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@ -4,34 +4,40 @@ This project implements an abstraction of objects that can have access to a vari
# Why Use Data-Transport ?
Mostly data scientists that don't really care about the underlying database and would like a simple and consistent way to read/write and move data are well served. Additionally we implemented lightweight Extract Transform Loading API and command line (CLI) tool. Finally it is possible to add pre/post processing pipeline functions to read/write
1. Familiarity with **pandas data-frames**
2. Connectivity **drivers** are included
3. Reading/Writing data from various sources
4. Useful for data migrations or **ETL**
Data transport is a simple framework that enables read/write to multiple databases or technologies that can hold data. In using **data-transport**, you are able to:
- Enjoy the simplicity of **data-transport** because it leverages SQLAlchemy & Pandas data-frames.
- Share notebooks and code without having to disclosing database credentials.
- Seamlessly and consistently access to multiple database technologies at no cost
- No need to worry about accidental writes to a database leading to inconsistent data
- Implement consistent pre and post processing as a pipeline i.e aggregation of functions
- **data-transport** is open-source under MIT License https://github.com/lnyemba/data-transport
## Installation
Within the virtual environment perform the following :
Within the virtual environment perform the following,the options for installation are: