semvec/pypi-packages huggingface dataset:
ultravox-client 0.1.0
Python client SDK for Ultravox.
Requires Python: <4,>=3.10
Keywords: ultravox, audio, realtime, artificial intelligence

# Ultravox client SDK for Python
Python client SDK for [Ultravox](https://ultravox.ai).

[![pypi-v](https://img.shields.io/pypi/v/ultravox-client.svg?label=ultravox-client&color=orange)](https://pypi.org/project/ultravox-client/)

## Getting started

```bash
pip install ultravox-client
```

## Usage

```python
import asyncio
import signal

import ultravox_client as uv

session = uv.UltravoxSession()
done = asyncio.Event()

@session.on("status")
def on_status():
    if session.status == uv.UltravoxSessionStatus.DISCONNECTED:
        done.set()

await session.join_call(os.getenv("JOIN_URL", None))
loop = asyncio.get_running_loop()
loop.add_signal_handler(signal.SIGINT, lambda: done.set())
loop.add_signal_handler(signal.SIGTERM, lambda: done.set())
await done.wait()
await session.leave_call()
```

See the included example app for a more complete example. To get a `joinUrl`, you'll want to integrate your server with the [Ultravox REST API](https://fixie-ai.github.io/ultradox/).
franc 0.3.2
Evaluation framework for noise mitigation methods and implementations of different static and adaptive filtering techniques.
Requires Python: <3.14,>=3.10
Keywords: LeastMeanSquares, Wiener filter, filtering, noise cancellation, prediction

# FraNC - Framework for Noise Cancellation in gravitational wave detection

![Test status](https://github.com/NewtonianNoise/franc/actions/workflows/testing.yml/badge.svg)
![Linting status](https://github.com/NewtonianNoise/franc/actions/workflows/pylint.yml/badge.svg)
![Static type check status](https://github.com/NewtonianNoise/franc/actions/workflows/mypy.yml/badge.svg)

A framework to develop and evaluate noise cancellation techniques.
Includes python implementations of different static and adaptive filtering techniques.
The techniques for the prediction of a correlated signal component from witness signals provide a unified interface.

[Documentation](https://franc.readthedocs.io/en/latest/)

## Install

From pypi: `pip install franc`

From repository: `pip install .`

From repository (editable): `pip install hatchling ninja && make ie`

## License

Copyright (C) 2025  Tim J. Kuhlbusch et al.

```
    This program is free software: you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
    the Free Software Foundation, either version 3 of the License, or
    (at your option) any later version.

    This program is distributed in the hope that it will be useful,
    but WITHOUT ANY WARRANTY; without even the implied warranty of
    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
    GNU General Public License for more details.

    You should have received a copy of the GNU General Public License
    along with this program.  If not, see <https://www.gnu.org/licenses/>.
```
number-words-converter 0.1.0
Convert numbers to words and words to numbers
Requires Python: >=3.6

# Number Words Converter

A simple Python library for converting numbers to words and words to numbers.

## Installation
```bash
pip install number-words-converter
```

## Usage
```python
from number_words import number_to_words, words_to_number

# Convert number to words
print(number_to_words(342))  # "three hundred forty two"

# Convert words to number
print(words_to_number("three hundred forty two"))  # 342
```

## Features

- Convert integers to their word representation
- Convert word representation back to integers
- Support for numbers up to billions
- Simple and intuitive API

## Examples
```python
from number_words import number_to_words, words_to_number

# Numbers to words
print(number_to_words(0))           # "zero"
print(number_to_words(15))          # "fifteen"
print(number_to_words(99))          # "ninety nine"
print(number_to_words(1000))        # "one thousand"
print(number_to_words(123456))      # "one hundred twenty three thousand four hundred fifty six"
print(number_to_words(1000000))     # "one million"
print(number_to_words(5000000000))  # "five billion"

# Words to numbers
print(words_to_number("nine hundred"))              # 900
print(words_to_number("two million"))               # 2000000
print(words_to_number("five billion"))              # 5000000000
print(words_to_number("three hundred forty two"))   # 342
```

## License

MIT License
pixelemon 0.7.0
Citra's basic image processing package
Requires Python: <3.13,>=3.9

# pixelemon

Citra's Python plate solver using Tetra3 via cedar-solve.

## Features

- Define and configure telescope sensors and optics
- Load and process FITS images
- Plate solve images using Tetra3

## Installation

Install via pip (requires Python 3.9+ and <3.13):

```bash
pip install pixelemon
```

Or for development:

```bash
git clone https://github.com/citra-space/pixelemon.git
cd pixelemon
pip install -e '.[dev]'
```

## Example Usage

```python
from pathlib import Path
from pixelemon.sensors import IMX174
from pixelemon.optics import WilliamsMiniCat51
from pixelemon import Telescope, TelescopeImage, TetraSolver

TetraSolver.high_memory() # IMPORTANT <----

sensor = IMX174()
optical_assembly = WilliamsMiniCat51()
telescope = Telescope(sensor=sensor, optics=optical_assembly)

img_path = Path("./local/2025-10-17-021315.fits")
image = TelescopeImage.from_fits_file(img_path, telescope)

image.crop(10.0) # optional
solve = image.plate_solve
```

## Requirements

- Python 3.9+
- [pydantic](https://pydantic-docs.helpmanual.io/)
- [cedar-solve](https://github.com/citra-space/cedar-solve)
- [sep](https://github.com/kbarbary/sep)
- [astropy](https://www.astropy.org/)

## License

MIT

## Authors

- Brandon Sexton <brandon@citra.space>