semvec/pypi-packages huggingface dataset:
chgksuite 0.28.2
A package for chgk automation
Requires Python: >=3.9

**chgksuite** is an utility that helps chgk editors.

[Chgk](https://en.wikipedia.org/wiki/What%3F_Where%3F_When%3F) (short for Chto? Gde? Kogda?) is a popular russian quiz.

Project home on gitlab: https://gitlab.com/peczony/chgksuite

Documentation (in Russian): https://peczony.gitlab.io/chgksuite
pysamsungnasa 1.2.0
Connect to Samsung ASHP / AC units over NASA via RS485
Requires Python: >=3.13.0

# pysamsungnasa

[![Tests](https://github.com/pantherale0/pysamsungnasa/actions/workflows/test.yml/badge.svg)](https://github.com/pantherale0/pysamsungnasa/actions/workflows/test.yml)
[![codecov](https://codecov.io/gh/pantherale0/pysamsungnasa/branch/main/graph/badge.svg)](https://codecov.io/gh/pantherale0/pysamsungnasa)

A Python library to communicate with Samsung heat pumps, in theory both cool only and cool+heat units are supported, although only tested on an EHS unit (cool+heat)

## Features

- Connect and disconnect from Samsung HVAC/EHS units via a TCP socket over the F1/F2 connectors (NasaClient).
- Discover new devices on the NASA network and manage known devices (SamsungNasa).
- Send commands to devices and handle responses (SamsungNasa, NasaClient).
- Parse incoming data packets from devices (NasaPacketParser, various message classes).
- Represent devices with attributes and control their functions (NasaDevice, DhwController, ClimateController).
- Control DHW (Domestic Hot Water) settings like power, operation mode, and target temperature (DhwController).
- Control climate settings like power, mode, target temperature, fan speed, and more (ClimateController).
- Provide a mechanism for callbacks to be notified of device and packet updates (NasaDevice).
- Support reading device configurations (NasaDevice).
- Handle message construction and parsing based on message types (protocol.factory).
- Define specific message formats for indoor and outdoor units (protocol.factory.messages).

## Future plans

These might not end up happening, but I would like to have a go at creating these one day.

- Simulate a remote controller for a "dummy" zone 2
- Send custom Z1/Z2 temperature readings to the master controller
- Implement TPI/load awareness/preditive model algorithms for an advanced complete custom controller

## Installation

```bash
pip install pysamsungnasa
```

## Usage

TODO

## Configuration

TODO

## Contributing

TODO

## Thanks

This project utilizes or incorporates ideas, code and work from the following sources,
and I would like to express my sincere gratitude to their creators and contributors:

- [ESPHome Samsung HVAC Bus](https://github.com/omerfaruk-aran/esphome_samsung_hvac_bus/)
- [Samsung NASA MQTT Bridge](https://github.com/70p4z/samsung-nasa-mqtt/)
- [Samsung ASHP NASA link MQTT bridge / Home Assistant](https://community.openenergymonitor.org/t/contribution-samsung-ashp-nasa-link-mqtt-bridge-home-assistant)
- [OpenEnergyMonitoring Forum](https://community.openenergymonitor.org/search?q=samsung) for all the shared wisdom on multiple threads.
- @betaphi for the [EHS Wiki](https://wiki.myehs.eu/wiki/Main_Page), which provided valuable insights into different messages. The protocol is mostly documented [here](NOTES.md) as the NASA Protocol page is no longer on the wiki. More messages are defined within the parser classes from the latest version of S-Net.

None of this would have been possible without the above.
TCAMpy 0.1.1
Cellular Automaton Model for Tumor Growth
Requires Python: >=3.12

# TCAMpy

This is a single python module for a cellular automaton, modeling tumor growth. The user can set the parameters, create unique initial states, view and save statistics, save data and also use a streamlit dashboard as a graphical interface. Growth plots, histograms and animation is available for visualization in an easy to use way. (Online version available here, without writing a single line a code: [Online dashboard](https://tcampy.streamlit.app/).)

The theoretical background for this model is based on the work of Carlos A Valentim, José A Rabi and Sergio A David. I expanded this model by simulating an immune response during the growth of the tumor cells, as well as random mutations, influencing tumor survival. Other ideas, like nutrition may also be implemented in the future. There are also basic Machine Learning functions for dataset generation, model training, and predicting tumor size or confluence based on a new set of parameters.

Valentim CA, Rabi JA, David SA. Cellular-automaton model for tumor growth dynamics: Virtualization of different scenarios. Comput Biol Med. 2023 Feb;153:106481. doi: 10.1016/j.compbiomed.2022.106481. Epub 2022 Dec 28. PMID: 36587567.
(url: https://pubmed.ncbi.nlm.nih.gov/36587567/)

This documentation provides detaild description on how to use the module, with example codes and links to example files. Detailed description is available in the uploaded paper: [to be uploaded]

## Example Results

Visualization from running a single model. If enabled, the user recieves an image of the growth, a map for mutations, a line graph of cell numbers over time and a histogram of proliferation potentials.

![Plot example](https://github.com/Fetasalyt/TCAMpy/blob/main/Images/single_example.png?raw=true)

Animation is available to turn on when running the model as well. Visualizing a dataframe containing results from multiple model executions is also possible. A cell number line graph of the average numbers
and a histogram of the average proliferation potentials can be plotted with standard deviations.

![Averages plot example](https://github.com/Fetasalyt/TCAMpy/blob/main/Images/avg_example.png?raw=true)

---

## Links

- [Homepage](https://github.com/FetasaLYt/TCAMpy)
- [Documentation](https://tcampy.readthedocs.io/en/latest/)
- [Online dashboard](https://tcampy.streamlit.app/)
- [Repository](https://github.com/FetasaLYt/TCAMpy)
- [Issues](https://github.com/FetasaLYt/TCAMpy/issues)