semvec/pypi-packages huggingface dataset:
text-extensions-for-pandas 0.2.2
Natural language processing support for Pandas dataframes.
Requires Python: >=3.7

<!-- Package description for PyPI -->

Natural language processing support for Pandas DataFrames.

[![Documentation Status](https://readthedocs.org/projects/text-extensions-for-pandas/badge/?version=latest)](https://text-extensions-for-pandas.readthedocs.io/en/latest/?badge=latest)


Text Extensions for Pandas adds [extension types](https://pandas.pydata.org/docs/development/extending.html) to Pandas DataFrames for representing natural
language data, plus a library of functions for working with these extension
types.

## Features

### SpanArray: A Pandas extension type for *spans* of text

* Connect features with regions of a document
* Visualize the internal data of your NLP application
* Analyze the accuracy of your models
* Combine the results of multiple models

### TensorArray: A Pandas extension type for tensors

* Represent BERT embeddings in a Pandas series
* Store logits and other feature vectors in a Pandas series
* Store an entire time series in each cell of a Pandas series

### Pandas front-ends for popular NLP toolkits

* [SpaCy](https://spacy.io/)
* [Transformers](https://github.com/huggingface/transformers)
* [IBM Watson Natural Language Understanding](https://www.ibm.com/cloud/watson-natural-language-understanding)
* [IBM Watson Discovry Table Understanding](https://cloud.ibm.com/docs/discovery-data?topic=discovery-data-understanding_tables)

## Documentation

For examples of how to use the library, take a look at the notebooks in 
[this directory](https://github.com/CODAIT/text-extensions-for-pandas/tree/master/notebooks).

API documentation can be found at [https://text-extensions-for-pandas.readthedocs.io/en/latest/](https://text-extensions-for-pandas.readthedocs.io/en/latest/)

## Source Code

The source code for Text Extensions for Pandas is available at [https://github.com/CODAIT/text-extensions-for-pandas](https://github.com/CODAIT/text-extensions-for-pandas).

We welcome code and documentation contributions!  See the [README file](https://github.com/CODAIT/text-extensions-for-pandas/blob/master/README.md#contributing) 
for more information on contributing.
comicbot-api 0.1.19
A client to retrieve new releases of comic books, filterable by publisher and format.
Requires Python: <4.0,>=3.9

# ComicBot API
<img width="75" src="https://img.shields.io/badge/python-3670A0?style=for-the-badge&logo=python&logoColor=ffdd54"></img>
<img width="90" src="https://img.shields.io/pypi/v/comicbot-api"></img>
<img width="55" src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json"></img>



![](./docs/images/fortress-of-solitude.jpeg)
<!-- TOC -->
* [ComicBot API](#comicbot-api)
  * [Requirements](#requirements)
* [Project Expectations](#project-expectations)
  * [How to get started](#how-to-get-started)
    * [Create a virtual environment](#create-a-virtual-environment)
    * [Enter virtual environment](#enter-virtual-environment)
    * [Install Poetry, the package manager for this project](#install-poetry-the-package-manager-for-this-project)
    * [Build distribution of project](#build-distribution-of-project)
    * [Running Unit Tests](#running-unit-tests)
      * [Pytest to run all unit tests in `test/`](#pytest-to-run-all-unit-tests-in-test)
    * [Pytest to run all unit tests and lint code with `Pylama`](#pytest-to-run-all-unit-tests-and-lint-code-with-pylama)
    * [Linting](#linting)
    * [Deployment](#deployment-)
  * [Roadmap](#roadmap)
<!-- TOC -->

## Requirements
- Python 3.9 or above
- Virtualenv 20.14.1 or above

# Project Expectations
- Client library to get new releases, or releases for a given date. 
- Client can filter by the format of releases e.g. 'single-issue' or by publisher e.g. 'marvel'
- Client should be straight forward and easy to use by using the KISS model (Keep It Simple Stupid)
- Cache results where possible as not to hit provider with too many requests for the same data

## How to get started
### Create a virtual environment
```bash
virtualenv -p python3.9 venv
```

### Enter virtual environment
```bash
source venv/bin/activate
```

### Install Poetry, the package manager for this project
```bash
pip install poetry
```

### Build distribution of project
```bash
poetry build
```
Build artifacts will be located in `dist/`
### Running Unit Tests
#### Pytest to run all unit tests in `test/`
```bash
pytest
```

### Pytest to run all unit tests and lint code with `Pylama`
```bash
pytest --pylama
```

### Linting
This project strives to keep the code style in line with [PEP8](https://peps.python.org/pep-0008/).
To test the project for compliance with PEP8, I use [Ruff](https://github.com/astral-sh/ruff)
```bash
ruff check
```

### Deployment
Github actions auto creates and pushes releases to PyPi on creating a tag/release.
#### Manual
To deploy, one must obtain an API key from the public pypi (https://pypi.org/project/comicbot-api/)
and add it to the local `poetry` configuration with the following command:
```bash
poetry config pypi-token.pypi <pypi-token>
```
Once we have a valid token, we can push distributions to PyPi. 
```bash
poetry build
poertry publish
```
or do both with
```bash
poetry publish --build
```
***
## Roadmap
- [ ] Database to cache results from source
- [ ] Sphinx Automatic Documentation Creation
django-starter-toolkit 0.1.0
Un toolkit con utilidades y helpers para Django, que incluye formularios, funciones JS y utilidades generales.

# django-starter-toolkit

## Descripción

**django-starter-toolkit** es un paquete de utilidades para proyectos Django que te ayuda a acelerar el desarrollo al incluir:

- **Formularios Mejorados**: Mixins y clases base (como `BootstrapFieldsMixin`, `BaseForm` y `ModelBaseForm`) que integran automáticamente estilos de Bootstrap y validaciones en tus formularios.
- **Funciones Utilitarias**: Helpers y funciones comunes para facilitar tareas recurrentes en Django (definidas en `utils.py`).
- **Recursos JavaScript**: Un archivo `functions.js` con funcionalidades para tooltips, peticiones AJAX con manejo de CSRF, manejo de formularios modales, entre otros, que podrás incluir fácilmente en tus templates.

## Características

- **Formularios Dinámicos**: Configuración automática de campos en formularios Django.
- **Helpers Generales**: Funciones útiles para mejorar la eficiencia en tareas diarias.
- **Integración de JS**: Archivo JavaScript listo para ser usado en tus proyectos, facilitando interacciones y mejoras en la UI.

## Instalación

Instala el paquete mediante pip:

```bash
pip install django-starter-toolkit
word-by-word-captions 1.0.0
Generate synchronized word-by-word captions for videos using WhisperX timestamps
Requires Python: >=3.8
Keywords: captions, video, whisperx, subtitles

# Word-By-Word Captions (wbw-captions)

A Python tool to generate synchronized one-word captions for videos using word-level timestamps from WhisperX.

## Overview

WBW takes WhisperX's word-level timestamp JSON output and creates visually appealing videos with synchronized one-word captions.

The JSON file generated by [WhisperX](https://github.com/m-bain/whisperX) with the high-precision word-level timestamps is required as input.

## Installation

```bash
pip install word-by-word-captions
```

## Dependencies

- ffmpeg (for video processing)

## Usage

### 1. Generate Word-level Timestamps

First, use WhisperX to generate word-level timestamps for your audio/video:

```bash
# Install WhisperX
pip install git+https://github.com/m-bain/whisperX.git

# Generate word-level timestamps
whisperx <audio.wav> --hf_token <your-token> --vad_method silero --language <lang> --model <model> --align_model <align_model>
```

This will create a JSON file with precise word timings.

### 2. Create Captioned Video

```bash
# Add captions to an existing video
wbw-captions -v input_video.mp4 -j whisperx_output.json -o output.mp4
```

Options:
- `-v, --video`: Input video file (optional)
- `-j, --json`: WhisperX JSON output file (required)
- `-o, --output`: Output video file path (required)
- `--max_lines`: Maximum number of lines per subtitle (default: 1)
- `--max_line_chars`: Maximum characters per line (default: 40)

## Example Output

The tool creates videos where:
- Each word is highlighted in yellow as it's spoken
- Words are synchronized with precise timing from WhisperX
- Text is easily readable with proper contrast and outlines
- Captions are positioned at the bottom with proper margins

## Development

To set up the development environment:

1. Clone the repository
2. Install development dependencies:
   ```bash
   pip install -e ".[dev]"
   ```
3. Run tests:
   ```bash
   pytest
   ```

## License

MIT License
pipeline-logging 0.1.0
Inject logging formatter for Azure and GitHub pipelines
Requires Python: >=3.9
Keywords: ADO, Azure, GitHub, pipeline

# logging_pipeline

Python module to inject logging handler for printing message in the format captured by pipeline.

Install with:

```bash
pip install logging_pipeline
```

If logging is imported a handler is added to the root logger to print the error and warning messages
in addition with a format recognized by the pipeline environment executing the script. If the script
is executed outside a pipeline nothing is printed. Supported pipelines are:

- Azure pipelines
- GitHub actions

## Compatibility

`logging_pipeline` uses a live-patching system to target the `logging` library and add a handler.

## PyInstaller

The method used to automatically adding a logging handler relies on a .pth file script that python
loads at startup. This method does not work when a python application is bundled into an executable
with PyInstaller (or similar).
If you want to use this tool in an application built with PyInstaller it will need to be manually
enabled in your application.
This can be done by adding the following line to the top of your main application script:

```python
import logging_pipeline.wrapt_logging
```

This must be run before logging is imported.

## Acknowledgements

The method of patching at runtime is built from the [pip_system_certs](https://pypi.org/project/pip-system-certs/)
module.