Metadata-Version: 2.4
Name: tricahue
Version: 0.0b5
Summary: This package extracts experimental data and metadata, converts to stardard formats, uploads to SynBioHub and Flapjack, and connects them
Author-email: Gonzalo Vidal <gonzalo.vidalpena@colorado.edu>
Maintainer-email: Gonzalo Vidal <gonzalo.vidalpena@colorado.edu>
License-Expression: MIT
Project-URL: Homepage, https://github.com/MyersResearchGroup/Tricahue
Project-URL: Bug Tracker, https://github.com/MyersResearchGroup/Tricahue/issues
Keywords: SBOL,test,data,experimental,synthetic biology
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: excel2flapjack>=1.0.11
Requires-Dist: excel2sbol>=1.1.14
Requires-Dist: numpy==1.26.1
Requires-Dist: pandas==1.3.3
Provides-Extra: test
Requires-Dist: pytest<5.0.0; extra == "test"
Requires-Dist: pytest-cov[all]; extra == "test"

# Tricahue

Welcome to the Tricahue repository, our Python package for experimental data and metadata standardization, upload to databases and connection for creating distributed datasets.

<img src="https://github.com/Gonza10V/Tricahue/blob/main/images/tricahue_logo.jpeg#gh-light-mode-only" alt="LOICA logo" width="350"/>
<img src="https://github.com/Gonza10V/Tricahue/blob/main/images/tricahue_logo.jpeg#gh-dark-mode-only" alt="LOICA night logo" width="350"/>


![PyPI - Version](https://img.shields.io/pypi/v/tricahue)

As you may have noticed, our logo features a beautiful "loro tricahue" or burrowing parrot[(_Cyanoliseus patagonus bloxami_)](https://en.wikipedia.org/wiki/Burrowing_parrot); a bird native to Chile and Argentina known for its distinctive colors green on head and body, red and yellow on the chest, and a blue tail. These parrots excavate burrows on cliff faces or ravines that are connected forming a complex system of tunnels and chambers[.](https://youtu.be/v2AC41dglnM)

## Installation

Installing Tricahue is super simple! 

Do:

`pip install tricahue`


## Tricahue allows you to:

- Extract experimental data from Excel, CSV and TSV files
- Standardize experimental data into Tidy format
- Stadardize experimental metadata into SBOL
- Upload experimental data to Flapjack
- Upload experimental metadata to SynBioHub
- Connect data from SynBioHub and Flapjack to create complete data sets
