A Jupyter and Dask-powered open source data science platform.
Project description
Your open source data science platform. Built for scale, designed for collaboration.
Information | Links |
---|---|
Project | |
Community | |
CI |
Table of contents
- Table of contents
- Nebari
- Installation 💻
- Usage 🚀
- Nebari HPC
- Contributing to Nebari 👩🏻💻
- Code of Conduct 📖
- Ongoing Support
- License
⚠️ Warning ⚠️ The project has recently been renamed from QHub to Nebari. If your deployment is still managed by
qhub
, performing an in place upgrade will IRREVOCABLY BREAK your deployment. This will cause you to lose any data stored on the platform, including but not limited to, NFS (file system) data,conda-store
environments, Keycloak users and groups, etc. Make sure to back up your data before attempting an upgrade.
Automated data science platform. From JupyterHub to Cloud environments with Dask Gateway.
Nebari is an open source data platform that enables users to build and maintain cost-effective and scalable compute platforms on HPC or Kubernetes with minimal DevOps overhead.
This repository details the Nebari (Kubernetes) version.
Not sure what to choose? Check out our documentation on choosing a deployment platform
Nebari
The Kubernetes version of Nebari uses Terraform, Helm, and GitHub Actions.
- Terraform handles the build, change, and versioning of the infrastructure.
- Helm helps to define, install, and manage Kubernetes resources.
- GitHub Actions is used to automatically create commits when the configuration file (
nebari-config.yaml
) is rendered, as well as to kick off the deployment action.
Nebari aims to abstract all these complexities for its users. Hence, it is not necessary to know any of the technologies mentioned above to have your project successfully deployed.
TLDR: If you know GitHub and feel comfortable generating and using API keys, you should have all it takes to deploy and maintain your system without the need for a dedicated DevOps team. No need to learn Kubernetes, Terraform, or Helm.
Cloud Providers ☁️
Nebari offers out-of-the-box support for the major public cloud providers: Digital Ocean, Amazon AWS, GCP, and Microsoft Azure.
Installation 💻
Pre-requisites
- Operating System: Currently, Nebari supports development on macOS and Linux operating systems. Windows is NOT supported. However, we would welcome contributions that add and improve support for Windows.
- You need Python >= 3.7 on your local machine or virtual environment to work on Nebari.
- Adopting virtual environments (
conda
,pipenv
orvenv
) is also encouraged.
Install Nebari
To install Nebari type the following commands in your command line:
-
Install using
conda
:conda install -c conda-forge nebari # if you prefer using mamba mamba install -c conda-forge nebari
-
Install using
pip
:pip install nebari
Once finished, you can check Nebari's version (and additional CLI arguments) by typing:
nebari --help
If successful, the CLI output will be similar to the following:
usage: nebari [-h] [-v] {deploy,destroy,render,init,validate} ...
Nebari command line
positional arguments:
{deploy,destroy,render,init,validate}
Nebari
optional arguments:
-h, --help show this help message and exit
-v, --version Nebari version
Usage 🚀
Nebari requires setting multiple environment variables to automate the deployments fully. For details on obtaining those variables, check the Nebari Get started documentation.
Once all the necessary credentials are gathered and set as UNIX environment variables, Nebari can be deployed in minutes.
For detailed step-by-step instructions on how to deploy Nebari, check the Nebari documentation.
Nebari HPC
An HPC version of Nebari is currently not available. There is one under development for Nebaris precursor QHub. Curious? Check out the QHub HPC repository.
Contributing to Nebari 👩🏻💻
Thinking about contributing? Check out our Contribution Guidelines to get started.
Installing the Development version of Nebari ⚙️
To install the latest developer version (unstable) use:
pip install git+https://github.com/nebari-dev/nebari.git
Questions? 🤔
Have a look at our Frequently Asked Questions (FAQ) to see if your query has been answered.
Getting help:
- GitHub Discussions is our user forum. It can be used to raise discussions about a subject, such as: "What is the recommended way to do X with Nebari?"
- Issues for queries, bug reporting, feature requests, documentation, etc.
We work around the clock to make Nebari better, but sometimes your query might take a while to get a reply. We apologize in advance and ask you to please, be patient :pray:.
Code of Conduct 📖
To guarantee a welcoming and friendly community, we require all community members to follow our Code of Conduct.
Ongoing Support
The v0.4.0
release introduced many changes that will irrevocably break your deployment if you attempt an in-place upgrade; for details, see our
RELEASE notes. To focus on the future direction of the project, we have decided as a team that we will provide limited support for older versions. Any new user is encouraged to use v0.4.0
or greater.
If you're using an older version of Nebari and would like professional support, please get in touch with the Nebari development team.
License
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file nebari-2023.7.1.tar.gz
.
File metadata
- Download URL: nebari-2023.7.1.tar.gz
- Upload date:
- Size: 380.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.11.4
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2a17741aa760ea1f9245e595401c1c66589c42f99074cb87ae560b01cddcb7d2 |
|
MD5 | b5ccfb2aa8489fe1f07b3fa3568460bc |
|
BLAKE2b-256 | 2d49a2ad88b2514274dccc273c33528d97ae2662dad69859693ec84531f0a643 |
Provenance
File details
Details for the file nebari-2023.7.1-py3-none-any.whl
.
File metadata
- Download URL: nebari-2023.7.1-py3-none-any.whl
- Upload date:
- Size: 412.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.11.4
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 4beac116dfd40e81dc765567798306bce205b29116be6c576d72a8ab721685a4 |
|
MD5 | c5aa8856844238f7746be0bbea94620a |
|
BLAKE2b-256 | b51d3a8e23a9c16312cb1a9fad53ce5b2b4f2e2721f1b9288cd8fa5fdb1f459d |