blocks|key|4578691|text|这是因为需要一个额外的步骤--您需要显式地安装一个指向新的Python虚拟环境的Jupyter内核。您不能简单地从虚拟环境中激活Jupyter-lab或Notebook。这之前也曾让我被绊倒过。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4578692|遵循这里的建议：|4578693|事实上，可能会出现内核仍然没有指向正确的Python二进制文件的问题，在这种情况下，您需要在上面的建议过程中更改一个建议：|4578694|来自：ipython+kernel+install+--user+--name=projectname|offset|length|style|CODE|4578695|收件人：python3+-m+ipykernel+install+--user+--name=projectname|4578696|(这一修正来自a+comment+to+。)|4578697|*，别忘了重启VSCode|BOLD|4578698|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/jupyter/notebook/issues/2563#issuecomment-330472953^0|0|0|0|3|1C|0|4|1I|0|7|D|0|0|1|C|0^^$0|@$1|2|3|4|5|6|7|10|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|11|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|12|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|13|8|@$H|14|I|15|J|K]]|9|@]|A|$]]|$1|L|3|M|5|6|7|16|8|@$H|17|I|18|J|K]]|9|@]|A|$]]|$1|N|3|O|5|6|7|19|8|@]|9|@$H|1A|I|1B|1|1C]]|A|$]]|$1|P|3|Q|5|6|7|1D|8|@$H|1E|I|1F|J|R]]|9|@]|A|$]]|$1|S|3|-4|5|6|7|1G|8|@]|9|@]|A|$]]]|T|$U|$5|V|W|X|A|$Y|Z]]]]

It's because there is an extra step needed - you need to explicitly install a Jupyter kernel that points to your new Python virtual environment. You can't simply activate Jupyter-lab or Notebook from the virtual environment. This has tripped me up before, too.
Follow the advice here: <a href="https://anbasile.github.io/programming/2017/06/25/jupyter-venv/" rel="noreferrer">Using Jupyter notebooks with a virtual environment</a>
And, in fact, there can be an issue where your kernel still doesn't point to the correct Python binary, in which case you need to change one suggestion in the above advice process:
From: <code>ipython kernel install --user --name=projectname</code>
To: <code>python3 -m ipykernel install --user --name=projectname</code>
(This correction comes from <a href="https://github.com/jupyter/notebook/issues/2563#issuecomment-330472953" rel="noreferrer">a comment to Jupyter Notebook is loading incorrect Python kernel #2563</a>.)
*and don't forget to restart VSCode

blocks|key|2467771|text|我发现使用pipenv+install+ipykernel一次性设置带有Jupyter内核的虚拟环境很容易(在rocksteady's+answer上发表评论)。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|2467772|entityMap|0|LINK|mutability|MUTABLE|url|https://stackoverflow.com/questions/58119823/jupyter-notebooks-in-visual-studio-code-does-not-use-the-active-virtual-environm/58134257#58134257^0|5|O|1J|J|0|0^^$0|@$1|2|3|4|5|6|7|N|8|@$9|O|A|P|B|C]]|D|@$9|Q|A|R|1|S]]|E|$]]|$1|F|3|-4|5|6|7|T|8|@]|D|@]|E|$]]]|G|$H|$5|I|J|K|E|$L|M]]]]

I find it easy to use <code>pipenv install ipykernel</code> to set up the virtual environment with the Jupyter kernel in one go (comment on <a href="https://stackoverflow.com/questions/58119823/jupyter-notebooks-in-visual-studio-code-does-not-use-the-active-virtual-environm/58134257#58134257">rocksteady's answer</a>).

blocks|key|2467822|text|对于我来说，通过将我的venv路径添加到settings.json，|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2467823|现在可以自动检测内核了|2467824|“"P:\Miniconda3_64bit\venv\Scripts\python.exe"，”：python.pythonPath|2467825|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|H|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|I|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|J|8|@]|9|@]|A|$]]|$1|F|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|G|$]]

for me solved by adding the path of my venv to the settings.json,
now the kernel is detected automatically
&quot;python.pythonPath&quot;: &quot;P:\Miniconda3_64bit\venv\Scripts\python.exe&quot;,

blocks|key|5995643|text|尝试以下几种方法：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|5995644|5995645|确保您可以使用带有相同Conda+environment.|ordered-list-item|5995646|If的"ipython“提示符从Visual+Studio+code终端运行代码。如果有时是缓存问题，请关闭您的文件并打开一个新文件。|5995647|5995648|entityMap^0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|K|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|L|8|@]|9|@]|A|$]]|$1|C|3|D|5|E|7|M|8|@]|9|@]|A|$]]|$1|F|3|G|5|E|7|N|8|@]|9|@]|A|$]]|$1|H|3|-4|5|6|7|O|8|@]|9|@]|A|$]]|$1|I|3|-4|5|6|7|P|8|@]|9|@]|A|$]]]|J|$]]

Try a few things:
<ol>
<li>Make sure you can run the code from a Visual Studio Code terminal using the &quot;ipython&quot; prompt with the same Conda environment.</li>
<li>If it works then sometimes it is a caching issue, so close your file and open a new one.</li>
</ol>

blocks|key|4578808|text|在macOS上，我的.ipynb所在的文件夹中有.venv/|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4578809|.+.venv/bin/activate
pip+install+ipykernel|code-block|syntax|javascript|4578810|然后在项目文件夹中重新启动VSCode，打开笔记本，在Select+Kernel下拉菜单中看到.venv/bin/python|offset|length|style|CODE|4578811|选择了这一点，现在它就可以工作了。|4578812|entityMap^0|0|0|R|D|1B|G|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|R|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|S|8|@$I|T|J|U|K|L]|$I|V|J|W|K|L]]|9|@]|A|$]]|$1|M|3|N|5|6|7|X|8|@]|9|@]|A|$]]|$1|O|3|-4|5|6|7|Y|8|@]|9|@]|A|$]]]|P|$]]

On macOS I have .venv/ in the same folder as my .ipynb
<pre><code>. .venv/bin/activate
pip install ipykernel
</code></pre>
Then I restart VSCode in the project folder, open the notebook, and in the <code>Select Kernel</code> dropdown I see <code>.venv/bin/python</code>
Selecting that, now it works.

blocks|key|2467694|text|尝试安装Anaconda扩展包。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2467695|当我在Visual+Studio+code中编写代码时，此扩展位于左下角，我可以选择要在其中执行代码的虚拟环境。因此，安装这个包应该可以解决这个问题。|2467696|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|F|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|G|8|@]|9|@]|A|$]]|$1|D|3|-4|5|6|7|H|8|@]|9|@]|A|$]]]|E|$]]

Try installing the Anaconda Extension pack.
When I code in Visual Studio Code with this extension in the bottom left corner, I can select the virtual environment I want to execute my code in. Hence installing this package should make the trick.

I write Python code in Visual Studio Code and run the program from a terminal in which I have activated a virtual environment, and it works fine.
However, if I create notebook cells using #%% and run those interactively, the virtual environment is not used. How can I fix this?

Jupyter notebooks in Visual Studio Code does not use the active virtual environment

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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我用Visual Studio code编写Python代码，并在激活了虚拟环境的终端上运行该程序，它工作得很好。但是，如果我使用#%%创建notebook单元并以交互方式运行这些单元，则不会使用虚拟环境。我该如何解决这个问题呢？

问Visual Studio代码中的Jupyter notebooks不使用活动虚拟环境
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