Metadata-Version: 2.1
Name: tangos
Version: 1.9.1
Summary: TANGOS, the agile numerical galaxy organisation system
Home-page: UNKNOWN
Author: Andrew Pontzen
Author-email: a.pontzen@ucl.ac.uk
License: BSD
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: License :: OSI Approved :: BSD License
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Provides-Extra: rmdbs
Provides-Extra: test
License-File: LICENSE

Tangos - The agile numerical galaxy organisation system
-------------------------------------------------------

[![Build Status](https://github.com/pynbody/tangos/actions/workflows/build-test.yaml/badge.svg?branch=master)](https://github.com/pynbody/tangos/actions) [![DOI](https://zenodo.org/badge/105990932.svg)](https://zenodo.org/badge/latestdoi/105990932)

_Tangos_ lets you build a database (along the lines of [Eagle](http://icc.dur.ac.uk/Eagle/database.php)
or [MultiDark](https://www.cosmosim.org/cms/documentation/projects/multidark-bolshoi-project/))
 for your own cosmological and zoom simulations.

It's a modular system for Python 3.6+, capable of generating and querying databases. _Tangos_:

 - is designed to store and manage results from your own analysis code;
 - provides web and python interfaces;
 - allows users to construct science-focussed queries, including across entire merger trees,
   without requiring any knowledge of SQL;

When building databases, _tangos_:

 - manages the process of populating the database with science data, including auto-parallelising
   your analysis;
 - can be customised to work with multiple python modules such as
   [pynbody](http://pynbody.github.io/pynbody/) or [yt](http://yt-project.org) to
   process raw simulation data;
 - can use your favourite database as the underlying store, thanks to [sqlalchemy](https://www.sqlalchemy.org).
   By default, _tangos_ uses the file-based database [sqlite](https://sqlite.org), but it is also routinely
   tested against the server-based MySQL (from v1.5) and PostgreSQL (from v1.7).


 Getting started
 ---------------

 For information on getting started refer to the [tutorials on our github pages](https://pynbody.github.io/tangos/).
 These tutorials are also available in markdown format [within the tangos repository](docs/index.md).


Acknowledging the code
----------------------
When using _tangos_, please acknowledge it by citing the release paper:
Pontzen & Tremmel, 2018, ApJS 237, 2. [DOI 10.3847/1538-4365/aac832](https://doi.org/10.3847/1538-4365/aac832);  [arXiv:1803.00010](https://arxiv.org/pdf/1803.00010.pdf). Optionally you can also cite the Zenodo DOI for the specific version of _tangos_ that you are using, which may be found [here](https://doi.org/10.5281/zenodo.1243070).


