semvec/pypi-packages huggingface dataset:
audiofile 1.6.0
Fast reading of all kind of audio files
Requires Python: >=3.10
Keywords: audio, tools

=========
audiofile
=========

|tests| |coverage| |docs| |python-versions| |license|

The Python package **audiofile** handles all kind of audio files
with a focus on `reading speed`_.

It can read and request information
on channels, duration, number of samples and sampling rate
for all files that are supported by
ffmpeg_,
sox_,
and mediainfo_.
In addition,
it can write WAV, FLAC, MP3, and OGG files.

Have a look at the installation_ and usage_ instructions as a starting point.

Code example for reading a file:

.. code-block:: python

    import audiofile

    signal, sampling_rate = audiofile.read("signal.wav")

Under the hood it uses soundfile_ to read the audio files,
converting non-supported formats first to WAV files.
The same approach is applied
when requesting duration for formats that need to be decoded
to ensure that duration and number of samples match.


.. _ffmpeg: https://www.ffmpeg.org/
.. _installation: https://audeering.github.io/audiofile/installation.html
.. _mediainfo: https://mediaarea.net/en/MediaInfo/
.. _usage: https://audeering.github.io/audiofile/usage.html
.. _reading speed: https://audeering.github.io/audiofile/benchmark.html
.. _sox: https://sourceforge.net/projects/sox/
.. _virtualenv: https://virtualenv.pypa.io/
.. _soundfile: https://python-soundfile.readthedocs.io/

.. |tests| image:: https://github.com/audeering/audiofile/workflows/Test/badge.svg
    :target: https://github.com/audeering/audiofile/actions?query=workflow%3ATest
    :alt: Test status
.. |coverage| image:: https://codecov.io/gh/audeering/audiofile/branch/main/graph/badge.svg?token=LVF0621BKR
    :target: https://codecov.io/gh/audeering/audiofile/
    :alt: code coverage
.. |docs| image:: https://img.shields.io/pypi/v/audiofile?label=docs
    :target: https://audeering.github.io/audiofile/
    :alt: audiofile's documentation
.. |python-versions| image:: https://img.shields.io/pypi/pyversions/audiofile.svg
    :target: https://pypi.org/project/audiofile/
    :alt: audiofile's supported Python versions
.. |license| image:: https://img.shields.io/badge/license-MIT-green.svg
    :target: https://github.com/audeering/audiofile/blob/main/LICENSE
    :alt: audiofile's MIT license
hero-core 1.1.2
Hero is a framework for AI agent.
Requires Python: >=3.12

Hero 是一个渐进式的 Agent 框架，能够帮助你快速构建和部署 Agent 应用。

Hero 提供了一种任务反馈循环机制，使得 Agent 具备了完善的反馈反思，自我纠错、自我提升机制。通过 Hero 创建的智能体，会根据任务的执行情况，不断调整自己的行为，反复迭代，最终完成任务。

框架将 Agent 的常见概念如 模型、任务、工具、记忆 等进行了封装和抽象，你可以深度定制相关模块，最大限度的发挥 Agent 的潜力。同时，我们将 Hero-Core 的架构设计的足够简单和渐进式，开发者可以直接上手使用。
bw2data-perf 4.5.4
Tools for the management of inventory databases and impact assessment methods. Part of the Brightway LCA framework.
Requires Python: >=3.9

# bw2data

[![PyPI](https://img.shields.io/pypi/v/bw2data.svg)][pypi status]
[![Status](https://img.shields.io/pypi/status/bw2data.svg)][pypi status]
[![Python Version](https://img.shields.io/pypi/pyversions/bw2data)][pypi status]
[![License](https://img.shields.io/pypi/l/bw2data)][license]

[![Tests](https://github.com/brightway-lca/brightway2-data/actions/workflows/python-test.yml/badge.svg)][tests]
[![Codecov](https://codecov.io/gh/brightway-lca/bw2data/branch/main/graph/badge.svg)][codecov]

[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)][pre-commit]
[![Black](https://img.shields.io/badge/code%20style-black-000000.svg)][black]

[pypi status]: https://pypi.org/project/bw2data/
[read the docs]: https://bw2data.readthedocs.io/
[tests]: https://github.com/brightway-lca/brightway2-data/actions?workflow=Tests
[codecov]: https://app.codecov.io/gh/brightway-lca/bw2data
[pre-commit]: https://github.com/pre-commit/pre-commit
[black]: https://github.com/psf/black

This package provides tools for the management of inventory databases and impact assessment methods.
It is part of the [Brightway LCA framework](https://brightway.dev).
[Online documentation](https://docs.brightway.dev/) is available, and the source code is hosted on [GitHub brightway-lca organization](https://github.com/brightway-lca/brightway2-data).

Note that version 4.0 and higher are only compatible with Brightway 2.5, as described in the [changelog](https://github.com/brightway-lca/brightway2-data/blob/main/CHANGES.md).

## Installation

You can install _bw2data_ via [pip] from [PyPI]:

```console
$ pip install bw2data
```

## Contributing

Contributions are very welcome.
To learn more, see the [Contributor Guide][Contributor Guide].

## License

Distributed under the terms of the [BSD 3 Clause license][License],
_bw2data_ is free and open source software.

## Issues

If you encounter any problems,
please [file an issue][Issue Tracker] along with a detailed description.


<!-- github-only -->

[command-line reference]: https://bw2data.readthedocs.io/en/latest/usage.html
[License]: https://github.com/brightway-lca/bw2data/blob/main/LICENSE
[Contributor Guide]: https://github.com/brightway-lca/bw2data/blob/main/CONTRIBUTING.md
[Issue Tracker]: https://github.com/brightway-lca/bw2data/issues


## Building the Documentation

You can build the documentation locally by installing the documentation Conda environment:

```bash
conda env create -f docs/environment.yml
```

activating the environment

```bash
conda activate sphinx_bw2data
```

and [running the build command](https://www.sphinx-doc.org/en/master/man/sphinx-build.html#sphinx-build):

```bash
sphinx-build docs _build/html --builder=html --jobs=auto --write-all; open _build/html/index.html
```
myst-docutils 5.0.0
An extended [CommonMark](https://spec.commonmark.org/) compliant parser,
Requires Python: >=3.11
Keywords: markdown, lexer, parser, development, docutils, sphinx

# MyST-Parser

Note: myst-docutils is identical to myst-parser, but without installation requirements on sphinx

[![Github-CI][github-ci]][github-link]
[![Coverage Status][codecov-badge]][codecov-link]
[![Documentation Status][rtd-badge]][rtd-link]
[![Code style: black][black-badge]][black-link]
[![PyPI][pypi-badge]][pypi-link]
[![Conda][conda-badge]][conda-link]
[![PyPI - Downloads][install-badge]][install-link]


**MyST is a rich and extensible flavor of Markdown meant for technical documentation and publishing**.

MyST is a flavor of markdown that is designed for simplicity, flexibility, and extensibility.
This repository serves as the reference implementation of MyST Markdown, as well as a collection of tools to support working with MyST in Python and Sphinx.
It contains an extended [CommonMark](https://commonmark.org)-compliant parser using [`markdown-it-py`](https://markdown-it-py.readthedocs.io/), as well as a [Sphinx](https://www.sphinx-doc.org) extension that allows you to write MyST Markdown in Sphinx.

[**See the MyST Parser documentation for more information**](https://myst-parser.readthedocs.io/en/latest/).

## Installation

To install the MyST parser, run the following in a
[Conda environment](https://docs.conda.io) (recommended):

```bash
conda install -c conda-forge myst-docutils
```

or

```bash
pip install myst-docutils
```

Or for package development:

```bash
git clone https://github.com/executablebooks/MyST-Parser
cd MyST-Parser
git checkout master
pip install -e .[code_style,linkify,testing,rtd]
```

To use the MyST parser in Sphinx, simply add: `extensions = ["myst_parser"]` to your `conf.py`.

## Contributing

We welcome all contributions!
See the [Contributing Guide](https://myst-parser.readthedocs.io/en/latest/develop/index.html) for more details.

[github-ci]: https://github.com/executablebooks/MyST-Parser/workflows/continuous-integration/badge.svg?branch=master
[github-link]: https://github.com/executablebooks/MyST-Parser
[codecov-badge]: https://codecov.io/gh/executablebooks/MyST-Parser/branch/master/graph/badge.svg
[codecov-link]: https://codecov.io/gh/executablebooks/MyST-Parser
[rtd-badge]: https://readthedocs.org/projects/myst-parser/badge/?version=latest
[rtd-link]: https://myst-parser.readthedocs.io/en/latest/?badge=latest
[black-badge]: https://img.shields.io/badge/code%20style-black-000000.svg
[pypi-badge]: https://img.shields.io/pypi/v/myst-docutils.svg
[pypi-link]: https://pypi.org/project/myst-docutils
[conda-badge]: https://anaconda.org/conda-forge/myst-docutils/badges/version.svg
[conda-link]: https://anaconda.org/conda-forge/myst-docutils
[black-link]: https://github.com/ambv/black
[install-badge]: https://img.shields.io/pypi/dw/myst-docutils?label=pypi%20installs
[install-link]: https://pypistats.org/packages/myst-docutils
myst-parser 5.0.0
An extended [CommonMark](https://spec.commonmark.org/) compliant parser,
Requires Python: >=3.11
Keywords: markdown, lexer, parser, development, docutils, sphinx

# MyST-Parser

[![Github-CI][github-ci]][github-link]
[![Coverage Status][codecov-badge]][codecov-link]
[![Documentation Status][rtd-badge]][rtd-link]
[![Code style: black][black-badge]][black-link]
[![PyPI][pypi-badge]][pypi-link]
[![Conda][conda-badge]][conda-link]
[![PyPI - Downloads][install-badge]][install-link]


**MyST is a rich and extensible flavor of Markdown meant for technical documentation and publishing**.

MyST is a flavor of markdown that is designed for simplicity, flexibility, and extensibility.
This repository serves as the reference implementation of MyST Markdown, as well as a collection of tools to support working with MyST in Python and Sphinx.
It contains an extended [CommonMark](https://commonmark.org)-compliant parser using [`markdown-it-py`](https://markdown-it-py.readthedocs.io/), as well as a [Sphinx](https://www.sphinx-doc.org) extension that allows you to write MyST Markdown in Sphinx.

[**See the MyST Parser documentation for more information**](https://myst-parser.readthedocs.io/en/latest/).

## Installation

To install the MyST parser, run the following in a
[Conda environment](https://docs.conda.io) (recommended):

```bash
conda install -c conda-forge myst-parser
```

or

```bash
pip install myst-parser
```

Or for package development:

```bash
git clone https://github.com/executablebooks/MyST-Parser
cd MyST-Parser
git checkout master
pip install -e .[code_style,linkify,testing,rtd]
```

To use the MyST parser in Sphinx, simply add: `extensions = ["myst_parser"]` to your `conf.py`.

## Contributing

We welcome all contributions!
See the [Contributing Guide](https://myst-parser.readthedocs.io/en/latest/develop/index.html) for more details.

[github-ci]: https://github.com/executablebooks/MyST-Parser/workflows/continuous-integration/badge.svg?branch=master
[github-link]: https://github.com/executablebooks/MyST-Parser
[codecov-badge]: https://codecov.io/gh/executablebooks/MyST-Parser/branch/master/graph/badge.svg
[codecov-link]: https://codecov.io/gh/executablebooks/MyST-Parser
[rtd-badge]: https://readthedocs.org/projects/myst-parser/badge/?version=latest
[rtd-link]: https://myst-parser.readthedocs.io/en/latest/?badge=latest
[black-badge]: https://img.shields.io/badge/code%20style-black-000000.svg
[pypi-badge]: https://img.shields.io/pypi/v/myst-parser.svg
[pypi-link]: https://pypi.org/project/myst-parser
[conda-badge]: https://anaconda.org/conda-forge/myst-parser/badges/version.svg
[conda-link]: https://anaconda.org/conda-forge/myst-parser
[black-link]: https://github.com/ambv/black
[install-badge]: https://img.shields.io/pypi/dw/myst-parser?label=pypi%20installs
[install-link]: https://pypistats.org/packages/myst-parser
OLIV 1.1.1
Open Library for Image Velocimetry
Requires Python: >=3.12

General Description
===================

OLIV (Open Library for Image Velocimetry) is an open-source toolbox developed by EDF, INRAE, Toulouse INP and CERFACS.

The main developer is Pierre Horgue (Toulouse INP).

Installation
------------

The recommended way to install ``oliv`` is via PyPI:

.. code:: sh

   pip install oliv

You can use ``oliv`` directly in your python scripts with:

.. code-block:: python

   from oliv import *

Note: If you downloaded the oliv archive directly, ensure you add its path to your Python script:

.. code-block:: python

   import sys
   sys.path.append("/path/to/oliv")
   from oliv import *

Documentation
-------------

Informations about classes and usage can be found at : https://oliv.readthedocs.io/en/main/

Script example can be found in **validation/** directory.