blocks|key|4456555|text|我发现这个链接非常有用：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4456556|https://ocefpaf.github.io/python4oceanographers/blog/2014/09/01/ipython_kernel/|offset|length|4456557|确保将jupyter安装到您的virtualenv中。以防链接稍后消失，要点如下：|4456558|你需要创建一个新的内核。您可以使用JSON文件指定内核。您的内核通常位于~/.ipython/kernels。创建一个与您的virtualenv同名的目录，并在其中创建kernel.json文件。例如，我的一条路径看起来像~./ipython/kernels/datamanip/kernel.json|style|CODE|4456559|下面是我的kernel.json文件的样子：|4456560|{
++"display_name":+"Data+Manipulation+(Python2)",
++"language":+"python",
++"codemirror_mode":+{
++++"version":+3,
++++"name":"ipython"
++},
++"argv":+[
++++"/Users/ed/.virtualenvs/datamanip/bin/python",
++++"-c",
++++"from+IPython.kernel.zmq.kernelapp+import+main;+main()",
++++"-f",
++++"{connection_file}"
++++]
}|code-block|syntax|javascript|4456561|我不确定codemirror_mode对象到底在做什么，但它似乎没有什么坏处。|4456562|entityMap|0|LINK|mutability|MUTABLE|url^0|0|0|27|0|0|0|10|I|33|14|0|0|0|0^^$0|@$1|2|3|4|5|6|7|11|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|12|8|@]|9|@$D|13|E|14|1|15]]|A|$]]|$1|F|3|G|5|6|7|16|8|@]|9|@]|A|$]]|$1|H|3|I|5|6|7|17|8|@$D|18|E|19|J|K]|$D|1A|E|1B|J|K]]|9|@]|A|$]]|$1|L|3|M|5|6|7|1C|8|@]|9|@]|A|$]]|$1|N|3|O|5|P|7|1D|8|@]|9|@]|A|$Q|R]]|$1|S|3|T|5|6|7|1E|8|@]|9|@]|A|$]]|$1|U|3|-4|5|6|7|1F|8|@]|9|@]|A|$]]]|V|$W|$5|X|Y|Z|A|$10|C]]]]

I found this link to be very useful:

<a href="https://ocefpaf.github.io/python4oceanographers/blog/2014/09/01/ipython_kernel/">https://ocefpaf.github.io/python4oceanographers/blog/2014/09/01/ipython_kernel/</a>

Make sure that you pip install jupyter into your virtualenv. In case the link goes away later, here's the gist:

You need to create a new kernel. You specify your kernel with a JSON file. Your kernels are usually located at <code>~/.ipython/kernels</code>. Create a directory with the name of your virtualenv and create your kernel.json file in it. For instance, one of my paths looks like <code>~./ipython/kernels/datamanip/kernel.json</code>

Here's what my kernel.json file looks like:

<pre><code>{
 "display_name": "Data Manipulation (Python2)",
 "language": "python",
 "codemirror_mode": {
 "version": 3,
 "name":"ipython"
 },
 "argv": [
 "/Users/ed/.virtualenvs/datamanip/bin/python",
 "-c",
 "from IPython.kernel.zmq.kernelapp import main; main()",
 "-f",
 "{connection_file}"
 ]
}
</code></pre>

I am not certain exactly what the codemirror_mode object is doing, but it doesn't seem to do any harm.

blocks|key|4456598|text|让notebook内核在其他笔记本中可用的更简单的解决方案。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4456599|我使用的是Linux+%2B+virtualenv+%2B+virtualenvwrapper。如果您使用的是不同的设置，请将一些命令更改为适当的命令，但您应该明白这一点。|4456600|mkvirtualenv+jupyter2
workon+jupyter2
(jupyter2)+pip+install+jupyter
(jupyter2)+ipython+kernel+install+--name+"jupyter2_Python_2"+--user|code-block|syntax|javascript|4456601|最后一条命令创建~/.local/share/jupyter/kernels/jupyter2\+python\+2/目录|offset|length|style|CODE|4456602|3的东西是一样的|4456603|mkvirtualenv+-p+/usr/bin/python3+jupyter3
//+this+uses+python3+as+default+python+in+virtualenv
workon+jupyter3
(jupyter3)+pip+install+jupyter
(jupyter3)+ipython+kernel+install+--name+"jupyter3_Python_3"+--user|4456604|完成后，无论您使用什么环境来启动jupyter，您都应该看到两个内核。您可以直接在~/.local/share/jupyter/kernels/中删除指向内核的链接。要指定位置，请向ipython+kernel+install+(--help)提供选项，或者如果只想从一个笔记本运行多个内核，则只需将目录从~/.local/share/jupyter/kernels/复制到~/envs/jupyter3/share/jupyter。|4456605|entityMap^0|0|0|0|8|1F|0|0|0|15|V|2J|V|49|V|57|T|0^^$0|@$1|2|3|4|5|6|7|W|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|X|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|Y|8|@]|9|@]|A|$G|H]]|$1|I|3|J|5|6|7|Z|8|@$K|10|L|11|M|N]]|9|@]|A|$]]|$1|O|3|P|5|6|7|12|8|@]|9|@]|A|$]]|$1|Q|3|R|5|F|7|13|8|@]|9|@]|A|$G|H]]|$1|S|3|T|5|6|7|14|8|@$K|15|L|16|M|N]|$K|17|L|18|M|N]|$K|19|L|1A|M|N]|$K|1B|L|1C|M|N]]|9|@]|A|$]]|$1|U|3|-4|5|6|7|1D|8|@]|9|@]|A|$]]]|V|$]]

A bit more simple solution to get notebook kernels available in other notebooks.

I'm using Linux + virtualenv + virtualenvwrapper. If you are using different setup, change some commands to the appropriate ones, but you should get the idea.

<pre><code>mkvirtualenv jupyter2
workon jupyter2
(jupyter2) pip install jupyter
(jupyter2) ipython kernel install --name "jupyter2_Python_2" --user
</code></pre>

last command creates <code>~/.local/share/jupyter/kernels/jupyter2\ python\ 2/</code> directory

same stuff for 3

<pre><code>mkvirtualenv -p /usr/bin/python3 jupyter3
// this uses python3 as default python in virtualenv
workon jupyter3
(jupyter3) pip install jupyter
(jupyter3) ipython kernel install --name "jupyter3_Python_3" --user
</code></pre>

When done you should see both kernels, no matter what env are you using to start jupyter.
You can delete links to kernels directly in <code>~/.local/share/jupyter/kernels/</code>.
To specify location provide options to <code>ipython kernel install (--help)</code> or just copy directories from <code>~/.local/share/jupyter/kernels/</code> to <code>~/envs/jupyter3/share/jupyter</code> if you want to run multiple kerenels from one notebook only.

blocks|key|4456529|text|@singer的解决方案对我不起作用。以下是有效的方法：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4456530|.+/path/to/virtualenv/.venv/bin/activate
python+-m+ipykernel+install+--user+--name+.venv+--display-name+.venv|code-block|syntax|javascript|4456531|参考资料：Kernels+for+different+environments+(官方文档)|offset|length|4456532|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/ipython/ipython/blob/7c12b021ee7bdcaf8cec814a624203d8e74aab08/docs/source/install/kernel_install.rst#kernels-for-different-environments^0|0|0|5|Y|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|T|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|U|8|@]|9|@$I|V|J|W|1|X]]|A|$]]|$1|K|3|-4|5|6|7|Y|8|@]|9|@]|A|$]]]|L|$M|$5|N|O|P|A|$Q|R]]]]

@singer's solution didn't work for me. Here's what worked:

<pre><code>. /path/to/virtualenv/.venv/bin/activate
python -m ipykernel install --user --name .venv --display-name .venv
</code></pre>

Reference: <a href="https://github.com/ipython/ipython/blob/7c12b021ee7bdcaf8cec814a624203d8e74aab08/docs/source/install/kernel_install.rst#kernels-for-different-environments" rel="noreferrer">Kernels for different environments</a> (official docs)

blocks|key|4456593|text|以下是对我有效的方法(非conda+python)：(MacOS，python的brew版本。如果您正在使用system+python，您可能(将)需要在每个命令前面加上sudo)|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|4456594|首先激活虚拟环境|4456595|如果重新启动，那么例如，您可以使用virtualenvwrapper|4456596|$pip+install+virtualenvwrapper
$mkvirtualenv+-p+python2+py2env+
$workon+py2env

#+This+will+activate+virtualenv

(py2env)$+

#+Then+install+jupyter+within+the+active+virtualenv
(py2env)$+pip+install+jupyter

#+jupyter+comes+with+ipykernel,+but+somehow+you+manage+to+get+an+error+due+to+ipykernel,+then+for+reference+ipykernel+package+can+be+installed+using:
(py2env)$+pip+install+ipykernel|code-block|syntax|javascript|4456597|接下来，设置内核|4456598|(py2env)$+python+-m+ipykernel+install+--user+--name+py2env+--display-name+"Python2+(py2env)"|4456599|然后启动jupyter+notebook+(该步骤不需要激活venv+)|4456600|(py2env)$+jupyter+notebook
#+or
#$+jupyter+notebook|4456601|在jupyter+notebook下拉菜单中：Kernel+>>+Change+Kernel+>>+<list+of+kernels>，您应该看到Python2+(py2env)内核|4456602|这也使得识别内核的python版本和同时维护两个版本变得很容易。|4456603|这是指向详细文档http://ipython.readthedocs.io/en/stable/install/kernel_install.html的链接|4456604|entityMap|0|LINK|mutability|MUTABLE|url|http://ipython.readthedocs.io/en/stable/install/kernel_install.html^0|C|5|2D|4|0|0|0|0|0|0|0|0|N|18|21|G|0|0|8|1V|0|0^^$0|@$1|2|3|4|5|6|7|1A|8|@$9|1B|A|1C|B|C]|$9|1D|A|1E|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|1F|8|@]|D|@]|E|$]]|$1|H|3|I|5|6|7|1G|8|@]|D|@]|E|$]]|$1|J|3|K|5|L|7|1H|8|@]|D|@]|E|$M|N]]|$1|O|3|P|5|6|7|1I|8|@]|D|@]|E|$]]|$1|Q|3|R|5|L|7|1J|8|@]|D|@]|E|$M|N]]|$1|S|3|T|5|6|7|1K|8|@]|D|@]|E|$]]|$1|U|3|V|5|L|7|1L|8|@]|D|@]|E|$M|N]]|$1|W|3|X|5|6|7|1M|8|@$9|1N|A|1O|B|C]|$9|1P|A|1Q|B|C]]|D|@]|E|$]]|$1|Y|3|Z|5|6|7|1R|8|@]|D|@]|E|$]]|$1|10|3|11|5|6|7|1S|8|@]|D|@$9|1T|A|1U|1|1V]]|E|$]]|$1|12|3|-4|5|6|7|1W|8|@]|D|@]|E|$]]]|13|$14|$5|15|16|17|E|$18|19]]]]

Here's what worked for me (non <code>conda</code> python):
(MacOS, brew version of python. if you are working with system python, you may (will) need prepend each command with <code>sudo</code>)

first activate virtualenv 

if starting afresh then, e.g., you could use virtualenvwrapper 

<pre><code>$pip install virtualenvwrapper
$mkvirtualenv -p python2 py2env 
$workon py2env

# This will activate virtualenv

(py2env)$ 

# Then install jupyter within the active virtualenv
(py2env)$ pip install jupyter

# jupyter comes with ipykernel, but somehow you manage to get an error due to ipykernel, then for reference ipykernel package can be installed using:
(py2env)$ pip install ipykernel
</code></pre>

Next, set up the kernel

<pre><code>(py2env)$ python -m ipykernel install --user --name py2env --display-name "Python2 (py2env)"
</code></pre>

then start jupyter notebook (the venv need not be activated for this step)

<pre><code>(py2env)$ jupyter notebook
# or
#$ jupyter notebook
</code></pre>

in the jupyter notebook dropdown menu: <code>Kernel &gt;&gt; Change Kernel &gt;&gt; &lt;list of kernels&gt;</code> you should see <code>Python2 (py2env)</code> kernel

This also makes it easy to identify python version of kernel, and maintain either side by side.

here is the link to detail docs
<a href="http://ipython.readthedocs.io/en/stable/install/kernel_install.html" rel="noreferrer">http://ipython.readthedocs.io/en/stable/install/kernel_install.html</a>

blocks|key|4456696|text|nb_canda非常有用：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4456697|conda+install+nb_conda|code-block|syntax|javascript|4456698|因此，您可以使用conda虚拟环境创建和选择您自己的python内核，并在venv中管理软件包。|4456699|截图|4456700|列表项|4456701|​|4456702|📷|atomic|offset|length|4456703|4456704|jupyter+notebook中的conda环境管理器Conda选项卡允许您直接从笔记本中管理环境。|4456705|Change+Kernel通过使用kernel菜单中的Change+kernel选项，还可以选择在哪个内核中运行notebook|4456706|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/79504f27a662df430db5adf7aa8f5f68.png|imageAlt^0|0|0|0|0|0|0|0|1|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|17|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|18|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|19|8|@]|9|@]|A|$]]|$1|I|3|J|5|6|7|1A|8|@]|9|@]|A|$]]|$1|K|3|L|5|6|7|1B|8|@]|9|@]|A|$]]|$1|M|3|N|5|6|7|1C|8|@]|9|@]|A|$]]|$1|O|3|P|5|Q|7|1D|8|@]|9|@$R|1E|S|1F|1|1G]]|A|$]]|$1|T|3|N|5|6|7|1H|8|@]|9|@]|A|$]]|$1|U|3|V|5|6|7|1I|8|@]|9|@]|A|$]]|$1|W|3|X|5|6|7|1J|8|@]|9|@]|A|$]]|$1|Y|3|-4|5|6|7|1K|8|@]|9|@]|A|$]]]|Z|$10|$5|11|12|13|A|$14|15|16|-4]]]]

the nb_canda is useful:

<pre><code>conda install nb_conda
</code></pre>

so,you can create and select your own python kernel with conda virtual environment,and manage the packages in venv

<h2>Screenshots</h2>

List item

<a href="https://i.stack.imgur.com/EtZ5n.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/EtZ5n.png" alt="Screenshot"></a>

conda environment manager Conda tab in jupyter notebook allows you to manage your environments right from within your notebook.

Change Kernel
You can also select which kernel to run a notebook in by using the Change kernel option in Kernel menu

I would like to execute a long running Python script from within a Jupyter notebook so that I can hack on the data structures generated mid-run.

The script has many dependencies and command line arguments and is executed with a specific virtualenv. Is it possible to interactively run a Python script inside a notebook from a specified virtualenv (different to that of the Jupyter installation)?

Thanks!

Execute Python script within Jupyter notebook using a specific virtualenv

我想从Jupyter笔记本中执行一个长时间运行的Python脚本，这样我就可以破解运行过程中生成的数据结构。该脚本具有许多依赖项和命令行参数，并使用特定的virtualenv执行。是否可以从指定的virtualenv (与Jupyter安装不同)以交互方式在notebook中运行Python脚本？谢谢!

问使用特定的虚拟环境在Jupyter notebook中执行Python脚本
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