Docker / Linux / python · 1月 15, 2023 0

Docker Installs Miniconda on a Jupyter Server for Data Science



Anaconda is the leading open data science platform .The open source version of Anaconda includes over 100 of the most popular Python packages for data science.Additionally, it provides access to over 720 Python and R packages that can easily be installed using the conda dependency and environment manager.


Miniconda is a free small installer for conda.Miniconda is a small, bootstrap version of Anaconda. It includes only conda, and the packages they depend on. It also includes a small number of other useful packages, including pip, zlib and a few others.Use the conda install command to install 720+ additional conda packages .
System requirements oppress.

  • License: Free use and redistribution under the terms of the EULA.
  • operating system: Windows 8 or newer, 64-bit Macintosh 10.13+ or Linux, including Ubuntu, Red Hat, CentOS 7+ and others.
  • The installer of the Linux-aarch64 Miniconda requires glibc2.26 and will not work with Debian 9, Ubuntu 16.04, or Chrishan 9.
  • It takes 400 MB of disk space to download and install.

On Windows, macOS, and Linux, it is best to install Miniconda for the local user, which does not require administrator permissions.If you need to, you can install Miniconda system wide. It does require administrator permission.

miniconda3 DockerContainer

DockerContainer with bootstrapped installation of Miniconda (based on Python 3.X) .
The Miniconda distribution is installed into the /opt/conda folder.
Use of the library.
You can download and run this image using the following commands:

docker pull continuumio/miniconda3
docker run -i -t continuumio/miniconda3 /bin/bash

You can , for example , start a Jupyter Notebook server and interact with Miniconda via your browser :

docker run -i -t -p 8888:8888 continuumio/miniconda3 /bin/bash -c "\
    conda install jupyter -y --quiet && \
    mkdir -p /opt/notebooks && \
    jupyter notebook \
    --notebook-dir=/opt/notebooks --ip='*' --port=8888 \
    --no-browser --allow-root"

You can then view the Jupyter Notebook by opening the website in your browser or at the website – DOCKER-MACHINE-IP>8888 if you use a Docker.

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