semvec/pypi-packages huggingface dataset:
CelluKeyGA 0.1.0
A Python library that integrates **Cellular Genetic Algorithm (Cellular GA)** with **Biased Random-Key Genetic Algorithm (BRKGA)** to enhance optimization capabilities.
Requires Python: >=3.6

![Python](https://img.shields.io/badge/Python-3.8%2B-blue?style=flat-square&logo=python)
[![License](https://img.shields.io/github/license/SevgiAkten/pycellga)](https://github.com/SevgiAkten/CelluKeyGA/blob/main/LICENSE)
[![Doc](https://img.shields.io/badge/docs-dev-blue.svg)](https://sevgiakten.github.io/CelluKeyGA/)
![Status](https://img.shields.io/badge/Status-Development-orange?style=flat-square)
![Repo Size](https://img.shields.io/github/repo-size/SevgiAkten/pycellga)
![GitHub Contributors](https://img.shields.io/github/contributors/SevgiAkten/CelluKeyGA)
[![PyPI version](https://img.shields.io/pypi/v/CelluKeyGA.svg)](https://pypi.org/project/CelluKeyGA/)


Note: This section is under development......


# CelluKeyGA

🚀 **CelluKeyGA** is a Python library that integrates **Cellular Genetic Algorithm (Cellular GA)** with **Biased Random-Key Genetic Algorithm (BRKGA)** to enhance optimization capabilities. This project aims to provide a flexible and efficient evolutionary computing framework for solving complex optimization problems.

## 🔹 Features
- Combines **Cellular GA** and **BRKGA** for improved solution diversity and performance.
- Designed for solving **combinatorial and continuous optimization** problems.
- **Modular and extensible** structure for easy customization.

## 🛠️ Applications
CelluKeyGA can be applied in various domains, including:
- ✅ Scheduling and routing problems.
- ✅ Machine learning hyperparameter optimization.
- ✅ Engineering design optimization.
- ✅ Any problem requiring robust metaheuristic search strategies.

## 📦 Installation
```bash
pip install CelluKeyGA 
```

## 🚀 Getting Started
```python
from cellukeyga import CelluKeyGA

# Example usage
ckga = CelluKeyGA()
ckga.run()
```

## 📂 Roadmap
- [ ] Implement core algorithm.
- [ ] Add benchmark test problems.
- [ ] Provide detailed documentation.
- [ ] Integrate with pymoo.

## 🤝 Contributing
Contributions are welcome! Feel free to open issues and pull requests.

## 📜 License
MIT License (or any other license you prefer).
spelis-sgui 0.1.0
Lightweight and easy-to-use Immediate Mode GUI library for Python and Raylib
Requires Python: >=3.8

# SGUI - Spelis's GUI Library 
![PyPI - Version](https://img.shields.io/pypi/v/spelis_sgui)
![PyPI - Python Version](https://img.shields.io/pypi/pyversions/spelis_sgui)
![GitHub repo size](https://img.shields.io/github/repo-size/spelis/sgui)


A lightweight and easy-to-use GUI library inspired by the [ImGui](https://github.com/ocornut/imgui) library. The library is written in Python and uses the [Raylib](https://github.com/raysan5/raylib) library for rendering.

[Documentation](https://sgui.readthedocs.io/en/latest/)

### Contributions are very welcome! :D

## Features
- Minimal dependencies
- Easy to use and integrate

## Installation
1. Install the package: `pip install spelis-sgui`
2. Import the library: `import sgui as gui`
3. If something went wrong and raylib (pyray) isnt installed, run this command: `pip install raylib`

## Example Usage
```python
import sgui as gui
from pyray import * # Raylib

init_window(800,600,"SGUI Example")
gui.init() # initialize the library after raylib
win = gui.Window(10,10,150,150,"My Window!") # create a window

while not window_should_close(): # raylib drawing functions
    begin_drawing()
    clear_background(BLACK)
    gui.NotifTick() # update the notifications (optional)
    with win: # this is a context manager that sets the window as the current window
        gui.label("Hello World!") # displays a little label inside the window
    end_drawing()

close_window()
```
runcrate 0.6.1
Workflow Run RO-Crate toolkit
Requires Python: <4,>=3.9
Keywords: ro-crate, workflow, provenance, CWL, CommonWL

Runcrate is a software toolkit to manipulate `Workflow Run RO-Crate <https://www.researchobject.org/workflow-run-crate/>`_ packages. Documentation is at http://www.researchobject.org/runcrate/.
proxy-api-package 0.1.1
A Python client for interacting with a REST API
Requires Python: >=3.6


# Proxy API Documentation

## Overview

The Proxy API is a Python client for interacting with a REST API. It provides a simple interface for performing CRUD operations and supports authentication via JWT.

## Features

- Authentication using JWT
- CRUD operations for various resources
- Filtering and excluding resources
- Error handling with logging

## Installation

To use the Proxy API, simply copy the code into your Python environment. Ensure you have the required dependencies installed:

```bash
pip install requests pandas
```

## Usage

### Initialization

Initialize the `APIClient` with the base URL of your API. You can also pass an optional token for authentication.

```python
from api_client import APIClient

# Initialize the API client
client = APIClient(base_url='http://localhost:3000')

# Authenticate (if required)
client.login(email="john@example.com", password="secret")
```

### Resource Operations

The `APIClient` initializes proxies for various resources. You can perform operations like fetching all resources, filtering, and excluding specific IDs.

```python
# Get all users
users = client.user.all()

# Get users from ID 1 to 10
users_range = client.user.all()[1:11]

# Exclude users with IDs 7, 8, 9 and get all reamining users
users_excluded = client.user.exclude([7, 8, 9])

# Filter stations by date range
stations = client.station.filter(start_date="2025-01-01", end_date="2025-12-31")
```

### Error Handling

The API client logs errors and raises exceptions when API requests fail. This ensures that issues are bubbled up to the caller for handling.

## API Reference

### Classes

- `APIClient`: Main client for interacting with the API. Handles authentication and resource operations.
- `ResourceProxy`: Proxy for performing operations on a specific resource. Supports CRUD operations and filtering.

### Methods

- `APIClient.login(email: str, password: str)`: Authenticate and obtain a JWT token.
- `ResourceProxy.all()`: Fetch all resources.
- `ResourceProxy.get(id: Union[int, str])`: Fetch a single resource by ID.
- `ResourceProxy.filter(**kwargs)`: Filter resources by query parameters.
- `ResourceProxy.exclude(ids: List[int])`: Fetch all resources excluding specified IDs.

## License

This project is licensed under the MIT License.
venv-py 0.1.1
virtual environment lifecycle manager
Requires Python: >=3.8

# 🐍 Virtual Environment Manager 

[![Python Versions](https://img.shields.io/badge/python-3.8%20%7C%203.9%20%7C%203.10%20%7C%203.11%20%7C%203.12-blue.svg)](https://pypi.org/project/virtual-env-manager/)
[![License](https://img.shields.io/badge/License-MIT-green.svg)](LICENSE)
[![Build Status](https://img.shields.io/badge/build-passing-brightgreen.svg)]()
[![Code Style](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

## 🌟 Elevate Your Python Development Workflow

`venv_py` virtual environment lifecycle manager.

---

### ✨ Key Features

- 🚀 **Effortless Environment Management**
  - Create and run commands in virtual environments on the fly
  - Cross-platform support (Windows and Unix-like systems)

- 🔍 **Smart Consistency Checking**
  - Validate environment configurations
  - Ensure package and file integrity

- 🛡️ **Robust Error Handling**
  - Detailed logging
  - Comprehensive error messages

- 🔧 **Flexible Command Execution**
  - Run commands directly within virtual environments
  - Retrieve and inspect command results

---
### Usage

```python
from venv_py import EnvManager

# Installing libraries
EnvManager(".some_env").run("pip", "install", "requests", "pandas").result()

# Reset the state, flushing libraries
EnvManager(".some_env").flush().run("python script.py").result()

```

### Context Manager Usage

```python
with EnvManager(".venv") as venv:
    # Automatic environment lifecycle management
    venv.run("python", "my_script.py").result()
```

## 📦 Requirements

- **Python**: 3.8+
- **Platforms**: Windows, macOS, Linux

---

## 🤝 Contributing

1. 🍴 Fork the repository
2. 🌿 Create a feature branch
3. 🔨 Make your changes
4. ✅ Run tests
5. 📤 Submit a pull request

---

## 📄 License

[MIT License](LICENSE) - Free to use, modify, and distribute

---

## 🌈 Powered By

- Pure Python
- Standard Library
- Community Love ❤️
zeit.msal 1.3.1
Microsoft Azure AD authentication helper for CLI applications

=========
zeit.msal
=========

Helper to authenticate against Microsoft Azure AD and store the resulting tokens for commandline applications.

Usage
=====

1. Run interactively to store a refresh token in the cache
2. Use in e.g. automated tests to retrieve an ID token from the cache (which automatically refreshes it if necessary).

::

    $ msal-token --client-id=myclient --client-secret=mysecret \
        --cache-url=file:///tmp/msal.json login
    Please visit https://login.microsoftonline.com/...
    # Perform login via browser


    def test_protected_web_ui():
        auth = zeit.msal.Authenticator(
            'myclient', 'mysecret', 'file:///tmp/msal.json')
        http = requests.Session()
        http.headers['Authorization'] = 'Bearer %s' % auth.get_id_token()
        r = http.get('https://example.zeit.de/')
        assert r.status_code == 200


Alternatively, retrieve the refresh token after interactive login, and use that in tests::

    auth.login_with_refresh_token('myrefreshtoken')


1.3.1 (2025-02-18)
------------------

Changes
+++++++

- Update to non-deprecated msal search API (msal)


zeit.msal changes
=================

1.4.0 (unreleased)
------------------

- Nothing changed yet.


1.3.0 (2025-02-17)
------------------

- Update to current msal API when requesting an ID token


1.2.1 (2024-03-28)
------------------

- Dilligently close file handles


1.2.0 (2024-03-21)
------------------

- Preserve query parameters in redis url


1.1.0 (2021-07-28)
------------------

- Add `get_access_token` method, make scopes configurable

- Implement redis cache


1.0.0 (2021-07-23)
------------------

- Initial release
yaml-editor 0.1.8
A web-based YAML editor with tabular interface
Requires Python: <4.0,>=3.7

# YAML Editor

A web-based YAML editor with a tabular interface that makes it easy to view and edit YAML files.

## Features

- Web-based interface for editing YAML files
- Tabular view of YAML data
- Add and delete rows
- Search functionality
- Real-time editing
- File browser for YAML files

## Installation

Install using pip:

```bash
pip install yaml-editor
```

Or install from source using Poetry:

```bash
git clone https://github.com/yourusername/yaml-editor.git
cd yaml-editor
poetry install
```

## Usage

Start the YAML editor by running:

```bash
yaml-editor
```

Options:
- `--host`: Host to bind the server to (default: 127.0.0.1)
- `--port`: Port to bind the server to (default: 8000)
- `--dir`: Directory containing YAML files (default: current directory)

Example:
```bash
yaml-editor --host 0.0.0.0 --port 8080
```

Once started, open your web browser and navigate to the displayed URL to use the YAML editor.