Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Data Engineering Zoomcamp | 13,734 | 6 days ago | 48 | Jupyter Notebook | ||||||
Free Data Engineering course! | ||||||||||
Deep Image Prior | 7,492 | a month ago | 65 | other | Jupyter Notebook | |||||
Image restoration with neural networks but without learning. | ||||||||||
Docker Stacks | 7,306 | a day ago | 19 | other | Python | |||||
Ready-to-run Docker images containing Jupyter applications | ||||||||||
Jupyterhub | 7,213 | 255 | 115 | 14 hours ago | 66 | June 06, 2022 | 188 | other | Python | |
Multi-user server for Jupyter notebooks | ||||||||||
Deepo | 6,312 | 4 months ago | 1 | mit | Python | |||||
Setup and customize deep learning environment in seconds. | ||||||||||
Nuclio | 4,865 | 10 hours ago | 65 | April 25, 2021 | 111 | apache-2.0 | Go | |||
High-Performance Serverless event and data processing platform | ||||||||||
Deeplearningproject | 4,043 | 3 years ago | 3 | mit | HTML | |||||
An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch. | ||||||||||
Orchest | 3,867 | 8 days ago | 14 | April 06, 2022 | 126 | agpl-3.0 | TypeScript | |||
Build data pipelines, the easy way 🛠️ | ||||||||||
Quantum | 3,715 | 10 | 15 | 14 hours ago | 124 | September 01, 2022 | 43 | mit | Jupyter Notebook | |
Microsoft Quantum Development Kit Samples | ||||||||||
Helk | 3,511 | 2 years ago | 37 | gpl-3.0 | Jupyter Notebook | |||||
The Hunting ELK |
Jupyter Docker Stacks are a set of ready-to-run Docker images containing Jupyter applications and interactive computing tools. You can use a stack image to do any of the following (and more):
You can try a relatively recent build of the jupyter/base-notebook image on mybinder.org by simply clicking the preceding link. Otherwise, the examples below may help you get started if you have Docker installed, know which Docker image you want to use and want to launch a single Jupyter Server in a container.
The User Guide on ReadTheDocs describes additional uses and features in detail.
Example 1:
This command pulls the jupyter/scipy-notebook
image tagged 2023-06-01
from Docker Hub if it is not already present on the local host.
It then starts a container running a Jupyter Server and exposes the container's internal port 8888
to port 10000
of the host machine:
docker run -p 10000:8888 jupyter/scipy-notebook:2023-06-01
You can modify the port on which the container's port is exposed by changing the value of the -p
option to -p 8888:8888
.
Visiting http://<hostname>:10000/?token=<token>
in a browser loads JupyterLab,
where:
hostname
is the name of the computer running Dockertoken
is the secret token printed in the console.The container remains intact for restart after the Jupyter Server exits.
Example 2:
This command pulls the jupyter/datascience-notebook
image tagged 2023-06-01
from Docker Hub if it is not already present on the local host.
It then starts an ephemeral container running a Jupyter Server and exposes the server on host port 10000.
docker run -it --rm -p 10000:8888 -v "${PWD}":/home/jovyan/work jupyter/datascience-notebook:2023-06-01
The use of the -v
flag in the command mounts the current working directory on the host (${PWD}
in the example command) as /home/jovyan/work
in the container.
The server logs appear in the terminal.
Visiting http://<hostname>:10000/?token=<token>
in a browser loads JupyterLab.
Due to the usage of the flag --rm
Docker automatically cleans up the container and removes the file
system when the container exits, but any changes made to the ~/work
directory and its files in the container will remain intact on the host.
The -it
flag allocates pseudo-TTY.
Please see the Contributor Guide on ReadTheDocs for information about how to contribute recipes, features, tests, and community maintained stacks.
We value all positive contributions to the Docker stacks project, from bug reports to pull requests to help with answering questions. We'd also like to invite members of the community to help with two maintainer activities:
Anyone in the community can jump in and help with these activities anytime. We will happily grant additional permissions (e.g., the ability to merge PRs) to anyone who shows an ongoing interest in working on the project.
Following Jupyter Notebook notice, JupyterLab is now the default for all the Jupyter Docker stack images.
It is still possible to switch back to Jupyter Notebook (or to launch a different startup command).
You can achieve this by passing the environment variable DOCKER_STACKS_JUPYTER_CMD=notebook
(or any other valid jupyter
subcommand) at container startup;
more information is available in the documentation.
According to the Jupyter Notebook project status and its compatibility with JupyterLab, these Docker images may remove the classic Jupyter Notebook interface altogether in favor of another classic-like UI built atop JupyterLab.
This change is tracked in the issue #1217; please check its content for more information.
x86_64
and aarch64
platformsaarch64-
or x86_64-
tag prefixes, for example, jupyter/base-notebook:aarch64-python-3.10.5
2022-09-21
, we create multi-platform images (except tensorflow-notebook
)2023-06-01
, we create multi-platform tensorflow-notebook
image as wellThis project only builds one set of images at a time.
If you want to use older Ubuntu
and/or python
version, you can use following images:
Build Date | Ubuntu | Python | Tag |
---|---|---|---|
2022-10-09 | 20.04 | 3.7 | 1aac87eb7fa5 |
2022-10-09 | 20.04 | 3.8 | a374cab4fcb6 |
2022-10-09 | 20.04 | 3.9 | 5ae537728c69 |
2022-10-09 | 20.04 | 3.10 | f3079808ca8c |
2022-10-09 | 22.04 | 3.7 | b86753318aa1 |
2022-10-09 | 22.04 | 3.8 | 7285848c0a11 |
2022-10-09 | 22.04 | 3.9 | ed2908bbb62e |
2023-05-30 | 22.04 | 3.10 | 4d70cf8da953 |
weekly build | 22.04 | 3.11 | latest |