I use Jupyter notebook in a browser for Python programming, I have installed Anaconda (Python 3.5). But I'm quite sure that Jupyter is running my python commands with the native python interpreter and not with anaconda. How can I change it and use Anaconda as interpreter?
8 Answers
import sys
sys.executable
will give you the interpreter. You can select the interpreter you want when you create a new notebook. Make sure the path to your anaconda interpreter is added to your path (somewhere in your bashrc/bash_profile most likely).
For example I used to have the following line in my .bash_profile, that I added manually :
export PATH="$HOME/anaconda3/bin:$PATH"
EDIT: As mentioned in a comment, this is not the proper way to add anaconda to the path. Quoting Anaconda's doc, this should be done instead after install, using conda init
:
Should I add Anaconda to the macOS or Linux PATH?
We do not recommend adding Anaconda to the PATH manually. During installation, you will be asked “Do you wish the installer to initialize Anaconda3 by running conda init?” We recommend “yes”. If you enter “no”, then conda will not modify your shell scripts at all. In order to initialize after the installation process is done, first run
source <path to conda>/bin/activate
and then runconda init
import sys
print(sys.executable)
print(sys.version)
print(sys.version_info)
Seen below :- output when i run JupyterNotebook outside a CONDA venv
/home/dhankar/anaconda2/bin/python
2.7.12 |Anaconda 4.2.0 (64-bit)| (default, Jul 2 2016, 17:42:40)
[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)]
sys.version_info(major=2, minor=7, micro=12, releaselevel='final', serial=0)
Seen below when i run same JupyterNoteBook within a CONDA Venv created with command --
conda create -n py35 python=3.5 ## Here - py35 , is name of my VENV
in my Jupyter Notebook it prints :-
/home/dhankar/anaconda2/envs/py35/bin/python
3.5.2 |Continuum Analytics, Inc.| (default, Jul 2 2016, 17:53:06)
[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)]
sys.version_info(major=3, minor=5, micro=2, releaselevel='final', serial=0)
also if you already have various VENV's created with different versions of Python you switch to the desired Kernel by choosing KERNEL >> CHANGE KERNEL from within the JupyterNotebook menu... JupyterNotebookScreencapture
Also to install ipykernel within an existing CONDA Virtual Environment -
Source --- https://github.com/jupyter/notebook/issues/1524
$ /path/to/python -m ipykernel install --help
usage: ipython-kernel-install [-h] [--user] [--name NAME]
[--display-name DISPLAY_NAME]
[--profile PROFILE] [--prefix PREFIX]
[--sys-prefix]
Install the IPython kernel spec.
optional arguments: -h, --help show this help message and exit --user Install for the current user instead of system-wide --name NAME Specify a name for the kernelspec. This is needed to have multiple IPython kernels at the same time. --display-name DISPLAY_NAME Specify the display name for the kernelspec. This is helpful when you have multiple IPython kernels. --profile PROFILE Specify an IPython profile to load. This can be used to create custom versions of the kernel. --prefix PREFIX Specify an install prefix for the kernelspec. This is needed to install into a non-default location, such as a conda/virtual-env. --sys-prefix Install to Python's sys.prefix. Shorthand for --prefix='/Users/bussonniermatthias/anaconda'. For use in conda/virtual-envs.
You can check python version using
!python -V
Python 3.6.5 :: Anaconda, Inc.
Or
!python --version
Python 3.6.5 :: Anaconda, Inc.
You can add Conda environment to your jupyter notebook
Step 1: Create a Conda environment.
conda create --name firstEnv
Step 2: Activate the environment using the command as shown in the console.
conda activate firstEnv
conda install -c conda-forge <package-name>
E.g.
conda install -c conda-forge tensorflow
Step 3: set this conda environment on your jupyter notebook
conda install -c anaconda ipykernel
python -m ipykernel install --user --name=firstEnv
Step 4: Just check your Jupyter Notebook, to see firstEnv
You can refer this article
Assuming you have the wrong backend system you can change the backend kernel
by creating a new or editing the existing kernel.json
in the kernels
folder of your jupyter data path jupyter --paths
. You can have multiple kernels (R, Python2, Python3 (+virtualenvs), Haskell), e.g. you can create an Anaconda
specific kernel:
$ <anaconda-path>/bin/python3 -m ipykernel install --user --name anaconda --display-name "Anaconda"
Should create a new kernel:
<jupyter-data-dir>/kernels/anaconda/kernel.json
{
"argv": [ "<anaconda-path>/bin/python3", "-m", "ipykernel", "-f", "{connection_file}" ],
"display_name": "Anaconda",
"language": "python"
}
You need to ensure ipykernel
package is installed in the anaconda distribution.
This way you can just switch between kernels and have different notebooks using different kernels.
Creating a virtual environment for Jupyter Notebooks
A minimal Python install is
sudo apt install python3.7 python3.7-venv python3.7-minimal python3.7-distutils python3.7-dev python3.7-gdbm python3-gdbm-dbg python3-pip
Then you can create and use the environment
/usr/bin/python3.7 -m venv test
cd test
source test/bin/activate
pip install jupyter matplotlib seaborn numpy pandas scipy
# install other packages you need with pip/apt
jupyter notebook
deactivate
You can make a kernel for Jupyter with
ipython3 kernel install --user --name=test