How can I use Julia in Jupyter lab, MacBook M1? - macos

Julia REPL run well in my M1 mac, but I can't use it in jupyter lab.
I tried same way as in Win10, just like below.
using Pkg
ENV["JUPYTER"]="Users/(user name)/opt/anaconda3/bin/jupyter.exec"
Pkg.build("IJulia")
Pkg.add("IJulia")
The path in Win10 was
ENV["JUPYTER"]="C:\\Users\\(user name)\\Anaconda3\\Scripts\\jupyter.exe"
But the jupyter file is located in different path in mac, so I changed the path.
After this setting, Julia symbol appears right in jupyter lab launcher, but I get some error message when I click.
Error Starting Kernel
Unhandled error
Unhandled error
What's the right way to set Julia in JupyterLab in osX, M1?

Related

Can Jupyter Notebook run on Windows 10

I installed Jupyter Notebook on Windows 10. But I got an error when launching it in Visual Studio Code as:
jupyter : The term 'jupyter' is not recognized as the name of a cmdlet, function, script file, or operable program. Check the spelling of the name, or if a path was included, verify that the path is correct and try again.
After searching online, I decided to install Anaconda first and run Jupyter from it. But launching it from Anaconda was directed to a web address. It looks like Jupyter is only a web application.
I wonder if it is possible to run the Jupyter Notebook as a desktop application on Windows.
There is a JupyterLab Desktop App, see here and here. I don't know how old of a version of Windows works for it.
Rest was built from discussion in comments:
On Jupyter with VS Code:
Jupyter itself works with VScode to run Jupyter notebooks in VScode. You wouldn't need the JupyterLab Desktop App in that case. You do need Jupyter though. See here if you are interested in using Jupyter notebooks in VSCode.
On installing packages that worked before installed Anaconda:
The easiest solution would be to reinstall them. It is possible you could add the already installed ones to your path, but if you have room it is easiest to keep your Anaconda installed stuff where it is and separate from what you had. The easiest way to sort where to install them is to let Jupyter handle it. For example, if you want to work with Pandas in a notebook, in that notebook run %conda install -c anaconda pandas, based on here and the magic install command. For the packages that conda cannot install, and only for those, use %pip install <package_name>.
You can delete the install commands out of the notebook after if you want. You may just want to comment them out so you remember. For the short term you are fine re-running the commands because if the package is already installed by conda or pip it won't get reinstalled; however, if the package gets a new release and you aren't specifying versions, you'll get the latest when that install command next runs and if there is an error or incompatibility, then you'll have caused yourself an issue you could have avoided.

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