documentation ... readme

v2.2.0
Steve Nyemba 2 weeks ago
parent a31481e196
commit 4c2efc2892

@ -4,12 +4,11 @@ This project implements an abstraction of objects that can have access to a vari
# Why Use Data-Transport ? # 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 Data transport is a simple framework that:
- easy to install & modify (open-source)
1. Familiarity with **pandas data-frames** - enables access to multiple database technologies (pandas, SQLAlchemy)
2. Connectivity **drivers** are included - enables notebook sharing without exposing database credential.
3. Reading/Writing data from various sources - supports pre/post processing specifications (pipeline)
4. Useful for data migrations or **ETL**
## Installation ## Installation
@ -18,19 +17,16 @@ Within the virtual environment perform the following :
pip install git+https://github.com/lnyemba/data-transport.git pip install git+https://github.com/lnyemba/data-transport.git
## Features Options to install components in square brackets
- read/write from over a dozen databases pip install data-transport[nosql,cloud,warehouse,all]@git+https://github.com/lnyemba/data-transport.git
- run ETL jobs seamlessly
- scales and integrates into shared environments like apache zeppelin; jupyterhub; SageMaker; ...
## What's new
Unlike older versions 2.0 and under, we focus on collaborative environments like jupyter-x servers; apache zeppelin: ## Additional features
1. Simpler syntax to create reader or writer - In addition to read/write, there is support for functions for pre/post processing
2. auth-file registry that can be referenced using a label - CLI interface to add to registry, run ETL
3. duckdb support - scales and integrates into shared environments like apache zeppelin; jupyterhub; SageMaker; ...
## Learn More ## Learn More

Loading…
Cancel
Save