#6 Data Engineering — EXTRACT DATA using APIs
This is the sixth blog in the series of posts related to Data Engineering. I have been writing all the important things that I learn as a part of the Data Scientist Nanodegree Program, Udacity. I have realized it is the best way to test my understanding of the course material and maintain the discipline to study. Please check the other posts as well.
Instead of downloading World Bank data via a CSV file, you’re going to download the data using the World Bank APIs. The purpose of this exercise is to gain experience with another way of extracting data.
API is an acronym that stands for an application programming interface. API’s provide a standardized way for two applications to talk to each other. In this case, the applications communicating with each other are the server application where World Bank stores data and our Jupyter notebook.
If you wanted to pull data directly from the World Bank’s server, you’d have to know what database system the World Bank was using. You’d also need permission to log in directly to the server, which would be a security risk for the World Bank. And if the World Bank ever migrated its data to a new system, you would have to rewrite all of your code again. The API allows you to execute code on the World Bank server without getting direct access.
The Github code is here.
