semvec/pypi-packages huggingface dataset:
liblab-petstore 1.0.0
A sample API that uses a petstore as an example to demonstrate features in the swagger-2.0 specification
Requires Python: >=3.7

# LiblabPetstore Python SDK 1.0.0

Welcome to the LiblabPetstore SDK documentation. This guide will help you get started with integrating and using the LiblabPetstore SDK in your project.

## Versions

- API version: `1.0.0`
- SDK version: `1.0.0`

## About the API

A sample API that uses a petstore as an example to demonstrate features in the swagger-2.0 specification

## Table of Contents

- [Setup & Configuration](#setup--configuration)
  - [Supported Language Versions](#supported-language-versions)
  - [Installation](#installation)
- [Setting a Custom Timeout](#setting-a-custom-timeout)
- [Sample Usage](#sample-usage)
- [Services](#services)
- [Models](#models)

## Setup & Configuration

### Supported Language Versions

This SDK is compatible with the following versions: `Python >= 3.7`

### Installation

To get started with the SDK, we recommend installing using `pip`:

```bash
pip install liblab_petstore
```

## Setting a Custom Timeout

You can set a custom timeout for the SDK's HTTP requests as follows:

```py
from liblab_petstore import LiblabPetstore

sdk = LiblabPetstore(timeout=10000)
```

# Sample Usage

Below is a comprehensive example demonstrating how to authenticate and call a simple endpoint:

```py
from liblab_petstore import LiblabPetstore, Environment

sdk = LiblabPetstore(
    base_url=Environment.DEFAULT.value,
    timeout=10000
)

result = sdk.pets.list_pets(limit=4)

print(result)

```

## Services

The SDK provides various services to interact with the API.

<details> 
<summary>Below is a list of all available services:</summary>

| Name |
| :--- |
| pets |

</details>

## Models

The SDK includes several models that represent the data structures used in API requests and responses. These models help in organizing and managing the data efficiently.

<details> 
<summary>Below is a list of all available models:</summary>

| Name   | Description |
| :----- | :---------- |
| Pet    |             |
| NewPet |             |

</details>
deltachat-chatbot 0.3.0
Conversational chat-bot for Delta Chat
Requires Python: >=3.8
Keywords: deltachat, bot, chatbot, ai

# ChatBot

[![Latest Release](https://img.shields.io/pypi/v/deltachat-chatbot.svg)](https://pypi.org/project/deltachat-chatbot)
[![CI](https://github.com/deltachat-bot/chatbot/actions/workflows/python-ci.yml/badge.svg)](https://github.com/deltachat-bot/chatbot/actions/workflows/python-ci.yml)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

Conversational chat-bot for Delta Chat, using GPT4All.

## Install

```sh
pip install deltachat-chatbot
```

## Usage

Configure the bot:

```sh
chatbot init bot@example.com PASSWORD
```

Start the bot:

```sh
chatbot serve
```

Run `chatbot --help` to see all available options.
pingze-classifier 0.11
A Python package for classifying Chinese characters based on the Pingshui rhyme scheme
Requires Python: >=3.6

# Ping-ze Classifier

**Ping-ze Classifier** is a Python package designed to classify Chinese characters as 'ping' (平) or 'ze' (仄) tonal patterns based on the [Pingshui Rhyme](https://zh.wikisource.org/wiki/%E5%B9%B3%E6%B0%B4%E9%9F%BB) (平水韻) rhyme scheme. You can read more about ping-ze, or tonal patterns, [here.](https://en.wikipedia.org/wiki/Tone_pattern) The package includes a pre-scraped JSON file that contains the complete data from the rhyme dictionary, and also provides a scraper to update the data if necessary.

## Features

- **Classify Chinese characters**: Easily classify characters as 'ping' or 'ze' based on the Pingshui Rhyme scheme.
- **Pre-packaged data**: Includes a pre-scraped JSON file with the complete rhyme data.
- **Scraper**: An optional scraper is included to regenerate the JSON file when the source data changes.

## Installation

You can install the package by running:

```bash
pip install pingze_classifier
```

## Usage

### Classifying Characters

Once installed, you can use the PingZeClassifier to classify Chinese characters based on the Pingshui Rhyme (平水韻) scheme:

```python
from pingze_classifier import PingZeClassifier

# Initialize the classifier (uses pre-packaged JSON by default)
classifier = PingZeClassifier()

# Classify a sentence
sentence = "知否？知否？應是綠肥紅瘦。"
result = classifier.classify(sentence)
print(result)
# Output: ['ping', 'ze', 'unknown', 'ping', 'ze', 'unknown', 'ping', 'ze', 'ze', 'ping', 'ping', 'ze', 'unknown']
```

### Scraping and Regenerating the JSON Data

The package includes a pre-generated JSON file, but if the Pingshui Rhyme source from wikisource changes you can run the scraper.

#### Running the Scraper

By default, the scraper won't run if the JSON file already exists. To force a refresh and regenerate the JSON data, run the following command:

```bash
scrape-pingze --force-refresh
```

This will scrape the latest data from the source and regenerate the `organized_ping_ze_rhyme_dict.json` file.

## Dependencies

    `requests`: For web scraping the Pingshui Rhyme data.
    `beautifulsoup4`: For parsing the HTML content from the Pingshui Rhyme source page.
polarscore 0.5.0
Lightning-fast credit scorecard building with Polars
Requires Python: >=3.9

# Polarscore

![PyPI - Downloads](https://img.shields.io/pypi/dm/polarscore)

## Overview

Polarscore is a Python library designed for lightning-fast credit scorecard building.

## Features

- **High Performance**: Built on top of Polars, ensuring fast data processing and manipulation.
- **Easy to Use**: Simple and intuitive API for building credit scorecards.
- **Scalable**: Capable of handling large datasets with ease.
- **Integration with Scikit-Learn**: Seamlessly integrates with scikit-learn API and pipeline.
oots-get 1.2.0
Download all 'Order of the Stick' comics for local reading.
Requires Python: >=3.9

# oots-get

[![PyPI version fury.io](https://badge.fury.io/py/oots-get.svg)](https://pypi.python.org/pypi/oots-get/)
[![PyPI license](https://img.shields.io/pypi/l/oots-get.svg)](https://pypi.python.org/pypi/oots-get/)
[![PyPI status](https://img.shields.io/pypi/status/oots-get.svg)](https://pypi.python.org/pypi/oots-get/)

This is a simple Python script to maintain a local archive of the web comic
['The Order of the Stick'][oots], though can probably be modified reasonably
easily for others if required.

This is a __work in progress__ although base functionality is working perfectly.

Primarily an exercise in using ['Beautiful Soup'][bs] with a live target. Also I
love this comic and when I originally wrote it I often spent  a lot of time
without any internet.

This is a rewrite from scratch of my original Ruby script of the same name.

## Usage

### Install

Using pipx to install globally (recommended) :

```bash
pipx install oots-get
```

Or use pip:

```bash
pip install oots-get
```

### Quick start

Run the script :

```bash
oots-get
```

This will parse the OOTS website, then download any missing comics. These comics
will be stored in the `comics/oots` subdirectory of the users home directory by
default though this will be changable shortly via settings file.

This package has been tested to work under both Linux and Windows 10.

## Configuration File

To be added.

## Command line switches

- `--only-new` ( short form: `-n`) : only check for new up to the last comic
  already downloaded, this speeds up operation.

## To-Do

see the [TODO.md](TODO.md) file.

## Contributing

1. Fork it
2. Create your feature branch (`git checkout -b my-new-feature`)
3. Commit your changes (`git commit -am 'Added some feature'`)
4. Push to the branch (`git push origin my-new-feature`)
5. Create new Pull Request

I'll add a proper CONTRIBUTING.md file soon.

## Copyright

(C) Grant Ramsay (<grant@gnramsay.com>) 2021-2024.

[oots]: http://www.giantitp.com/comics/oots.html
[bs]: https://www.crummy.com/software/BeautifulSoup/