I need some advice. So I am a big fan of VS Code and I always use its embedded notebooks. I built a remote Jupyter Server on Oracle Cloud hoping I could connect from vscode. To create the server I based on this article, but migrating as advised by Jupyter to JupyterServer. I've also used miniconda isntead of venv.
The server seems to work correctly, I can access it from my browser and in my Windows Terminal SSH, open Jupyter Lab, create and run noteboooks in it, etc. The problem is when I try to use it with VS Code, when I try to specify de Jupyter Server for connections, it allows me to do it, it even prompts me that it is an insecure connection (I use self signed ssl certificate), and it does mark Jupyter Server: Remote BUT, when I try to select my interpreter, change my kernel, it only shows my local conda envs. if I run !hostname it shows me my local hostname, not my remotes, it isn't really connecting or using the remote Jupyter server to run the cells.
I've looked around and can`t find a way to make it work, I really want it to work with VS Code, any help?
This has no impact on the actual use of jupyter. Your confusion is actually a misunderstanding caused by the definition of names.
As stated in the official document, when you connect to a remote server, everything runs in the server ather than the local computer.
At present, there is an issue for changing the naming on GitHub, which you can read in detail.
Related
It seems that DataSpell is trying to execute this command: C:\Windows\system32\wsl.exe --distribution Debian --exec /bin/sh -c "export LANGUAGE='' && export LC_ALL=en_US.UTF-8 && export LANG=en_US.UTF-8 && /usr/bin/python3 -m jupyter notebook --no-browser '--notebook-dir=/mnt/c/Users/Andy Zhou/Desktop/Year 2 stuff/GPT-2/code/SERI MATS IOI' --ip=172.22.246.59"
However, when I directly execute the part after --exec on WSL it works.
Adding some additional information regarding your problem, such as the error code that DataSpell likely returned to you, or whether or not htop shows a running Jupyter server, would make providing an accurate answer much easier.
As such, I believe your question could be read two ways, and I've provided an answer for each.
Server starts but will not connect
When DataSpell launches a local WSL-based Jupyter server it makes certain assumptions about how the connection should work, it also uses the LAN address for your WSL instance to attempt to connect. The default Jupyter config assumes a local connection, so DataSpell's connection via an external IP address is rejected immediately.
Steps to resolve this issue:
In WSL run jupyter notebook --generate-config, it will print out the path of your new config file
Vim into the new file and set the following values:
# Please note that the below values can be unsafe, consider changing these values to only allow your IP address to connect; alternatively you could require authentication to access the server.
## The IP address the notebook server will listen on.
c.NotebookApp.ip = '0.0.0.0'
## Set the Access-Control-Allow-Origin header
c.NotebookApp.allow_origin = '*'
## Allow requests where the Host header doesn't point to a local server
c.NotebookApp.allow_remote_access = True
Configure a WSL Python interpreter, detailed here: https://www.jetbrains.com/help/dataspell/using-wsl-as-a-remote-interpreter.html
Change the Jupyter connection for your project to use the interpreter you just set up, detailed here: https://www.jetbrains.com/help/dataspell/using-wsl-as-a-remote-interpreter.html
Run a cell in your notebook, a server should start up automatically and connect just fine.
A good resource on this is the following question: Why I can't access remote Jupyter Notebook server?
Sever does not start when using WSL
Unfortunately this is far more broad, and will almost certainly require more information to solve, but the following issues are highly likely causes:
Your WSL installation didn't include rsync: https://www.jetbrains.com/help/dataspell/using-wsl-as-a-remote-interpreter.html#prereq
WSl does not have Jupyter installed:
Install Jupyter via pip, or conda: {pip|conda} install jupyter
WSL isn't running when DataSpell attempts to run a notebook
Unfortunately without more information, or at least an error code, it isn't possible to give you a definitive answer; but hopefully this helped you in the right direction!
I wrote a code for a Django server, and it works perfectly inside the shell of Pycharm.
Now, I want to run this server on a local computer constantly without being inside Pycharm's shell.
Also, because it's for a client of mine I don't want any open CMD windows or any other weird GUI- I want him to just access the website like any other website.
I've seen all kinds of solutions- running runserver with &, creating a virtual machine and running the server on it and etc.
I am familiar with Vmware and all, so if the proper solution is this It's OK. But I wonder- are there any other ways to run a server on a PC without installing any additional programs?
I want to use a remote Jupyter server via SSH with VSCode but I get an error whenever I try to specify the URI of any server. This also happens with local instances of Jupyter. Any server that is not started by VS Code seems to be unusable.
I am just starting a server like this
$ jupyter notebook --no-browser --port 8080
Then I enter the address in VSCode with the correct port and token
Nothing happens and I get this error, as you can see in the log below.
Command 'Python: Specify local or remote Jupyter server for connections' resulted in an error (Running the contributed command: 'python.datascience.selectjupyteruri' failed.)
Has anyone else been experiencing anything similar? I honestly have no idea how to troubleshoot this. It is worth noting that selecting the Default: VS Code will automatically start a server for you on localhost option raises the same error.
It looks like you're running a fairly old version of the Python extension, as the python.datascience.selectjupyteruri command no longer exists in the Python extension—it is now provided in a standalone Jupyter extension. Please consider upgrading to the latest version of the Python and Jupyter extensions. If that doesn't resolve the problem, please file an issue at https://github.com/microsoft/vscode-jupyter/issues and we'll be happy to help.
I know how to run a Python script made locally on a remote server and have seen a lot of questions in that regard. But I am in a situation where I cannot install python packages on the remote server I am accessing. Specifically, I need to use pypostal, which requires libpostal to be installed and I cannot do so. Moreover, I need pyspark to play with Hive tables.
Therefore, I need the script to run locally, where I can manage my packages and everything executes fine, but certain commands need to access the server in order to grab data. For example, using pyspark to get Hive tables on the server into a local dataframe. Essentially, I need all the Python to be executed using my local distribution with my local packages but perform its actions on the remote server.
I have looked into things like paramiko. But as far as I can workout, is just like an SSH client, which would use the Python distro on the remote server and not locally. Though, perhaps I don't understand how to use it properly.
I am running python 3.6 on Ubuntu 18.04 using WSL. The packages I am using are pandas, numpy, pyspark, and postal (subsequently libpostal).
TLDR;
Is it possible to run a script locally, have parts of it execute remotely but using my local Python? Or if there are other possible solutions, I would be grateful.
I am leading a team of analysts and want to introduce them to Jupyter Notebook as a window into Python programming.
We have Anaconda downloaded and installed on our Linux server. I've asked our IT to help set it up to run on Google Chrome and they have been able to only provide the following steps:
source /R_Data/anaconda3/etc/profile.d/conda.sh
this kicks off Anaconda on the server, must run in PUTTY. We stored the installation in the same location as RStudio hence the R_Data in the filepath.
/R_Data/anaconda3/bin/jupyter-notebook --ip 0.0.0.0 --port 8889
This sets up the port 8889 with a token generated each time from scratch. We then need to grab the token id and paste into Chrome with the full URL per step 3
http://localhost:8889/?token=ea97e502a7f45d....
When I paste this in Chrome it loads Jupyter.
While this gets the job done it seems less than ideal for an entire team of analysts to have to do this each time. We also have RStudio installed on the same server but that simply opens from Chrome using a URL since I assume it is always running in the background. Jupyter and Anaconda seem to only run once they are kicked off first in PUTTY and I would like a way to bypass those steps.
I am familiar with the Jupyter config file however my limited understanding as a non-developer tells me it applies only to each user and cannot be applied to all users simultaneously (i.e. as a root user on the server or something to that effect).
I am hoping someone here might point me in the right direction. I should also point out that as a Redhat user I can't follow instructions based in Ubuntu since that syntax seems different.
Many thanks for the help.
Yoni
A convenient way is to run jupyter notebook --no-browser --port=12345 on your server while connecting through the ssh tunel as ssh -N -f -L 12345:localhost:12345 myserveralias. Now jupyter is on your 12345 localhost. Things like AutoSSH or Keep Alive will help with an erratic network, however, take security into account.