在Jupyter notebook中使用特定虚拟环境中的python的kernel

    在虚拟环境tf中安装完tensorflow后，在虚拟环境tf打开的jupyter里发现只有一个kernel-python3，新建一个文件， import tensorflow as tf ，发现报错，没有tf这个模块。
    一开始还以为是tf的问题安装失败，后来才意识到是jupyter的问题。因为在虚拟环境tf中，虽然有jupyter(或者自己再安装pip install jupyter，他会提示说已存在)，但这个jupyter还是原python环境中的jupyter。在虚拟环境tf中用命令 (tf) treamy ~ $ which jupyter 得/usr/local/bin/jupyter 再用 (tf) treamy ~ $ find ~/code/pydir/env -name "jupyter*" 发现虚拟环境中无jupyter。故虚拟环境中的jupyter还是原python环境中的jupyter，kernel为python3，而我的原python3并没有安装tensorflow，所以报错了。

 

 

 

之前查网上按这个方法解决：（但无效）

(tf) treamy ~ $ ipython kernelspec install-self --user

[TerminalIPythonApp] WARNING | Subcommand `ipython kernelspec` is deprecated and will be removed in future versions.

[TerminalIPythonApp] WARNING | You likely want to use `jupyter kernelspec` in the future

[InstallNativeKernelSpec] WARNING | `jupyter kernelspec install-self` is DEPRECATED as of 4.0. You probably want `ipython kernel install` to install the IPython kernelspec.

[InstallNativeKernelSpec] Installed kernelspec python3 in /Users/treamy/Library/Jupyter/kernels/python3

(tf) treamy ~ $ mkdir -p ~/.ipython/kernels
(tf) treamy ~ $ mv /Users/treamy/Library/Jupyter/kernels/python3 ~/.ipython/kernels/tfkernel

打开kernel.json文件，然后将display_name 后面的内容修改为tfkernel

(tf) treamy ~ $ vim ~/.ipython/kernels/tfkernel/kernel.json

但这样并无效果，因为创建的kernel相当于只是原kernel的复制品即python3，从上面那个json文件就可以看出来。

 

 

解决方案：

(tf) treamy ~ $ python3 -m ipykernel install --user --name tf --display-name "Python3(tf)"

# Installed kernelspec tf in /Users/treamy/Library/Jupyter/kernels/tf

cd 到 /Users/treamy/Library/Jupyter/kernels/tf

里面含 kernel.json  logo-32x32.png  logo-64x64.png 

查看这个json文件： cat kernel.json 

{

"argv": [

"/Users/treamy/code/pydir/env/tf/bin/python3",

"-m",

"ipykernel_launcher",

"-f",

"{connection_file}"

],

"display_name": "Python3(tf)",

"language": "python"

}

 

然后也不用移动它，就这样就OK了。刷新jupyter后就可以看到Python3(tf)这个选项。

详细官方文档：

https://github.com/ipython/ipython/blob/7c12b021ee7bdcaf8cec814a624203d8e74aab08/docs/source/install/kernel_install.rst#kernels-for-different-environments