semvec/pypi-packages huggingface dataset:
my_utilities 0.1.4
Add your description here
Requires Python: >=3.12

# MyUtils 

[![Coverage Status](https://img.shields.io/badge/%20Python%20Versions-%3E%3D3.12-informational)](https://pypi.org/project/orch-serv/)
[![Coverage Status](https://coveralls.io/repos/github/Shchusia/MyUtils/badge.svg?branch=master)](https://coveralls.io/github/Shchusia/MyUtils?branch=master)

[![Coverage Status](https://img.shields.io/badge/Version-0.1.1-informational)](https://pypi.org/project/orch-serv/)
[![Coverage Status](https://img.shields.io/badge/Docs-passed-green)](https://shchusia.github.io/MyUtils/)



> Library with help functions and classes for work

### Installation

```bash
pip install my_utilities
```


What contains:
+ helper functions for working with [iterables](https://github.com/Shchusia/MyUtils/tree/master/my_utilities/iterables/README.MD) objects 
+ helper functions for working with [probability](https://github.com/Shchusia/MyUtils/tree/master/my_utilities/probability/README.MD)
+ helper functions for pretty [view](https://github.com/Shchusia/MyUtils/tree/master/my_utilities/view/README.MD)
+ [mixins](https://github.com/Shchusia/MyUtils/tree/master/my_utilities/mixins/README.MD)
ggshu 0.2.1
Grammar of Graphics for shu.
Requires Python: >=3.10

# ggshu

> ⚠️ This is alpha software and very subject to change!

A utility package to transform dataframes into [shu](https://github.com/biosustain/shu/) data.

![Shu grammar graphics schema](schema.png)

## Example

```python
(
    ggmap(
        df_cond,
        aes(reaction="r", color="flux", size="flux", condition="cond", y="kcat"),
    )
    # plot flux to color and size of reactions
    + geom_arrow()
    # plot kcat as histogram shows on left side of reactions
    + geom_hist(side="left")
    # plot conc to color of metabolites
    + geom_metabolite(aes=aes(color="conc", metabolite="m"))
    # plot km as density plots shows on hover on metabolites
    + geom_kde(aes=aes(y="km"), mets=True)
).to_json("shu_data")
C-healthy 0.2.6
A library for calculating body index and and give advice
Requires Python: >=3.6
Keywords: BMI, BMR, TDEE, INSTRUCT, WHR, LBM, BFP, BBW, IBW, MA, FFMI, RFM, VFR, BSA, VO2MAX, HSI, MMI, BFM, NABMI, NABMR, NATDEE, NAWHR, NALBM, NABFP, NABBW, NAIBW, NAMA, NAFFMI, NARFM, NAVFR, NABSA, NAVO2MAX, NAHSI, NAMMI, NABFM

# C_healthy

C_healthy là thư viện Python để tính toán các chỉ số sức khỏe (BMI, BMR, TDEE, và nhiều chỉ số khác) bên cạnh đó còn đưa ra lời khuyên với chỉ số sức khỏe hiện tại

## Cách cài đặt
```bash
pip install C_healthy
```
## Cách sử dụng 
```bash
from C_healthy import *

bmi = BMI(70, 1.75)
bmr = BMR("nam", 60, 1.75, 18)
tdee = TDEE("nam", 60, 1.75, 18, 3)
lbm = LBM("nam", 70, 1.75)
ffmi = FFMI("nam", 60, 1.7)
rfm = RFM(85, 1.7)
bfp = BFP("nam", 70, 1.75, 20)
ibw = IBW("nam", 1.75)
whr = WHR("nam", 85, 95)
bbw = BBW(60)
ma = MA("nam", 70, 1.7, 18)
vfr = VFR(85, 95)
bsa = BSA(1.7, 60)
vo2max = VO2MAX(110, 60)
hsi = HSI("nam", 60, 1.7, 18, 200, 110)
mmi = MMI("nam", 60, 1.7)
bfm = BFM("nam", 60, 1.7, 18)

print("BMI:", bmi, "\nLời khuyên:", NABMI(bmi))
print("BMR:", bmr, "\nLời khuyên:", NABMR("nam", bmr))
print("TDEE:", tdee, "\nLời khuyên:", NATDEE("nam", tdee))
print("LBM:", lbm, "\nLời khuyên:", NALBM(lbm))
print("FFMI:", ffmi, "\nLời khuyên:", NAFFMI(ffmi))
print("RFM:", rfm, "\nLời khuyên:", NARFM(rfm))
print("BFP:", bfp, "\nLời khuyên:", NABFP(bfp))
print("IBW:", ibw, "\nLời khuyên:", NAIBW(ibw))
print("WHR:", whr, "\nLời khuyên:", NAWHR(whr))
print("BBW:", bbw, "\nLời khuyên:", NABBW(bbw))
print("MA:", ma, "\nLời khuyên:", NAMA(ma))
print("VFR:", vfr, "\nLời khuyên:", NAVFR(vfr))
print("BSA:", bsa, "\nLời khuyên:", NABSA(bsa))
print("VO2MAX:", vo2max, "\nLời khuyên:", NAVO2MAX(vo2max))
print("HSI:", hsi, "\nLời khuyên:", NAHSI(hsi))
print("MMI:", mmi, "\nLời khuyên:", NAMMI(mmi))
print("BFM:", bfm, "\nLời khuyên:", NABFM(bfm))

print(INSTRUCT()) # hàm hướng dẫn 
```

CUỐI CÙNG CẢM ƠN CÁC BẠN ĐÃ TIN DÙNG THƯ VIỆN CỦA MÌNH
metadidomi-server-plus 1.0.1
Un serveur avancé pour Metadidomi
Requires Python: >=3.6

README - Py Protector Prototype

Ce dépôt contient un prototype minimal pour:
1) compiler et chiffrer un projet Python (encrypt_project.py)
2) déchiffrer et exécuter le bytecode en mémoire (launcher.py)
3) packager le runtime embeddable + fichiers chiffrés (packager.py)

Pré-requis:
- Python 3.10+
- pip install pycryptodome

Usage rapide:
1) Place ton point d'entrée (ex: main.py) dans project_src/
2) python encrypt_project.py --src project_src --out build_encrypted --password "MonMotDePasseFort"
3) python packager.py --embedded-python PATH_TO_PYTHON_EMBEDDABLE --encrypted-dir build_encrypted --out MyApp
4) MyApp\python_embedded\python.exe launcher.py

Sécurité:
- La clé est dérivée du mot de passe via PBKDF2.
- Le bytecode est chargé en mémoire (pas d'écriture en clair).
pilab-regis 0.0.13
Implementation of regis
Keywords: registration

# Registration Operations

Welcome to the Registration Operations's Github repository! 

[![PyPI](https://img.shields.io/pypi/v/pilab_regis?label=pypi%20package)](https://pypi.org/project/pilab_regis/)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/pilab_regis)](https://pypi.org/project/pilab_regis/)

## Description

This package contains helpful functions enabling an easier use of registration functions.


## Installing & importing

### Online install

The BinaMa package is available through ```pip install``` under the name ```pilab-regis```. Note that the online version might not always be up to date with the latest changes.

```
pip install pilab-regis
```
To upgrade the current version : ```pip install pilab-regis --upgrade```.

To install a specific version of the package use
```
pip install pilab-regis==0.0.1
```
All available versions are listed in [PyPI](https://pypi.org/project/pilab-regis/). The package names follow the rules of [semantic versioning](https://semver.org/).

### Local install

If you want to download the latest version directly from GitHub, you can clone this repository
```
git clone https://github.com/PiLAB-Medical-Imaging/registration
```
For a more frequent use of the library, you may wish to permanently add the package to your current Python environment. Navigate to the folder where this repository was cloned or downloaded (the folder containing the ```setup.py``` file) and install the package as follows
```
cd registration
pip install .
```

If you have an existing install, and want to ensure package and dependencies are updated use --upgrade
```
pip install --upgrade .
```
### Importing
At the top of your Python scripts, import the library as
```
import regis.core as rg
```

### Checking current version installed

The version of the TIME package installed can be displayed by typing the following command in your python environment
```
regis.__version__
``` 

### Uninstalling
```
pip uninstall pilab-regis
```
morse-coder 1.0.1
A simple Morse code encoder and decoder for Python.
Requires Python: >=3.8
Keywords: morse, encoder, decoder, text, python

# morse-coder
[![GitHub Repo](https://img.shields.io/badge/GitHub-morsepy-black?logo=github&style=for-the-badge)](https://github.com/ElisaGenesio/morsepy)
[![PyPI](https://img.shields.io/pypi/v/morsepy?style=for-the-badge&color=blue)](https://pypi.org/project/morsepy/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg?style=for-the-badge)](https://opensource.org/licenses/MIT)

![Python](https://img.shields.io/badge/Python-3.8%2B-blue)
![Last Commit](https://img.shields.io/github/last-commit/acrazypie/morsepy)
![Stars](https://img.shields.io/github/stars/acrazypie/morsepy?style=social)

[![Maintained by acrazypie](https://img.shields.io/badge/maintained%20by-acrazypie-9cf?logo=github&style=flat-square)](https://egenesio.com)

A simple and lightweight Python library to encode and decode Morse code.  
Supports letters, numbers, and punctuation symbols — perfect for small projects, learning, or creative experiments.

---

## 🚀 Installation

You can install it directly from PyPI:

```bash
pip install morse-coder
```

Or, if you’re developing locally:

```bash
pip install -e .
```

---

## 🧠 Usage

```python
from morsepy import encode, decode

text = "ciao mondo!"
code = encode(text)
print("Morse:", code)

decoded = decode(code)
print("Decoded:", decoded)
```

Output:

```
Morse: _._. .. ._ ___ / __ ___ _. _.. ___ _._.__
Decoded: ciao mondo!
```

---

## 📚 Features

-   🔤 Encode any text into Morse code
-   🔁 Decode Morse code back to text
-   🧩 Supports A–Z, 0–9, and common punctuation
-   ⚡ Lightweight, dependency-free

---

## 📦 Project Structure

```
morsepy/
├── morsepy/
│   ├── __init__.py
│   └── core.py
├── pyproject.toml
├── README.md
└── LICENSE
```

---

## 🪪 License

Released under the [MIT License](./LICENSE)  
© 2025 Elisa
engioptiqa 0.2.2
Engineering Optimization with Quantum Annealing
Requires Python: >=3.10

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.10222617.svg)](https://doi.org/10.5281/zenodo.10222617)
[![Test Examples](https://github.com/EngiOptiQA/EngiOptiQA/actions/workflows/test_examples.yml/badge.svg)](https://github.com/EngiOptiQA/EngiOptiQA/actions/workflows/test_examples.yml)

# EngiOptiQA: Engineering Optimization with Quantum Annealing

**Please note:** _EngiOptiQA_ is currently in a very early stage of development. As the project progresses, documentation, additional features, and enhancements will be added.

## Overview
_EngiOptiQA_ is a Python software library dedicated to **Engi**neering **Opti**mization with **Q**uantum **A**nnealing (QA).
This project provides a set of tools to formulate engineering optimization problems suitable for QA.

A minimal documentation can be found under [https://engioptiqa.github.io/EngiOptiQA/](https://engioptiqa.github.io/EngiOptiQA/). To learn more about the background of _EngiOptiQA_ and the implemented problem formulations, please refer to the corresponding publication [[1]](#pub1).

## Citation

If you use _EngiOptiQA_ in your research or work, please consider citing it using the software's [DOI](https://zenodo.org/doi/10.5281/zenodo.10222617) and the corresponding publication [Key2024](#pub1).

## Quick Example

Run this example for the design optimization of a rod under self-weight loading presented in [Key2024](#pub1), Section 3.2, solved using *simulated annealing (SA)*:

```bash
pip install -r requirements.txt
python3 examples/rod_1d/design_optimization_sa.py
```

The expected $H_1$ error for the best solution is approximately $1.59 \times 10^{-2}$:

```bash
H1 Error 0.015873015873015817 0.015873015873015817
```

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## References
  1. <a name="pub1"></a>Key F, Freinberger L. A Formulation of Structural Design Optimization Problems for Quantum Annealing. Mathematics. 2024; 12(3):482. [https://doi.org/10.3390/math12030482](https://doi.org/10.3390/math12030482)