I have IPython notebooks running on a server, and I'm editing/prototyping them locally. I use rsync to push my local notebooks when I'm ready to show them to others.
Problem is, with all these notebooks open, it's easy to accidentally edit things on the server notebooks instead of the local ones. Is there some reasonable mechanism to prevent accidental editing of notebooks? I still want to be able to run the server-notebooks, and they still should be able to write output - I just want to somehow lock them so they can't be edited.
You can also just change the notebook permissions to be read-only by opening a new Terminal directly in your Jupyter server.
Related
I am trying to connect to remote jupyter server which is running in remote server inside a docker. from vs code (local machine) with the help of jupyter extension, and running a newly created notebook.
The problem seems to be the kernel creation via this method for this newly created notebook.
My Jupyter Server is running in remote server, inside a docker environment, with port forwarding enable.
I can access it via my browser by http://{remote_machine_ip}:{port}/, and I am able to create new jupyter notebook.
However when I use the vs code to open local notebook file, and connect to the remote jupyter server.
When I try to run the cells, it shows the following error:
Failed to start the Kernel.
'_xsrf' argument missing from POST.
View Jupyter log for further details.
Possible solution
However, if I try to open a new kernel in browser, and connect it to same kernel in vs code, the problem goes away.
This issue seems to be arising when vs code sends the request to create jupyter kernel to the jupyter server.
As, when I tested with already running jupyter kernel in vs code, it works fine.
The issue here is, security implementation of jupyter server, which don't allow cross site request to create a kernel, as it security vulnerability.
For more details about _xsrf token, you can read here, although it doesn't talk about specific to jupyter server, its very easy to deduce the logic.
In one post of jetbrains, I found the solution, to make jupyter ignore _xsrf token, by adding new flag while starting the jupyter server,
--NotebookApp.disable_check_xsrf=True
Or add it to your notebook config.
Also, to make sure your request are not been blocked, as suggested by vscode blog. Add the following flag too,
--NotebookApp.allow_origin='*'
I have got downloaded a file that got downloaded in a format .ipynb extension but its not in a readable format. Can anyone help me to figure out how to make it in a readable format? Attaching a screenshot of the file when I tried opening it in notepad.
how to open it in readable format
One of the easiest ways to just view a notebook file that is also 100% secure in case what you are being sent is sensitive: nbpreview.
When you go there it asks you to choose a local file. The file isn't uploaded anywhere. It remains in your browser's local cache so it is useful for sensitive stuff that cannot be public.
Similarly, you can upload it to the notebook{sharing}space which is billed as "the fastest way to share your notebooks". It would provide you with a link to view the notebook you have and can be private if you limit sharing the link.
If the notebook can be posted to Github (repository or gist) or online, you can point nbviewer at it and have it rendered nicely. In fact, although it is technically 'static', nbviewer can render some interactive Plotly plots and widget controls that enable playing back animations comprised of frames. This rendering form is also very nice for sharing with non-programmers as the GitHub cruft is not surrounding the content.
You can use Jupyter running in your browser and backed by a free Jupyter community-run service to view the notebook file as an active notebook, on what is equivalent to a temporary remote machine.
Go to Try Jupyter and select either 'JupyterLab' or 'Jupyter Notebook' from the offerings presented. I'd suggest JupyterLab as the steps outline below are made easier as you have the file navigation pane on the left.
After your session spins up in your browser, if you chose JupyterLab, drag your file from your local machine into the file navigation pane on the left side. It will get a gray dashed line around it when you have dragged it to the right place. Drop it in and let it upload. Now double click on it to open it.
If you don't want to drag-and-drop or you chose Jupyter notebooks (classic notebook interface) make a text file and paste in the content you showed. (It's json format as that is the underlying .ipynb format presently.) Save that file with an .ipynb extension. You should then be able to open it the Jupyter Dashboard. (Note the following in the rest of this section was written before the 'Try Jupyter' offerings were switched to using the exerpimental JupyterLite and so your mileage may vary. If you drag-and-drop into JupyterLite, it actually is in your machine; however, it is in a virtual system in your browser that your local file system cannot access directly. To get what this section was specifically written for now, go here and click on the launch binder badge to trigger a session on a true remote machine served by MyBinder.) You used to click on the logo in the upper left to get to the dashboard but it will now take you to JupyterLab and you can double click to open your notebook file. If you really need the classic dashboard, change the end of the URL to change /lab to /tree.
Note because the environment backing your notebook hasn't been set up to handle everything, you'll be out of luck for now trying to run it. You'd have to add your pokemon.csv and install anything else besides pandas. There are ways to use the MyBinder system to handle that as well; however, probably best learned about later this stage.
The MyBinder session is temporary and unique to you. It will close after 10 minutes of inactivity and no longer be accessible. You can always open another session later and redo the steps. Or learn about other options eventually.
Related:
Nbpreview and a lot of the related tools mentioned here are also covered in Sharing R code in Jupyter notebooks.
(These following suggestions mostly assume the notebook is already online, usually at Github. You can still use a local notebook by uploading it to the session as I suggest above. They do though provide additional ways to learn about using MyBinder to serve active notebooks in your browser.)
How to save code file on GitHub and run on Jupyter notebook?
Run a Jupyter notebook directly online (without downloading it locally)
You need Jupyter Notebook in your machine. That is one option. Otherwise, you can upload the file into GitHub and open the .ipynb file from there.
I have a remote server with a long-running jupyter notebook process (keras training).
When I reconnect to the notebook (either by reloading the chrome tab or by clicking on the notebook in the list of running notebooks), I get a tab marked as "running" (hourglass icon instead of the book icon), and I can confirm that the process is running by ssh to the server.
However, the progress indicator and stdout of the process running is lost. The bar
71255/225127 [========>.....................] - ETA: 3:32:43 - loss: 2.1890
is never updated. Other (non-keras) processes lose their stdout (unless I also write to a file).
Is this a known problem?
Is there a way to recover the output stream after reconnecting?
This is a known problem, and as far as I know IPython has already published a collaboration jupyter notebook option, that they said "could solve the problem in the collaboration mode"
Sadly, if it's lost, there's no way to find it back (unless you outputted to a file or to a variable, or you know how to do some intricate tricks that could recover the data)
One way to solve this, to prevent the issue in advance, is to use magic code
%%capture <VARIABLE NAME> in the cell you want to save the stdout when closed the notebook in your browser (don't terminate your notebook). In this way, output will be save in <VARIABLE NAME> and later on you can access it using print(<VARIABLE NAME>.stdout), after the process is finished.
I am trying to connect from google colab to local host - it does not work,
google troubleshooting advise suggests that I should allow local Jupyter notebook to accept colab requests - how to do it ?
Screenshot from local host which confirms that requests from colab are forbidden.
There should be some config modification to allow such requests, is not it ?
Advise from colab:
How I fixed my connection issues:
If after the above commands don't work, what finally did it for me was creating a firewall rule for port 8888.
Another big one that is in the instructions in your command line but not stated on the provided Google tutorial that some people will miss is that you need to open the URL in your browser that's given to you after launching Jupyter in order for it to create the access cookie and make it valid (sort of speak).
From the screenshot you provided, make sure you have "http://localhost:8888/?token=2534..." opened in your browser that is logged in with the same account accessing colab before it will allow access to colab (a separate window or tab will usually pops up on it's own when you run the command though).
Alternatively, you can also add the --no-browser tag to prevent the need to open it in your browser
Other solutions that involve installation issues to mitigate network issues:
There were a number of other troubleshooting steps that were particular to me but dont know if will apply to you but did you have any issues when installing Jupyter?
For me, even though jupyter would still launch, there were errors when installing on Windows, and to fix those I had to replace pip with pipwin and go through the steps that way.
For example
pipwin install jupyterlabs
pipwin install jupyter_http_over_ws
And in case it helps anyone else coming across this in the future, if you're using the DOS cmd line and have issues launching jupyter, replace the "" with a "^" to indicate continuation
i.e.:
jupyter notebook --NotebookApp.allow_origin="https://colab.research.google.com" --port=8888 --NotebookApp.port_retries=0
I'm new to Ipython Notebook. I can cut and paste from other apps into my notebooks, but how do I copy/paste code out of notebook into a different app?
I'm accessing a Linux VNC session via Chicken. I can cut/paste with wild abandon between OSX/Linux using both command X/C/V and/or middle mouse button. I can also copy code into IPython notebook. I'm stopped dead in my tracks trying to get code out of IpyNotebook.
Using Notebook's 'Edit/Copy Cell' doesn't work, neither does 'Ctrl-m c'.
I'm running IPython 0.13.1
You have to select and copy code using normal Ctrl-C Ctrl-V. 'Edit/Copy Cell' is a specific action in javascript that does a little more and that browser security policy prevent us to bind with clipboard.