Different virtual on one Jupyter laptop

Question

I am working on an installation where several developers working in different projects execute their code on a remote machine using a Jupyter laptop.

Since each project requires a different virtualenv , now it happens that each developer sets up a specific virtualenv project for each project, installs a laptop for it, runs it on a different port, and connects to the remote computer through this port.

Is there a way to have 1 Jupyter block running on a remote computer, but be able to choose which virtualenv use as a kernel?

My main consideration is that you can only open one port on a remote computer, but be able to use another python virtual environment to run laptops

Answer 1

I am working on an installation where several developers

If you have many developers working on a remote computer, you should use JupyterHub, JupyterHub was created for this, and JupyterHub is the first step to relieve your pain; if you do not use JupyterHub, everything will be wrong.

After you install JupyterHub, your developers will be able to connect to their account using a single port and will be able to start / stop laptop servers without having to log in.

Once this is done, you will be able to examine several veins.

In each environment you want to install ipykernel . This is a module that knows how to talk with a laptop. And in each environment, you need to release python -m ipykernel install --user --name=my-env-name , as said in the comments below your posts. This register every env with Jupyter, telling him: "Hey, I exist, exposing me to your users." You can also install this , which does part of this automatically for you, but has some caveats.

As other commentators note, you probably want to read the Jake post , and if you have multiple users, you should absolutely always use JupyterHub with almost no questions.

Answer 2

Is there a way for 1 Jupyter to work on the remote control of the machine, but can you choose which virtual user to use as the kernel?

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Here's how I managed to use multiple cores in one instance of a Jupyter laptop

conda install nb_conda

nb_conda is a laptop extension that allows you to manage conda environments from your laptop. It also allows you to switch kernels directly from the Kernal menu.
I noticed that the above command installs it with a few extra features ( nbpresent , nb_anacondacloud ) that may optionally be disabled.

 jupyter-nbextension disable nb_anacondacloud --py --sys-prefix jupyter-serverextension disable nb_anacondacloud --py --sys-prefix jupyter-nbextension disable nbpresent --py --sys-prefix jupyter-serverextension disable nbpresent --py --sys-prefix 

If you are not using conda yet, you should consider it for package management and virtualenv [ source ].

I believe that there are not many errors mentioned in the jakesvdp post on this system that @denfromufa mentions , since the nb_conda laptop nb_conda should deal with all internal components.

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Screenshots

The Conda tab in your jupyter laptop allows you to control your environment right from your laptop.

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You can also choose which kernel the laptop starts using the Change kernel option in the Kernel menu

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