I have written Julia scripts and accessed different Julia libraries without issue in Jupyter. I have not noticed any limitations on its use or any performance degradation. I imagine some aspects of Julia that are very screen dependent (such as using the Julia Webstack to build a website) may be hampered by conflicting uses of the same concept.
I have repeatedly seen updates being run when I am attempting to run a Julia script, as in the following screenshot. I am not sure why they decided to always update the underlying tool rather than use what is in play and have the user specify whether to update libraries:
I have also noticed that once a Julia notebook is opened, even though I have closed the page, it will still display Running on the home page. I don't recall seeing this behavior with the other script languages available.
Another issue has been trying to use a secured package in my script, for example, plotly
. It appears to be a clean process to get credentials, but using the prescribed methods for passing your credentials to plotly
does not work under Windows. I am hesitant to provide examples that do not work in both environments.
Further interactions with Windows are also limited, for example, attempting to access environment variables by calls to standard C libraries that are normally not present on a Windows installation.
I have another issue with Julia itself-regardless of whether it's running in Jupyter or not. When using a package, it will complain about features that are used in the package that have been deprecated or improved. As a user of the package, I have no control over this behavior, so it does not help me in my work.
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