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Last pushed: a month ago
Short Description
Scientific python Jupyter Notebook server
Full Description

Jupyter Notebook Scientific Python Stack

What it Gives You

  • Jupyter Notebook 4.2.x
  • Conda Python 3.x and Python 2.7.x environments
  • pandas, matplotlib, scipy, seaborn, scikit-learn, scikit-image, sympy, cython, patsy, statsmodel, cloudpickle, dill, numba, bokeh pre-installed
  • tini as the container entrypoint and as the default command

Basic Use

The following command starts a container with the Notebook server listening for HTTP connections on port 8888 without authentication configured.

docker run -d -p 8888:8888 jupyter/scipy-notebook

Conda Environments

The default Python 3.x Conda environment resides in /opt/conda. A second Python 2.x Conda environment exists in /opt/conda/envs/python2. You can switch to the python2 environment in a shell by entering the following:

source activate python2

You can return to the default environment with this command:

source deactivate

The commands jupyter, ipython, python, pip, easy_install, and conda (among others) are available in both environments. For convenience, you can install packages into either environment regardless of what environment is currently active using commands like the following:

# install a package into the python2 environment
pip2 install some-package
conda install -n python2 some-package

# install a package into the default (python 3.x) environment
pip3 install some-package
conda install -n python3 some-package
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