jupyterlab

jupyterlab

CONTAINERS IMAGES RUN BUILD

Running the jupyerlab container will automatically start a JupyterLab server in the background on port 8888, with default login password nvidia. The JupyterLab server logs will be saved to /data/logs/jupyter.log if you need to inspect them (this location is automatically mounted under your jetson-containers/data directory)

To change the default settings, you can set the $JUPYTER_ROOT, $JUPYTER_PORT, $JUPYTER_PASSWORD, and $JUPYTER_LOG environment variables when starting the container like so:

jetson-containers run \
  --env JUPYTER_ROOT=/home/user \
  --env JUPYTER_PORT=8000 \
  --env JUPYTER_PASSWORD=password \
  --env JUPYTER_LOGS=/dev/null \
  $(autotag jupyterlab)

The /start_jupyter script is the default CMD that the container runs when it starts - however, if you don't want the JupyterLab server started by default, you can either add a different CMD in your own Dockerfile, or override it at startup:

# skip straight to the terminal instead of starting JupyterLab first
jetson-containers run /bin/bash

You can then still manually run the /start_jupyter script later when desired.

CONTAINERS

jupyterlab:latest
Aliases	jupyterlab
Requires	L4T ['>=32.6']
Dependencies	build-essential pip_cache:cu126 cuda:12.6 cudnn:9.3 python tensorrt numpy cuda-python pycuda rust
Dependants	audiocraft diffusion_policy dli-nano-ai efficientvit jupyter_clickable_image_widget jupyterlab:latest-myst l4t-ml l4t-text-generation langchain:samples lerobot llama-index:samples openpi pytorch:2.1-all pytorch:2.2-all pytorch:2.3-all pytorch:2.3.1-all pytorch:2.4-all pytorch:2.5-all pytorch:2.6-all pytorch:2.7-all pytorch:2.8-all sam tam voice-pro voicecraft warp:1.7.0-all warp:1.8.1-all whisper
Dockerfile	Dockerfile
Notes	will autostart Jupyter server on port 8888 unless container entry CMD is overridden

jupyterlab:latest-myst
Aliases	jupyterlab:myst
Requires	L4T ['>=32.6']
Dependencies	build-essential pip_cache:cu126 cuda:12.6 cudnn:9.3 python tensorrt numpy cuda-python pycuda rust jupyterlab:latest
Dependants	lerobot llama-index:samples openpi
Dockerfile	Dockerfile.myst
Notes	will autostart Jupyter server on port 8888 unless container entry CMD is overridden

jupyterlab:4.2.0
Requires	L4T ['>=32.6']
Dependencies	build-essential pip_cache:cu126 cuda:12.6 cudnn:9.3 python tensorrt numpy cuda-python pycuda rust
Dependants	jupyterlab:4.2.0-myst
Dockerfile	Dockerfile
Notes	will autostart Jupyter server on port 8888 unless container entry CMD is overridden

jupyterlab:4.2.0-myst
Requires	L4T ['>=32.6']
Dependencies	build-essential pip_cache:cu126 cuda:12.6 cudnn:9.3 python tensorrt numpy cuda-python pycuda rust jupyterlab:4.2.0
Dockerfile	Dockerfile.myst
Notes	will autostart Jupyter server on port 8888 unless container entry CMD is overridden

CONTAINER IMAGES

Repository/Tag	Date	Arch	Size
dustynv/jupyterlab:r32.7.1	2024-03-07	arm64	0.7GB
dustynv/jupyterlab:r35.2.1	2023-12-06	arm64	5.3GB
dustynv/jupyterlab:r35.3.1	2024-03-07	arm64	5.4GB
dustynv/jupyterlab:r35.4.1	2023-10-07	arm64	5.3GB
dustynv/jupyterlab:r36.2.0	2024-03-07	arm64	0.6GB
dustynv/jupyterlab:r36.4.0	2025-03-10	arm64	5.8GB
dustynv/jupyterlab:r36.4.0-cu128-24.04	2025-03-03	arm64	5.1GB

_{Container images are compatible with other minor versions of JetPack/L4T:
    • L4T R32.7 containers can run on other versions of L4T R32.7 (JetPack 4.6+)
    • L4T R35.x containers can run on other versions of L4T R35.x (JetPack 5.1+)}

RUN CONTAINER

To start the container, you can use jetson-containers run and autotag, or manually put together a docker run command:

# automatically pull or build a compatible container image
jetson-containers run $(autotag jupyterlab)

# or explicitly specify one of the container images above
jetson-containers run dustynv/jupyterlab:r36.4.0

# or if using 'docker run' (specify image and mounts/ect)
sudo docker run --runtime nvidia -it --rm --network=host dustynv/jupyterlab:r36.4.0

^{jetson-containers run forwards arguments to docker run with some defaults added (like --runtime nvidia, mounts a /data cache, and detects devices)
autotag finds a container image that's compatible with your version of JetPack/L4T - either locally, pulled from a registry, or by building it.}

To mount your own directories into the container, use the -v or --volume flags:

jetson-containers run -v /path/on/host:/path/in/container $(autotag jupyterlab)

To launch the container running a command, as opposed to an interactive shell:

jetson-containers run $(autotag jupyterlab) my_app --abc xyz

You can pass any options to it that you would to docker run, and it'll print out the full command that it constructs before executing it.

BUILD CONTAINER

If you use autotag as shown above, it'll ask to build the container for you if needed. To manually build it, first do the system setup, then run:

jetson-containers build jupyterlab

The dependencies from above will be built into the container, and it'll be tested during. Run it with --help for build options.