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JupyterLab 4.0

blog.jupyter.org

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Re: JupyterLab 4.0

#21

Post by aidos »

mkl wrote: post #7
abdullahkhalids wrote: post #3

I see no mention of an improved debugger. IMHO, the atrocious debugger in JupyterLab is one of the primary reasons why it is difficult to write good code in this environment. Even a simple improvement like remembering the sizes of various subpanels in the debugger sidebar will make me feel like I am not pulling teeth when I use it. And don't get me started on inspecting the value of variables. If you are looking for…

Do you know how it compares to using Visual Studio Code's debugger with notebooks? I'm wanting to find a notebook debugger recommendation for my students.

Is this in the context of students learning to code, or something else where they need to use the notebooks to supplement their study?

Re: JupyterLab 4.0

#22

Post by rollinDyno »

I have been using VSCode notebooks with .ipynb file extensions, this gives me many advantages as I am able to configure things I'm not able in JupyterLab. I also have access to a very rich ecosystem of plugins. If there is anyone aware of VSCode as a solution but keeps using JupyterLab, could they explain why?

Re: JupyterLab 4.0

#23

Post by anvuong »

bityard wrote: post #16
mikepurvis wrote: post #13

I keep experimenting with Jupyter in the context of telemetry/fault analysis and then hitting a wall with it where: - I get an analysis that I like, but there isn't a good way to share it with others, so I end up just taking screenshots. - There isn't a good way to take the same analysis and plug new data into it, other than to copy-paste the entire notebook. - The process to "promote" fragments of a notebook into be…

> There aren't good boundaries between Jupyter's own Python environment, and that of your notebooks— if you have a dependency which conflicts with one of Jupyter's dependencies, then good luck. It's cumbersome, and I'm not totally sure it's the correct way, but I remember getting around this by creating a virtualenv for my projects and then using that virtualenv's python as Jupyter's "kernel".

This is the way. I use miniconda to create env for Jupyter and install only Jupyter and its dependency on that, then I just config it to point to all the other Python envs I use for my different projects. This is only one-time setup and it is absolutely worth it given how messy the ecosystem is.

Re: JupyterLab 4.0

#24

Post by anvuong »

rollinDyno wrote: post #22

I have been using VSCode notebooks with .ipynb file extensions, this gives me many advantages as I am able to configure things I'm not able in JupyterLab. I also have access to a very rich ecosystem of plugins. If there is anyone aware of VSCode as a solution but keeps using JupyterLab, could they explain why?

Maybe because the Jupyter is setup on the computing server, where everyone needs to log in to do their works? This was the case for my last 4 companies.

Re: JupyterLab 4.0

#25

Post by nigma »

mikepurvis wrote: post #13

I keep experimenting with Jupyter in the context of telemetry/fault analysis and then hitting a wall with it where: - I get an analysis that I like, but there isn't a good way to share it with others, so I end up just taking screenshots. - There isn't a good way to take the same analysis and plug new data into it, other than to copy-paste the entire notebook. - The process to "promote" fragments of a notebook into be…

I’m using Jupyter Book (https://jupyterbook.org/) to build all kinds of daily reports and it works really well. Individual notebooks can also be converted to HTML or pdf with nbconvert using command line or “download as” menu item.

Re: JupyterLab 4.0

#26

Post by rollinDyno »

anvuong wrote: post #24
rollinDyno wrote: post #22

I have been using VSCode notebooks with .ipynb file extensions, this gives me many advantages as I am able to configure things I'm not able in JupyterLab. I also have access to a very rich ecosystem of plugins. If there is anyone aware of VSCode as a solution but keeps using JupyterLab, could they explain why?

Maybe because the Jupyter is setup on the computing server, where everyone needs to log in to do their works? This was the case for my last 4 companies.

I see. If I faced the same constraint I would try to find whether VSCode can access files remotely, which is very likely.

Re: JupyterLab 4.0

#27

Post by modriano »

bityard wrote: post #16
mikepurvis wrote: post #13

I keep experimenting with Jupyter in the context of telemetry/fault analysis and then hitting a wall with it where: - I get an analysis that I like, but there isn't a good way to share it with others, so I end up just taking screenshots. - There isn't a good way to take the same analysis and plug new data into it, other than to copy-paste the entire notebook. - The process to "promote" fragments of a notebook into be…

> There aren't good boundaries between Jupyter's own Python environment, and that of your notebooks— if you have a dependency which conflicts with one of Jupyter's dependencies, then good luck. It's cumbersome, and I'm not totally sure it's the correct way, but I remember getting around this by creating a virtualenv for my projects and then using that virtualenv's python as Jupyter's "kernel".

Yeah, that's essentially the right way (I use conda envs, but venvs are probably fine too). Have one env for running the Jupyter Lab/Notebook server (install jupyter, jupyter widgets, nbextensions, etc into this env) and then create other envs for your projects and register that kernel with jupyter [0]. You can also just install all of the jupyter ide cruft in each env if you want, but dependencies can get annoying.

[0] https://stackoverflow.com/questions/39604271/conda-environme....

Re: JupyterLab 4.0

#28

Post by Xeamek »

mkl wrote: post #17
Xeamek wrote: post #14

Earlier quoted context omitted.

Have you tried pyCharm? I believe even community (free) edition should have support You are looking for

No I haven't, but it looks like the community edition can't do notebooks: https://www.jetbrains.com/help/pycharm/jupyter-notebook-supp...

Ah, my bad then.

If it's for student, you could maybe get educational license, that is completely free for all their products, but I imagine it could be quite a hassle

Re: JupyterLab 4.0

#29

Post by garbagecoder »

bityard wrote: post #16
mikepurvis wrote: post #13

I keep experimenting with Jupyter in the context of telemetry/fault analysis and then hitting a wall with it where: - I get an analysis that I like, but there isn't a good way to share it with others, so I end up just taking screenshots. - There isn't a good way to take the same analysis and plug new data into it, other than to copy-paste the entire notebook. - The process to "promote" fragments of a notebook into be…

> There aren't good boundaries between Jupyter's own Python environment, and that of your notebooks— if you have a dependency which conflicts with one of Jupyter's dependencies, then good luck. It's cumbersome, and I'm not totally sure it's the correct way, but I remember getting around this by creating a virtualenv for my projects and then using that virtualenv's python as Jupyter's "kernel".

I just do a venv inside the venv so I can target several Python versions. I also use Jupiter for C#, Clojure, and Julia. I wish the Clojure integration was as good as the others I listed.

I’m to the point now where if anything other than venv/pip is required I won’t use it. Unfortunately there are many things that insist on conda.

Re: JupyterLab 4.0

#30

Post by spywaregorilla »

mikepurvis wrote: post #13

I keep experimenting with Jupyter in the context of telemetry/fault analysis and then hitting a wall with it where: - I get an analysis that I like, but there isn't a good way to share it with others, so I end up just taking screenshots. - There isn't a good way to take the same analysis and plug new data into it, other than to copy-paste the entire notebook. - The process to "promote" fragments of a notebook into be…

> The process to "promote" fragments of a notebook into being reusable functions seemed very high-friction: basically you're rewriting it as a normal Python package and then adding that to Jupyter's environment.

Don't get in that situation to begin with. Pop an `%load_ext` `%autoreload 2` at the top and just write functions in an imported .py file from the get go.

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