semvec/pypi-packages huggingface dataset:
sphinxext-bsb 7.2.1
BSB Sphinx documentation extension
Requires Python: <4,>=3.10

[![Build Status](https://github.com/dbbs-lab/bsb/actions/workflows/main.yml/badge.svg)](https://github.com/dbbs-lab/bsb/actions/workflows/main.yml)
[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)

# sphinxext-bsb

Sphinx extension for the BSB documentation.
osekit 0.4.3
OSEkit
Requires Python: >=3.12

<br>
<br>
<div align="center">

[![OSEkit logo](https://raw.githubusercontent.com/Project-OSmOSE/OSEkit/refs/heads/main/docs/logo/osekit_mid.png)](https://github.com/Project-OSmOSE/OSEkit)

<br>
<br>

![version](https://img.shields.io/pypi/v/osekit?label=osekit)
![PyPI status](https://img.shields.io/pypi/status/osekit)
[![Coverage Status](https://coveralls.io/repos/github/Project-OSmOSE/OSEkit/badge.svg?branch=version-bump)](https://coveralls.io/github/Project-OSmOSE/OSEkit?branch=version-bump)
![license](https://img.shields.io/github/license/mashape/apistatus.svg)
![Open Source Love](https://img.shields.io/badge/open%20source-♡-lightgrey)
![Python 3.12](https://img.shields.io/pypi/pyversions/osekit)


**OSEkit** is an open source python package dedicated to the management and analysis of data in underwater passive acoustics.

[Presentation](#presentation) •
[Getting into it](#getting-into-it) •
[Acknowledgements](#acknowledgements)
# ㅤ

</div>

### Presentation

**OSEkit** is a Python open source package designed for effortless manipulation of audio data.

It is primarily designed for working on underwater passive acoustics data, but can be used on any audio data.

**OSEkit** provides:

- Seamless, timestamp-based access across multiple files (e.g., pick a 3-minutes long segment spannign over two 1.5-minutes long files without manual file picking)
- Preprocessing utilities: resampling, normalization...
- Spectral analysis routines: compute power spectra, spectrograms, LTAS...

**OSEkit** treats your audio dataset as a continuous timeline, whatever the raw files configuration.
You request audio by time intervals and the package fetches from the raw files behind the scenes: no manual I/O juggling required.

<br>

### Getting into it

All details to start using our toolkit and make the most out of it are given in our [documentation](https://project-osmose.github.io/OSEkit/).

<br>


<div align="center">

[![OSmOSE logo](https://raw.githubusercontent.com/Project-OSmOSE/OSEkit/refs/heads/main/docs/logo/osmose_texte_sombre_small.png)](https://osmose.ifremer.fr/)

</div>

<br>

<sub>© OSmOSE team, 2023-present</sub>
parladata-base-api 0.3.2b4
Cached api for parladata
Requires Python: >=3.7

# Parladata base API


Python API with cacheing data for Parladata `https://github.com/danesjenovdan/parladata`

## Installation

Parladata base API is available on PyPI:

```console
$ python -m pip install parladata-base-api
```

## Quickstart
example:

```python
    >>> from parladata_base_api import DataStorage
    >>> storage = DataStorage(MANDATE, MANDATE_STARTIME, MAIN_ORG_ID, API_URL, API_USERNAME, API_PASSWORD)
    >>> perosn_object = storage.people_storage.get_or_add_object({"name": "Name Surname"})
```