semvec/pypi-packages huggingface dataset:
kurlui 0.2
A simple UI library inspired by Rayfield
Requires Python: >=3.6

# KurlUI

KurlUI is a Python UI library inspired by the Roblox Rayfield library, built with Tkinter.

## Installation

```sh
pip install kurlui
```

## Usage

```python
from kurlui import KurlUI 

def on_button_click():
    print("Button Clicked!")

ui = RayfieldUI()
tab = ui.create_tab("Main")
ui.add_button(tab, "Click Me", on_button_click)
ui.run()
```
imitatio-ostendendi 0.2.0
Mock widgets for tkinter/ttk testing (Latin: Display Imitation)
Requires Python: >=3.7

# Imitatio Ostendendi

*Latin for "Display Imitation" - A comprehensive mocking library for tkinter/ttk testing*

## Features

- Mock implementations of common tkinter/ttk widgets
- Support for basic widget operations (insert, delete, configure)
- Event simulation capabilities
- Logging for better test debugging
- Easy integration with unittest.mock

## Installation

```bash
pip install imitatio-ostendendi
```

## Usage

```python
from imitatio_ostendendi.widgets import Text, Entry, Button
from imitatio_ostendendi.constants import END, NORMAL, DISABLED

class TestMyGUIApp(TestCase):
    def setUp(self):
        # Create mock widgets
        self.text = Text()
        self.entry = Entry()
        self.button = Button()
        
    def test_text_operations(self):
        # Insert text
        self.text.insert("1.0", "Hello World")
        self.assertEqual(self.text._text, "Hello World")
        
        # Delete text
        self.text.delete("1.0", END)
        self.assertEqual(self.text._text, "")
        
    def test_entry_state(self):
        # Test state changes
        self.entry.configure(state=DISABLED)
        self.assertEqual(self.entry._state, DISABLED)
```

## Widget Support

Currently supported widgets:
- Text
- Entry
- Button
- Frame
- LabelFrame
- Label
- Scrollbar
- Notebook
- StringVar
- IntVar
- BooleanVar

## Why "Imitatio Ostendendi"?

The name comes from Latin:
- "Imitatio" meaning "imitation" or "mock"
- "Ostendendi" meaning "to display" or "to show"

Together, they form "Display Imitation" - a fitting name for a library that provides mock implementations of display widgets.

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## License

This project is licensed under the MIT License - see the LICENSE file for details.
culligan 1.1.5
Python API for Culligan products
Requires Python: >=3.10

# Culligan
A discovery for Culligan smart water products

# Water Softener
The Excel sheet contains a listing of endpoints and what is needed for interaction with the Aylanetworks API. This data was gathered from proxy traffic. 

The powershell module is a way to interact with the endpoints via Powershell.

The python code is for packageability and publishing to PyPi as a module.

The softener does have an http webpage for wifi status and connect/disconnect. 
Local control of the device does not seem possible without understanding how Ayla sends commands to the device.

# Ayla References
This device is integrated by/with Ayla Networks and (generally) uses their documentation. 

See [Ayla-iot-unofficial](https://github.com/rewardone/ayla-iot-unofficial)

## Local Wifi Module Doc
Direct doc linked from the reference above: [salesforce doc](https://ayla.my.salesforce.com/sfc/p/#F00000005wvT/a/2A000000ZKSc/k2aXubMGof8Gooqm.nGLRqd.vyluxZLK9Qwe9xWUphQ)


## Installation
From PyPi
```bash
pip install culligan
```

Build from source
```bash
pip install build
pip build
pip install culligan
```

## Library Requirements
Requires typical http interaction and datatype packages like requests, aiohttp, ujson, and the ayla-iot-unofficial module to handle devices and communication.

## User Requirements
Reqiures a username and password (typically a smart device's app login credentials).
The Culligan specific app_id is included in the package (obtained from the Culligan app).

## Usage
### Class Object
Instantiate a new class object through new_culligan_api() or Culligan() directly.


### Access Tokens
The Culligan() object will call sign_in() automatically to obtain Culligan IoT and Ayla access_tokens. 
Then, it will instantiate an AylaApi() object with the Ayla access_token (no sign_in() required). 

Use Culligan for communication with the Culligan IoT domain.
Use the Ayla property of the Culligan object for direct communication with Ayla Networks.

### Devices
Gather devices by calling the Ayla.get_devices().

By default, calling get_devices() will return a list of class specific device objects with updated properties for use.

See ayla-iot-unofficial/device.py for implemented device classes.

## Typical Operation
```python
python3 -m pip install Culligan
```

```python
import Culligan

USERNAME = 'me@email.com'
PASSWORD = '$7r0nkP@s$w0rD'

CulliganApi = new_culligan_api(username, password)
CulliganApi.sign_in()
CulliganApi.Ayla = CulliganApi.get_ayla_api()

device_list = CulliganApi.Ayla.list_devices()
devices = CulliganApi.Ayla.get_devices()

# Example Water Softener Devices
softener = devices[0]

softener.capacity_remaining_gallons
softener.set_vacation_mode()
```

## License
[MIT](https://choosealicense.com/licenses/mit/)
PDF-Mind 0.1.0
Agent for extracting structured content from PDFs using LangGraph
Requires Python: <4.0,>=3.10

# PDFMind

An agent for extracting structured content from PDFs using LangGraph and OpenAI.

## Features

- Extract and format text content from PDFs
- Convert tables to markdown format
- Extract images with AI-generated descriptions
- Use LangGraph for agent-based orchestration

## Setup

```bash
# Install Poetry if you don't have it
curl -sSL https://install.python-poetry.org | python3 -

# Install dependencies
poetry install

# Install other dependencies
brew install ghostscript
brew install poppler
# apt install ghostscript poppler
```

## Usage

```python
from pdf_agent import PDFExtractionAgent

agent = PDFExtractionAgent()
result = agent.process("path/to/document.pdf")
print(result)
```

Alternatively, look at [example.py](example.py) for an example that will output metadata on extracted items and token usage:

## Development

```bash
# Run tests
poetry run pytest

# Lint code
poetry run ruff check .
poetry run black .
```
PyCockByEmir 0.1.0
Boy ve ayak uzunluğu hesaplamaları için bir Python kütüphanesi
Requires Python: >=3.6

# PyCockByEmir

Bu kütüphane, boy uzunluğu ve ayak uzunluğu oranını hesaplar. :D

## Kullanım

Python'da bu kütüphaneyi kullanarak boy uzunluğu ve ayak uzunluğu oranını hesaplayabilirsiniz.

### Örnek Kullanım:

```python
from PyCockByEmir import calculate_ratio

sonuc = calculate_ratio(180, 25)
print(sonuc)