Installation¶
You can get help on Gitter, GitHub, or by email.
Pick one way to install atoti:
Python package¶
atoti is available as a Python package on the public PyPI repository and can thus be installed with Python package managers such as pip or Poetry.
Install atoti and its JupyterLab extension:
pip install atoti[jupyterlab]
Installing graphviz is also recommended as it can be used to display the schema of an atoti session.
Conda package¶
Install Miniconda 64-bit or Anaconda 64-bit.
Note
Conda 64-bit is required since recent versions of some packages are not available with Conda 32-bit.
Add the conda-forge channel:
conda config --add channels conda-forge
Add the atoti channel:
conda config --add channels https://conda.atoti.io
Create a new Conda environment:
conda create --name atoti
Activate it:
conda activate atoti
Install atoti and its JupyterLab extension:
conda install atoti atoti-jupyterlab python
Docker image¶
The atoti image on DockerHub contains the atoti library and its JupyterLab extension ready to use.
Note
This Docker image is a good playground to try atoti with JupyterLab locally. However, it should not be used as a base image for deploying atoti applications on the cloud since JupyterLab will not be needed in this situation. Starting from a bare Python image would be more suited for that.
Pull the image:
docker pull atoti/atoti
Create a volume where the data (notebooks, files, etc.) can be persisted when the Docker container is stopped:
docker volume create atoti-volume
Run the Docker image using the created volume:
docker run --publish 8888:8888 --volume atoti-volume:/home/jovyan/work atoti/atoti
Open the URL printed by Jupyter Server (e.g. http://localhost:8888?token=XXXXX with its security token).
Advanced¶
Building a custom image¶
Our Dockerfile can be used as a starting point for custom images (e.g. to pre-install other dependencies).