semvec/pypi-packages huggingface dataset:
mannrs 2.0.0
A Mann turbulence generator for Python written in Rust
Requires Python: >=3.9

# Mann.rs

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**Mann.rs** is a high-performance turbulent wind field generator based on the Mann turbulence model, designed for wind turbine and wind farm simulations. It produces three-dimensional coherent wind fields and supports both unconstrained and constrained turbulence generation.

Built in Rust for speed and efficiency, Mann.rs provides seamless Python bindings and a command-line interface for easy integration and scalability into engineering workflows.

## **Installation**
**Mann.rs** is available for **Windows**, **MacOS**, and **Linux** as a Python package.
```bash
pip install mannrs
```
For more details on the installation process, see the [**installation Guide**](installation).
## **Usage**

### **Command line**
```bash
mannrs input.toml
```
Define your simulation parameters in a TOML file. See the [**Input file format**](api/schema) for details.

### **Python**

```python
from mannrs import Stencil

...

(
    Stencil(**mann_params)    # Define a stencil with Mann parameters
    .constrain(constraints)   # Apply velocity constraints (optional)
    .build()                  # Build the turbulence stencil
    .turbulence(ae, seed)     # Generate turbulent wind field
    .write("out.npz")         # Save windfield to file
)

```
For a step-by-step walkthrough, visit the [**Basic usage**](usage/basic_usage) page.



# Contributions
If you have suggestions or issues with Mann.rs, feel free raise an issue in the [Mann.rs Github repository](https://github.com/jaimeliew1/Mann.rs). Pull requests are welcome.

# Citation
If you want to cite Mann.rs, please use this citation:
```
Liew, J., Riva, R., & Göçmen, T. (2023). Efficient Mann turbulence generation for offshore wind farms with applications in fatigue load surrogate modelling. Journal of Physics: Conference Series, 2626, 012050. DOI: 10.1088/1742-6596/2626/1/012050
```
hop-cli 0.2.2
hop compiler and tooling
Requires Python: >=3.7
Keywords: hop, compiler, language

# Hop Language

The hop compiler and tooling.

## Installation

```bash
pip install hop-cli
```

## Usage

```bash
hop --help
```

For more information, visit [https://github.com/hoplang/hop](https://github.com/hoplang/hop)
ragflow-mcp-server-aider 0.1.0
RAGFlow MCP Server Aider
Requires Python: >=3.10

# ragflow-mcp-server-aider MCP server

RAGFlow MCP Server Aider

## Components



### Tools
  
### Tools
  
1. list_datasets
    - 列出所有数据集
    - 返回数据集的 ID 和名称

2. create_chat
    - 创建一个新的聊天助手
    - 输入：
      - name: 聊天助手的名称
      - dataset_id: 数据集的 ID
    - 返回创建的聊天助手的 ID、名称和会话 ID

3. chat
    - 与聊天助手进行对话
    - 输入：
      - session_id: 聊天助手的会话 ID
      - question: 提问内容
    - 返回聊天助手的回答
4. retrieve
   - 检索相关信息
    - 输入：
      - dataset_ids: 数据集的 ID
      - question: 提问内容
    - 返回从知识库检索到的内容

## Configuration

[TODO: Add configuration details specific to your implementation]

## Quickstart

### Install

#### Claude Desktop

On MacOS: `~/Library/Application\ Support/Claude/claude_desktop_config.json`
On Windows: `%APPDATA%/Claude/claude_desktop_config.json`

<details>
  <summary>Development/Unpublished Servers Configuration</summary>
  ```
  "mcpServers": {
    "ragflow-mcp-server-aider": {
      "command": "uv",
      "args": [
        "--directory",
        ".\path\to\ragflow-mcp-server-aider",
        "run",
        "ragflow-mcp-server-aider"
      ]
    }
  }
  ```
</details>

<details>
  <summary>Published Servers Configuration</summary>
  ```
  "mcpServers": {
    "ragflow-mcp-server-aider": {
      "command": "uvx",
      "args": [
        "ragflow-mcp-server-aider"
      ]
    }
  }
  ```
</details>

## Development

### Building and Publishing

To prepare the package for distribution:

1. Sync dependencies and update lockfile:
```bash
uv sync
```

2. Build package distributions:
```bash
uv build
```

This will create source and wheel distributions in the `dist/` directory.

3. Publish to PyPI:
```bash
uv publish
```

Note: You'll need to set PyPI credentials via environment variables or command flags:
- Token: `--token` or `UV_PUBLISH_TOKEN`
- Or username/password: `--username`/`UV_PUBLISH_USERNAME` and `--password`/`UV_PUBLISH_PASSWORD`

### Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging
experience, we strongly recommend using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector).


You can launch the MCP Inspector via [`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) with this command:

```bash
npx @modelcontextprotocol/inspector uv --directory .\path\to\ragflow-mcp-server-aider run ragflow-mcp-server-aider
```


Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.
weather-mcp-x 0.1.2
A weather information tool based on FastMCP framework with support for Chinese city weather alerts
Requires Python: >=3.12

# Weather-X 天气查询工具

Weather-X 是一个基于 FastMCP 框架开发的天气查询工具，可以获取中国各城市的天气信息和警报。

## 功能特性

- 获取指定城市的天气信息
- 查询天气警报
- 基于高德地图天气API实现
- 支持异步请求处理

## 安装

```bash
pip install weather-x
```

或从源码安装：

```bash
git clone <repository-url>
cd weather-x
pip install -e .
```

## 使用方法

```python
from weather import mcp

# 运行MCP服务器
mcp.run(transport='stdio')
```

或直接运行：

```bash
python main.py
```

## API接口

### get_alerts(city: str) -> str

获取指定城市的天气警报信息。

参数:
- city: 城市名称（例如：北京、上海）

返回:
- 包含天气信息的字符串

## 依赖

- Python >= 3.12
- fastmcp >= 2.12.4
- httpx >= 0.28.1
- mcp[cli] >= 1.18.0

## 配置

项目使用高德地图天气API，需要在代码中配置API密钥。

## 开发

安装开发依赖：

```bash
pip install -e ".[dev]"
```

## 许可证

MIT