semvec/pypi-packages huggingface dataset:
crypto-functions 1.0.0
A simple and secure Python module for hashing and encrypting data and files.
License: MIT
Requires Python: >=3.8

# 🔐 Crypto Tools — Secure Hashing & Encryption for Python

A lightweight, beginner-friendly yet secure cryptography toolkit for Python.
It supports password hashing, data hashing, and AES-GCM-based file encryption & decryption — all using modern, industry-standard cryptographic practices.

---

## 🚀 Features

✅ **Password Hashing** — Uses Argon2 (the most secure modern algorithm) <br>
✅ **Data Hashing** — Fast and deterministic SHA-256 hashing <br>
✅ **File Encryption** — AES-GCM authenticated encryption (confidentiality + integrity = security Pro Max) <br>
✅ **File Decryption** — Securely decrypts files encrypted with the same password <br>
✅ **Key Derivation** — PBKDF2-HMAC-SHA256 with 500,000 iterations <br>
✅ **Simple API** — Four clean, easy-to-use functions <br>

---

## 📦 Installation

**1. Clone the repo:** <br>
`git clone https://github.com/Anish-Sethi-12122/Crypto-Tools` <br>
`cd Crypto-Tools`


**2. Install dependencies:** <br>
`pip install -r requirements.txt`

### Or even better !!  
Download it directly as a module and use it in your python projects.   
`pip install crypto-functions argon2-cffi cryptography`  

---

## 📁 File Structure <br> <br>
Crypto-Tools/  
├── LICENSE  
├── README.md  
├── crypto_functions.py  
├── requirements.txt  
└── example.py  

---

**Caution- Always store your encryption passwords safely — losing them makes decryption impossible.**

---

## Security Pro Max:  
AES-GCM for authenticated encryption  
PBKDF2-HMAC-SHA256 with 500,000 iterations for key derivation  
Argon2 for password hashing  

---

## 🧪 Example Files

An example script is provided to demonstrate how to use each function.

---

## 🧑‍💻 Author

Anish Sethi  
B.Tech CSE Student  

💼 [LinkedIn](https://www.linkedin.com/in/anish-sethi-dtu-cse/)  
⭐ Don’t forget to star the repo if you like it!  

---

### 🪪 License
This project is licensed under the MIT License — feel free to use, modify, and share.
moon-cloud-coder 0.0.1
AI-powered command line tool for developers using Qwen models
License: MIT

# Moon-Cloud-Coder

AI-powered command line tool for developers using Qwen models

## 项目描述

Moon-Cloud-Coder 是一个基于阿里云通义千问（Qwen）模型的AI命令行工具，专为开发者设计。它可以帮助开发者完成代码分析、生成、调试等任务。

## 功能特性

- 交互式AI对话
- 代码分析和生成
- 支持多种认证方式（API Key、OAuth）
- 丰富的命令行选项
- 文件内容分析支持

## 安装

```bash
pip install moon-cloud-coder
```

## 使用方法

### 交互模式
```bash
moon-cloud-coder
```

### 非交互模式
```bash
moon-cloud-coder --prompt "你的问题或请求"
```

### 认证设置
```bash
# 使用命令行进行认证
moon-cloud-coder
# 然后在交互模式中输入 /auth 命令
```

## 认证方式

项目支持两种认证方式：
1. API Key - 通过 `DASHSCOPE_API_KEY` 环境变量
2. Qwen OAuth - 通过OAuth流程，享有免费额度

## 配置

可以创建 `MoonCloud.md` 文件来自定义AI交互指令。

## 开发

```bash
# 克隆项目
git clone <repository-url>

# 安装开发依赖
pip install -e ".[dev]"
```

## 许可证

MIT
aiocli 1.12.0
Simple and lightweight async console runner.
License: MIT
Requires Python: >=3.10
Keywords: asyncio, async, aio, cli, console

# Async cli client/commander framework

[![PyPI version](https://badge.fury.io/py/aiocli.svg)](https://badge.fury.io/py/aiocli)
[![PyPIDownloads](https://static.pepy.tech/badge/aiocli)](https://pepy.tech/project/aiocli)
[![CI](https://github.com/aiopy/python-aiocli/actions/workflows/ci.yml/badge.svg?branch=main)](https://github.com/aiopy/python-aiocli/actions/workflows/ci.yml)

aiocli is a Python library for simple and lightweight async console runner.

Full compatibility with argparse module and highly inspired by aiohttp module.

## Installation

Use the package manager [pip](https://pypi.org/project/aiocli/) to install aiocli.

```bash
pip install aiocli
```

## Documentation

- Visit [aiocli docs](https://aiopy.github.io/python-aiocli/).

## Usage

```python
from logging import getLogger, Logger, StreamHandler
from os import getenv

from aiocli.commander import run_app, Application, Depends, State

app = Application(state={
    'envs': {
        'LOGGER_NAME': str(getenv('LOGGER_NAME', 'example_app')),
        'LOGGER_LEVEL': str(getenv('LOGGER_LEVEL', 'INFO')),
    }
})

def _get_logger(state: State) -> Logger:
    logger = getLogger(state.get('envs')['LOGGER_NAME'])
    logger.setLevel(state.get('envs')['LOGGER_LEVEL'])
    handler = StreamHandler()
    logger.addHandler(handler)
    return logger

@app.command(name='greet:to', positionals=[('name', {'default': 'World!'})])
async def handle_greeting(name: str, logger: Logger = Depends(_get_logger)) -> int:
    logger.info(f'Hello {name}')
    return 0

@app.command(name='div', optionals=[('--a', {'type': float}), ('--b', {'type': float})])
async def handle_division(a: float, b: float, logger: Logger = Depends(_get_logger)) -> int:
    try:
        logger.info(f'Result {a} / {b} = {(a / b)}')
        return 0
    except BaseException as err:
        logger.error(f'Error: {err}')
        return 1

# python3 main.py <command> <positionals> <optionals>
if __name__ == '__main__':
    run_app(app)
```

## Requirements

- Python >= 3.10

## Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

## License

[MIT](https://github.com/aiopy/python-aiocli/blob/master/LICENSE)
bloret-api-tool 0.1.0
A Python library for interacting with Bloret Launcher API
License: MIT
Requires Python: >=3.7

# Bloret Launcher API Tool

A Python library for interacting with Bloret Launcher API. This library can be used both as a module that you can import in your Python applications and as a command-line tool using the `BLAPI` command.

## Installation

```bash
pip install bloret-api-tool
```

Or install from source:

```bash
pip install .
```

## Usage

### As a Library

```python
from bloret_api_tool import Client, request_api

# Using the Client class
client = Client(base_url="https://api.bloret.com", token="your-token")
response = client.request("GET", "/v1/games")

# Using the convenience function
response = request_api("GET", "/v1/games", token="your-token")
```

### As a Command-Line Tool

After installation, you can use the `BLAPI` command:

```bash
# Make a GET request
BLAPI get /v1/games

# Make a POST request with data
BLAPI post /v1/games --data '{"name": "New Game"}'

# Specify a custom base URL and token
BLAPI --base-url https://api.bloret.com --token your-token get /v1/games

# Save output to a file
BLAPI get /v1/games --output games.json
```

## Commands

- `get` - Make a GET request to an endpoint
- `post` - Make a POST request to an endpoint
- `put` - Make a PUT request to an endpoint
- `delete` - Make a DELETE request to an endpoint

## Options

- `--base-url` - Base URL for the API (default: https://api.bloret.com)
- `--token` - Authorization token for API requests
- `--output`, `-o` - Output file (default: stdout)

## Development

To install the package in development mode:

```bash
pip install -e .
```

To run tests:

```bash
pytest
```

## License

MIT
gemini-search-mcp 0.3.1
MCP server that exposes Gemini web search and document question answering tools.
License: MIT
Requires Python: >=3.9
Keywords: mcp, gemini, search, google, ai, model-context-protocol

# Gemini Search MCP

[![PyPI version](https://badge.fury.io/py/gemini-search-mcp.svg)](https://badge.fury.io/py/gemini-search-mcp)
[![npm version](https://badge.fury.io/js/gemini-search-mcp.svg)](https://badge.fury.io/js/gemini-search-mcp)
[![CI Tests](https://github.com/MIMICLab/GeminiSearchMCP/actions/workflows/ci.yml/badge.svg)](https://github.com/MIMICLab/GeminiSearchMCP/actions/workflows/ci.yml)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

Gemini Search MCP packages a [Model Context Protocol](https://www.modelcontextprotocol.io/) server that exposes five tools:

- **web_search** – Uses Gemini with Google Search grounding to answer general questions.
- **document_question_answering** – Converts local documents to captioned markdown and asks Gemini to answer questions about their contents.
- **get_document_content** – Converts a document to markdown and returns the full content for reading.
- **get_document_chunk** – Retrieves specific chunks of large documents for easier processing.
- **get_next_chunk** – Automatically continues reading from where you left off (stateful).

## Installation

### Python (pip)

```bash
pip install gemini-search-mcp
```

### Node.js (npm)

```bash
npm install -g gemini-search-mcp
```

## Usage

Set your Google API key (must have Gemini access):

```bash
export GOOGLE_API_KEY="your-key"
```

Run the MCP server (defaults to stdio transport):

```bash
gemini-search-mcp run
# or simply
# gemini-search-mcp
```

Configure Codex automatically (writes to `~/.codex/config.toml` by default):

```bash
gemini-search-mcp configure --api-key "YOUR_KEY"
```

Configure Copilot CLI (writes to `~/.copilot/config.json`):

```bash
gemini-search-mcp configure --cli-type copilot --api-key "YOUR_KEY"
```

Configure both Codex and Copilot CLI at once:

```bash
gemini-search-mcp configure --cli-type both --api-key "YOUR_KEY"
```

For npm/npx installation with custom command:

```bash
gemini-search-mcp configure --command npx --command-args -y gemini-search-mcp --api-key "YOUR_KEY"
```

Clear cached conversion artifacts:

```bash
gemini-search-mcp clear-cache
# 선택 옵션: --cache-dir /custom/path --remove-root
```

## Development

Install in editable mode with testing dependencies:

```bash
pip install -e .
```

Ensure LibreOffice is installed and on `PATH` if you plan to convert non-PDF documents.

## Contributing

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

## Publishing

For maintainers: See [PUBLISHING.md](PUBLISHING.md) for instructions on how to publish new versions to PyPI and npm.

## Changelog

See [CHANGELOG.md](CHANGELOG.md) for a list of changes in each version.

## License

MIT – all rights reserved.