Skip to main content

persistent, pythonic trees for heterogeneous data

Project description

===========================================================
datreant: persistent, pythonic trees for heterogeneous data
===========================================================

|docs| |build| |cov|

In many fields of science, especially those analyzing experimental or
simulation data, there is often an existing ecosystem of specialized tools and
file formats which new tools must work around, for better or worse.
Furthermore, centralized database solutions may be suboptimal for data
storage for a number of reasons, including insufficient hardware
infrastructure, variety and heterogeneity of raw data, the need for data
portability, etc. This is particularly the case for fields centered around
simulation: simulation systems can vary widely in size, composition, rules,
paramaters, and starting conditions. And with increases in computational power,
it is often necessary to store intermediate results obtained from large amounts
of simulation data so it can be accessed and explored interactively.

These problems make data management difficult, and serve as a barrier to
answering scientific questions. To make things easier, **datreant** is a Python
package that addresses the tedious and time-consuming logistics of intermediate
data storage and retrieval. It solves a boring problem, so we can focus on
interesting ones.

For more information on what **datreant** is and what it does, check out the
`official documentation`_.

.. _`official documentation`: http://datreant.readthedocs.org/

Getting datreant
================
See the `installation instructions`_ for installation details.
The package itself is pure Python.

If you want to work on the code, either for yourself or to contribute back to
the project, clone the repository to your local machine with::

git clone https://github.com/datreant/datreant.git

.. _`installation instructions`: http://datreant.readthedocs.org/en/develop/install.html

Contributing
============
This project is still under heavy development, and there are certainly rough
edges and bugs. Issues and pull requests welcome!

Check out our `contributor's guide`_ to learn how to get started with
contributing back.

.. _`contributor's guide`: http://datreant.readthedocs.org/en/develop/contributing.html

.. |docs| image:: https://readthedocs.org/projects/datreant/badge/?version=develop
:alt: Documentation Status
:scale: 100%
:target: http://datreant.readthedocs.org/en/develop/?badge=develop

.. |build| image:: https://travis-ci.org/datreant/datreant.svg?branch=develop
:alt: Build Status
:target: https://travis-ci.org/datreant/datreant

.. |cov| image:: http://codecov.io/github/datreant/datreant/coverage.svg?branch=develop
:alt: Code Coverage
:scale: 100%
:target: http://codecov.io/github/datreant/datreant?branch=develop



Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

datreant-1.0.2.tar.gz (41.2 kB view details)

Uploaded Source

Built Distribution

datreant-1.0.2-py2.py3-none-any.whl (46.0 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file datreant-1.0.2.tar.gz.

File metadata

  • Download URL: datreant-1.0.2.tar.gz
  • Upload date:
  • Size: 41.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for datreant-1.0.2.tar.gz
Algorithm Hash digest
SHA256 16930239dac17f478e5f5f1e499b77b1e9f1769a8b0b48ed7e7e93f5ffa5a0ca
MD5 1643a5ec57ea07f586f06ed438103ba6
BLAKE2b-256 ce4577fa672311c48f06c47ed71ff788badf881f829bb7807fc63b783fc61088

See more details on using hashes here.

File details

Details for the file datreant-1.0.2-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for datreant-1.0.2-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 e45850a2139a77895d1f1e38e354a30f01da1bfb657e1c326742057e17bd5b11
MD5 50edf89172d96f522136c13c59c1d535
BLAKE2b-256 3cb0ca871aba0a332b706971c80eae57190aefd1300c30fa6e8155db23090a82

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page