semvec/pypi-packages huggingface dataset:
yuquedd 1.0.3
Tool for converting yuque.com knowledge base documents to markdown documents.
License: MIT
Requires Python: >=3.8

<p align="center">
  <h3 align="center">欢迎来到 YuQueDD</h3>
  <p align="center">
    <a href="https://github.com/gupingan/yuquedd/main.py">查看Demo</a>
    ·
    <a href="https://github.com/gupingan/yuquedd/issues">报告Bug</a>
    ·
    <a href="https://github.com/gupingan/yuquedd/issues">提出新特性</a>
  </p>
</p>

<p align="center">
  <img src="https://img.shields.io/badge/language-python-brightgreen" alt="Language">
  <a href="https://github.com/gupingan/yuquedd/graphs/contributors">
    <img src="https://img.shields.io/github/contributors/gupingan/yuquedd.svg" alt="Contributors">
  </a>
  <a href="https://github.com/gupingan/yuquedd/network/members">
    <img src="https://img.shields.io/github/forks/gupingan/yuquedd.svg?style=flat" alt="Forks">
  </a>
  <a href="https://github.com/gupingan/yuquedd/stargazers">
    <img src="https://img.shields.io/github/stars/gupingan/yuquedd.svg?style=flat" alt="Stargazers">
  </a>
  <a href="https://github.com/gupingan/yuquedd/issues">
    <img src="https://img.shields.io/github/issues/gupingan/yuquedd.svg" alt="Issues">
  </a>
  <a href="https://github.com/gupingan/yuquedd/blob/master/LICENSE">
    <img src="https://img.shields.io/github/license/gupingan/yuquedd.svg" alt="MIT License">
  </a>
</p>

## 目录

- [简述](#简述)
- [安装模块](#安装模块)
  - [本地](#1-本地)
  - [网络](#2-网络)
- [快速使用](#快速使用)

## 简述

`yuquedd` 是一个基于 `Python` 开发、可以将语雀的公共知识库 `html` 文档转为 `markdown` 文档格式的工具，尽管无法百分百还原，但是已经足够使用。

注意：本项目采用 MIT 许可证。请查看 [LICENSE](https://github.com/gupingan/yuquedd/blob/main/LICENSE) 文件以了解更多信息。

> 本项目为开源项目，仅供学习研究使用，如若商用或者其他用途，请使用其他模块，使用本模块产生的任何纠纷与作者无关。
>
> 如该项目侵犯到贵司或组织的相关权益，请尽快联系我删除。


## 安装模块

### 1. 本地

如果您不想从源代码安装，您可以直接安装发布到 GitHub Releases 页面的打包版本。

首先，下载最新的发布包 `yuquedd-x.x.x.tar.gz` 从 [GitHub Releases](https://github.com/gupingan/yuquedd/releases) 页面。

接着，您可以使用 pip 等包管理工具来安装下载的 `.tar.gz` 文件：

```bash
pip install ./yuquedd-x.x.x.tar.gz
```

其中 `x.x.x` 为您下载 `.tar.gz` 文件确版本，并确保指定安装包文件路径是正确的。

### 2. 网络

```bash
pip install yuquedd
```

假如上述命令执行后发生了一些错误，可以选择使用`pip3`命令或者添加镜像源等等方式解决。

## 快速使用

安装完本模块后，您可以按照以下方式使用 `yuquedd`：

```bash
# 在任意终端位置，使用下述命令
yuquedd <url>  # 其中 url 形如：https://www.yuque.com/.../.../...
```

或者，新建一个 python 文件：

```python
import yuquedd

yuquedd.cli_execute(('https://www.yuque.com/.../.../...',))
```
fast-edit-distance 1.2.2
Implementation of edit distance calculation.
License: MIT
Requires Python: >=3.7


# Fast calculation of Edit Distance (ED)
[![](https://img.shields.io/pypi/v/fast-edit-distance)](https://pypi.org/project/fast-edit-distance/)
[![](https://img.shields.io/pypi/dm/fast-edit-distance?label=PyPI%20Downloads)](https://pypi.org/project/fast-edit-distance/)
![](https://img.shields.io/github/license/youyupei/fast_edit_distance)

A implementation of edit distance with improved runtime. Implemented using C and cython.

## Highlight:
This edit distance calculation is significantly faster than most of existing python package.
It enables a max edit distance search, specifically, if you have a query sequence and wanted 
to find the most similar item in a long list, you could set a maximum edit distance and enable
a fast search.

## Installation:
Install using pip:
```
pip install fast-edit-distance
```
or build from source
```
git clone https://github.com/youyupei/fast_edit_distance.git
cd fast_edit_distance
python3 setup.py build
python3 setup.py install --user
```
## Usage:
```
from fast_edit_distance import edit_distance

# example
edit_distance(string1, string2, max_ed=5)
```

## Compare with [Levenshtein.distance](https://maxbachmann.github.io/Levenshtein/levenshtein.html#distance)
The `fast_edit_distance.edit_distance` has the same function as  [Levenshtein.distance](https://maxbachmann.github.io/Levenshtein/levenshtein.html#distance) with significantly improved runtime. Especially when people need to identied pair of strings whose ED are smaller than a number (set `max_ed` in fast_edit_distance.edit_distance). Here is the runtime test with some random sequence (Run the [test/test.py](test/test.py) to reproduce this comparison):
```
Runtime test no max ed cutoff(1_000_000 iteration):
Levenshtein.distance: 46.49s
fast_edit_distance.edit_distance: 12.75s

Runtime test with max ed cutoff 1 (1_000_000 iteration):
Levenshtein.distance: 46.45s
fast_edit_distance.edit_distance: 0.50s
```