DataFrame Library

A lightweight DataFrame library designed for reading, validating, and writing data entries with a unified API for local, AWS, and GCP storage backends.

Features

• Unified API: Interact with data across local, AWS, and GCP storage seamlessly.
• Data Validation: Ensure data integrity with built-in validation mechanisms.
• Flexible Storage: Read and write data from various storage backends without changing your code.
• Lightweight: Minimal dependencies and overhead for efficient data handling.

Installation

pip install dataframe-library

Usage

from dataframe_library import DataFrame
# Create a DataFrame instance
df = DataFrame()
# Read data from a local file
df.read('data.csv')
# Validate the data
df.validate()
# Write data to an AWS S3 bucket
df.write('s3://my-bucket/data.csv')
# Read data from a GCP bucket
df.read('gs://my-bucket/data.csv')
# Write data to a local file
df.write('output.csv')

Documentation

For detailed documentation, please visit DataFrame Library Documentation.

Contributing

We welcome contributions! Please read our Contributing Guidelines for more information on how to get involved.

License

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

Contact

For any questions or issues, please open an issue on our [GitHub repository]