<<<<<<< HEAD # ce community edition of data-transport ======= # Introduction This project implements an abstraction of objects that can have access to a variety of data stores, implementing read/write with a simple and expressive interface. This abstraction works with **NoSQL**, **SQL** and **Cloud** data stores and leverages **pandas**. # Why Use Data-Transport ? Data transport is a simple framework that: - easy to install & modify (open-source) - enables access to multiple database technologies (pandas, SQLAlchemy) - enables notebook sharing without exposing database credential. - supports pre/post processing specifications (pipeline) ## Installation Within the virtual environment perform the following : pip install git+https://github.com/lnyemba/data-transport.git Options to install components in square brackets pip install data-transport[nosql,cloud,warehouse,all]@git+https://github.com/lnyemba/data-transport.git ## Additional features - In addition to read/write, there is support for functions for pre/post processing - CLI interface to add to registry, run ETL - scales and integrates into shared environments like apache zeppelin; jupyterhub; SageMaker; ... ## Learn More We have available notebooks with sample code to read/write against mongodb, couchdb, Netezza, PostgreSQL, Google Bigquery, Databricks, Microsoft SQL Server, MySQL ... Visit [data-transport homepage](https://healthcareio.the-phi.com/data-transport) >>>>>>> v2.2.0