semvec/pypi-packages huggingface dataset:
khulnasoft 0.1.25
Python SDK for the khulnasoft.com API.
License: MIT
Requires Python: >=3.8
Keywords: khulnasoft, sdk

# python-khulnasoft

`khulnasoft` is a light [Khulnasoft API](https://api.docs.khulnasoft.com/) SDK that wraps [requests](https://requests.readthedocs.io/) and automatically manages authentication.

Usage examples and use cases are documented in the [Khulnasoft API documentation](https://api.docs.khulnasoft.com/sdk/python).

## Installing

`khulnasoft` is [available on PyPI](https://pypi.org/project/khulnasoft/).

The library can be installed via `pip install khulnasoft`.

## Basic Usage

```python
import os

from khulnasoft import KhulnasoftApiClient


client = KhulnasoftApiClient(
    api_key=os.environ["KHULNASOFT_API_KEY"],
    tenant_id=None,  # Use my default tenant.
)

resp = client.get("/tokens/test")

print(resp.json())
```

## Contributing

- `make test` will run tests
- `make format` format will format the code
- `make lint` will run typechecking + linting
dravida-kavacham 0.1.0
Abusive Content Detection
License: MIT
Requires Python: <4.0,>=3.10

<div align="center">
    <h1>
    DravidaKavacham
    </h1>
    <p>
        DravidaKavacham  is an open-source tool for detecting abusive content in Dravidian focused on harmful language targeting women.</p>
</div>

<div align="center">
  <img src="https://img.shields.io/badge/Python-3.10%2B-blue?logo=python&logoColor=white" alt="Python 3.10+" />
  <img src="https://img.shields.io/badge/PyTorch-2.2.0%2B-red?logo=pytorch&logoColor=white" alt="PyTorch" />
  <img src="https://img.shields.io/github/license/Luxshan2000/dravida-kavacham" alt="MIT License" />
<img src="https://img.shields.io/pypi/dm/dravida-kavacham" alt="Downloads" />
</div>

---

## 🛠️ Installation  

Install DravidaKavacham via [PyPI](https://pypi.org/project/dravida-kavacham)
```bash
pip install dravida-kavacham
```  

---

## 💡 Quick Start  

### Load the Library  
```python
from dravida_kavacham import AbuseDetector

# Initialize the detector
detector = AbuseDetector()
```

### Predict Abusive Content  
```python
text = "Example abusive text in Tamil or Malayalam"
result = detector.predict(text)

if result == "Abusive":
    print("⚠️ Abusive content detected!")
else:
    print("✔️ Text is clean.")
```  

---

## 🚀 Key Features  
- **Multilingual Detection**: Designed for Tamil 🇮🇳 and Malayalam 🇮🇳 text.  
- **Plug-and-Play**: No complex setup. Just install, load, and detect!  
- **Efficient Local Processing**: Downloads the pre-trained model on first use.  
- **Customizable**: Extendable for additional use cases with minor adjustments.  

---

## 🌍 Supported Languages  

| Language     | Script          | Status       |  
|--------------|-----------------|--------------|  
| **Tamil**    | Tamil script    | ✅ Supported |  
| **Malayalam**| Malayalam script| ✅ Supported |  

---

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

---

## 🙌 Acknowledgements  

Special thanks to the dataset authors and owners for providing the valuable resources that made this project possible!

---

## ⭐ Support  

If you like this project, please consider giving it a ⭐ on [DravidaKavacham](https://github.com/Luxshan2000/dravida-kavacham)!
MeliAPIClient 0.0.4
Este paquete nos permite consumir el API de mercado libre
License: MIT
Keywords: python, mercado libre, mercadolibre.com

# MeliAPIClient

Este módulo permite interactuar con el API de mercado libre para leer, actualizar y crear productos y órdenes. Este módulo es útil para integrar el API de Mercado libre con otros sistemas.

## Instalación

Para instalar este módulo, ejecute el siguiente comando:

```bash
pip install MeliAPIClient
```

### Uso básico

Para usar este módulo, debemos guardar las credenciales en 3 archivos tipo JSON. El archivo `ml_keys` almacena el `client_id` y `client_secret`, `ml_token` almacena la información para renovar la sesión después del límite de 6 horas, y `ml_user` que almacena la información del usuario, donde el dato más importante es el ID del usuario.

```python
from MeliAPIClient import Session
from MeliAPIClient import Order


def run():

    session = Session("ml_keys.json", 'ml_token.json', "ml_user.json")
    orders = Order(session)

    orders.list(year=2024, month=5)


if __name__ == "__main__":
    run()
```

## Créditos

Camilo Andrés Rodriguez

## referencias

https://developers.mercadolibre.com/

## Licencia

Este proyecto está bajo la Licencia [MIT].