Metadata-Version: 2.4
Name: bliss_audio
Version: 0.2.0
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Summary: A package containing helpers to make audio playlists.
Author-email: Polochon_street <polochonstreet@gmx.feature>
Requires-Python: >=3.7
Description-Content-Type: text/markdown; charset=UTF-8; variant=GFM
Project-URL: Homepage, https://github.com/Polochon-street/bliss-rs
Project-URL: Issues, https://github.com/Polochon-street/bliss-rs/issues

Python bindings for [bliss-rs](https://github.com/Polochon-street/bliss-rs).

Audio library used as a building block to make playlists from songs.

Installation
============

bliss-audio is available for Python 3.5+ via pip:

```
$ pip install bliss-audio
```

Usage
=====

```python
from bliss_audio import Song
import numpy as np

song1 = Song("/path/to/song1")

print(f'Song "{song1.title}" has the following analysis:')
for key, value in sorted(song1.analysis_dict.items()):
    print(f"{key}: {value}")

song2 = Song("/path/to/song2")

distance = np.linalg.norm(np.array(song1.analysis) - np.array(song2.analysis))

print(f'\nDistance between song1 and song2 is {distance}')
```

Then you most likely want to analyze a bunch of songs like that, store the
result somewhere, and generate playlists on the fly by taking a song and
finding the next one by computing the one with the smallest distance to it.

