Docker

The community maintains a docker image, which can be found on DockerHub. For our image manimcommunity/manim, there are the following tags:

Note

When using Manim’s CLI within a Docker container, some flags like -p (preview file) and -f (show output file in the file browser) are not supported.

Basic usage of the Docker container

Assuming that you can access the docker installation on your system from a terminal (bash / PowerShell) via docker, you can render a scene CircleToSquare in a file test_scenes.py with the following command.

docker run --rm -it -v "/full/path/to/your/directory:/manim" manimcommunity/manim manim -qm test_scenes.py CircleToSquare

Tip

For Linux users there might be permission problems when letting the user in the container write to the mounted volume. Add --user="$(id -u):$(id -g)" to the docker CLI arguments to prevent the creation of output files not belonging to your user.

Instead of using the “throwaway container” approach outlined above, you can also create a named container that you can modify to your liking. First, run

docker run -it --name my-manim-container -v "/full/path/to/your/directory:/manim" manimcommunity/manim /bin/bash

to obtain an interactive shell inside your container allowing you to, e.g., install further dependencies (like texlive packages using tlmgr). Exit the container as soon as you are satisfied. Then, before using it, start the container by running

docker start my-manim-container

which starts the container in the background. Then, to render a scene CircleToSquare in a file test_scenes.py, run

docker exec -it my-manim-container manim -qm test_scenes.py CircleToSquare

Running JupyterLab via Docker

Another alternative to using the Docker image is to spin up a local JupyterLab instance. To do that, simply run

docker run -it -p 8888:8888 manimcommunity/manim jupyter lab --ip=0.0.0.0

and then follow the instructions in the terminal.