semvec/pypi-packages huggingface dataset:
deepcolor 0.0.6
Analyze colocalization patterns between single cell gene expression profiles.
Requires Python: >=3.7

# deepCOLOR: DEEP Generative model for single-cell COLOcalization Representation
DeepCOLOR is intended to analyze colocalization relation ships between single cell transcriptomes, integrating them with spatial transcriptome.

## Instalation
You can install deepCOLOR using pip command from your shell.
```shell
pip install deepcolor  imgaug==0.2.5
```

## Usage
You need to prepare [`AnnData` objects](https://anndata.readthedocs.io/en/latest/) which includes raw count matrix of gene expression for single cell and spatial transcriptome respectively. You can see the usage in [IPython Notebook](tutorial/deepcolor_tutorial.ipynb).
fastpypi 1.0.0
A package enabling user to create and update existing PyPI packages in an easy-to-use gui.
Requires Python: >=3.6

# FastPyPI

FastPyPI is a package enabling user to create and update existing PyPI packages in an easy-to-use gui. 

(creates ```pip install XXX``` for your package)

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install FastPyPI.

```
pip install fastpypi
```

## Usage

Run a Python interpreter in console/terminal
```
>>> import fastpypi.fastpypi_core
```

This will launch a FastPyPI GUI (as in the picture).


![alt text](https://github.com/DovaX/fastpypi/blob/master/fastpypi_tool.png?raw=true)


## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

## License
[MIT](https://choosealicense.com/licenses/mit/)
route-halo 0.1.2
Halo the route optimizer tool
Requires Python: >=3.8
Keywords: route,optimizer,tsp

## Introduction

Halo is an open-source OSM (OpenStreetMap) route optimization engine. Built on FastAPI, this RESTful backend provides efficient route calculation and data processing. Leveraging SQLAlchemy for database management and Redis for fast data access, the project maximizes performance.

## Key Features

- **Route Optimization**: Utilizes OSM data to provide accurate route optimization.
- **High-Performance Backend**: Developed with FastAPI for fast and efficient service.
- **Data Management**: Supports structured database management with SQLAlchemy.
- **Caching Mechanism**: Enhances repetitive data request processing speeds using Redis.

## Technology Stack

- **FastAPI**: A modern, fast web framework for easy API development.
- **SQLAlchemy**: Offers powerful SQL toolkit and ORM (Object-Relational Mapping).
- **Redis**: A high-performance key-value store used for data caching.
- **OpenStreetMap**: Provides map data necessary for route optimization, free to use.

## Installation and Execution

```bash
git clone https://github.com/yourusername/halo.git
cd halo
docker-compose up -d
```

## Example ERD
- https://www.erdcloud.com/p/f5MEA63DBzZb7cCJ9
persai 0.0.5
Big Five Personality Analysis based on Twitter (X) posts.

# Persai

![Persai Logo](images/logo.png)

## Introduction 🔎

Persai is a Python package designed to analyze Twitter (X) posts and provide insights into the Big Five personality traits (Openness, Conscientiousness, Extraversion, Agreeableness, Neuroticism). This tool leverages data from your Twitter archive to offer a unique perspective on your social media presence. 🐦

![Diagram](images/diagram.png)

[Visit our website for more information and documentation](https://www.persai.org/)

## Installation 🛠️

Install Persai easily using pip:

```bash
pip install persai
```

## How to Use 💡

Follow these steps to analyze your Twitter (X) data using Persai:

1. **Export Your Twitter Data**:
   - Follow Twitter's guidelines to [download your Twitter (X) archive](https://help.twitter.com/en/managing-your-account/how-to-download-your-twitter-archive).

2. **Prepare Your Data**:
   - Locate the `twitter.js` file in your downloaded Twitter (X) data.
   - Save this file in the directory where you plan to run the Persai package.

3. **Set Your OpenAI Key**:
   - Assign your OpenAI key to a variable. For security reasons, avoid hardcoding the key in your script. Instead, consider using environment variables or other secure methods.

3. **Run Persai**:
   - Use the following Python code to perform the Big Five analysis:

   ```python
    from persai import big_five

    openai_key = "your_openai_key_here"
    data = "twitter.js"
    result = big_five(data, openai_key)
    print(result)
   ```

## Sample Output 📈

After running the script, you'll receive a dictionary with the analysis results. It will look something like this:

```json
{
  "openness": "high",
  "conscientiousness": "low",
  "extraversion": "low",
  "agreeableness": "low",
  "neuroticism": "low"
}
```

These results provide a snapshot of the personality traits expressed in your Twitter (X) posts.

## Contributing

Feel free to contribute to the project or suggest improvements! 🌟

## Acknowledgments :clap:

This project is a reimplementation of the ideas and methodologies presented in the paper [Is ChatGPT a Good Personality Recognizer? A Preliminary Study](https://arxiv.org/pdf/2307.03952.pdf). Thank you for providing this research.

## License

This project is licensed under the [MIT License](LICENSE).
pkrtablegui 1.0.0
A Poker Package for Graphic User Interface
Keywords: poker pktable table pkr pokertablegui PokerTableGui PokerTable GUI


# PokerGUI

## Description
`PokerGUI` est un outil d'interface graphique pour du Texas Hold'Em Poker.
Il s'articule avec les autres éléments de ManggyPoker

Readme à modifier...

## Fonctionnalités
- Téléchargement des fichiers d'historique de poker vers un bucket S3.
- Option pour télécharger tous les fichiers depuis le début de l'année en cours.
- Option pour télécharger uniquement les fichiers du jour.
- Vérifie si un fichier existe déjà dans le bucket pour éviter les doublons.

## Utilisation
1. Assurez-vous d'avoir les dépendances requises installées en utilisant :
```
pip install -r requirements.txt
```

2. Créez un fichier `.env` à la racine du projet avec les configurations nécessaires. Voir le template ci-dessous.

3. Pour télécharger tous les fichiers depuis le début de l'année, exécutez :
```
python daily_upload.py
```

4. Pour télécharger uniquement les fichiers du jour, exécutez :
```
python frequent_upload.py
```

## Configuration
- Les clés d'accès à S3 et d'autres configurations sont chargées à partir du fichier `.env`. Assurez-vous de le définir correctement avec le template suivant :
```
DO_REGION=VotreRégion
DO_ENDPOINT=VotreEndpoint
AWS_ACCESS_KEY_ID=VotreAccessKeyID
AWS_SECRET_ACCESS_KEY=VotreSecretAccessKey
```

- Le répertoire par défaut pour chercher les fichiers est basé sur le répertoire de l'utilisateur courant. Vous pouvez le changer si nécessaire dans le code.

## Planification avec Crontab
Si vous souhaitez exécuter les scripts en tant que tâches planifiées avec `crontab`, voici comment vous pouvez le faire :

Pour `daily_upload.py` :
```
0 0 * * * /chemin/vers/python /chemin/vers/le/projet/daily_upload.py
```

Pour `frequent_upload.py` :
```
0 * * * * /chemin/vers/python /chemin/vers/le/projet/frequent_upload.py
```

Assurez-vous de remplacer `/chemin/vers/python` par le chemin complet vers votre interpréteur Python et `/chemin/vers/le/projet/` par le chemin complet vers le dossier du projet.

## Contribution
Si vous souhaitez contribuer au projet, n'hésitez pas à faire des pull requests ou à ouvrir des issues.