如何通过conda安装我自己的python模块（包）并观察它的变化

How to install my own python module (package) via conda and watch its changes

提问by Michael

I have a file mysql.py, which I use in almost all of my projects. Since I do not want to copy and paste the same file into each of these projects I wrote a module - possibly a package in the future.

我有一个文件mysql.py，我几乎在所有项目中都使用它。由于我不想将相同的文件复制并粘贴到每个项目中，因此我编写了一个模块 - 将来可能是一个包。

Question

题

How do I add a local module to my conda environment, and automatically update or watch it when I change something in mysql.py? How to do the same for a package?

如何将本地模块添加到我的 conda 环境中，并在我更改某些内容时自动更新或监视它mysql.py？如何对包做同样的事情？

I would like to avoid to set up a local channel/repository and just reference to the folder with mysql.py.

我想避免设置本地频道/存储库，而只是引用带有mysql.py.

回答by Michael

While the previous answers are doing what I need, I just want to show what I will be using instead. Since it was my plan to learn about conda packages anyway...

虽然以前的答案正在做我需要的事情，但我只想展示我将使用的内容。因为无论如何我都计划学习 conda 包......

0. Good sources

0. 好货源

1. Michael Sarahan - Making packages and packaging "just work" | YouTube
2. GitHub - audreyr/cookiecutter: A command-line utility that creates projects from cookiecutters (project templates)and use one of these templates:
   • GitHub - audreyr/cookiecutter-pypackage: Cookiecutter template for a Python package.
   • GitHub - conda/cookiecutter-conda-python: A cookiecutter template for conda packages using Python(This is what I used)

1. Michael Sarahan - 制作包装和包装“恰到好处” | YouTube
2. cookiecutter,从 cookiecutter (项目模板) 创建项目并使用以下模板之一的 命令行实用程序,下载cookiecutter的源码_GitHub_酷徒
   • cookiecutter-pypackage,Python 包的 Cookiecutter 模板,下载cookiecutter-pypackage的源码_GitHub_酷徒
   • cookiecutter-conda-python,使用 Python 的 conda 包的 cookiecutter 模板(这是我使用的),下载cookiecutter-conda-python的源码_GitHub_酷徒

1. Create a python package template for conda using cookiecutter

1.使用cookiecutter为conda创建python包模板

conda install -c conda-forge cookiecutter

Now change to the directory where you want to initialize your package, then do:

现在切换到要初始化包的目录，然后执行以下操作：

cookiecutter https://github.com/conda/cookiecutter-conda-python.git

This will ask for some basic information about the package that you want to create. Then change into your repo

这将询问有关您要创建的包的一些基本信息。然后换成你的回购

cd myrepo

2. Build your package

2. 构建你的包

make sure conda-buildis installed, if not run

确保conda-build已安装，如果没有运行

conda install conda-build

Make sure to set the CONDA_BLD_PATHas mentioned in anaconda - using a different conda-build root directory - Stack Overflow. This will be the directory where you can find your packages, then run:

确保CONDA_BLD_PATH按照anaconda 中所述进行设置- 使用不同的 conda-build 根目录 - 堆栈内存溢出。这将是您可以找到包的目录，然后运行：

conda build conda.recipe

to build your package and clean up after you with

构建你的包并在你之后清理

conda build purge

3. Set up your own local channel (no uploading to anaconda.org)

3.建立自己的本地频道（不上传到anaconda.org）

Read

读

• Creating custom channels — Conda documentation
• python - add local channel to .condarc on windows - Stack Overflow

• 创建自定义通道 — Conda 文档
• python - 在Windows上将本地频道添加到.condarc - VoidCC

for help.

求助。

Index each platform. Maybe someone can confirm that this step is not needed, as my builds already contain the repodata.json. Otherwise:

索引每个平台。也许有人可以确认不需要这一步，因为我的构建已经包含repodata.json. 除此以外：

conda index D:\CODE\condamychannel\win-64

Test if the package can be found with

测试是否可以找到包

conda search -c file:///D:\CODE\condamychannel --override-channels mypackage

or add the channel to the config directly (per environment)

或直接将频道添加到配置中（每个环境）

conda config --add channels file:///D:\CODE\condamychannel

4. Install (and update) the package

4.安装（和更新）包

activate myenv

and

和

conda install mypackage

Once I change mypackage, I give it a new version number in meta.yamland setup.pyand build the package with conda build conda.recipe. Updating is simply

一旦我改变mypackage，我给它一个新的版本号，meta.yaml并setup.py用conda build conda.recipe. 更新很简单

conda update mypackage

See if your package works:

看看你的包是否有效：

python
>>> import cli from mypackage
>>> cli.cli()
CLI template

---

---

This may not be the optimal way, but I could not find a tutorial that contains all the steps I outlined above.

这可能不是最佳方式，但我找不到包含我上面概述的所有步骤的教程。

回答by darthbith

If you install the conda build package (and you have a package, not just a script), you can install in "editable" mode:

如果你安装了 conda 构建包（并且你有一个包，而不仅仅是一个脚本），你可以在“可编辑”模式下安装：

conda develop .

(running from the directory with your script). This is very similar to the "editable" mode from pip

（从带有脚本的目录运行）。这与 pip 的“可编辑”模式非常相似

pip install -e .

Either approach lets you uninstall packages with either

这两种方法都可以让您卸载软件包

conda develop -u .

or

或者

pip uninstall .

If you just have a script (not a package), you can edit or set the PYTHONPATHenvironment variable to include the directory with the script.

如果您只有一个脚本（不是包），您可以编辑或设置PYTHONPATH环境变量以将目录包含在脚本中。

回答by amanb

I had a wrapper function that I had to call multiple times on different scripts.So, I copied that file wrappers.pyto the Anaconda site-packagesfolder. On my computer this was at: C:\ProgramData\Anaconda3\Lib\site-packages. Then, whenever I needed wrappers.py, I'd just import it in my scripts, like this:

我有一个包装函数，我必须在不同的脚本上多次调用它。所以，我将该文件复制wrappers.py到了 Anaconda站点包文件夹。在我的电脑上，这是在：C:\ProgramData\Anaconda3\Lib\site-packages。然后，每当我需要时wrappers.py，我都会将它导入到我的脚本中，如下所示：

import wrappers

If you want to make sure that the import was successful, you could either select Anaconda as your dev environment in your IDE and then invoke the Intellisense after import: from wrappers import (intellisense suggestions). Or you could also use IDLE:

如果你想确保导入成功，您既可以选择如蟒蛇在IDE的开发环境，然后调用智能感知导入后：from wrappers import (intellisense suggestions)。或者你也可以使用 IDLE：

>>> import wrappers
>>>(if you get this prompt, this means the import was successful).

Conda integration is only possible if you create custom channels. This is because conda searches for packages in the following locations(based on your OS) and to tell conda to search for your module at certain location(s), you must install conda-buildto create a custom channel:

Conda 集成只有在您创建自定义渠道时才可能。这是因为 conda 在以下位置搜索包（基于您的操作系统）并告诉 conda 在特定位置搜索您的模块，您必须安装conda-build以创建自定义通道：

- https://repo.continuum.io/pkgs/main/win-64
- https://repo.continuum.io/pkgs/main/noarch
- https://repo.continuum.io/pkgs/free/win-64
- https://repo.continuum.io/pkgs/free/noarch
- https://repo.continuum.io/pkgs/r/win-64
- https://repo.continuum.io/pkgs/r/noarch
- https://repo.continuum.io/pkgs/pro/win-64
- https://repo.continuum.io/pkgs/pro/noarch
- https://repo.continuum.io/pkgs/msys2/win-64
- https://repo.continuum.io/pkgs/msys2/noarch

If you want to avoid creating a repo/channel, then a simple import as above should do the job. In addition, if you make any changes to your module and save it, you will always have the latest importin your scripts.

如果你想避免创建一个 repo/channel，那么上面的简单导入应该可以完成这项工作。此外，如果您对模块进行任何更改并保存它，您将始终拥有import脚本中的最新版本。