semvec/pypi-packages huggingface dataset:
apisix-client 0.5.0
Python sdk for apisix admin api
Requires Python: >=3.9
Keywords: apisix, sdk, neuronum

# Apisix Python Client
[![pypi](https://img.shields.io/pypi/v/apisix_client.svg)](https://pypi.python.org/pypi/apisix_client)
[![license](https://img.shields.io/pypi/l/apisix_client.svg)](https://pypi.python.org/pypi/apisix_client)

The Apisix client Library provides convenient access to the Apisix admin API from applications written in Python.


# Documentation
Explore the Apisix admin API documentation [here](https://apisix.apache.org/docs/apisix/admin-api/).


# Installation

```sh
pip install --upgrade apisix-client
```

# Usage

```python
from apisix_client import ApisixClient

apisix_client = ApisixClient(base_url='YOUR_APISIX_URL', api_key="YOUR_API_KEY")
```
graph-segment 0.0.2
Graph-based image segmentation
Keywords: graph, segmentation, tracking

# Graph Segment Algorithms for Graph Neural Network-based Tracking

### Installation
```bash
pip install graph_segment
```

### Test
Download the data `python3 download_data.py`. And then `./build/bin/walk_through data/debug_graph.dot`.


### Developer Guide
Install a Python virtual environment and activate it:
```bash
python3 -m venv .venv
source .venv/bin/activate
pip install --upgrade pip
pip install cibuildwheel build twine
```

Then you can run
```bash
pipx run cibuildwheel --platform linux
```

### Packing and Uploading
```bash
python3 -m build
twine upload dist/*
```
#### Note
The code was improved by `OpenAI o1Pro` model. The execution time was reduced from 403 ms to 190 ms.
Image-Processing-Peralta 0.0.1
A project that will too a images matchmaking and also show their diferences.
Requires Python: >=3.8

# package_name

Description. 
The package package_name is used to:
   - Processing:
	    - Histogram matching
	    - Structural similarity
        - Resize image
   - Utils:
        - Read image
        - Save image
        - Plot image 
        - Plot result 
        - Plot Histogram
## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install package_name

```bash
pip install image_processing
```

## Usage



## Author
JoÃ£o Filipe

## License
[MIT](https://choosealicense.com/licenses/mit/)
oimalib 0.3
Optical Interferometry Modelling and Analysis Library
Requires Python: >=3.10

# Introduction

oimalib is a package to analyze and modelize optical interferometry data. This package can also read mcfost models and extract interferometric observables (differential visibility amplitudes and phases).

![Python versions](https://img.shields.io/badge/python-3.9%20%7C%203.10%20%7C%203.11-blue.svg)
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/DrSoulain/oimalib/blob/main/LICENSE)

[![CI](https://github.com/DrSoulain/oimalib/actions/workflows/ci.yml/badge.svg)](https://github.com/DrSoulain/oimalib/actions/workflows/ci.yml) [![codecov](https://codecov.io/gh/DrSoulain/oimalib/branch/main/graph/badge.svg?token=7XitVDSK6n)](https://codecov.io/gh/DrSoulain/oimalib)

[![Code style: Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/format.json)](https://github.com/astral-sh/ruff)

## Installation

```shell
python -m pip install .
```

## What can oimalib do for you ?

## Use policy and reference publication

## Acknowledgements
decent-bench 0.2.2
A benchmarking framework for decentralized optimization
Requires Python: >=3.13

<img src="https://raw.githubusercontent.com/team-decent/decent-bench/refs/heads/main/docs/source/_static/logo.png" alt="decent-bench logo" align="right" width="70" />

# Welcome to decent-bench
[![Docs](https://img.shields.io/readthedocs/decent-bench)](
https://decent-bench.readthedocs.io/)
[![PyPI downloads](https://img.shields.io/pypi/dm/decent-bench?label=PyPI%20downloads)](
https://pypi.org/project/decent-bench/)

decent-bench allows you to benchmark decentralized optimization algorithms under various communication constraints,
providing realistic algorithm comparisons in a user-friendly and highly configurable setting.


## Installation
Requires [Python 3.13+](https://www.python.org/downloads/)
```
pip install decent-bench
```


## Author
decent-bench was created by [Elias Ram](https://github.com/elramen/) under the supervision of 
[Dr. Nicola Bastianello](https://bastianello.me/).