I tried installing jupyter notebook without using anaconda and ran into some issues, specifically the red 'Kernel Error' that kept showing up.
However through this ques I was somewhat able to identify the issue where the default pythonpath in the kernel.json file in C:\Users\Ashish\AppData\Roaming\jupyter\kernels\python3 was for anaconda, so I added my python path using where python.
On running jupyter notebook on cmd and opening a .ipynb file causes a popup to show : Could not find a kernel matching Python 3. Please select a kernel, which shows an empty drop down list.
My Updated kernel.json file:
{
"argv": [
"C:\Users\Ashish\AppData\Local\Programs\Python\Python38\python.exe",
"-m",
"ipykernel_launcher",
"-f",
"{connection_file}"
],
"display_name": "Python 3",
"language": "python"
}
Nvm, on running jupyter kernelspec list showed an error:
json.decoder.JSONDecodeError: Invalid \escape: line 3 column 6 (char 18)
Fixed it by using C:\\Users\\Ashish\\AppData\\Local\\Programs\\Python\\Python38\\python.exe in the kernel.json file
Related
With my conda environment activated I set an environment variable with the command
conda env config vars set ROOT_DIRECTORY=$PWD
Now, if a run echo $ROOT_DIRECTORY the output shows /home/augusto/myproject
How can I get that variable inside Jupyter Notebook? I tried with the command below, but the output shows None.
import os
print(os.getenv('ROOT_DIRECTORY'))
By the way, I have shure that Jupyter Notebook are using the correct Kernel. Running the above code inside a .py file works correctly, i.e. the output shows /home/augusto/myproject.
Find env dir
jupyter kernelspec list
cd path_to_kernel_dir
sudo nano kernel.json
Add environment section to json
json should look something like this
{
"argv": [
"/home/jupyter-admin/.conda/envs/tf/bin/python3",
"-m",
"ipykernel_launcher",
"-f",
"{connection_file}"
],
"env": {"LD_LIBRARY_PATH":"/home/jupyter-admin/.conda/envs/tf/lib/"},
"display_name": "tf_gpu",
"language": "python",
"metadata": {
"debugger": true
}
}
I have added the conda environment to my Jupyter notebook, but the Python version is still 3.8 (Fig 1). What I would like to do is to create an environment which contains Python version 3.7 in a Jupyter notebook without starting from a command prompt and running two separate Jupyter notebooks (Fig 2). Is it possible to have simply one jupyter notebook with two separate environments and two different Python versions?
Fig1
Fig2
Please read this page of the docs for ipykernel.
In your environment you want to install only ipykernel (not full Jupyter), and use one of the ipykernel install --name command to register the kernels with Jupyter.
If that does not work, use jupyter kernelspec list to see which kernels jupyter see and where. A kernelspec is at minimum a kernel.json file in the right place to tell jupyter how to find kernels.
For example I have the following
$ cat ~/miniconda3/share/jupyter/kernels/python3/kernel.json
{
"argv": [
"~/miniconda3/bin/python",
"-m",
"ipykernel_launcher",
"-f",
"{connection_file}"
],
"display_name": "Python 3 (ipykernel)",
"language": "python",
"metadata": {
"debugger": true
}
}
I can use the documentation above, or create the following by hand:
$ cat ~/miniconda3/share/jupyter/kernels/python3.6/kernel.json
{
"argv": [
"~/miniconda3/envs/mypython36env/bin/python",
"-m",
"ipykernel_launcher",
"-f",
"{connection_file}"
],
"display_name": "Python 3.6 !!",
"language": "python",
"metadata": {
"debugger": true
}
}
and assuming I have the corresponding Python 3.6 env, then I'll get two kernel one of them being Python 3.6
I installed a new python 64 bit in my program files folder. I changed my jupyter kernel file in AppData/Roaming/Jupyter/kernels/kernel.json to take this new python as the python.
the kernel. JSON is
{
"argv": [
"C:/Program Files/Python",
"-m",
"ipykernel_launcher",
"-f",
"{connection_file}"
],
"display_name": "python 3.7 64 bit",
"language": "python"
}
The error when I open a new notebook is PermissionError: [WinError 5] Access is denied
What should I change to solve it?
your operating system is not allowing to edit your file. Try open your notebook in administrator mode.
Right click on file
Open as administrator
make changes.
try this I hope your problem will be solved.
In VScode I can write a python file with markdown and python cells and then convert it to a notebook via the command palette. Everything works well, but I would like to automate this with a task.
I know I could just define a shortcut for the conversion but then I would still need to manually save the notebook with the file explorer. Can I automate this with a task? If so how do I access the function for the conversion? Is this some internal function of VScode or can I access this function via the command line?
I tried a few things with the jupyter command in the command line but didn't have any luck. It seems like there is no command to convert a python file to a Jupyter notebook. Also I could not find a comprehensive documentation for the jupyter command.
Another question in regards to Jupyter notebooks in VScode: Is there a way how I can hide a cell from showing up? I know it would be possible if I edit the metadata of the notebook, but I hope there is a better way.
In case anyone else is still wondering about this, I'm now using jupytext for converting python files to jupyter notebooks.
I wrote two very simple bash scripts to automate the conversion and viewing of notebooks.
conversion:
#!/usr/bin/env bash
# retrieve file names and folder from arguments
full_fname=$1
fbase_name_no_ext=$2
dir_name=$3
workspace_folder=$4
full_path_no_ext="$dir_name/$fbase_name_no_ext"
notebook_save_path=$(cd ${dir_name}/.. && pwd)
# activate venv (venv should be in vscode workspace root)
source "${workspace_folder}/my_env/bin/activate"
echo "saving to: $notebook_save_path"
# convert to jupyter notebook
jupytext --to notebook ${full_fname}
# run all cells and save output to notebook file
jupyter nbconvert --to notebook --execute "${full_path_no_ext}.ipynb" --output "${notebook_save_path}/${fbase_name_no_ext}"
# cleanup intermediate notebook (contains only cells no output)
rm "${full_path_no_ext}.ipynb
viewing a notebook:
#!/usr/bin/env bash
# retrieve file names and folder from arguments
fbase_name_no_ext=$1
dir_name=$2
workspace_folder=$3
source "${workspace_folder}/my_env/bin/activate"
# notebooks are stored in the parent directory of the source file
notebook_folder=$(cd ${dir_name}/.. && pwd)
# view notebook in a browser window
jupyter notebook "${notebook_folder}/${fbase_name_no_ext}.ipynb"
Here is my vscode tasks file:
{
// See https://go.microsoft.com/fwlink/?LinkId=733558
// for the documentation about the tasks.json format
"version": "2.0.0",
"tasks": [
{
"label": "convert to NB",
"type": "shell",
"command": "${workspaceFolder}/convert",
"args": [
"${file}",
"${fileBasenameNoExtension}",
"${fileDirname}",
"${workspaceFolder}"
],
"group": {
"kind": "build",
"isDefault": true
},
"presentation": {
"echo": true,
"reveal": "always",
"focus": true,
"panel": "shared",
"showReuseMessage": true,
"clear": true
}
},
{
"label": "view NB",
"type": "shell",
"command": "${workspaceFolder}/viewNB",
"args": [
"${fileBasenameNoExtension}",
"${fileDirname}",
"${workspaceFolder}"
]
}
]
Since I'm no bash expert, there might be multiple things that could be done in a better way. Critique is always welcome!
Hope this is helpful to someone.
In earlier versions of IPython it was possible to load a specific profile by
ipython notebook --profile=my_profile
so that I can include things like autoreload in my_profile.
Since using IPython 4.0.1 (Jupyter actually) I'm getting the
[W 09:21:32.868 NotebookApp] Unrecognized alias: '--profile=my_profile', it will probably have no effect.
warning, and the profile is not loaded. Have you come across a workaround?
In Jupyter create a kernel for each profile.
Find the kernels directory under the jupyter configuration directory {jupyter configuration}/kernels (on my Mac this is $HOME/Library/Jupyter/kernels):
$ mkdir profile-x-kernel
$ cat << EOF > profile-x-kernel/kernel.json
{
"display_name": "Profile X (Python 3)",
"language": "python3",
"env": { },
"argv": [ "python3", "-m", "ipykernel", "--profile", "profile_x", "-f", "{connection_file}" ]
}
EOF
Then you can select the kernel from the kernel menu in Jupyter, without having to restart the whole notebook server.