将 Conda 环境与 Jupyter Notebook 链接 [英] Link Conda environment with Jupyter Notebook

问题描述

我正在尝试为使用 python 做一些科学工作设置一个良好的环境.为此，我安装了 Jupyter &迷你康达.

I'm trying to set a good environnement for doing some scientific stuff with python. To do so, I installed Jupyter & miniconda.

然后我希望能够拥有不同的环境并将它们与 Jupyter 笔记本一起使用.所以我用 conda 创建了两个自定义环境:py27 和 py35.

Then I want to be able to have different environnement and use them with Jupyter notebooks. So I created two custom envs with conda : py27 and py35.

> conda env list
# conda environments:
#
py27                     /Users/***/miniconda3/envs/py27
py35                     /Users/***/miniconda3/envs/py35
root                  *  /Users/***/miniconda3

然后在我的笔记本上，我有两个内核 python 2 和 python 3.在笔记本中，我使用 python3 内核得到以下信息:

Then on my notebook I have two kernels python 2 and python 3. Inside a notebook, I get the following with the python3 kernel :

> import sys
> print(sys.executable)
/Users/***/miniconda3/envs/py35/bin/python

这与 python2 内核:

And this with the python2 kernel :

> import sys
> print(sys.executable)
/usr/local/opt/python/bin/python2.7

• 如何将 sys.executable 设置为 python2 的 miniconda env?
• 如何将 conda env 与笔记本内核绑定?
• source activate py35 是否与 jupyter notebook 有链接?
• How can I set the sys.executable to miniconda env for python2 ?
• How can I bind a conda env with a notebook kernel ?
• Is doing source activate py35 has a link with jupyter notebook ?

我想我真的错过了一些东西.

I think I really missed something.

谢谢大家.

--- 编辑

我有多个 jupyter bin :

I have multiple jupyter bin :

> where jupyter
/usr/local/bin/jupyter
/usr/local/bin/jupyter
/Users/ThomasDehaeze/miniconda3/bin/jupyter

我这里只有一个内核 /usr/local/share/jupyter/kernels/python2.但是在 Jupyter 内部，我有两个内核，python2 和 python3.我在哪里可以找到另一个?

I have only one kernel here /usr/local/share/jupyter/kernels/python2. But inside Jupyter, I have two kernels, python2 and python3. Where can I find the other one ?

我从 /usr/local/share/jupyter/kernels/python2 修改了 kernel.json :

{
 "display_name": "Python 2",
 "language": "python",
 "argv": [
  "/Users/***/miniconda3/envs/py27/bin/python2.7",
  "-m",
  "ipykernel",
  "-f",
  "{connection_file}"
 ]
}

然后:

import sys
print(sys.executable)
/usr/local/opt/python/bin/python2.7

所以什么都没有改变

推荐答案

对于 Anaconda，我建议你一个更简单、更合适的解决方案；只需看看 nb_conda_kernels 包.

For Anaconda I suggest you a much easier and proper solution; just give a look at the nb_conda_kernels package.

它允许您在 Jupyter Notebook 中管理基于 conda 环境的内核".

It allows you to "manage your conda environment-based kernels inside the Jupyter Notebook".

从 Anaconda 版本 4.1.0 开始就应该包含它，否则只需使用

Is should be included since Anaconda version 4.1.0, otherwise simply use

conda install nb_conda

现在您应该可以直接从 Notebook 界面进行管理了.

Now you should be able to manage all direcly from the Notebook interface.

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