semvec/pypi-packages huggingface dataset:
flowgeo 0.2.0
A lightweight 3D geometry presentation library for math education
License: MIT
Requires Python: >=3.8
Keywords: geometry, 3d, visualization, education, math, plotly, presentation, teaching

# FlowGeo

FlowGeo 是一个专为数学教师打造的 3D 几何可视化库，让您的立体几何与解析几何课件制作变得简单、优雅。

## 🎯 愿景

- **零门槛**：无需复杂前端技能，用 Python 写"幻灯片"就能生成交互式 3D PPT。
- **所见即所得**：支持本地预览，一键导出为可分享的静态 HTML。
- **可扩展性**：分层设计，方便您根据教学场景定制主题、动画与交互。

## 🚀 快速开始

### 安装依赖

```bash
pip install numpy plotly jinja2 pyyaml
```

### 使用

API还在初级建设阶段，暂时不提供使用方案。
partigraph 0.1.0
Graph partitioning algorithms using random spanning trees
License: MIT
Requires Python: >=3.12
Keywords: graph, partition, spanning-tree, redistricting

# Partigraph

Graph partitioning algorithms using random spanning trees.

Partigraph implements algorithms for partitioning graphs into districts of approximately equal weight. It uses random spanning trees to find transfer moves between partitions and iteratively improve divisions to meet weight constraints.

## Features

- **Uniform Random Spanning Trees**: Implementation of Wilson's algorithm for generating uniformly random spanning trees
- **Weight-Balanced Partitioning**: Divide graphs into districts with configurable weight constraints
- **Iterative Improvement**: Refine partitions through random spanning tree-based transfers
- **Flexible Weight Functions**: Support for custom node weight functions or node attributes

## Installation

```bash
pip install partigraph
```



## Algorithm

Partigraph uses a divide-and-conquer approach:

1. Generate a random spanning tree of the graph using Wilson's algorithm
2. Find the edge cut that best divides the graph into the target weights
3. Recursively partition each side
4. Iteratively improve the partition by finding beneficial transfers between districts

The random spanning tree approach ensures good connectivity properties and helps avoid gerrymandering-like artifacts.

## Requirements

- Python >= 3.12
- NetworkX

## License

MIT License - see LICENSE file for details

## References

Wilson's algorithm for uniform random spanning trees:
- Wilson, D. B. (1996). "Generating Random Spanning Trees More Quickly than the Cover Time"
ngen-apigw 0.1.4
GitOps-friendly API Gateway Configuration Tool
License: MIT
Requires Python: >=3.7
Keywords: cli, apigateway, gitops, api

# ngen-apigw

GitOps-friendly API Gateway Configuration Tool.

## Description

`ngen-apigw` is a CLI and web server tool designed to manage API Gateway configurations in a GitOps workflow. It supports migrating monolithic `apigateway.json` files into manageable partial configurations, serving a local development environment to visualize changes, and checking KrakenD configurations.

## Features

-   **Migrate**: Convert monolithic configuration to host-grouped partials.
-   **Server**: Local web interface to view and manage endpoints.
-   **Check**: Validate KrakenD configurations.
-   **GitOps**: Built for version control and automated deployments.

## Installation

```bash
pip install ngen-apigw
```

## Usage

```bash
apigw --help
```

### Commands

-   `apigw migrate`: Migrate `apigateway.json` to partials.
-   `apigw server`: Start the web interface.
-   `apigw check`: Validate configuration logic.
-   `apigw merge`: Merge partials back into a single JSON file.