I am using remote server with ssh and running jupyterlab there.
When I run some codeblock (It needs more than 5 min to run I guess), it automatically restart before I see the result.
Memory is enough. and log shows something strange
Could not determine jupyterlab build status without nodejs
Notebook .ipynb is not trusted
KernelRestarter: restarting kernel (1/5), keep random ports
Related
Running jupyter notebook and jupyter server give me very similar results and the descriptions are also quite similar.
❯ jupyter notebook -h
The Jupyter HTML Notebook.
This launches a Tornado based HTML Notebook Server that serves up an
HTML5/Javascript Notebook client.
❯ jupyter server -h
The Jupyter Server.
This launches a Tornado-based Jupyter Server.
There are differences like server doesn't load nbextensions but I don't understand why there are two commands that have so much overlap.
For reference, this are the versions of various modules.
❯ jupyter --version
jupyter core : 4.7.1
jupyter-notebook : 6.3.0
qtconsole : 5.0.3
ipython : 7.22.0
ipykernel : 5.3.4
jupyter client : 6.1.12
jupyter lab : 3.0.11
nbconvert : 6.0.7
ipywidgets : 7.6.3
nbformat : 5.1.3
traitlets : 5.0.5
Jupyter Notebook (notebook module) contains both:
the server for notebooks (the backend of the web application that hosts the notebook contents, proxies interaction with kernels, and interacts with the operating system by e.g. opening an internet browser on start; this part is generally written in Python), and
the client (the frontend of the web application, e.g. HTML code, javascript, and some extra REST API points on the server).
However, because there are now multiple clients (frontends) providing different web applications for notebooks:
Jupyter Notebook
JupyterLab
RetroLab
nteract
multiple proprietary clients developed outside of project Jupyter
It made sense to split the server component used by all of these so that e.g. JupyterLab does not have to depend on notebook. This also means that if a fix to the server component is needed, it can be released quickly independent of Jupyter Notebook release cycle (and users of all frontents can benefit immediately).
As a consequence, and to make the break up clean, the old Jupyter Notebook was split into:
jupyter-server - the server which was adapted by JuptyterLab, RetroLab, nteract
nbclassic - the Jupyter Notebook as a jupyter-server extension
This implies changes for users and developers, some already described in "migrate from notebook" docs:
the options specific to server rather than notebook were renamed from c.NotebookApp to c.ServerApp (the options specific to notebook remain c.NotebookApp)
the server-specific configuration is now stored in jupyter_server_config.py rather than jupyter_notebook_config.py (same for .json version)
users should now use jupyter server extension rather than jupyter serverextension (note the extra space!) to list, enable or disable extensions
the server extensions need to place their files in a new location: etc/jupyter/jupyter_server_config.d rather than etc/jupyter/jupyter_notebook_config.d (in practice most extensions that were updated to support jupyter server are now placing files in both locations for backward compatibility with notebook, but this will change in the future)
It is important to note that depending on how you start your jupyter notebook, you will see different servers being used:
jupyter nbclassic (assuming nbclassic is installed) will use the new jupyter-server
jupyter notebook will use the old notebook server
jupyter lab will use new jupyter-server starting with JupyterLab 3.0 unless running on JupyterHub/Binder where it might still be using old notebook server, depending on configuration
This also implies that you may see different extensions when running jupyter notebook vs jupyter nbclassic (depending on whether their developers updated the locations, and whether they decided they want to support the legacy notebook server).
The creation of nbclassic replacement rather than removal of the server code from existing notebook package was meant to ensure backward compatibility, and this is why you still have two copies of the Tornado server (one provided by jupyter notebook and one by jupyter server). To make the situation simpler you could remove notebook and install nblcassic, but given that the transition is in progress you may need to adjust a few things manually. However, this is only a temporary situation, as it is planned that Notebook will be migrated to use jupyter server starting with v7.0.
This might look inconvenient for now, but this step ensures greater maintainability of the core Jupyter infrastructure in the future and will benefit users and system admins greatly later on.
I shut down all kernels and close jupyterlab in the browser, but when I open it again it starts a session, and a kernel, for all opened notebooks
I'd followed the code and found that in jupyterlab notebook code the start session function calls (POST /api/sessions) on notebook load if there is not any running kernel for the current notebook. and the API creates a session and also starts a kernel.
I can't find any config for stopping this action in jupyter configs or jupyterlab settings (settings -> advanced settings editor)
You can prevent automatically starting kernels when you open a notebook by running Jupyterlab with the jupyter lab --LabServerApp.notebook_starts_kernel=False flag.
To make the configuration permanent, you can add
c.LabServerApp.notebook_starts_kernel = False to $(jupyter --config-dir)/jupyter_lab_config.py. If this file doesn't exist yet, generate it by running jupyter lab --generate-config.
See this issue comment for more details:
https://github.com/jupyterlab/jupyterlab/issues/12019#issuecomment-1145841583
I am using the Google AI platform which provides jupyterlab notebooks. I have 2 notebook instances set up to run R of which only one notebook now opens. The first notebook will not open regardless of the number of stops and resets I performed. The notebook overview can be seen in this image and circled is a difference (it is 'started'):
The only reason I can imagine for this difficulty is that I changed the machine type for the notebook where I decreased the number of CPUs from 4 to 2 and the RAM from 15 to 7.5. Now I cannot open it and it has a blank for where the environment should say R3.6. I would not mind deleting it and starting over if there was not nonbacked-up work on it.
What can be done to bring the notebook back to operation and if it cannot be done, how can I download it or extract some key files?
As it was commented before, there are two ways to inspect the Notebook Instance using Cloud Console:
GCP Console > AI Platform > Notebooks
GCP Console > Compute Engine > VM Instances. The name of the GCE VM Instance will be the same as the Notebook Instance name.
It looks like you were able to connect to your Notebook instance via SSH button. Additionally you can use gcloud command to connect to instances via SSH that you have permission to access by following:
gcloud compute ssh --project <PROJECT> --zone <ZONE> <INSTANCE>
After you connect, use the terminal to run commands to verify the status of your jupyter service and the service logs by running:
sudo service jupyter status
sudo journalctl -u jupyter.service --no-pager
You can restart the jupyter service to try to recover it:
sudo service jupyter restart
If you want to use other methods or third parties to create a SSH connection to your Notebook instance, you can follow this.
If you were not able to recover your jupyter service, you can copy your files from your VM by click the gear icon in the upper right of the SSH from the Browser window and select Download file.
As it was mentioned before, the gsutil cp command allows you to copy data between your local file system and the cloud, within the cloud, and between cloud storage providers. For example, to upload all files from the local directory to a bucket, you can run:
gsutil cp -r dir gs://my-bucket
Use the -r option to copy an entire directory tree
I would like to setup a system such that it not only runs jupyter notebook on start, but it also starts executing a specific notebook on that jupyter server (running all cells in sequence).
Is this possible? I specifically want to be able to access the notebook web interface and inspect/stop/etc the running notebook at any point.
I know nbconvert can execute a notebook, but it seems to run independently of any existing jupyter servers?
Maybe there is some API I can access so that I can write a shell script to run jupyter notebook and then use the API to open and run a notebook?
Installed WSL on Windows 10.
Installed Anaconda according to the Anaconda documentation with the following commands:
bash Anaconda3-2020.02-Linux-x86_64.sh
source ~/.bashrc
You can see the '(base)' in the beginning of each command input line, indicating the conda is activated.
Then I run jupyter notebook by typing:
jupyter notebook
Then I see the following changes as shown in the screen record.
Briefly, the WSL terminal window showed some information very quickly, but is changed to the windows powershell window before you could even tell the information that showed up. I know those information should contain a file and url for opening the jupyter notebook in the web browser. But they flashed out so quickly. Does anyone know why this happens?
Here is a dynamic graph of the Screen record of this issue:
Solved:
1. Wait for a bit more time on the windows cmd and the jupyter notebook running information will show up, where includes the url to open jupyter notebook in the web browser.
OR
Open up another wsl terminal, activate the same environment and type jupyter notebook list, which will show the current running jupyter notebook server. The url is also can be found there.