semvec/pypi-packages huggingface dataset:
mi-chainlink 0.0.9
A flexible record linkage framework that enables matching between multiple datasets using both exact and fuzzy matching techniques.
Requires Python: <4.0,>=3.10
Keywords: python

# mi-chainlink

A powerful, flexible framework for entity resolution and record linkage using DuckDB as the database engine built upon the work of [Who Owns Chicago](https://github.com/mansueto-institute/who-owns-chi/) by the [Mansueto Institute for Urban Innovation](https://miurban.uchicago.edu/) including the work of [Kevin Bryson](https://github.com/cmdkev), [Ana (Anita) Restrepo Lachman](https://github.com/anitarestrepo16), [Caitlin P.](https://github.com/CaitlinCP), [Joaquin Pinto](https://github.com/joaquinpinto), and [Divij Sinha](https://github.com/divij-sinha). 


This package enables you to load data from various sources, clean and standardize entity names and addresses, and create links between entities based on exact and fuzzy matching techniques.

Source: [https://github.com/mansueto-institute/mi-chainlink](https://github.com/mansueto-institute/mi-chainlink)

Documentation: [https://mansueto-institute.github.io/mi-chainlink/](https://mansueto-institute.github.io/mi-chainlink/)

Issues: [https://github.com/mansueto-institute/mi-chainlink/issues](https://github.com/mansueto-institute/mi-chainlink/issues)

## Overview

This framework helps you solve the entity resolution problem by:

1. Loading data from multiple sources into a DuckDB database
2. Cleaning and standardizing entity names and addresses
3. Creating exact matches between entities based on names and addresses
4. Generating fuzzy matches using TF-IDF similarity
5. Exporting the resulting linked data for further analysis

The system is designed to be configurable through YAML files and supports incremental updates to an existing database.

## Installation

Package is available on PyPI. You can install it using pip or uv:

```bash
pip install mi-chainlink
```

```bash
uv add mi-chainlink
```

## Usage

### Command Line Interface

```bash
# Run interactive session
chainlink

# Run with path to config yaml
chainlink path/to/config.yaml
```

```python
# run as a python function

from chainlink import chainlink

chainlink(
    config: dict, ## dict with config details
    config_path: str | Path = DIR / "configs/config.yaml", ## path to store dict post processing
)
```
RateLimiterX 0.1.1
RateLimiter提供在指定时间内执行指定数量的任务功能，并且可以指定执行速度
Requires Python: >=3.12

# RateLimiterX
RateLimiterX提供在指定时间内执行指定数量的任务功能，并且可以指定执行速度。另外支持以下功能：  
1. 设置执行速率：尽可能平均执行、尽可能快地执行  
2. 支持多个任务队列，每个队列可单独设置任务、速率等，例如多个代理设置不同的速率  

## 使用说明
```
from ratelimiterx.ratelimiterx import RateLimiterX, Task, Speed
def example():
    rl = RateLimiterX(10 * 1000, 10)
    rate_limiterx_queue_id = init_ratelimiterx.create_queue(1000, 5)
    def fun1():
        # do something
        pass

    for i in range(10):
        init_ratelimiterx.add_task(rate_limiter_queue_id, Task(fun1))

    init_ratelimiterx.join()
    init_ratelimiterx.destroy()
```
                                                                       
## 项目说明
### 目录说明
- README.md: 包含使用手册、项目说明

### 执行依赖安装
pip install -r requirements.txt

### 依赖固化
pip freeze > requirements.txt

### 打包
1. pip install build
2. python -m build

### 发布到pypi
1. pip install twine  
2. python -m twine upload --repository pypi dist/*
3. 输入用户名和API Token。
utilsz 0.1.3
Python common utils
Requires Python: >=3.12

# UtilsZ
Python common utils

## 使用说明

                                                                       
## 项目说明
### 目录说明
- README.md: 包含使用手册、项目说明

### 执行依赖安装
pip install -r requirements.txt

### 依赖固化
pip freeze > requirements.txt

### 打包
1. pip install build
2. python -m build

### 发布到pypi
1. pip install twine  
2. python -m twine upload --repository pypi dist/*
3. 输入用户名和API Token。
yzm-util 0.0.2
Tool class
Requires Python: >=3.7
Keywords: tool, util

# yzm_util

> **`File read and write operations`**

This is a simple log package. You can see
[Github-yzm_util](https://github.com/YuZhengM/yzm_util)
[PyPI-yzm_util](https://pypi.org/project/yzm_util/)

## Use

> install

```shell
pip install yzm_util
```

> import

```shell
import yzm_util as yu
```