semvec/pypi-packages huggingface dataset:
gamest 4.1.8
Tracks game play time.

# Gamest

Gamest is a tool for keeping a record of time spent playing video games.

## Installation

Use pip to install gamest:

```
pip install gamest
```

Gamest may be launched by calling `gamest` from the command line. The executable
`gamest.exe` is located in python's `Scripts` folder, so a shortcut may be
placed wherever is convenient.

## Configuration

Out of the box, gamest will track runtime of desired apps. To add an app to be
tracked, start the app, then click 'Pick Game`, choose the app from the list,
and click 'Pick Game' to select it. In most cases, no advanced settings will be
required, so click 'Add Game' to finish adding the app to the database. In the
future, the app will be automatically detected whenever it is running.

Gamest may be configured by clicking the 'Settings' button on the program
window. Any installed plugins may be configured in the same way.

## License

Copyright (C) 2018  Tracy Poff

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.

## Credits

* Icon: clipboard by Naveen from the Noun Project
py-research 5.1.3
Collection of utilities for R&D coding in Python 🐍
Requires Python: <3.14,>=3.11

# py-research

[![PyPI - Version](https://img.shields.io/pypi/v/py-research)](https://pypi.org/project/py-research)
[![Docs](https://github.com/cloudlane-one/py-research/actions/workflows/docs.yml/badge.svg)](https://cloudlane-one.github.io/py-research)
[![Tests](https://github.com/cloudlane-one/py-research/actions/workflows/lint-and-test.yml/badge.svg)](https://github.com/cloudlane-one/py-research/actions/workflows/lint-and-test.yml)
[![Build](https://github.com/cloudlane-one/py-research/actions/workflows/release.yml/badge.svg)](https://github.com/cloudlane-one/py-research/actions/workflows/release.yml)
[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
[![Black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![Codecov](https://codecov.io/gh/cloudlane-one/py-research/graph/badge.svg?token=J8GLAWTPWX)](https://codecov.io/gh/cloudlane-one/py-research)
[![CodeFactor](https://www.codefactor.io/repository/github/cloudlane-one/py-research/badge)](https://www.codefactor.io/repository/github/cloudlane-one/py-research)
[![CodeClimate Maintainability](https://api.codeclimate.com/v1/badges/4cc310489b325e793d1d/maintainability)](https://codeclimate.com/github/cloudlane-one/py-research/maintainability)

## About this project

This repository is a collection of Python utilities to help you analyze & visualize data, automate workflows and manage knowledge while working in an interdisciplinary R&D project. More precisely, it serves these main puposes:

1. Extend existing, well-established packages (e.g. pandas, numpy sqlalchemy, structlog, ...) with small helper functions and abstractions to provide lacking functionality or make them easier to use & automate.
2. Enforce best practices on scientific code to make it more reliable, quick to deploy, and easy to monitor.
3. Provide a framework for knowledge and information management backed by different data sources and databases, to which analysis / dataviz functions can tie in seamlessly.

## Current status

This project is actively maintained, but still under construction. The modules in their current form are working and continuously tested, but documentation is still minimal and many components of the framework are not yet implemented. Release versioning follows the [Semver Spec](https://semver.org/), so breaking changes in existing API will only happen with major version upgrades, of which there are expected to be a few before the framework is complete.

Furthermore, some of the current functionality may be outsourced into a separate repo and package with these upgrades.

## How to install

`py-research` is available as a Python package on PyPI:

```bash
pip install py-research
```

Alternatively, you can install it directly from git via:

```bash
pip install git+https://github.com/cloudlane-one/py-research.git
```

## Contents

```{toctree}
docs/ref-api/index
```

## Indices and Tables

- {ref}`genindex`
- {ref}`modindex`
- {ref}`search`
allyin 0.1.4
Allyin: Modular AI tools for enterprise data processing
Requires Python: >=3.8



# Allyin Libraries

Multimodal2text is a Python library that extracts text from various file formats including PDFs, DOCX, XLSX, PPTX, images, HTML, and audio.

## Installation

First, ensure that `openai-whisper` is installed (used for audio transcription):

```bash
pip install git+https://github.com/openai/whisper.git
```

Then install Allyin:

```bash
pip install allyin
```

> Note: You may need to install system dependencies like `ffmpeg` for Whisper and `tesseract` for OCR.

## Usage

### Import

```python
from allyin.multimodal2text import extract_text
```

### Supported File Types

| Format      | Description               |
|-------------|---------------------------|
| `.pdf`      | Extracts text from PDFs   |
| `.docx`     | Extracts text from Word   |
| `.xlsx`     | Extracts text from Excel  |
| `.pptx`     | Extracts text from Slides |
| `.png/jpg`  | OCR-based text extraction |
| `.html`     | Extracts visible content  |
| `.mp3/.wav` | Transcribes audio         |

### Example

```python
from allyin.multimodal2text import extract_text

result = extract_text("/path/to/your/file.pdf")
print(result["text"])
```

## License

MIT