semvec/pypi-packages huggingface dataset:
spatula 1.0.0
A modern Python library for writing maintainable web scrapers.
License: MIT
Requires Python: >=3.8

# Overview

*spatula* is a modern Python library for writing maintainable web scrapers.

**Please note, the official repository has changed to Codeberg; GitHub will only be used as a mirror.**

Source: [https://codeberg.org/jpt/spatula/](https://codeberg.org/jpt/spatula/)

Documentation: [https://jamesturk.github.io/spatula/](https://jamesturk.github.io/spatula/)

Issues: [https://codeberg.org/jpt/spatula/issues](https://codeberg.org/jpt/spatula/issues)

[![PyPI badge](https://badge.fury.io/py/spatula.svg)](https://badge.fury.io/py/spatula)

## Features

- **Page-oriented design**: Encourages writing understandable & maintainable scrapers.
- **Not Just HTML**: Provides built in [handlers for common data formats](https://jamesturk.github.io/spatula/reference/#pages) including CSV, JSON, XML, PDF, and Excel.  Or write your own.
- **Fast HTML parsing**: Uses `lxml.html` for fast, consistent, and reliable parsing of HTML.
- **Flexible Data Model Support**: Compatible with `dataclasses`, `attrs`, `pydantic`, or bring your own data model classes for storing & validating your scraped data.
- **CLI Tools**: Offers several [CLI utilities](https://jamesturk.github.io/spatula/cli/) that can help streamline development & testing cycle.
- **Fully Typed**: Makes full use of Python 3 type annotations.
LinearRegression-pkg-kaid 0.1
A simple linear regression model implemented from scratch.
License: MIT
Requires Python: >=3.6

# LinearRegression_pkg

`LinearRegression_pkg` is a Python library for Linear Regression

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install `package_name`.

```bash
pip install LinearRegression_pkg
```

## Usage

```python
import LinearRegression

#
LinearRegression.fit(epochs , lr)

# returns prediction for inp
LinearRegression.predict(inp)

# returns 'phenomenon'
LinearRegression.module_name('phenomena')
```

## License

[MIT](https://choosealicense.com/licenses/mit/)
HerdCats 0.1.5
A tool for exploring open data sources.
License: MIT
Requires Python: <4.0,>=3.11
Keywords: open data, data catalogues, datastores, ckan, open datasoft

# HerdingCATs 🐈‍⬛

[![codecov](https://codecov.io/gh/CHRISCARLON/Herding-CATs/graph/badge.svg?token=Y9Z0QA39S3)](https://codecov.io/gh/CHRISCARLON/Herding-CATs)

[Documentation](https://herdingcats.dev)📚

> [!NOTE]
> Version 0.1.5 PyPi is now available .
>
> HerdingCATs is currently under active development.
>
> Features may change as the project evolves.

---

**The aim of this project is simple...**

Speed up how data analysts explore and interact with open data sources.

- Navigate the open data ecosystem
- Find the data that you need
- Get that data into a format and/or location for further analysis

**Install Commands:**

```bash
pip install HerdCats
```

or

```bash
poetry add HerdCats
```

or

```bash
uv add HerdCats
```

---

## Contributing

Contributions are welcome! Please feel free to submit a PR.

For major changes, please open an issue first to discuss what you would like to change.
airfoilplotter 0.0.1
A Python library for generating and plotting NACA airfoils (4-, 5-, 6-, and 7-series).
License: MIT
Requires Python: >=3.8

# airfoilplotter

A Python library for generating and plotting NACA airfoils (4, 5, 6, and 7 series).

## ✈️ Features
- Generate NACA 4, 5, 6, and 7 series airfoil coordinates
- Plot airfoil shape with Matplotlib
- Lightweight and easy to use

## 📦 Installation

# How to Use Library

# Example 1: NACA 4-series

# Unsymmetric airfoil (NACA 2412)
from airfoilplotter import naca4, plot_airfoil
xu, yu, xl, yl = naca4(0.02, 0.4, 0.12, symmetric=False)
plot_airfoil(xu, yu, xl, yl, "NACA 2412 (Unsymmetric)")

# Symmetric airfoil (NACA 0012)
xu, yu, xl, yl = naca4(0, 0, 0.12, symmetric=True)
plot_airfoil(xu, yu, xl, yl, "NACA 0012 (Symmetric)")

# Example 2: NACA 5-series
from airfoilplotter import naca5, plot_airfoil
xu, yu, xl, yl = naca5(0.3, 0.4, 0.12)
plot_airfoil(xu, yu, xl, yl, "NACA 5-Series Airfoil")

# Example 3: NACA 6-series
from airfoilplotter import naca6, plot_airfoil
xu, yu, xl, yl = naca6(0.3, 0.12)
plot_airfoil(xu, yu, xl, yl, "NACA 6-Series Airfoil")

# Example 4: NACA 7-series
from airfoilplotter import naca7, plot_airfoil
xu, yu, xl, yl = naca7(0.3, 0.12)
plot_airfoil(xu, yu, xl, yl, "NACA 7-Series Airfoil")