semvec/pypi-packages huggingface dataset:
rgbconv 1.1
fast RGB image pixel format conversion module written in C

# NAME

rgbconv - Fast RGB image pixel format conversion module written in C

# DESCRIPTION

This manual page documents **rgbconv** module, a Python module for rapidly
converting image pixel format from BGRA (Blue, Green, Red, and Alpha) to RGBA
(Red, Green, Blue, and Alpha).

Different aplications/modules use different pixel formats for represenging
pixels in images and photos.  One of the most popular formats are 24-bit RGB
(8 bits each for red, green, and blue) and 32-bit RGBA (8 bits each for red,
green, blue, alpha).  Other formats include 32-bit BGRA (8 bits for blue,
green, red, and alpha) and 32-bit RGBX (8bits for red, gree, blue, and
unused).

**rgbconv** provides *bgra2rgba*, which rapidly converts from the BGRA format
to the RGBA format.  **rgbconv** is implemented in C language for achieving
the almost optimal performance.

# EXAMPLES

```
import rgbconv

img = b'01234567890abcdef'
rgbconv.bgra2rgba(img)
print(img)

```

# WARNING

**rgbconv** directly modifies a byte-like object in Python for the maximal
performance even if the object is immutable, which may cause problems.  Use
**rgbconv** module with caution.

# INSTALLATION

```python
pip3 install rgbconv
```

# AVAILABILITY

The latest version of **rgbconv** module is available at PyPI
(https://pypi.org/project/rgbconv) .

# SEE ALSO

# AUTHOR

Hiroyuki Ohsaki <ohsaki[atmark]lsnl.jp>
filmhub-python-api 1.1.4.post2
A Python API for controlling FilmHUB fast film delivery software

# filmhub-python-api
Official FilmHUB fast film delivery Python API

Complete Python API reference can be found [here](https://sites.google.com/filmhub.cloud/python-api/).


Please use freely!


Henrik Norin, HDR AB, 2019
FilmHUB - fast film delivery and pipeline sync
http://filmhubsoftware.com
cabot-alert-webhooks 0.1.0
A Webhook plugin for Cabot
Keywords: cabot,webhook,status check

==========================
Cabot Webhook Alert Plugin
==========================

A plugin for `Cabot`_ service monitoring that will post alerts to a URL.

The plugin will POST a payload like the following to a user-defined endpoint::

    {
      'service': 'my_service_name',
      'status': 'ERROR',
      'old_status': 'PASSING',
    }


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

Install from pip::

    $ pip install cabot-alert-webhook
    $ foreman stop

Edit `conf/*.env`::

    # add cabot_alert_webhook to your comma separated list
    CABOT_PLUGINS_ENABLED=cabot_alert_webhook

Run migrations and restart cabot::

    $ foreman run python manage.py migrate
    $ foreman start

.. _Cabot: https://cabotapp.com
pyiets 0.1.17
A tool for calculating inelastic tunneling spectra

Install with:

.. code-block:: bash

   ./install

The full documentation can be found under https://www.chemie.uni-hamburg.de/institute/ac/arbeitsgruppen/herrmann/software.html
The source files of the documentation can be found in `docs`. To build the documentation type:

.. code-block:: bash

   make documentation
vocalist 0.0.1.dev1
A package to convert speech to long-form work-flows, using plugable trained NLP models

# Vocalist

[![travis status](https://travis-ci.com/colinjlacy/vocalist.svg?branch=master "Travisstatus")](https://travis-ci.com/colinjlacy/vocalist)
[![Coverage Status](https://coveralls.io/repos/github/colinjlacy/vocalist/badge.svg?branch=master&service=github)](https://coveralls.io/github/colinjlacy/vocalist?branch=master&service=github)

This is a simple project still in very early development, meant to be used to parse speech into text.  In its current state, it only works on Mac, and only where a compatible version of [PortAudio](http://www.portaudio.com/) has been installed.

It was built following the tutorial found here: [https://realpython.com/python-speech-recognition/](https://realpython.com/python-speech-recognition/)

## Setup

Using Homebrew, install PortAudio:
```bash
$ brew install portaudio 
```

From there you can install dependencies as you normally would:
```bash
$ pip install -r requirements.txt
```

## Usage

If you want to call it directly just run the package as is:
```bash
$ python ./main.py
``` 

It's not currently deployed for package management.
big-num-format 0.4
A package to convert very large numbers into human readable text.

# big-num-format

big-num-format is a package which converts very large numbers into human readable text.

### Installation

Simply type the following in a command line to install the package:

`pip install big-num-format`

### Usage

Use the format_num() function to format numbers.

e.g.

```python
from big_num_format import *
format_num(123456789.55)
# '123 million, 456 thousand and 789.55'
format_num(1e50/3, shorten=True, precision=5, decimal_precision=10)
# '33QDe 333qDe 333TDe 333DDe 333.3359375UDe'
```