEST.in ，还有最新的 Pipfile。

基于此， poetry 将所有的配置都放置在一个 toml 文件中，这些配置包括：依赖管理、构建、打包、发布。

poetry 的灵感来自于其他语言的一些工具： composer(PHP) 和 cargo (Rust) 。

配置

poetry 的项目配置文件是 pyproject.toml ，一个简单的示例文件如下：

[tool.poetry]
name = "poetry"
version = "0.11.5"
description = "Python dependency management and packaging made easy."
authors = [
    "Sébastien Eustace <sebastien@eustace.io>"
]
license = "MIT"

readme = "README.md"

homepage = "https://poetry.eustace.io/"
repository = "https://github.com/sdispater/poet"
documentation = "https://poetry.eustace.io/docs"

keywords = ["packaging", "dependency", "poetry"]

classifiers = [
    "Topic :: Software Development :: Build Tools",
    "Topic :: Software Development :: Libraries :: Python Modules"
]

# Requirements
[tool.poetry.dependencies]
python = "~2.7 || ^3.4"
cleo = "^0.6.7"
requests = "^2.18"
cachy = "^0.2"
requests-toolbelt = "^0.8.0"
jsonschema = "^2.6"
pyrsistent = "^0.14.2"
pyparsing = "^2.2"
cachecontrol = { version = "^0.12.4", extras = ["filecache"] }
pkginfo = "^1.4"
html5lib = "^1.0"
shellingham = "^1.1"
tomlkit = "^0.4.4"

# The typing module is not in the stdlib in Python 2.7 and 3.4
typing = { version = "^3.6", python = "~2.7 || ~3.4" }

# Use pathlib2 for Python 2.7 and 3.4
pathlib2 = { version = "^2.3", python = "~2.7 || ~3.4" }
# Use virtualenv for Python 2.7 since venv does not exist
virtualenv = { version = "^16.0", python = "~2.7" }

[tool.poetry.dev-dependencies]
pytest = "^3.4"
pytest-cov = "^2.5"
mkdocs = "^1.0"
pymdown-extensions = "^4.9"
pygments = "^2.2"
pytest-mock = "^1.9"
pygments-github-lexers = "^0.0.5"
black = { version = "^18.3-alpha.0", python = "^3.6" }
pre-commit = "^1.10"
tox = "^3.0"


[tool.poetry.scripts]
poetry = "poetry.console:main"

命令

poetry 提供了一系列覆盖整个开发流程的命令，这些命令使用简单：

poetry 命令

名称 功能

1. new 创建一个项目脚手架，包含基本结构、pyproject.toml 文件

2. init 基于已有的项目代码创建 pyproject.toml 文件，支持交互式填写

3. install 安装依赖库

4. update 更新依赖库

5. add 添加依赖库

6. remove 移除依赖库

7. show 查看具体依赖库信息，支持显示树形依赖链

8. build 构建 tar.gz 或 wheel 包

9. publish 发布到 PyPI

10. run 运行脚本和代码

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