I just downloaded vscode using homebrew and install python#3.11 using homebrew as well. I used pip3 install jupyter as I saw other recommend to fix this issue and still no luck. I have downloaded all the extensions on vscode and I have set the kernal to homebrew version of python and I still recieve this issue. Note that I have used notebooks in the past and have never gotten this issue so I am not really sure what it is this time. I have not installed anaconda.
I have tried uninstalling and installing the extensions but no luck. I have tried to pip3 uninstall jupyter, pip3 uninstall notebook and reinstall them and still no luck. I have tried to change the kernal to the default python3 on the mac and still nothing. My mac is m1 running on Ventura 13.2. I am able to run python code on regular python files just not using jupyter notebook. I followed the instructions how to set it up on vscode website but I got this error. Any help would be appreciated thank you.
I have same issue using VSCode on Mac OS.
VSCode's 'Jupyter' plugin is broken, causing VSCode unable to bind with python interpreter. Downgrading from v2023.1.2000312134 to v2022.11.1003412109 fixed my issue.
I had the same issue, running on m1 mac (Ventura 13.2). If you aren't already, make sure you are utilising a python virtual environment:
# Create a python virtual environment
$ python -m venv venv
# Activate your python virtual environment
$ source venv/bin/activate
Form your VSCode Command Palette (Shift+Command+P), search and then choose
Jupyter: Select Interpreter to Start Jupyter Server
You should then select the python version that is associated to your virtual environment (venv).
After updating VSCode, I have been unable to run Jupyter notebooks anymore. I am using VSCode on a MacBook Pro Max M1 and am encountering the following error:
Failed to start the Kernel.
Jupyter server crashed. Unable to connect.
Error code from Jupyter: 1
usage: jupyter.py [-h] [--version] [--config-dir] [--data-dir] [--runtime-dir]
[--paths] [--json] [--debug]
[subcommand]
Jupyter: Interactive Computing
positional arguments:
subcommand the subcommand to launch
options:
-h, --help show this help message and exit
--version show the versions of core jupyter packages and exit
--config-dir show Jupyter config dir
--data-dir show Jupyter data dir
--runtime-dir show Jupyter runtime dir
--paths show all Jupyter paths. Add --json for machine-readable
format.
--json output paths as machine-readable json
--debug output debug information about paths
Available subcommands: kernel kernelspec migrate run troubleshoot
Jupyter command jupyter-notebook not found.
View Jupyter log for further details.
Unfortunately, none of the steps I tried have worked.
I am using January 2023 (version 1.75) release and extesion versions are as follows:
Python v2023.2.0
Jupyter v2023.1.2010391206
Has anyone else faced this issue? I would greatly appreciate any suggestions or solutions.
Thank you!
I have tried a number of steps to resolve the issue, including:
Making sure that jupyter-notebook is running in the terminal
Installing Jupyter in new conda and Python virtual environments
Removing VSCode and its related directories completely and downloading it again
Trying the "Switch to Pre-Release Version" for both Jupyter and Python extensions in VSCode
Tried updating jupyter and notebook liberaries
Tried running VSCode with code --no-sandbox
solved downgrading to previous version (November 2022) then updating to latest version again. Running same Python and Jupyter version. Good luck
I ran into this too. I was able to work around it by switching the Jupyter extension to the pre-release version (which was a suggestion in a different question that I can't find anymore).
I am trying to use the hidecode tag as shown here, but for some reason, it's not working on my local Jupyter Notebook server. The code remains visible, and no button on the right of the cell is displayed. I even downloaded the same notebook used in the page above, no dice.
I am running Ubuntu 18.04.2 LTS, Jupyter Notebook Server 5.2.2, Python 3.6.7, and IPython 5.5.0. The command I ran to start the server is sudo jupyter notebook --allow-root.
If you need any more info, please let me know. I appreciate any help I can get in figuring this out.
If you want to hide the code, the output or the prompt of your cells you can install the hide_code extension:
https://pypi.org/project/hide_code/0.2.0/
Stop jupyter
Run these commands
pip install hide_code
jupyter nbextension install --py hide_code
jupyter nbextension enable --py hide_code
jupyter serverextension enable --py hide_code
NOTE: I run the first two commands as root and the last two with the same user used to launch jupyter.
Restart jupyter
I found this extension very useful because I needed to print the notebook to a pdf file and all the tools like nbpublish, nbconvert was failing. In this way I can print the notebook directly from the "print" feature of the browser.
I have jupyter/anaconda/python3.5.
How can I know which conda environment is my jupyter notebook running on?
How can I launch jupyter from a new conda environment?
As mentioned in the comments, conda support for jupyter notebooks is needed to switch kernels. Seems like this support is now available through conda itself (rather than relying on pip).
http://docs.continuum.io/anaconda/user-guide/tasks/use-jupyter-notebook-extensions/
conda install nb_conda
which brings three other handy extensions in addition to Notebook Conda Kernels.
Question 1: Find the current notebook's conda environment
Open the notebook in Jupyter Notebooks and look in the upper right corner of the screen.
It should say, for example, "Python [env_name]" if the language is Python and it's using an environment called env_name.
Question 2: Start Jupyter Notebook from within a different conda environment
Activate a conda environment in your terminal using source activate <environment name> before you run jupyter notebook. This sets the default environment for Jupyter Notebooks. Otherwise, the [Root] environment is the default.
You can also create new environments from within Jupyter Notebook (home screen, Conda tab, and then click the plus sign).
And you can create a notebook in any environment you want. Select the "Files" tab on the home screen and click the "New" dropdown menu, and in that menu select a Python environment from the list.
which environment is jupyter executing:
import sys
print(sys.executable)
create kernel for jupyter notebook
source activate myenv
python -m ipykernel install --user --name myenv --display-name "Python (myenv)"
source activate other-env
python -m ipykernel install --user --name other-env --display-name "Python (other-env)"
http://ipython.readthedocs.io/en/stable/install/kernel_install.html#kernel-install
If the above ans doesn't work then try running conda install ipykernel in new env and then run jupyter notebook from any env, you will be able to see or switch between those kernels.
to show which conda env a notebook is using just type in a cell:
!conda info
if you have grep, a more direct way:
!conda info | grep 'active env'
You can also switch environments in Anaconda Navigator, install Jupiter and run it.
Because none of the answers above worked for me, I write here the solution that finally solved my problem on Ubuntu. My problem was:
I did the following steps:
Activate my environment: conda activate MyEnv
Start jupyter notebook:jupyter notebook
Although MyEnv was active in the terminal and had an asterix when writing conda env list, but jupyter notebook was started with the base environment.
Installing nb_conda and ipykernel didn't solve the problem for me either. Additionally, the conda tab wasn't appearing in jupyter notebook and also clicking on the kernels or going to the menu Kernel->Change Kernel didn't show the kernel MyEnv.
Solution was: install the jupyter_environment_kernel in MyEnv environment:
pip install environment_kernels
After that when starting jupyter notebook, it is started with the right environment. You can also switch between environments without stopping the kernel, by going to the menu Kernel->Change Kernel and selecting the desired kernel.
Question 1: How can I know which conda environment is my jupyter notebook running on?
Launch your Anaconda Prompt and run the command conda env list to list all the available conda environments.
You can clearly see that I've two different conda environments installed on my PC, with my currently active environment being root(Python 2.7), indicated by the asterisk(*) symbol ahead of the path.
Question 2: How can I launch jupyter from a new conda environment?
Now, to launch the desired conda environment, simply run activate <environment name>. In this case, activate py36
For more info, check out this link and this previous Stack Overflow question..
The following commands will add the env in the jupyter notebook directly.
conda create --name test_env
conda activate test_env
conda install -c anaconda ipykernel
python -m ipykernel install --user --name=test_env
Now It should say, "Python [test_env]" if the language is Python and it's using an environment called test_env.
To check on which environment your notebook is running type the following commands in the notebook shell
import sys
print(sys.executable)
To launch the notebook in a new environment deactivate that environment first. Create a conda environment and then install the ipykernel. Activate that environment. Install jupyter on that environment.
conda create --name {envname}
conda install ipykernel --name {envname}
python -m ipykernel install --prefix=C:/anaconda/envs/{envname} --name {envname}
activate envname
pip install jupyter
In your case path "C:/anaconda/envs/{envname}" could be different, check accordingly.
After following all steps, launch notebook and do step 1
run the following in shell.
sys.executable
This should show: Anaconda/envs/envname
On Ubuntu 20.04, none of the suggestions above worked.
I.e. I activated an existing environment. I discovered (using sys.executable and sys.path) that my jupyter notebook kernel was running the DEFAULT Anaconda python, and NOT the python I had installed in my activated environment. The consequence of this was that my notebook was unable to import packages that I had installed into this particular Anaconda environment.
Following instructions above (and a slew of other URLs), I installed ipykernel, nb_conda, and nb_conda_kernels, and ran: python -m ipykernel --user --name myenv.
Using the Kernels|Change Kernel... menu in my Jupyter notebook, I selected myenv, the one I had specified in my python -m ipykernel command.
However, sys.executable showed that this did not "stick".
I tried shutting down and restarting, but nothing resulted in my getting the environment I had selected.
Finally, I simply edited file kernel.json in folder:
~/.local/share/jupyter/kernels/myenv
Sure enough, despite my having performed all the steps suggested above, the first argument in this JSON file was still showing the default python location:
$Anaconda/bin/python (where $Anaconda is the location where I installed anaconda)
I edited file kernel.json with a text editor so that this was changed to:
$Anaconda/envs/myenv/bin/python
Hopefully, my use of myenv is understood to mean that you should replace this with the name of YOUR environment.
Having edited this file, my Jupyter notebooks started working properly - namely, they used the python specified for my activated environment, and I was able to import packages that were installed in this environment, but not the base Anaconda environment.
Clearly, something is messed up in how the set of packages ipykernel, nb_conda, and nb_conda_kernels are configuring Anaconda environments for jupyter.
I have tried every method mentioned above and nothing worked, except installing jupyter in the new environment.
to activate the new environment
conda activate new_env
replace 'new_env' with your environment name.
next install jupyter
'pip install jupyter'
you can also install jupyter by going to anaconda navigator and selecting the right environment, and installing jupyter notebook from Home tab
Adding to the above answers, you can also use
!which python
Type this in a cell and this will show the path of the environment. I'm not sure of the reason, but in my installation, there is no segregation of environments in the notebook, but on activating the environment and launching jupyter notebook, the path used is the python installed in the environment.
For windows 10,
Go into Anaconda Launcher
In the 'Applications on' dropdown menu, select the required conda environment.
Install Jupyter notebook in the Anaconda Launcher
Launch Jupyter notebook from the Anaconda Launcher
The Conda tab is visible in the Jupyter notebook where you can see your active conda env.
For checking on Which Python your Jupyter Notebook is running try executig this code.
from platform import python_version
print(python_version())
In order to run jupyter notebook from your environment
activate MYenv
and install jupyter notebook using command
pip install jupyter notebook
then just
jupyter notebook
What solved the issue for me was that I had to run the following command:
python -m ipykernel install --user --name myenv --display-name "Python (myenv)"
The issue was that I opened a jupyter notebook made with/for a kernel for another conda python environment. That was visible from the output on the terminal; it is handy op run jupyter notebook from a terminal on the conda environment so that you can easily see what error messages are shown. Then it became clear that the notebook tried to run python from another environment.
Inspecting the folder/files:
C:\Users\<username>\AppData\Roaming\jupyter\kernels\<env name>\kernel.json
"argv": [
"D:\\Users\\<username..path>\\envs\\<env name>\\python.exe",
"-m",
"ipykernel_launcher",
"-f",
"{connection_file}"
],
"display_name": "Python (env name)",
"language": "python",
"metadata": {
"debugger": true
}
}
So you can check and correct if necessary.
Second, when using anaconda/conda, make sure you have a healthy channel policy and execute the following commands when creating a new environment:
conda config --add channels conda-forge
conda config --set channel_priority strict
It solved this problem for me, I hope it helps you too.