According to Stack Overflow Developers’ Survey 2019, Python is the second “most loved” language with 73 percent of the developers choosing it above other languages prevailing in the market. Python is a highly versatile language that supports a wide variety of use cases across several languages. It is a language well-known for its ease of use, portability, and ability to handle large data sets. Here, we’ll discuss a few interesting things you should know about Python and Building a REST API with Python.

Table of Contents

  1. A REST API in Python Is a Client-Side Scripting Language
  2. There Are Many Use Cases for Developing a REST API With Python
  3. Building a REST API With Python Has Many Benefits
  4. Creating a REST API With Python Enables Big Data Analysis
  5. A REST API With Python Uses Open Source Code
  6. You Can Build a REST API in Python for ETL
  7. How Can Help with REST APIs in Python

A REST API in Python Is a Client-Side Scripting Language

The term scripting refers to the automation of computer tasks that would normally be handled manually one by one. Python is both a programming language and a scripting language. In fact, all scripting languages are programming languages. However, not all programming languages are scripting languages. There are distinct differences between the two. A scripting language uses what is known as an interpreter to run the code directly from the source commands. Programming languages, however, require a compiler to translate the code into machine format before it can be executed. There are two types of scripting languages.

Server Side

Server-side scripting runs on a web browser and processes web requests. When a client requests a page, the server responds by sending the content via HTTP.


In contrast, client-side scripting run on the end client in their browser. The benefit of client-side scripting is that they minimize demand on the server. By allowing the scripting to happen on the client, web pages can load faster.

Why Does it Matter?

Python is a language that is easy to learn. The code looks more like a conversation between a human and machine rather than the complex code seen in typical programming languages. It is highly intuitive and requires very little technical knowledge to learn.

There Are Many Use Cases for Developing a REST API With Python

The capabilities of Python extend beyond a basic data integration tool. It can be used to mine data for a variety of purposes. “Python has become the most popular language of choice for learning programming in school and university,” said Ben Finkel, who is a CBT Nuggets Trainer. “This is true not just in computer science departments, but also in other areas as programming has become more prevalent. Statistics, economics, physics, even traditionally non-technical fields such as sociology have all started introducing programming and data analysis into their curriculum.”

Data Science - Python is known for its computing capabilities which makes it ideal for the heavy analysis used in data science.

Machine Learning - Python’s code can handle complex algorithms to support machine learning for applications, such as voice recognition and content recommendations.

Data Mining - Python’s scalability and ability to handle complex data tasks make it ideally suited for mining large data sets.

Building a REST API With Python Has Many Benefits

Using Python scripting to build a REST API comes with many benefits which include:

Popularity - The language is open source and has a large community and is used across a variety of industries

Simple Syntax - Python is easy to learn as it uses simple English words to describe each step. Python is an excellent choice for most people to learn the basics of code, in the same way, that everyone learns how to read and write,” said Tom Hatch, who is the CTO of SaltStack.

Readability - Code written in Python is easy to read as it uses clean line breaks to end each command rather than semicolons and parenthesis as found in other languages.

Scalability - Scripts written in Python can easily be transferred to other platforms without the need to rewrite or adapt the code to fit the new environment.

Creating a REST API With Python Enables Big Data Analysis

Python pairs well with Hadoop. Many developers use Hadoop because it offers an extensive set of libraries for working with the language. Additionally, the language has a high processing speed. The code executes in a fraction of the time needed by other programming languages.

Another advantage to using Python is that it works well with unconventional and unstructured data such as graphs, social media comments, and phone transcripts.

A REST API with Python Uses Open Source Code

Python is open source making it freely usable and distributable for both personal and professional use. It is certified by the Open Source Initiative. Why is this important? It essentially means that you can use it to create new products without worrying about getting a license for it. 

Another benefit of Python being open source is that there is transparency in the codebase. You get full visibility into the code which can make addressing bugs easier. Also, the ability to leverage Python as open-source means you can achieve faster time to market by using a language that is readily accessible.

You Can Build a REST API in Python for ETL

Extract, Transform and Load (ETL) is a core component of a company’s digital transformation efforts. The ability to integrate data from disparate systems helps drive innovation and supports data-driven decision-making. Using Python to build a REST API allows you to leverage the language's strong capabilities in managing data. It also means you can customize every aspect of the pipeline as you see feet.

How Can Help With REST APIs in Python

Data integration fosters agility and innovation. Building REST APIs in Python enables companies to leverage an easily accessible language to build robust data integrations to uncover fine-grained details about customer data. is a low-code ETL tool that features pre-built connectors to over one hundred popular systems. Anyone, regardless of technical experience, can use these connectors to connect to APIs to integrate their data into a data pipeline. Are you looking to integrate your systems? Reach out to one of our data integration specialists today for a free demo.