semvec/pypi-packages huggingface dataset:
XMAItest 0.9.7
Small code King AI related library
Requires Python: >=3.7.0

# AI

## 简介
AI 是一个小码王开源的第三方 Python 库，支持生文、生图、生诗句等多场景的内容。需要学员提供对应的api秘钥才能使用。

## 安装
使用 pip 安装：
```bash
pip install XMAItest
```
xss-detector 0.1.0
A package for detecting XSS attacks using machine learning
Requires Python: >=3.7

# XSS Detector

A Python package for detecting Cross-Site Scripting (XSS) attacks using machine learning.

## Installation

```bash
pip install xss-detector
```

## Features

- Detect XSS attacks in text, URLs, files, and HTTP requests
- Command-line interface for quick checks
- REST API for integration with other tools
- Deep learning model trained on a comprehensive XSS dataset
- Automated model training and management

## Quick Start

### Command Line Usage

Check a specific string for XSS:

```bash
xss-detector check "<script>alert(1)</script>"
```

Check a file for XSS:

```bash
xss-detector file suspicious.html
```

Check a URL:

```bash
xss-detector url "https://example.com/?param=value"
```

Start the API server:

```bash
xss-detector server --port 5000
```

### Python API Usage

```python
from xss_detector import XSSDetector

# Initialize the detector
detector = XSSDetector()

# Check a single string
result = detector.detect('<img src="x" onerror="alert(1)">')
print(f"XSS detected: {result['is_xss']}, Confidence: {result['confidence']}")

# Analyze a full HTTP request
analysis = detector.analyze_request(
    url_params={'search': 'something<script>alert(1)</script>'},
    headers={'User-Agent': 'Mozilla/5.0'},
    cookies={'session': 'abc123'}
)
print(f"Request contains XSS: {analysis['xss_detected']}")
```

### REST API Usage

Start the server:

```bash
xss-detector server
```

Then make requests:

```bash
# Check a single string
curl -X POST http://localhost:5000/check \
  -H "Content-Type: application/json" \
  -d '{"text": "<script>alert(1)</script>"}'

# Analyze a full request
curl -X POST http://localhost:5000/proxy \
  -H "Content-Type: application/json" \
  -d '{"param": "<img src=x onerror=alert(1)>"}'
```

## Model Training

The package automatically downloads a dataset and trains a model on first use. To manually train a new model:

```bash
xss-detector train
```

## License

MIT
jnews-mcp-server 0.1.3
一个提供热点新闻头条信息功能的模型上下文协议（Model Context Protocol）服务器。
Requires Python: >=3.10

# Juhe News MCP Server

一个提供新闻头条信息功能的模型上下文协议（Model Context Protocol）服务器。该服务器使大型语言模型（LLMs）能够获取当前最新的热点新闻头条（包括：推荐、国内、科技、体育等类型）及详细内容信息。


## Components

### Tools

服务器实现了两个工具:

- get_news_list: 根据新闻类型获取今日热点新闻头条
  - 需要传入 "type"（新闻类型）作为选填的字符串参数。
```
async def get_news_list(type: str = "top", page: int = 1, page_size: int = 20) -> list[types.TextContent | types.ImageContent | types.EmbeddedResource]:
```

- get_news_content: 根据新闻类型获取今日热点新闻头条
  - 需要传入 "uniquekey"（新闻id）作为必须的字符串参数。
```
async def get_news_content(uniquekey: str) -> list[types.TextContent | types.ImageContent | types.EmbeddedResource]:
```



## Install
This server requires Python 3.10 or higher. Install dependencies using uv (recommended) or pip

### Using uv (recommended)
When using [uv](https://docs.astral.sh/uv/) no specific installation is needed. We will use [uvx](https://docs.astral.sh/uv/guides/tools/) to directly run jnews-mcp-server.

```bash
uvx jnews-mcp-server
```

### Using PIP
Alternatively you can install jnews-mcp-server via pip:
```
pip install jnews-mcp-server
```
After installation, you can run it as a script using:
```
python -m jnews_mcp_server
```

### Configuration

#### Environment Variables
`JUHE_NEWS_API_KEY`: 聚合数据的新闻头条API密钥。获取：[https://www.juhe.cn/docs/api/id/235](https://www.juhe.cn/docs/api/id/235)
```
JUHE_NEWS_API_KEY=your_api_key
```

#### Claude Desktop

- On MacOS: `~/Library/Application\ Support/Claude/claude_desktop_config.json`
- On Windows: `%APPDATA%/Claude/claude_desktop_config.json`

<details>
  <summary>Using uvx</summary>

  ```
  "mcpServers": {
    "jnews-mcp-server": {
      "command": "uvx",
      "args": [
        "jnews-mcp-server"
      ],
      "env": {
        "JUHE_NEWS_API_KEY": "your_api_key"
      }
    }
  }
  ```
</details>

<details>
  <summary>Using pip installation</summary>

  ```
  "mcpServers": {
    "jnews-mcp-server": {
      "command": "pip",
      "args": [
        "-m",
        "jnews-mcp-server"
      ],
      "env": {
        "JUHE_NEWS_API_KEY": "your_api_key"
      }
    }
  }
  ```
</details>

## Debugging
You can use the MCP inspector to debug the server. For uvx installations:

```bash
npx @modelcontextprotocol/inspector uvx jnews-mcp-server 
```

Or if you've installed the package in a specific directory or are developing on it:

```bash
cd path/to/servers/src/jnews-mcp-server
npx @modelcontextprotocol/inspector uv run jnews-mcp-server
```

## Examples of Questions for Cline
1. "今日有哪些热点新闻?"
2. "当前体育热点头条?"
3. "第5条新闻的详细内容"
DualNet-TCM 0.1a8
DualNet-TCM：分别从中医和西医维度对中药进行“以靶找药”和“以药找靶”的新型中药网络药理学
Requires Python: >=3.9
Keywords: network pharmacology

## DualNet-TCM

***DualNet-TCM***(TCM (中药) + Dual (双重网络) + Net (网络药理学)):
从网络药理学和中医理论双重视角出发，构建"方剂-中药-成分-靶点-病症"和"方剂-对症-症状-病证"双重关联网络。
同时，结合基因研究和文献计量学方法，开展转化医学研究：通过药物可用性评估和文献挖掘技术，对大量候选蛋白或基因进行系统筛选和分类，
从而精准缩小需要实验验证的目标范围，为中药现代化研究提供新的思路和方法。

- [安装](#安装)

- [使用](#使用)

- [环境要求](#requirements)

- [致谢](#致谢)

### 安装

### 注意

#### 1.关于Python版本

由于在 Python 3.9 之前的版本中，`tuple[...]` 和 `list[...]` 
这样的类型注解语法不被支持。
Python 3.9 引入了原生的类型注解支持（PEP 585），
但在早期版本中，需要使用 typing 模块中的 Tuple、List 等类型. 所以需要Python≥3.9，如果＜3.9的话，
可将`compute.py`函数中修改如下：

```python
from typing import Tuple, Union

def score(weights: Union[dict, None] = None) -> Tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]:
    # 函数逻辑
    pass
```

#### 2.数据下载 
整体大小为9个G，由于百度网盘限制，所以拆分成三个压缩包，解压后放data/文件夹即可

[下载链接1](https://pan.baidu.com/s/1zIlTjstJMscKdZnP30wc1g?pwd=2n2t) 

[下载链接2](https://pan.baidu.com/s/1tg8WQtJiJi70A8HIRYG_PA?pwd=9bvh) 

[下载链接3](https://pan.baidu.com/s/1tg8WQtJiJi70A8HIRYG_PA?pwd=9bvh)

### 使用

### Requirements

- pandas
- pyecharts
- numpy
- tqdm
- requests
- os

### Star History

[![Star History Chart](https://api.star-history.com/svg?repos=Carrie-HuYY/DualNet-TCM&type=Date)](https://star-history.com/#Carrie-HuYY/DualNet-TCM&Date)