scikitplot/scikit-plots repository overview

⁠ 🐳 Scikit-plots Docker Images Guide ⁠:

These containers are a quick way to run or try scikit-plots. The source is available on GitHub⁠⁠ and this file hub.docker.com.md⁠.
For building scikit-plots or extensions for scikit-plots, please see: the scikit-plots Build Dockerfiles⁠. Check If Needed: CI Build Docker Images⁠

• scikitplot/scikit-plots:latest (runtime minimal)⁠
• scikitplot/scikit-plots:latest-runtime (alias latest == latest-runtime)⁠
• scikitplot/scikit-plots:latest-devel (runtime pre-installed)⁠

⁠🐋 Quickstart

docker pull ghcr.io/scikit-plots/scikit-plots:latest-devel-python3.11

# podman pull quay.io/scikit-plots/scikit-plots
docker pull quay.io/scikit-plots/scikit-plots:latest-devel-python3.11

docker pull scikitplot/scikit-plots:latest-devel-python3.11

# docker run -it --rm scikitplot/scikit-plots[:latest|:latest-runtime|:latest-devel] -i -c "scikitplot -V"
# docker run -it --rm -v "$(pwd):/work/notebooks:delegated" -p 8891:8891 scikitplot/scikit-plots:latest-devel

[registry]/[namespace]/[repository]:[tag]

⁠🔧 Start a container, using the Python interpreter.

💡 How to Connect Running Container:

• (Recommended) Open Vscode and Attach to Running Container (Dev Containers)
• (Optionally) Open jupter notebook in browser, If configured ip:host

⁠Onto VS Code's Extension:

• ms-vscode-remote.remote-containers⁠
• ms-vscode-remote.vscode-remote-extensionpack⁠

⁠Run a Container with a Mounted Volume (Permanent External Folder Link)

⁠

⁠Other Examples

docker run -it -v "$(pwd):/work"  python:3.11-slim -c bash

docker run -it -v "$(pwd):/work"  mambaorg/micromamba:2.4.0 -c bash

docker run -it -v "$(pwd):/work" -p 8888:8888  jupyter/scipy-notebook:latest

⁠🐳 Getting Started

⁠🏷️ Base Image Tags

Images built are based on python:latest⁠, jupyter/tensorflow-notebook:latest⁠, etc.

• 1.xx-, latest-, and nightly- tags come with scikit-plots pre-installed. Versioned tags contain their version, the latest- tags contain the latest release (excluding pre-releases like release candidates, alphas, and betas), and the nightly images come with the latest scikit-plots nightly Python package.

⁠🏷️ Optional Features

• -jupyter tags include Jupyter and some scikit-plots tutorial notebooks.. They start a Jupyter notebook server on boot. Mount a volume to /work/notebooks to work on your own notebooks.

⁠🐳 Running Containers

⁠👉 latest (partial pre-installed (e.g., gcc, g++, micromamba))

⁠run interactive shell (default entrypoint bash)

⁠🚨 By using [bash] -ic "bash -i", you are explicitly forcing Bash's hand. The -i flag tells Bash: "I don't care how you were started, force yourself into interactive mode."

# docker run -it --rm scikitplot/scikit-plots:latest
docker run -it --rm scikitplot/scikit-plots:latest -ic "bash -i"

⁠🛠️ (with/without interactive shell) See default os python env package list

docker run -it --rm scikitplot/scikit-plots:latest -ic "bash -ic 'which python && pip list'"

⁠🛠️ (with/without interactive shell) See also pre-installed micromamba python env package list

docker run -it --rm scikitplot/scikit-plots:latest -ic "bash -ic 'micromamba info -e'"

docker run -it --rm scikitplot/scikit-plots:latest -ic "bash -ic 'which python && pip list'"

docker run -it --rm scikitplot/scikit-plots:latest -ic "bash -ic 'scikitplot -V'"

⁠👉 latest-python3.11 alias (latest-runtime-python3.11) (partial pre-installed (e.g., gcc, g++, micromamba))

⁠🏷️ fast-minimal (default entrypoint bash)

# docker run -it --rm scikitplot/scikit-plots:latest -ic "bash -c scikitplot -V"
docker run -it --rm scikitplot/scikit-plots:latest-python3.11 -ic "bash -i"

⁠👉 latest-jupyter (full pre-installed (e.g., conda, mamba))

⁠🏷️ pre-installed os/python packages (default entrypoint tini)

docker run -it --rm scikitplot/scikit-plots:latest-jupyter bash -ic "bash -i"

⁠🛠️ See also pre-installed conda/mamba env:

docker run -it --rm scikitplot/scikit-plots:latest-jupyter bash -ic "bash -ic 'conda info -e'"

docker run -it --rm scikitplot/scikit-plots:latest-jupyter bash -ic "bash -ic 'which python && pip list'"

docker run -it --rm scikitplot/scikit-plots:latest-jupyter bash -ic "bash -ic 'scikitplot -V'"

⁠🛠️ Update system packages (without interactive shell)

docker run -it --rm --user root scikitplot/scikit-plots:latest-jupyter bash -c "apt update"

⁠Scikit-plots Drop-in volume-mount

# PowerShell (man Resolve-Path `-v "$((Resolve-Path .).Path -replace '\\','/'):/work"`)
docker run -it -v "$(pwd):/work" scikitplot/scikit-plots:latest

# CMD (help cd)
docker run -it -v "%cd%:/work" scikitplot/scikit-plots:latest

⁠✅ Cross-Compatible Docker Command path $(pwd)

• Git Bash: pwd -W returns C:/path
• WSL/POSIX: pwd -W fails, then pwd -P is used

⁠⚠️ One-Line Command path for POSIX shells (Git Bash $(pwd -W), WSL/Linux/macOS $(pwd)) and PowerShell $(pwd):

# PowerShell `$(pwd)`
docker run -it --rm -v "$(pwd):/work/notebooks" -p 8891:8891 scikitplot/scikit-plots:latest

Mount the volume with :cached or :delegated (sometimes helps with sync lag)

• :cached Prioritizes container view of files, :delegated Prioritizes host view of files.
• Try :cached first if your container mostly reads code and rarely writes.
• If you actively build and write files inside container and want host to see changes fast, try :delegated.

# PowerShell `$(pwd)`
docker run -it -v "$(pwd):/work/notebooks:delegated" -p 8891:8891 scikitplot/scikit-plots:latest

# Optionally start jupyter notebook
docker run -it --rm -v "$(pwd):/work/notebooks" -p 8891:8891 scikitplot/scikit-plots:latest -ic "bash -ic 'jupyter notebook --notebook-dir=/work --ip=0.0.0.0 --no-browser --allow-root --port=8891'"

⁠⚠️ ("\") Multi-Line Command path for POSIX shells (Git Bash $(pwd -W), WSL/Linux/macOS $(pwd)):

# Detect if using Git Bash (check if pwd -W works) - "$( (...) || ... )"
# Uses $(...) for command substitution, not $(()) which is arithmetic.
# Inner parentheses (...) group the logic in a subshell (a separate environment) run and capture output.
docker run -it --rm \
  -p 8888:8888 \
  scikitplot/scikit-plots:latest-jupyter

Run a Jupyter notebook server with your own notebook directory (assumed here to be ~/notebooks). To use it, navigate to localhost:8888 in your browser.

⁠⚠️ For Development scikit-plots (Cloned and Mounted project folder)

See: Contributing Guidelines to scikit-plots⁠

# bash docker/scripts/git_add_safe_dirs.sh  # add safe directories for git
git config --global --add safe.directory '*'

## Git hooks manager Initialize, Ensures code meets quality standards before it
## Triggered when running `git commit ...;` if all checks pass, the commit proceeds, allowing you to push the changes.
pre-commit install

⁠✍️ Ready for Development...

install-the-development-version-of-scikit-plots⁠

⁠See Also:

• 🤗 https://huggingface.co/scikit-plots⁠