Metadata-Version: 2.1
Name: living-figures
Version: 0.2.0
Summary: Resource of interactive data widgets
Author-email: Samuel Minot <sminot@fredhutch.org>
Project-URL: Homepage, https://github.com/FredHutch/widgets-store
Project-URL: Bug Tracker, https://github.com/FredHutch/widgets-store/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE

# Living Figures
Collection of useful interactive data widgets

## Widgets

The interactive data widgets provided in this repository have been
created using the [widgets library](https://www.github.com/FredHutch/widgets).
The idea behind this approach is that the complete set of instructions
needed to visualize a dataset can be packaged together in a single HTML
file along with the data itself so that it can be viewed in any modern
web browser.
The underlying technology which enables this approach is Pyodide,
as well as the [stlite](https://github.com/whitphx/stlite) implementation
of [Streamlit](https://streamlit.io/).

## Using the Store

All of the widgets provided in this store can be installed with:

```
pip install living-figures
```

Once installed, you can load your data into one of these widgets
and save an interactive HTML file with:

```#!/usr/bin/env python
from living_figures.bio.epigenome.widgets import PanEpiGenomeBrowser
from pathlib import Path
import pandas as pd

# Instantiate the object
lfig = PanEpiGenomeBrowser()

# Read in your data of interest (in this case epigenetic motif CSVs)
lfig._get_child(
    "files",
    "pacbio"
).parse_files(
    Path('motif_folder').rglob('*.motifs.csv')
)

# Save an HTML file
lfig.to_html(Path("my_epigenomes.html"))
```
