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I write Python code in Visual Studio Code and run the program from a terminal in which I have activated a virtual environment, and it works fine.
However, if I create notebook cells using #%% and run those interactively, the virtual environment is not used. How can I fix this?
It's because there is an extra step needed - you need to explicitly install a Jupyter kernel that points to your new Python virtual environment. You can't simply activate Jupyter-lab or Notebook from the virtual environment. This has tripped me up before, too.
Follow the advice here: Using Jupyter notebooks with a virtual environment
And, in fact, there can be an issue where your kernel still doesn't point to the correct Python binary, in which case you need to change one suggestion in the above advice process:
From: ipython kernel install --user --name=projectname
To: python3 -m ipykernel install --user --name=projectname
(This correction comes from a comment to Jupyter Notebook is loading incorrect Python kernel #2563.)
*and don't forget to restart VSCode
All you need is to edit Vscode settings following these steps:
Open Open User settings using shortcut Ctrl + Shift + P
Type in search space "env"
Under Extentions -> Python , you will find Python: Venv Path
Type the absolute path to your enviroment "path/to/myenv/bin" in linux or "path/to/myenv/Script/"
Restart vsCode
Select the desired kernel using Notebook : Select Notebook kernel using shortcut Ctrl + Shift + P
Read more here: https://techinscribed.com/python-virtual-environment-in-vscode/
For VSCode, your Jupyter kernel is not necessarily using the same python interpreter you're using at the command line.
Use Ctrl + Shift + P to open the Command Palette, and select "Notebook: Select Notebook Kernel"
Then choose the interpreter you're using at the terminal
I find it easy to use pipenv install ipykernel to set up the virtual environment with the Jupyter kernel in one go (comment on rocksteady's answer).
Encounter the same behaviour. Python code works perfectly fine, but Jupyter refuses to pick up the local .venv.
The local venv is in Python: Select Interpreter but not in Jupyter's Select kernel list.
The problem is there're too many venv in the system!
If you encounter the same behaviour,
Press F1, then Jupyter: Filter kernels, uncheck everything, except the local env.
Then F1 -> Developer: Reload Window.
Jupyter will automatically use the default local venv.
for me solved by adding the path of my venv to the settings.json,
now the kernel is detected automatically
"python.pythonPath": "P:\Miniconda3_64bit\venv\Scripts\python.exe",
Make sure you have installed jupyter, notebook, ipykernel libraries in your virtual environment.
Then hit Ctrl + Shift +P , press >Python: Select Interpreter and choose your path of the venv.
After that, hit Ctrl + Shift +P again, run >Notebook: Select Notebook kernel.
If you have already opened the jupyter notebook window , reload it again and you can find your path of the venv in Jupyter's Select kernel list.
On macOS I have .venv/ in the same folder as my .ipynb
. .venv/bin/activate
pip install ipykernel
Then I restart VSCode in the project folder, open the notebook, and in the Select Kernel dropdown I see .venv/bin/python
Selecting that, now it works.
Here is how to do for venv with Jupyter Notebook on VSCode in Windows:
Create a venv and get the path to this venv in Windows. As an example, with Anaconda, I get: C:\Users\rascoussier\Anaconda3\envs\research310.
Now, we need to tell VSCode to use it. In VSCode, go to the Python Extension > Extension Settings. Search for Python: Venv Path. Add the path where the venvs are located. Here we added C:\Users\rascoussier\Anaconda3\envs\research310.
Restart VSCode.
Now launch command pallet(ctrl+shift+P) and run >Notebook: Select Notebook kernel. Normally the venv python should be available and it should then works.
Try a few things:
Make sure you can run the code from a Visual Studio Code terminal using the "ipython" prompt with the same Conda environment.
If it works then sometimes it is a caching issue, so close your file and open a new one.
Now let me show you a scenario. You select the interpreter in Visual Studio Code, and then you write codes below '# %%'. The moment you hit Ctrl + Enter, you are guessing that the IPython kernel that Visual Studio Code is using is not of the interpreters that you have selected. In this case you could write the following code to conform which interpreter is used for IPython kernel.
import sys
print(sys.executable)
This shows the executable path that the IPython kernel is using. If you see that it's not taking the correct interpreter then here's something that worked for me.
Just restart your computer. Then reopen Visual Studio Code and reselect the interpreter and again hit Ctrl + Enter. Now this time Visual Studio Code should take the correct interpreter and its IPython kernel.
See the final output image
If this happens while using WSL server, don't forget to install Python in the WSL as well, because it doesn't come automatically from the local installation to the server.
https://code.visualstudio.com/docs/remote/wsl-tutorial
Another alternative is to specify the folders where the environmental variables should be sought for.
Create your virtual environment using conda create --name ENV_NAME e.g conda create --name pwd
Then, conda activate pwd
It Should print out details like this:
Use that environment location
Edit Vscode settings following these steps:
Open Open User settings using shortcut Ctrl + Shift + P
Type in search space "env"
Under Extentions -> Python , you will find Python: Venv Folders
(See the image below)
Try installing the Anaconda Extension pack.
When I code in Visual Studio Code with this extension in the bottom left corner, I can select the virtual environment I want to execute my code in. Hence installing this package should make the trick.
As the title says I was messing with Visual Studio Code while I was checking the debugging functionality.
I obviously did something wrong because since then every new terminal I open, both on VSC and Ubuntu terminal opens with (base) environment
Any ideas how to fix it?
Somewhere you have run conda init, which adds an entry to your .bashrc file to automatically activate the base environment whenever you start a bash terminal.
If you want to undo this change completely, you can run:
conda init --reverse
However, this will mean that you can't run conda activate, for example.
If you just want to prevent conda from activating the base environment when you start your shell session, you can run:
conda config --set auto_activate_base false
This will create a .condarc file in your home directory, with an entry of auto_activate_base: false. This will override any conda defaults.
I have installed Anaconda for my Machine Learning course. I'm using it as IPython (Jupyter) notebook, in which we have lessons. OS is Ubuntu 14.04 LTS. Basically, I always run it from Terminal with:
jupyter notebook
I have created new environment called su_env from root environment (exact copy) with one package added. Now, I'm wondering: how can I set environment su_env as default one? I have dozen of notebooks so it's annoying to set up each time for every notebook the environment, in "web" GUI of Jupyter.
EDIT: I'm interested in a solution where you don't have to set environment before running notebook. My logic is that, somehow, automagically, jupyter sets root environment on its own while starting up. Because of that, I'm wondering is it possible to set some config file or something so jupyter sets su_env instead of root. Also, if you know that's not possible (and why), I would like to know that.
First activate the conda environment from the command line, then launch the notebook server.
For example:
$ source activate env_name
$ jupyter notebook
Note: This might only work with environments that were created from within Jupyter Notebook, not environments that were created using conda create on the command line.
In your ~/.bashrc, include the line:
alias jupyter="source activate su_env; jupyter"
This will condense the two commands into one, and you will activate su env whenever you call jupyter notebook or lab or whatever
Edit your bashrc and add source activate su_env then that env will always be active. To switch back to to root (or any other env) source activate env_name
You can use this on conda prompt:
conda activate env_name
jupyter notebook
source activate env_name gives me an error: 'source' is not recognized as an internal or external command, operable program, or batch file.
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.
I am having a really hard time adding python 2.7 as a kernel to my iphyton notebook. I have anaconda installed with a python environment called "python2." I can navigate to the environment folder and launch ipython (using python 2.7) in the script folder.
I have tried ipython kernelspec install-self using iphython.exe, however, it seems like ipython is not even a command in that window.
I tried it again in anaconda command window and it just install python3. Please help with precise steps.
Ok I got it. I had to:
Change my python.exe under envs to python2.exe. I also change pythonw to pythonw2.
Added Anacoda\envs\python2 folder that includes python2.exe and scripts to path variable
Then ran this command in Anaconda command window: python2 -m IPython kernelspec install-self
Then ipython kernelspec list to verify