semvec/pypi-packages huggingface dataset:
groupbyScore 0.0.5
You can group similar items (e.g., strings or dict fields) using the fuzzywuzzy package by comparing their similarity scores.
Requires Python: >=3.9

# 🔍 `groupbyScore` – Group Similar Items Using Fuzzy Matching in Python

[![GitHub](https://img.shields.io/badge/GitHub-Repo-181717?style=for-the-badge\&logo=github\&logoColor=white)](https://github.com/postboxat18/groupbyScore.git)

## Overview

`groupbyScore` is a Python function that groups similar records from a list of dictionaries using fuzzy matching. It utilizes the **`rapidfuzz`** package for high-performance string similarity scoring.

---

## 📦 Dependencies

* Python 3.6+
* [`rapidfuzz`](https://github.com/maxbachmann/RapidFuzz)

Install with:

```bash
pip install rapidfuzz
```

---

## 🚀 Function Signature

```python
groupbyScore(all_data, score, key)
```

### Parameters

* `all_data` (`List[dict]`): A list of dictionaries to be grouped.
* `key` (`Callable`): A function returning a tuple of values (e.g., `lambda x: (x["Notes"], x["page_num"])`) used to compare and group.

---

## ⚙️ How It Works

1. Iterates over all item pairs in the dataset.
2. Compares each field in the `key(...)` tuple:

   * **Strings**: `fuzz.partial_ratio` > 80
   * **Integers**: must match exactly
3. Groups items where **all** key fields match.
4. Yields:

   * the group key
   * the list of matching items

---

## ✅ Example Usage

```python
from groupbyScore.groupbyScore import groupbyScore

data = [
    {"Notes": "Chest Pain", "page_num": 1},
    {"Notes": "chest pain", "page_num": 1},
    {"Notes": "church", "page_num": 1},
    {"Notes": "Fever", "page_num": 2},
    {"Notes": "feverish", "page_num": 2}
]
# TUPLE
for key, group in groupbyScore(data, key=lambda x: (x["Notes"], x["page_num"]),score=90):
    print("Group Key:", key)
    print("Group Items:", group)
# STR
for key, group in groupbyScore(data, key=lambda x: x["Notes"],score=90):
    print("Group Key:", key)
    print("Group Items:", group)

```

---

## 📤 Example Output

```
#### OUTPUT 1
Group Key: ('Chest Pain', 1)
Group Items: [{'Notes': 'Chest Pain', 'page_num': 1}, {'Notes': 'chest pain', 'page_num': 1}]

Group Key: ('church', 1)
Group Items: [{'Notes': 'church', 'page_num': 1}]

Group Key: ('Fever', 2)
Group Items: [{'Notes': 'Fever', 'page_num': 2}, {'Notes': 'feverish', 'page_num': 2}]

#### OUTPUT 2
Group Key: Chest Pain
Group Items: [{'Notes': 'Chest Pain', 'page_num': 1}, {'Notes': 'chest pain', 'page_num': 1}]

Group Key: church
Group Items: [{'Notes': 'church', 'page_num': 1}]

Group Key: Fever
Group Items: [{'Notes': 'Fever', 'page_num': 2}, {'Notes': 'feverish', 'page_num': 2}]
```

---

## 📎 GitHub

🔗 [https://github.com/postboxat18/groupbyScore.git](https://github.com/postboxat18/groupbyScore.git)
aerofs 4.0.7
High-Performance Asynchronous File I/O for Python, powered by Rust
Requires Python: >=3.9
Keywords: async, file, io, rust, tokio, performance

# aerofs

<div align="center">
  <p><strong>High-Performance Asynchronous File I/O for Python</strong></p>
  <p>Powered by Rust, Tokio, and PyO3.</p>

  <p>
    <a href="https://pypi.org/project/aerofs/"><img src="https://img.shields.io/pypi/v/aerofs.svg" alt="PyPI"></a>
    <a href="https://github.com/ohmyarthur/aerofs/actions"><img src="https://github.com/ohmyarthur/aerofs/workflows/Release/badge.svg" alt="Release"></a>
    <a href="https://opensource.org/licenses/Apache-2.0"><img src="https://img.shields.io/badge/License-Apache%202.0-blue.svg" alt="License"></a>
  </p>
</div>

---

**aerofs** brings the power of Rust's asynchronous I/O to Python. By leveraging `tokio` and `PyO3`, it provides a non-blocking, thread-safe, and highly performant filesystem interface for `asyncio` applications.

> **Full documentation at the [Documentation Site](https://ohmyarthur.github.io/aerofs/).**

## Installation

```shell
pip install aerofs
```

## Quick Start
```python
import aerofs
import asyncio

async def main():
    async with aerofs.open('hello.txt', 'w') as f:
        await f.write('Hello via Rust!')

    async with aerofs.open('hello.txt', 'r') as f:
        print(await f.read())

if __name__ == "__main__":
    asyncio.run(main())
```

## Documentation

Guides and API references are available in the `docs/` directory or online:

- [Getting Started](https://ohmyarthur.github.io/aerofs/guide/getting-started.html)
- [File Operations](https://ohmyarthur.github.io/aerofs/guide/file-operations.html)

## License

Apache 2.0 License.
pyliblens 1.0.1
This is a lightweight utility library designed to audit your Python environment
Requires Python: >=3.12

# pyLibLens
This is a lightweight utility library designed to audit your Python environment. It scans your installed packages and requirement files to identify outdated versions and provide a summary

## Installation
```commandline
pip install pyliblens
```


## Usage
This lib can be used as both cli tool as well as python lib.

Using in Python 

```
from pyliblens import analyze_packages
# Need to provide the project source if the current file is not in the root directory
packages = analyze_packages()
```

using cli (use --help for details)

```commandline
pyliblens
```

for report export use below commands
```commandline
pip install pyliblens[report]
pyliblens -ex
```
this will create a index.html report for use.
bioamla 0.1.8
Bioacoustics & Machine Learning Applications
Requires Python: >=3.8

# bioamla

A Python CLI and library for Bioacoustics and Machine Learning Applications.

> **Prerelease Notice:** This is a prerelease version. Do not use on production data.

## Citation

```bibtex
@software{bioamla,
  author = {McMeen, John},
  title = {Bioamla: Bioacoustics and Machine Learning Applications},
  year = {2025},
  url = {https://github.com/jmcmeen/bioamla}
}
```

## License

This project is licensed under the GNU General Public License v3.0 - see the [LICENSE](LICENSE) file for details.