Generally, python is the first choice for the data engineers as it’s an object-oriented, high-level, interpreted programming language. It supports both dynamic typing as well as dynamic binding.

Highlights of python:

Easily comprehensible programming language that supports various modules and packages and code re-usability.

Easy-to-use code debugging capability

Wide range of libraries and frameworks are readily available for use.

Tasks could be easily automated with the help of various available tools and libraries.

Advantages:

Library Support: For small as well as medium scale projects (data), due to its outstanding library support from the community, python is highly recommended for analyzing and getting insights from the data.

PySpark API: It is an API for Spark framework. It was released by the Apache Spark in order to support the Python language in Spark. With the help of PySpark, the integrations and working on RDDs has become quite easy using Python language.

Readability: With the adoption of PySpark API — the maintenance, integrability, readability, and familiarity of the code has improved for spark based projects.