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pangeo-data
569 Stars 184 Forks 448 Commits 8 Opened issues

Description

Pangeo website + discussion of general issues related to the project.

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.. image:: docs/static/pangeosimple_logo.svg :width: 175 px :alt: Pangeo

A Community Platform for Big Data Geoscience

.. image:: https://img.shields.io/github/contributors/pangeo-data/pangeo?logo=github&style=flat-square :target: https://github.com/pangeo-data/pangeo :alt: GitHub contributors .. image:: https://img.shields.io/discourse/users?server=https%3A%2F%2Fdiscourse.pangeo.io%2F&style=flat-square&logo=discourse :target: https://discourse.pangeo.io/ :alt: Discourse Forum .. image:: https://img.shields.io/gitter/room/pangeo-data/lobby?color=blue&logo=gitter&style=flat-square :target: https://gitter.im/pangeo-data/Lobby :alt: Gitter .. image:: https://img.shields.io/twitter/follow/pangeodata?logo=twitter&style=flat-square :target: https://twitter.com/pangeodata :alt: Twitter

This repository is home to the Pangeo website:

pangeo.io 
. The website contains general information about the Pangeo project. This repo's
issue tracker 
also serves as a general-purpose discussion forum. For news and updates about Pangeo, check out our
Medium blog 
_ and our
Twitter feed 
. To engage with the Pangeo community, head over to our
Discourse forum 
or browse our
GitHub repos 
_.

What is Pangeo?

Pangeo is first and foremost a community promoting open, reproducible, and scalable science. This community provides documentation, develops and maintains software, and deploys computing infrastructure to make scientific research and programming easier. The Pangeo software ecosystem involves open source tools such as xarray, iris, dask, jupyter, and many other packages. There is no single software package called "pangeo"; rather, the Pangeo project serves as a coordination point between scientists, software, and computing infrastructure. Welcome to the Pangeo community!

Our Goals ^^^^^^^^^

. Foster collaboration around the open source scientific python ecosystem for

ocean / atmosphere / land / climate science.

. Support the development with domain-specific geoscience packages.

. Improve scalability of these tools to handle petabyte-scale datasets on

HPC and cloud platforms.

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