Metadata-Version: 2.1
Name: securedai
Version: 0.1.1
Summary: Secure your ML models using securedai
Home-page: https://github.com/arristigit/securedai
Author: Varinder Kumar
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: python-decouple==3.8

# SecuredAI Python Package
`securedai` is a Python package designed to easily implement security features for machine learning models or other applications. With simple commands, users can instantiate the package and quickly apply security layers to their models.

## Installation
You can install the `securedai` package using pip:
```bash
pip install securedai
```

## Quickstart
Once the package is installed, you can start using it immediately. Here's a simple example:
```python
from securedai import Secured

# Instantiate the Secured class
sc = Secured() 
# Console output: "Constructed secured instance"

# Apply security to 9 models
result = sc.implement(9)
# Console output: "Implemented securety for 9 models!"

print(result)
# Console output: {'status': True, 'message': 'Success'}
```

**Expected Output**:
```python
Constructed secured instance
Implemented security for 9 models!    
{'status': True, 'message': 'Success'}
```

## Features
- Easy Security Implementation: Apply security features to any number of models with one command.
- Clear Status Messages: Returns a success message with the status of the security implementation.

## Methods
`Secured.implement(model_count: int) -> dict`
- **Description**: Implements security for a specified number of models.
- **Parameters**:
    - `model_count (int)`: The number of models to apply security to.
- **Returns**:
    - A dictionary with `status` indicating success or failure, and a `message`.

## Contributing
Feel free to open issues or pull requests if you find any bugs or have feature requests.

## License
This project is licensed under the MIT License. See the LICENSE file for details.
