semvec/pypi-packages huggingface dataset:
mkdocstrings-shell 1.0.4
A shell scripts/libraries handler for mkdocstrings.
Requires Python: >=3.9

# mkdocstrings-shell

[![ci](https://github.com/mkdocstrings/shell/workflows/ci/badge.svg)](https://github.com/mkdocstrings/shell/actions?query=workflow%3Aci)
[![documentation](https://img.shields.io/badge/docs-mkdocs-708FCC.svg?style=flat)](https://mkdocstrings.github.io/shell/)
[![pypi version](https://img.shields.io/pypi/v/mkdocstrings-shell.svg)](https://pypi.org/project/mkdocstrings-shell/)
[![gitter](https://badges.gitter.im/join%20chat.svg)](https://app.gitter.im/#/room/#shell:gitter.im)

A shell scripts/libraries handler for mkdocstrings.
It uses [Shellman](https://github.com/pawamoy/shellman)
to collect documentation from shell scripts.

## Installation

```bash
pip install mkdocstrings-shell
```

## Configuration

In MkDocs configuration file:

```yaml title="mkdocs.yml"
plugins:
- mkdocstrings:
    default_handler: shell  # optional
```

The handler does not offer any option yet.

## Usage

Use *mkdocstrings* syntax to inject documentation for a script:

```md
::: relative/path/to/script
    handler: shell  
```

Specifying `handler: shell` is optional if you declared `shell`
as default handler in mkdocs.yml.
fairfru 1.9.2
A bias measure based on the fuzzy rough set theory
Requires Python: >=3.8

# Using fuzzy-rough sets to measure bias in pattern classification problems

This python package contains a bias metric based on the paper *"A fuzzy-rough uncertainty measure to discover bias encoded explicitly or implicitly in features of structured pattern classification datasets"* ([Link to publication](https://doi.org/10.1016/j.patrec.2022.01.005)). 

This bias metric measures the extent to which a feature in a dataset influences the outcome variable.  

fairfru ([see here](https://pypi.org/project/FairFRU/)) is a Python package providing algorithms able to quantify fairness in automated decision making using the fuzzy-rough set theory. 

## Installation
Use the package manager [pip](https://pip.pypa.io/en/stable/) to install FairFRU.

```bash
pip install fairfru
```
## Usage
```python
import fairfru
```

See the `Measuring_bias.ipynb` file for an example of how to use this approach.

## Contributing

Pull requests are welcome. For major changes, please open an issue first
to discuss what you would like to change.

## License

[MIT](https://choosealicense.com/licenses/mit/)
gimmie 0.1.0
A tool to download files from a list of URLs
Requires Python: >=3.7

# Gimmie

A simple command-line tool to download files from a list of URLs.

<!-- header-logo-start -->
<div align="center">
  <a href="https://github.com/laywill/gimmie" target="blank" title="Get Gimmie">
    <img src="https://github.com/laywill/gimmie/raw/main/docs/assets/images/gimmie_logo_1x1.jpeg" alt="Gimmie Logo" min-height="200px">
  </a>
</div>
<!-- header-logo-end -->

## Description

Gimmie ("Give me your files") is a lightweight utility that downloads files from a list of web addresses. Simply provide a text file with one URL per line, and Gimmie will handle the rest.

## Features

- Downloads files from multiple URLs in sequence
- Extracts filenames automatically from URLs
- Supports any file type available via HTTP/HTTPS
- Handles errors gracefully, continuing to the next file if one fails
- Option to specify a custom download directory

## Installation

### Requirements

- Python 3.7 or higher
- `pip` package manager

### From PyPI (Recommended)

```bash
pip install gimmie
```

### From Source

1. Clone the repository:

   ```bash
   git clone https://github.com/yourusername/gimmie.git
   cd gimmie
   ```

2. Install the package:

   ```bash
   pip install .
   ```

## Usage

### Basic Usage

1. Create a text file (e.g., `files-to-download.txt`) with one URL per line:

   ```plaintext
   https://example.com/file1.pdf
   https://example.com/file2.jpg
   https://example.com/file3.zip
   ```

2. Run Gimmie with the file as an argument:

   ```bash
   gimmie files-to-download.txt
   ```

3. Files will be downloaded to a `downloads` directory in your current working directory.

### Command-Line Options

```bash
gimmie [-h] [-d DIRECTORY] url_file
```

Arguments:

- `url_file`: Path to text file containing URLs (one per line)

Options:

- `-h, --help`: Show help message and exit
- `-d DIRECTORY, --directory DIRECTORY`: Directory to save downloaded files (default: downloads)

### Example

```bash
# Download files to a custom directory
gimmie files-to-download.txt -d my_files
```

## URL File Format

The URL file should contain one URL per line. The tool will:

- Strip whitespace from lines
- Skip empty lines and lines starting with '#' (for comments)

Example URL file:

```bash
# Files to download
https://example.com/file1.pdf
https://example.com/file2.jpg
https://example.com/file3.zip
```

## Development

### Setting Up Development Environment

1. Clone the repository
2. Create a virtual environment:

   ```bash
   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   ```

3. Install development dependencies:

   ```bash
   pip install -e ".[dev,test]"
   ```

### Running Tests

```bash
pytest
```

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (`git checkout -b feature/amazing-feature`)
3. Commit your changes (`git commit -m 'Add some amazing feature'`)
4. Push to the branch (`git push origin feature/amazing-feature`)
5. Open a Pull Request