Part of Jupyter Docker Scipy with Python SQL Driver

This image includes the packages that I use most of the entire Jupyter scientific ecosystem with the addition of the ODBC Driver for SQL Server (pyodbc)

The following components are included:

• Everything in cjadeveloper/jupyter-minimal and its ancestor images
• pandas, numexpr, matplotlib, scipy, seaborn, sympy, cloudpickle, dill, numba, bokeh, sqlalchemy, vincent, beautifulsoup, protobuf, and xlrd packages
• ipywidgets for interactive visualizations in Python notebooks
• pyodbc driver for SQL Server

Several ways to use this image

Example 1: This command pulls the lasted cjadeveloper/jupyter-scipy from Docker Hub if it is not already present on the local host. It then starts a container running a Jupyter Notebook server and exposes the server on host port 8888. The server logs appear in the terminal. Visiting http://<hostname>:8888/?token=<token> in a browser loads the Jupyter Notebook dashboard page, where hostname is the name of the computer running docker and token is the secret token printed in the console. The container remains intact for restart after the notebook server exits.:

docker run -p 8888:8888 cjadeveloper/jupyter-scipy

Example 2: This command performs the same operations as Example 1, but it exposes the server on host port 10000 instead of port 8888 and assign the name my_jupyter to the container. Visiting http://<hostname>:10000/?token=<token> in a browser loads the Jupyter Notebook dashboard page, where hostname is the name of the computer running docker and token is the secret token printed in the console.

docker run -p 8888:8888 --name my_jupyter cjadeveloper/jupyter-scipy

Example 3: This command pulls the lasted cjadeveloper/jupyter-scipy image from Docker Hub if it is not already present on the local host. It then starts an ephemeral container running a Jupyter Notebook server and exposes the server on host port 8888. The command mounts the current working directory on the host as /home/johndoe/work in the container. The server logs appear in the terminal. Visiting http://<hostname>:8888/?token=<token> in a browser loads JupyterLab, where hostname is the name of the computer running docker and token is the secret token printed in the console. Docker destroys the container after notebook server exit, but any files written to ~/work in the container remain intact on the host.

Linux/Mac Containers: Env vars with "$var"

docker run --rm -p 8888:8888 -e JUPYTER_ENABLE_LAB=yes -v "$PWD":/home/johndoe/work cjadeveloper/jupyter-scipy

Windows Container: Env vars with "%var%"

docker run --rm -p 8888:8888 -e JUPYTER_ENABLE_LAB=yes -v "%CD%":/home/johndoe/work cjadeveloper/jupyter-scipy

Basado en Docker Jupyter Stack