semvec/pypi-packages huggingface dataset:
QuickATETools 1.0.1
A collection of useful command-line tools
Requires Python: >=3.6

# QuickATETools

一个实用的命令行工具集合，目前包含生成对角矩阵并复制到剪贴板的功能。

## 安装

```bash
pip install QuickATETools
```

## 使用方法

### 生成对角矩阵并复制到剪贴板

```bash
qate clipboardMatrix -p <矩阵大小> [-c <对角线字符>]
```

#### 参数说明
- `-p`, `--size`: 矩阵的大小（行数和列数），必填
- `-c`, `--char`: 对角线使用的字符，默认为'M'

#### 示例

生成3x3的对角矩阵（默认使用'M'）：
```bash
qate clipboardMatrix -p 3
```

生成的矩阵：
```
M00
0M0
00M
```

生成4x4的对角矩阵，使用'X'作为对角线字符：
```bash
qate clipboardMatrix -p 4 -c X
```

生成的矩阵：
```
X000
0X00
00X0
000X
```

### 模板功能

这是一个新功能的空实现，用于展示如何扩展工具集。

```bash
qate templateFeature [-p <参数>]
```

#### 参数说明
- `-p`, `--param`: 参数说明

## 待开发功能
- 完善模板功能的具体实现
- 更多实用的命令行工具
minebase 0.3.0
Library providing an interface to minecraft-data
Requires Python: >=3.9
Keywords: data, minecraft

# <img src="https://i.imgur.com/nPCcxts.png" height="25" style="height: 25px"> minebase

[![discord chat](https://img.shields.io/discord/936788458939224094.svg?logo=Discord)](https://discord.gg/C2wX7zduxC)
![supported python versions](https://img.shields.io/pypi/pyversions/minebase.svg)
[![current PyPI version](https://img.shields.io/pypi/v/minebase.svg)](https://pypi.org/project/minebase/)
[![CI](https://github.com/py-mine/minebase/actions/workflows/main.yml/badge.svg)](https://github.com/py-mine/minebase/actions/workflows/main.yml)
[![minecraft-data autoupdate](https://github.com/py-mine/minebase/actions/workflows/update-minecraft-data.yml/badge.svg)](https://github.com/py-mine/minebase/actions/workflows/update-minecraft-data.yml)

Minebase is a python wrapper around [`PrismarineJS/minecraft-data`](https://github.com/PrismarineJS/minecraft-data). It
provides python bindings to access minecraft data useful for custom minecraft clients, servers and libraries.

## Installation

From PyPI (stable):

```bash
pip install minebase
```

From repo (latest):

```bash
pip install git+htps://github.com/py-mine/minebase
```

## Usage

```python
from minebase import load_version, load_common_data, Edition
from pprint import pprint  # pretty print (for easier readability)

common_data = load_common_data(Edition.PC)
version_info = load_version("1.21.6", Edition.PC)

status_server_bound_packets = version_info["protocol"]["status"]["toServer"]["types"]["packet"]
pprint(status_server_bound_packets)
```

Output:

```python
['container',
 [{'name': 'name',
   'type': ['mapper',
            {'mappings': {'0x00': 'ping_start', '0x01': 'ping'},
             'type': 'varint'}]},
  {'name': 'params',
   'type': ['switch',
            {'compareTo': 'name',
             'fields': {'ping': 'packet_ping',
                        'ping_start': 'packet_ping_start'}}]}]]
```
akpub 0.1.0
A generic ROS2 publisher for numbers, strings, images, and video.
Requires Python: >=3.6

akpub
=================

A generic ROS2 publisher that can publish numbers, strings, images, or video frames with minimal setup.

Installation
------------
First, make sure you have a working ROS2 environment with `rclpy` and `cv_bridge` installed.

Then clone this repository and install:

    git clone https://github.com/yourname/akpub.git
    cd akpub
    pip install .

Usage
-----
Example Python usage:

    import akpub

    akpub.metadata(
        mode=None,           # Auto-detect from datatype
        datatype="Float64",  # e.g., "String", "Int32", "Image"
        node_name="num_publisher",
        topic_name="number",
        value=42.5,          # Can be number, string, or image frame
        queue=10,
        delay=1.0
        # video_source=0     # Only needed for video mode
    )

Supported Datatypes
-------------------
- String (std_msgs.msg.String)
- Int32 (std_msgs.msg.Int32)
- Float32 (std_msgs.msg.Float32)
- Float64 (std_msgs.msg.Float64)
- Bool (std_msgs.msg.Bool)
- Image (sensor_msgs.msg.Image)

Notes
-----
- `mode` can be "number", "string", "image", "video", or None for auto-detect.
- For video mode, set `video_source` to a camera index (e.g., 0) or a video file path.
- Requires `rclpy` and `cv_bridge` to be installed in your ROS2 Python environment.
vibepython 0.0.5
🚀 Python vibe: Unleash the Magic of AI-Powered Coding Wizardry! 🌟
Requires Python: >=3.8

# vibepython: AI-Powered Interactive Python Code Generator

vibepython is an interactive command-line tool that uses AI to generate executable Python code from user prompts. Powered by OpenAI or alternative providers, it allows you to create, run, and capture code outputs while maintaining a contextual history stored in JSON. Ideal for developers, experimenters, and AI enthusiasts looking for a seamless coding experience.

## Example of work

![alt text](https://raw.githubusercontent.com/OldTyT/vibepython/main/resources/img/example.png)


## Features
- **Interactive Prompting**: Enter your ideas and receive AI-generated Python code.
- **AI Code Generation**: Leverages AI models with prompt history for accurate scripts.
- **Safe Code Execution**: Run generated code and capture stdout/stderr outputs.
- **Persistent History**: Uses Pydantic models to store interactions in JSON for ongoing context.
- **Customization via Environment Variables**: Adjust settings for personalized control.
- **Docker Support**: Easy deployment in containerized environments.

## Installation

### From PyPI
1. Install the package:
   ```
   pip install vibepython
   ```
2. Run the tool:
   ```
   vibepython
   ```

### From Source
1. Clone the repository:
   ```
   git clone https://github.com/OldTyT/vibepython.git
   ```
2. Navigate to the directory:
   ```
   cd vibepython
   ```
3. Install dependencies:
   ```
   pip install -r requirements.txt
   ```
4. Launch the application:
   ```
   python3 main.py
   ```

### Using Docker
Run the container with this command:
```
docker run --rm -ti -e HISTORY_PATH=/history/history.json -v my_history:/history ghcr.io/oldtyt/vibepython
```
- Set your OpenAI API key via the `OPENAI_API_KEY` environment variable (required for the 'openai' provider).

## Usage
Start the tool and follow the prompts:
- Enter a prompt (e.g., "Write a function to calculate factorial").
- The AI generates code based on your input and history.
- All interactions are logged to history for context.

To exit, press Ctrl+C.

## Environment Variables
Customize the tool using these environment variables:
| Variable          | Default       | Description |
|-------------------|---------------|-------------|
| `HISTORY_PATH` | `history.json` | Path to the JSON history file. |
| `HISTORY_SIZE` | `7` | Number of past interactions to include in AI context. |
| `OPENAI_API_KEY` | `None` | Required for the openai provider; your OpenAI API key. |
| `PROVIDER` | `gpt4free` | AI provider to use. Supports `gpt4free`, `ollama` and `openai`. |
| `MODEL_NAME` | Varies by provider (`gpt-4o` for `gpt4free`, `gpt-5-mini` for `openai`, `llama3` for `ollama`) | Model to use with the provider. |
| `OLLAMA_URL` | `http://localhost:11434` | Ollama URL(only for ollama provider). |

Example configuration:
```
export PROVIDER=openai
export OPENAI_API_KEY=your-api-key
export MODEL_NAME=gpt-5-mini
export HISTORY_SIZE=10
python3 main.py
```