We'll discuss it at our triage meeting. Sorry, something went wrong. Btw, there are other workarounds to this when you use a cloud provider anyway in your project S3, data storage, blob, Something similar probably exists for other cloud providers. Just found this issue and indeed, this would be a feature making the entire experience more round. The Jupyter remote server is on abstract level just a dumb number cruncher I use because:.
The current separation is jarring one file local but rest remote and breaks an unmatched feature of VS Code. I'm already pleased that the VSCode team is even considering this feature. So good job VS code team! Even this feature gets a green light, it will take some non-trivial dev effort. For now, there are some suboptimal workarounds that gives you the same result rsync, scripts that do something with git, syncing with any cloud blob or object store, etc.
Proposal Extend the Pycharm Jupyter extension to allow users to sync files with a remote running Jupyter notebook server. Additionally things we plan on working on in the next month or so will have a milestone appended. This item is on neither, so it's not on the radar at the moment.
It would likely need more upvotes to push up the queue of stuff we're looking at. Where can we upvote this? At the top. The upvotes under the main description are tracked as 'votes' for an item. This feature is critical to consider using an Azure remote compute instance as a viable option. I understand that it is currently not under any current plans, but would love to see this one move along.
In the meantime, would it be possible to have some sort of recommendation on how to sync local files to a remote instance? That would help alleviate the problem of not having something built-in.
I'm happy to contribute documentation on it if that needs to happen. There's no recommended way to sync files other than for you to put them in the same folder where you started the remote server that will make the relative paths work correctly. Feb 17, Jan 20, Jan 15, Oct 4, Sep 3, Sep 2, Jun 13, Feb 2, Jan 6, Sep 26, Sep 21, Apr 30, Apr 8, Mar 10, Nov 20, Nov 7, Oct 22, Oct 7, Sep 28, Jul 12, Jul 10, May 3, Apr 12, Aug 16, Aug 13, Jun 29, Jun 27, Dec 14, Nov 9, Jul 8, Mar 20, Nov 13, May 7, Mar 6, Jan 27, I can see users getting frustrated with having to specify it for every file they open.
But that affects both Python and IPython consoles, in all configurations external, dedicated and interactive. Skip to content. Star 6. New issue. Jump to bottom. Please add option to select the Python executable to the "Run settings" dialog.
Labels 2—5 stars type:Enhancement. Milestone not sorted. Copy link. Collaborator Author. Yep, can do. Should we always evaluate her script on the same interpreter? She could have a set of libraries that are only installed on that interpreter, so it won't make sense to use any interpreter. What if she wants to use the IPython console? She would need to install it first on her interpreter before trying to open a new one, or else things won't work!
So, assuming this is set on a per-project basis which I agree with : We would start an IPython kernel and python console using the given interpreter when the project is loaded, and all scripts would be run using that interpreter. Else, power users can open as many Spyder instances as they want, and evaluate their files with as many interpreters as they want ;- nod , we just need to maintain the current option to change Python executables.
That way we would avoid the issue with IPython, and all other things will continue to work as they are working right now :- Sorry that I've missed the point before ;-. It already is configurable in the console preferencies. Sign up for free to join this conversation on GitHub.
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