semvec/pypi-packages huggingface dataset:
pandera-alchemy 1.1.0
A package that enables using Pandera DataFrame Models to validate SQL Alchemy table schemas
Requires Python: <4.0,>=3.9

# Pandera Alchemy

<img src="./images/pandera_alchemy.png" alt="pandera_alchemy logo" width="700" height="500">

The `pandera_alchemy` package bridges Pandera and SQLAlchemy, allowing users to define the structure of a database table using Pandera DataFrameModels or DataFrameSchemas and validate that the table has the expected structure with SQLAlchemy.

## Motivation

In modern data pipelines, ensuring that the structure of database tables matches the expected schema is crucial for maintaining data integrity and consistency. The `pandera_alchemy` package provides a seamless way to define and validate these structures, leveraging the power of Pandera for schema definitions and SQLAlchemy for database interactions.

## Installation

### As a Library

To install the `pandera_alchemy` package as a dependency, retrieve it from the Python Package Index (PyPI) using `pip` or `poetry`.

```sh
pip install pandera_alchemy
```

or 

```sh
poetry add pandera_alchemy
```

### Local Development

If you want to contribute to the development of `pandera_alchemy`, you can clone the repository and set up a local development environment.


Clone the repository:
```sh
git clone https://github.com/TCRichards/pandera-alchemy.git
```

Change into the project directory:
```sh
cd pandera-alchemy
```


Create a virtual environment and install dependencies with `poetry`:
```sh
poetry install
```


# License

This project is licensed under the MIT License. See the [LICENSE](./LICENSE) file for details.
spherinator 0.4.0
Rotation-Invariant Hyperspherical Variational Convolutional Autoencoder
Requires Python: <4.0,>=3.10

[![Build Status](https://github.com/HITS-AIN/Spherinator/actions/workflows/python-package.yml/badge.svg?branch=main)](https://github.com/HITS-AIN/Spherinator/actions/workflows/python-package.yml?branch=main)
[![Documentation Status](https://readthedocs.org/projects/spherinator/badge/?version=latest)](https://spherinator.readthedocs.io/en/latest/?badge=latest)
![versions](https://img.shields.io/badge/python-3.10%20%7C%203.11%20%7C%203.12%20%7C%203.13-blue)

# Spherinator

[Spherinator](https://github.com/HITS-AIN/Spherinator) and
[HiPSter](https://github.com/HITS-AIN/HiPSter) are tools that provide explorative access
and visualization for multimodal data from extremely large astrophysical datasets, ranging from
exascale cosmological simulations to multi-billion object observational galaxy surveys.

A variational autoencoder (VAE) will be trained using
[PyTorch Lightning](https://lightning.ai/docs/pytorch/stable/)
to compress the structural data into a low-dimensional spherical latent space.


<p align="center">
  <img src="docs/assets/P404_f2.png" width="400" height="400">
</p>


## Installation

```bash
pip install spherinator
```

## Documentation

[Read The Docs](https://spherinator.readthedocs.io/en/latest/index.html)


## Acknowledgments

Funded by the European Union. This work has received funding from the European High-Performance Computing Joint Undertaking (JU) and Belgium, Czech Republic, France, Germany, Greece, Italy, Norway, and Spain under grant agreement No 101093441.

Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European High Performance Computing Joint Undertaking (JU) and Belgium, Czech Republic, France, Germany, Greece, Italy, Norway, and Spain. Neither the European Union nor the granting authority can be held responsible for them.


## License

This project is licensed under the [Apache-2.0 License](http://www.apache.org/licenses/LICENSE-2.0).


## Citation

If you use Spherinator in your research, we provide a [citation](./CITATION.cff) to use:

```bibtex
@article{Polsterer_Spherinator_and_HiPSter_2024,
author = {Polsterer, Kai Lars and Doser, Bernd and Fehlner, Andreas and Trujillo-Gomez, Sebastian},
title = {{Spherinator and HiPSter: Representation Learning for Unbiased Knowledge Discovery from Simulations}},
url = {https://arxiv.org/abs/2406.03810},
doi = {10.48550/arXiv.2406.03810},
year = {2024}
}
```
audioarxiv 0.1.2rc84.post1
Turn arXiv papers into audio. audioarxiv lets you fetch the research papers from arXiv and read them aloud.
Requires Python: >=3.9

# 🎧 audioarxiv

[![PyPI version](https://badge.fury.io/py/audioarxiv.svg)](https://pypi.org/project/audioarxiv/)
[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE)
[![Build](https://img.shields.io/github/actions/workflow/status/isaac-cf-wong/audioarxiv/CI.yml?branch=main)](https://github.com/isaac-cf-wong/audioarxiv/actions)
[![codecov](https://codecov.io/gh/isaac-cf-wong/audioarxiv/branch/main/graph/badge.svg)](https://codecov.io/gh/isaac-cf-wong/audioarxiv)
[![Python Version](https://img.shields.io/pypi/pyversions/audioarxiv)](https://pypi.org/project/audioarxiv/)
[![Security: bandit](https://img.shields.io/badge/security-bandit-yellow.svg)](https://github.com/PyCQA/bandit)
[![Documentation Status](https://img.shields.io/badge/documentation-online-brightgreen)](https://isaac-cf-wong.github.io/audioarxiv/)
[![DOI](https://zenodo.org/badge/956387048.svg)](https://doi.org/10.5281/zenodo.15251111)

📚 **Documentation**: [https://isaac-cf-wong.github.io/audioarxiv/](https://isaac-cf-wong.github.io/audioarxiv/)

**Turn arXiv papers into audio.**
`audioarxiv` lets you fetch the research papers from arXiv and read them aloud.

---

## 🚀 Features

- 🔍 Search and retrieve papers using the arXiv API
- 📄 Extract and parse the content from PDF (excluding title/abstract)
- 🗣️ Convert text to speech with natural voice output
- 🧠 Great for passive learning while commuting or doing chores

---

## 📦 Installation

Install from [PyPI](https://pypi.org/project/audioarxiv/):

```bash
pip install audioarxiv
```

---

## 🛠 Usage

```bash
audioarxiv --id "<arxiv id>"
```

### 🎙️ Text-to-Speech Options

You can customize the voice engine using `pyttsx3` by specifying the speaking rate, volume, voice, and pause between sentences.

```bash
audioarxiv --id "<arxiv id>" --rate <rate> --volume <volume> --voice "<voice>" --pause-seconds <pause-seconds>
```

- `rate`: Number of words per minutes. Defaults to 140.
- `volume`: Volume of the audio. Defaults to 0.9.
- `voice`: Voice of the audio. Defaults to the pyttsx3 default voice.
- `pause-seconds`: Number of seconds to pause between sentences.

The settings are saved, so you only need to provide your preferred settings once.

## Contributing

Contributions and suggestions are welcome! Whether it's fixing bugs, improving documentation, or adding new features, your help is appreciated.

Please read our [Code of Conduct](CODE_OF_CONDUCT.md) before contributing.

To get started:

- Fork the repository
- Create a new branch for your changes
- Submit a pull request

If you're unsure where to begin, feel free to open an issue or ask for guidance!
photography 2025.6.4
A CLI for managing a photo library.
Requires Python: >=3.12
Keywords: images, photography, photos, self-hosting

===============
``photography``
===============

|PyPI| |CI|

.. |PyPI| image:: https://img.shields.io/pypi/v/photography.svg
  :alt: PyPI version
  :target: https://pypi.org/project/photography/

.. |CI| image:: https://github.com/Julian/photography-cli/workflows/CI/badge.svg
  :alt: Build status
  :target: https://github.com/Julian/photography-cli/actions?query=workflow%3ACI

A command line tool for importing to and managing a photography library.
chatmcp-cli 1.1.1
ChatMCP CLI - AI pair programming with MCP server integration
Requires Python: <3.14,>=3.10

# ChatMCP CLI - your personal coding assistant!

Install with:
```bash
pip install chatmcp-cli
# or via Homebrew
brew install soulful-ai/tap/chatmcp-cli
```

Use with:
```bash
chatmcp --help
aider --help  # Legacy compatibility
```
text-select 0.0.1
Returns the text that you select in a textbox
Requires Python: >=3.7

# streamlit-custom-component

Streamlit component that allows you to do X

## Installation instructions

```sh
pip install streamlit-custom-component
```

## Usage instructions

```python
import streamlit as st

from my_component import my_component

value = my_component()

st.write(value)
```
jupyter-utility-widgets 0.0.7
Assortment of reusable common jupyter widget patterns

# python-utility

This project is an assortment of random composite widgets,
Seeing I have been using a few widgets "patterns" over and over,
I have decided to pack and share them in a convenient package.

## Installation

`pip install jupyter-utility-widgets`

requires jupyterlab installation.

## Widgets

1. Index Selector
    A simple combination of widgets that help exploring a list of options.  
    see `examples/index_selector.ipynb`
2. File Selector
    A combination of widgets that help exploring the file system
    see `examples/file_selector.ipynb`
3. Spectrogram Viewer
    A class for viewing spectrogram of data, with a simultaneous zoomed view.
    see `examples/spectrogram.ipynb`
4. Numerical Output
    A widget for inputing numerical values e.g. 1, 0.3333, 4/5
    seee `examples/numerical_input.ipynb`
c-apidocs 1.0.0
API Documentation Utilities
Requires Python: >=3.8

c-apidocs
=========

API Documentation Utilities

This project provides utilities to generate API documentation for C libraries,
as well as project documentation.

### Project

 * **Website**: <https://c-util.github.io/c-apidocs>
 * **Bug Tracker**: <https://github.com/c-util/c-apidocs/issues>

### Requirements

The requirements for this project are:

 * `hawkmoth >= 0.20`
 * `python >= 3.8`

### Repository:

 - **web**:   <https://github.com/c-util/c-apidocs>
 - **https**: `https://github.com/c-util/c-apidocs.git`
 - **ssh**:   `git@github.com:c-util/c-apidocs.git`

### License:

 - **Apache-2.0** OR **LGPL-2.1-or-later**
 - See AUTHORS file for details.