Metadata-Version: 2.1
Name: coffea-casa
Version: 2021.3.dev24
Summary: A Prototype U.S. CMS analysis facility
Home-page: http://github.com/CoffeaTeam/coffea-casa.git
Author: UNL
Author-email: oksana.shadura@cern.ch
License: BSD-3-Clause License
Platform: Any
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Software Development
Classifier: Topic :: Utilities
Description-Content-Type: text/markdown
Requires-Dist: dask-jobqueue
Provides-Extra: all
Requires-Dist: docutils (==0.15.2) ; extra == 'all'
Requires-Dist: ipython ; extra == 'all'
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coffea-casa - A Prototype U.S. CMS analysis facility for Columnar Object Framework For Effective Analysis
=========================================================

![CI/CD status](https://github.com/coffeateam/coffea-casa/workflows/CI/CD/badge.svg)
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[![Documentation Status](https://readthedocs.org/projects/coffea-casa/badge/?version=latest)](https://coffea-casa.readthedocs.io/en/latest/?badge=latest)

Latest DockerHub Images: https://hub.docker.com/orgs/coffeateam/repositories

| Image           | Description                                   |  Size | Pulls | Version | Layers |
|-----------------|-----------------------------------------------|--------------|-------------|-------------|-------------|
| coffea-casa     | Dask scheduler image for coffea-casa hub            | ![](https://img.shields.io/docker/image-size/coffeateam/coffea-casa?sort=date) | ![](https://img.shields.io/docker/pulls/coffeateam/coffea-casa?sort=date) | ![](https://img.shields.io/docker/v/coffeateam/coffea-casa?sort=date) | ![](https://img.shields.io/microbadger/layers/coffeateam/coffea-casa)
| coffea-casa-analysis | Dask worker image for coffea-casa hub    | ![](https://img.shields.io/docker/image-size/coffeateam/coffea-casa-analysis?sort=date) | ![](https://img.shields.io/docker/pulls/coffeateam/coffea-casa-analysis?sort=date) | ![](https://img.shields.io/docker/v/coffeateam/coffea-casa-analysis?sort=date) | ![](https://img.shields.io/microbadger/layers/coffeateam/coffea-casa-analysis)


About
============

The prototype analysis facility provides services for “low latency columnar analysis”, enabling rapid processing of data in a column-wise fashion. These services, based on Dask and Jupyter notebooks, aim to dramatically lower time for analysis and provide an easily-scalable and user-friendly computational environment that will simplify, facilitate, and accelerate the delivery of HEP results. The facility is built on top of a Kubernetes cluster and integrates dedicated resources with resources allocated via fairshare through the local HTCondor system. In addition to the user-facing interfaces such as Dask, the facility also manages access control through single-sign-on and authentication & authorization for data access. The notebooks in this repository and ![Coffea-casa tutorials](https://github.com/CoffeaTeam/coffea-casa-tutorials) include simple HEP analysis examples, managed interactively in a Jupyter notebook and scheduled on Dask workers and accessing both public and protected data.


Image tagging and "continuous building"
============

This repository uses GitHub Actions to build images, run tests, and push images to DockerHub.

1. Tags pushed to GitHub represent "production" releases with corresponding tags on dockerhub `coffeateam/coffea-casa:x.x.x` and `coffeateam/coffea-casa-analysis:x.x.x`. The latest tag also corresponds to the most recent GitHub tag.


References
============
The PyHEP introductory Youtube video is [here](https://www.youtube.com/watch?v=CDIFd1gDbSc).


