semvec/pypi-packages huggingface dataset:
kewkew 0.1.2
A tiny queue library leveraging asyncio
Requires Python: >=3.8

# kewkew

[![PyPI version](https://badge.fury.io/py/kewkew.svg)](https://badge.fury.io/py/kewkew)
[![License](https://img.shields.io/pypi/l/kewkew.svg)](https://pypi.org/project/kewkew/)

A tiny queue library leveraging asyncio for background tasks or scripting

## Install

You can install `kewkew` via pip.

```bash
python -m pip install kewkew
```

You can also download the `kewkew/kew.py` source from this repo. There are no external dependencies to worry about.

## Usage

The `Kew` class is meant to be a parent class. At a minimum, the child class needs to implement an async worker method which must do two things:

- Take a single argument that accepts data from the queue
- Returns a boolean if the data was processed successfully and can be removed from the queue

Here is a minimum viable implementation.

```python
from kewkew import Kew

class MyKew(Kew):
    async def worker(self, data) -> bool:
        print(data)
        return True
```

We then have two main ways of using the queue. `Kew` provides both sync and async methods to add items to the queue and tell the queue to finish processing (for a graceful shutdown).

This first example uses the sync calls so everything can be run in an interactive environment.

```python
from mykew import MyKew

kew = MyKew()
for i in range(100):
    kew.add_sync(i)
kew.finish_sync()
```

This second example uses the async calls within a coroutine.

```python
import asyncio as aio

async def main():
    kew = MyKew()
    for i in range(100):
        await kew.add(i)
    await kew.finish()

aio.run(main)
```

You can see this and an async database processing example in the [examples folder](examples/).

## Debug

Python Queues have a tendency to swallow runtime exceptions. You can debug your worker more easily by calling it directly.

```python
import asyncio as aio
from mykew import MyKew

kew = MyKew()
aio.run(kew.worker(1))
```
gamry-file-parser 0.1.0
A parser for Gamry EXPLAIN-formatted DTA files with neural interface specific data analysis
Requires Python: >=3.8

# GamryParser

GamryParser is a modular, Python-based toolkit for parsing, analyzing, and visualizing electrochemical data from Gamry `.DTA` files. It supports both local analysis and interactive visual exploration through Pyodide and Streamlit.

[![License](https://img.shields.io/github/license/maxtenenbaum/GamryParser)](LICENSE)
[![Python](https://img.shields.io/badge/python-3.9+-blue)](https://www.python.org/)

---

## Features

- 🔬 **Parse Gamry .DTA files** into clean pandas DataFrames
- 🌐 **Web viewer** powered by Pyodide (runs entirely in-browser)
- 📊 **Streamlit dashboard** for long-term studies and interactive analysis
- 🧪 Easy to test, extend, and integrate into research workflows

---