semvec/pypi-packages huggingface dataset:
pygamepal 1.1.1
A library of classes and helper functions to support game development in Pygame
Requires Python: >=3.7

# PygamePal

A library of classes and functions to support game development in Pygame.
- Simple, beginner-friendly interface.
- Choose the bits you want to use, and continue to use Pygame for everything else!

![Example](https://github.com/rik-cross/pygamepal/blob/main/examples/gifs/fullExample.gif?raw=true)

Includes:

- A Game class that extracts away a lot of Pygame boilerplate code
- Scenes
- Transitions
- Cameras, including zoom, shake and clamp
- Sprites
- Sprite Images, for creating images and/or animations for multiples states
- Input, including press, down, long-press and double-press
- Buttons that can be controlled by mouse or key press
- Lighting
- Particle Emitters
- Colliders, which have simple collision detection
- Triggers, which execute user-defined functions on collision

### Usage

- Install: `pip install pygamepal`, or
- Install from local source: `pip install -e [repo path]`

[Add suggestions and bugs here!](https://github.com/rik-cross/pygamepal/issues)

### Getting started

- See the [Documentation](https://pygamepal.readthedocs.io/en/latest/) on readthedocs.org.
- See the simple [examples](https://github.com/rik-cross/pygamepal/tree/main/examples) of functionality used (mostly) individually.
- See the [Full example](https://github.com/rik-cross/pygamepal/blob/main/examples/fullExample.py), using lots of PygamePal functionality.

### Licence

Distributed under the MIT License. See [LICENSE](https://github.com/rik-cross/pygamepal/blob/main/LICENSE) for more information.

All images taken from [Sprout Lands](https://cupnooble.itch.io/sprout-lands-asset-pack) asset pack by [Cup Nooble](https://cupnooble.itch.io/) and used under a non-commercial license.
csvquerylite 0.1.5
Run SQL-like queries on CSV files using a simple Python library or CLI.
Requires Python: >=3.6

# csvquerylite

`csvquerylite` is a lightweight Python library and command-line tool that allows you to run SQL-like queries on CSV files easily. Itâ€™s designed for developers, analysts, and anyone who wants the power of SQL for CSV data without setting up a database.

---

## Features

- Simple SQL-like syntax: `SELECT`, `WHERE`, `ORDER BY`, `LIMIT`
- Command-line interface (CLI) support
- Save output as CSV or JSON
- Pure Python + Pandas implementation
- Works on any CSV file

---

## Sample Usage (Python API)

```python
from csv_query.core import query_csv

df = query_csv("employees.csv", "SELECT name, age WHERE department == 'HR' ORDER BY age DESC LIMIT 2")
print(df)
```

---

## Sample Usage (CLI)

```bash
csv-query employees.csv "SELECT name, age WHERE age > 30 ORDER BY age DESC LIMIT 5"
```

To save output:

```bash
csv-query employees.csv "SELECT name, salary WHERE department == 'Engineering'" --output eng.csv
csv-query employees.csv "SELECT * ORDER BY age DESC LIMIT 3" --json top3.json
```

---

## Installation

Install dependencies and install locally:

```bash
git clone https://github.com/your-username/csv-query.git
cd csv-query
pip install -e .
```

---

## Command-Line Options

```bash
csv-query <file.csv> "<query>" [--output result.csv] [--json result.json]
```

| Option      | Description                      |
|-------------|----------------------------------|
| `file.csv`  | CSV file to query                |
| `"<query>"` | SQL-like query string            |
| `--output`  | Save result as CSV               |
| `--json`    | Save result as JSON              |

---

## Supported Syntax

Basic SQL-like support:
- `SELECT column1, column2`
- `WHERE condition` (use pandas-style conditions)
- `ORDER BY column [ASC|DESC]`
- `LIMIT N`

> Example: `SELECT name, salary WHERE department == 'Finance' ORDER BY salary DESC LIMIT 3`

---

## Roadmap

- [x] SELECT, WHERE, ORDER BY, LIMIT
- [x] CLI with CSV/JSON export
- [ ] Column aliasing (`AS`)
- [ ] JOIN support
- [ ] PyPI publishing
- [ ] Unit testing with `pytest`

---

## Author

- Name: Jahfar Muhammed
- GitHub: [jah-117](https://github.com/jah-117)
- Email: jahfarbinmuhammed117@gmail.com

---

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
chercher-plugin-pdf 0.1.6
Chercher plugin that adds support for PDF files.
Requires Python: >=3.13

# chercher-plugin-pdf

[Chercher](https://github.com/dnlzrgz/chercher) plugin that adds support for PDF files thanks to [PyMuPDF](https://pymupdf.readthedocs.io/en/latest/).

## Installation

> [!NOTE]
> This plugin is included with Chercher by default, so no additional installation is necessary

## Settings

> [!NOTE]
> This plugin does not requires any additional settings.
qa-ai 0.2.5
AI-powered test automation framework

# QA-AI Framework 🚀

**Умный генератор автотестов с AI-ассистентом**  
*Ускорьте создание тестов в 3 раза с помощью искусственного интеллекта*

[![Python](https://img.shields.io/badge/Python-3.10%2B-blue)](https://python.org)
[![Pydantic](https://img.shields.io/badge/Pydantic-v2-brightgreen)](https://pydantic.dev)
[![License](https://img.shields.io/badge/License-MIT-purple)](LICENSE)
![Free](https://img.shields.io/badge/free-open--source-green.svg)


[![Join telegram chat https://t.me/qa_ai_ru](https://img.shields.io/badge/chat-telegram-blue)](https://t.me/qa_ai_ru)

# Умная валидация:
 - Проверка синтаксиса
 - Контроль наличия assert-проверок
 - Автоисправление простых ошибок

# Интеграция с популярными инструментами:
```mermaid
graph LR
  A[QA-AI] --> B(pytest)
  A --> C(Allure)
  A --> D(GitLab CI)
```
# Архитектура
```mermaid
graph TD
    A[Описание теста] --> B{AI-генератор}
    B --> C[Код на Python]
    C --> D[Валидация]
    D --> E[Запуск через Pytest]
    E --> F[Allure-отчет]
```
## 🌟 Ключевые возможности

- **AI-генерация тестов** из описания на естественном языке
- **Поддержка всех видов тестирования**:
```python
# UI (Selene), API (Requests), Mobile (Appium)
generator.generate_test("Проверка логина", type="web")
```
## 🛠 Быстрый старт
*Установка*
bash
```bash
pip install qa_ai
```
**Пример использования**
```python

from qa_ai import OpenAITestGenerator

generator = OpenAITestGenerator(api_key="your_key")
test_code = generator.generate_test(
    description="Проверить корзину с 2 товарами",
    prompt_type="web/ecommerce"
)

exec(test_code)  # или сохраните в файл
```
# 📂 Структура проекта
```
.
├── ai/                  # AI-компоненты
├── autotests/           # Сгенерированные тесты
├── config/              # Настройки
└── docs/                # Примеры и руководства
```
# 🔧 Настройка
1. Создайте .env в корне проекта:

```ini
AI_OPENAI_API_KEY=your_key_here
AI_MODEL=gpt-4-turbo
```
2. Добавьте шаблоны в ai/prompts/:

```markdown
# web/login.md
Сгенерируй тест для: {description}
Требования:
- Используй PageObject
- Добавь 3 проверки
```
# 🤖 Поддерживаемые AI-провайдеры
| Провайдер |      Модели     |    Требования    |
|:---------:|:---------------:|:----------------:|
|   OpenAI  |    GPT-3.5/4    |     API-ключ     |
| Llama.cpp | Llama 3/Mistral |     8+ GB RAM    |
| Anthropic |      Claude     | Доступ по invite |
khojkar 0.4.0
A tool for conducting deep research on a given topic, using a combination of LLMs, search engines, and other tools.
Requires Python: <3.13,>=3.12

# khojkar

khojkar (pa: ਖੋਜਕਾਰ, ipa: /kʰoːd͡ʒ.kɑːɾ/) is a deep research agent.

## Installation

### Prerequisites
- Python 3.12
- [uv](https://github.com/astral-sh/uv) - Fast Python package installer and resolver

## Quick Start (PyPI)

The easiest way to run khojkar is directly using `uvx`, which will fetch it from PyPI:

```bash
# Run directly from PyPI using uvx
uvx khojkar research --topic "Your research topic" --output report.md
```

To set up credentials when using this method, create a `.env` file in your current working directory with your API keys. `uvx` will automatically load environment variables from a `.env` file.

## Setup Credentials

khojkar uses LLMs via the LiteLLM library, which requires API keys for the models you want to use.

1. Create a `.env` file in your current working directory:

   ```bash
   touch .env
   ```

2. Add your API keys to the `.env` file. You only need the key for the model you intend to use. The default is `gemini/gemini-2.0-flash`, which requires the `GEMINI_API_KEY`. For other providers like OpenAI or Anthropic, you would use `OPENAI_API_KEY` or `ANTHROPIC_API_KEY` respectively. You also need to add credentials for the Google Programmable Search Engine: `SEARCH_ENGINE_ID` and `SEARCH_ENGINE_API_KEY`.

   ```dotenv
   # Required for the default model (gemini/gemini-2.0-flash)
   GEMINI_API_KEY=your_gemini_api_key

   # Required for Google Programmable Search Engine
   SEARCH_ENGINE_ID=your_search_engine_id
   SEARCH_ENGINE_API_KEY=your_search_engine_api_key

   # Optional: add other LLM API keys as needed
   # OPENAI_API_KEY=your_openai_api_key
   # ANTHROPIC_API_KEY=your_anthropic_api_key
   ```

   *Note: Refer to the LiteLLM documentation for the specific environment variable names required for different LLM providers.*

## Usage

Basic Usage:
```bash
khojkar research --topic "Your research topic" --output report.md
```

Advanced Options:
```bash
# Use a different model
khojkar research --topic "Your research topic" --model "openai/gpt-4o" --output report.md

# Limit research steps
khojkar research --topic "Your research topic" --max-steps 5 --output report.md

# Use multi-agent research mode
khojkar research --topic "Your research topic" --multi-agent --output report.md
```

## License

See [LICENSE](LICENSE) file for details.
django-charm 0.2.3
Easily create a Django project and app with a single command in seconds.
Requires Python: >=3.7

# Django Charm

Welcome to **Django Charm**! This is a handy package that can save your time so you can focus on building what truly matters in your Django project.

## Features
- Users no longer need to install Django. 
- No need to manually create and configure a Django project and app separately.
- Automatically handles the `urls.py` and `settings.py` setup.
- Instantly creates `index.html` with a starter template — ready to go.

---

## django-charm

This package allows you to create a Django project and app by executing a single command (including generating `views.py`, `urls.py`, and a basic `index.html` template).

## Table of Contents
- [Installation](#installation)
- [Features](#features)
- [Examples](#examples)
- [License](https://github.com/AlokDas1234/Django-Charm/blob/main/LICENSE)


## Installation

```bash
pip install django-charm
```





# Examples:

  #####  Create the whole project:


- Activate your virtual environment.<br>

- Use the --createproject flag to specify the project name.<br>

- Use -a to specify the app name.



```bash

django-charm --createproject myproject -a myapp

```
  ##### Create  new app inside an existing project:

- Make sure your Django project already exists.<br>

- Use the --createapp flag to specify the new app name.<br>

- Use -p to specify the parent project name (where manage.py is located).

```bash

 django-charm  --createapp myapp -p parentproject

```
## GitHub Repository:
>https://github.com/AlokDas1234/Django-Charm

## License

This project is licensed under the MIT License - see the [LICENSE](https://github.com/AlokDas1234/Django-Charm/blob/main/LICENSE) file for details.
chercher-plugin-txt 0.1.8
Chercher plugin that adds support for plain text files.
Requires Python: >=3.13

# chercher-plugin-txt

[Chercher](https://github.com/dnlzrgz/chercher) plugin that adds support for plain text files.

## Installation

```bash
uv tool install --with chercher-plugin-txt chercher
```

## Settings

> [!NOTE]
> This plugin does not requires any additional settings.
desafio-poo 0.0.1
desafio poo
Requires Python: >=3.8

# desafio_poo

Description. 
The package desafio_poo is used to:
Desafio 3 de Sistema Bancario com POO
	- 
	-

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install desafio_poo

```bash
pip install desafio_poo
```
## Author
Diego Alves

## License
[MIT](https://choosealicense.com/licenses/mit/)