microsoft/devcontainers-miniconda

---

pull: mcr.microsoft.com/devcontainers/miniconda image: devcontainers/miniconda title: Miniconda Development Container Images

Miniconda (Python 3)

About

Develop Miniconda applications in Python 3. Installs dependencies from your environment.yml file and the Python extension.

See https://github.com/devcontainers/images/tree/main/src/miniconda/history for information on the contents of published images.

Using this image

Configuration

You can directly reference pre-built versions of .devcontainer/Dockerfile by using the image property in .devcontainer/devcontainer.json or updating the FROM statement in your own Dockerfile to the following. An example Dockerfile is included in this repository.

• mcr.microsoft.com/devcontainers/miniconda (or miniconda:3)

Refer to https://containers.dev/guide/dockerfile for more details.

You can decide how often you want updates by referencing a https://semver.org/ of each image. For example:

• mcr.microsoft.com/devcontainers/miniconda:1-3
• mcr.microsoft.com/devcontainers/miniconda:1.3-3
• mcr.microsoft.com/devcontainers/miniconda:1.3.2-3

See https://github.com/devcontainers/images/tree/main/src/miniconda/history for information on the contents of each version and here for a complete list of available tags.

Alternatively, you can use the contents of https://github.com/devcontainers/images/tree/main/src/miniconda/.devcontainer to fully customize your container's contents or to build it for a container host architecture not supported by the image.

Using Conda

This dev container and its associated image includes https://aka.ms/vscode-remote/conda/about. Additional packages installed using Conda will be downloaded from Anaconda or another repository if you configure one. To reconfigure Conda in this container to access an alternative repository, please see information on https://aka.ms/vscode-remote/conda/channel-setup.

Access to the Anaconda repository is covered by the https://aka.ms/vscode-remote/conda/terms, which may require some organizations to obtain a commercial license from Anaconda. However, when this dev container or its associated image is used with GitHub Codespaces or GitHub Actions, all users are permitted to use the Anaconda Repository through the service, including organizations normally required by Anaconda to obtain a paid license for commercial activities. Note that third-party packages may be licensed by their publishers in ways that impact your intellectual property, and are used at your own risk.

Using the forwardPorts property

By default, frameworks like Flask only listens to localhost inside the container. As a result, we recommend using the forwardPorts property (available in v0.98.0+) to make these ports available locally.

json
"forwardPorts": [5000]

The appPort property https://docs.docker.com/config/containers/container-networking/#published-ports rather than forwards the port, so applications need to listen to * or 0.0.0.0 for the application to be accessible externally. This conflicts with the defaults of some Python frameworks, but fortunately the forwardPorts property does not have this limitation.

Installing Node.js

Given JavaScript front-end web client code written for use in conjunction with a Python back-end often requires the use of Node.js-based utilities to build, you can use a https://github.com/devcontainers/features/tree/main/src/node to install any version of Node by adding the following to devcontainer.json:

json
{
  "features": {
    "ghcr.io/devcontainers/features/node:1": {
      "version": "latest"
    }
  }
}

Using different Conda channels

This image is based on the ContinuumIO/miniconda3 docker image, which has the conda and its dependencies (installed from conda's default channel) in the base environment. It is not recommended to install packages from different channels in one environment since it could cause conflicts. When installing a package from a different channel (e.g., conda-forge) is required, the better approach is to create a new conda environment.

Installing or updating Python utilities

This container installs all Python development utilities using https://pipxproject.github.io/pipx/ to avoid impacting the global Python environment. You can use this same utility add additional utilities in an isolated environment. For example:

bash
pipx install prospector

Note that if you change the version of Python from the default, you'll need to run a few commands to update the utilities and pipx. More on that next.

Installing a different version of Python

As covered in the https://docs.anaconda.com/anaconda/user-guide/faq for Anaconda, you can install different versions of Python than the one in this image by running the following from a terminal:

bash
conda install python=3.6
pip install --no-cache-dir pipx
pipx uninstall pipx
pipx reinstall-all

Or in a Dockerfile:

Dockerfile
RUN conda install -y python=3.6 \
    && pip install --no-cache-dir pipx \
    && pipx uninstall pipx \
    && pipx reinstall-all

See the https://pipxproject.github.io/pipx/docs/ for additional information.

[Optional] Adding the contents of environment.yml to the image

For convenience, this image will automatically install dependencies from the environment.yml file in the parent folder when the container is built. You can change this behavior by altering this line in the Dockerfile:

Dockerfile
RUN if [ -f "/tmp/conda-tmp/environment.yml" ]; then /opt/conda/bin/conda env update -n base -f /tmp/conda-tmp/environment.yml; fi \
    && rm -rf /tmp/conda-tmp

Support

The dev container spec images are maintained in the https://github.com/devcontainers/images repo. You can explore each image and open issues or feature requests.

License

Copyright (c) Microsoft Corporation. All rights reserved.

Licensed under the MIT License. See https://github.com/devcontainers/images/blob/main/LICENSE