等价于`pip`的`package.json'和`package-lock.json` [英] Equivalent of `package.json' and `package-lock.json` for `pip`

问题描述

JavaScript代码的包管理器(例如 npm 和 yarn )使用 package.json 来指定顶级'依赖项，并创建锁定文件来跟踪所有软件包(即顶级和子级别依赖项).

此外， package.json 允许我们区分顶级依赖项的类型，例如 production 和 development

另一方面，对于 Python ，我们有 pip .我想 lock 文件的 pip 等效项是 pip冻结>的结果.requirements.txt .

但是，如果仅维护单个 requirements.txt 文件，则很难区分顶级和子级依赖项(例如，需要 pipdeptree -r 找出答案).如果您想删除或更改顶级依赖项，这将是一个巨大的痛苦，因为很容易留下孤立的软件包(据我所知， pip 解决方案

今天至少有三个不错的选择:

1. pipenv 使用 pip ，因为它还可以创建和管理virtualenvs.

   这可能是当今最流行的选项，并且几乎可以肯定，它将取代许多开发人员工作流程中的 pip .

2. 诗歌 使用 pip-tools 提供了 pip-compile 和 pip-sync 命令.在这里， requirements.in 列出了您的直接依赖关系，通常具有宽松的版本限制，并且 pip-compile 从您的 .in 文件.

   我个人喜欢这个工具，因为它向后兼容(生成的 requirements.txt 可以由 pip 处理)和 pip-sync 工具可确保virtualenv与锁定版本完全匹配，从而将锁定"中未包含的内容删除.文件.

Package managers for JavaScript like npm and yarn use a package.json to specify 'top-level' dependencies, and create a lock-file to keep track of the specific versions of all packages (i.e. top-level and sub-level dependencies) that are installed as a result.

In addition, the package.json allows us to make a distinction between types of top-level dependencies, such as production and development.

For Python, on the other hand, we have pip. I suppose the pip equivalent of a lock-file would be the result of pip freeze > requirements.txt.

However, if you maintain only this single requirements.txt file, it is difficult to distinguish between top-level and sub-level dependencies (you would need for e.g. pipdeptree -r to figure those out). This can be a real pain if you want to remove or change top-level dependencies, as it is easy to be left with orphaned packages (as far as I know, pip does not remove sub-dependencies when you pip uninstall a package).

Now, I wonder: Is there some convention for dealing with different types of these requirements files and distinguishing between top-level and sub-level dependencies with pip?

For example, I can imagine having a requirements-prod.txt which contains only the top-level requirements for the production environment, as the (simplified) equivalent of package.json, and a requirements-prod.lock, which contains the output of pip freeze, and acts as my lock-file. In addition I could have a requirements-dev.txt for development dependencies, and so on and so forth.

I would like to know if this is the way to go, or if there is a better approach.

p.s. The same question could be asked for conda's environment.yml.

解决方案

There are at least three good options available today:

1. pipenv uses Pipfile and Pipfile.lock similarly to how you describe the similar JavaScript files. pipenv is a "bigger" tool than pip, in the sense that it also creates and manages virtualenvs.

   This is likely the most popular option available today, and it will almost certainly replace pip in many developers' workflows.

2. poetry uses pyproject.toml and poetry.lock files, also similarly to how you describe the JavaScript files.

3. pip-tools provides pip-compile and pip-sync commands. Here, requirements.in lists your direct dependencies, often with loose version constraints and pip-compile generates locked down requirements.txt files from your .in files.

   Personally, I like this tool since it's backwards-compatible (the generated requirements.txt can be processed by pip) and the pip-sync tool ensures that the virtualenv exactly matches the locked versions, removing things that aren't in your "lock" file.

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