What are some ways to parse JSON datasets in Python?

Modern web scraping often involved a lot of JSON parsing through hidden web data scraping or backend API scraping in particular. There are several ways to parse JSON data in Python.

JMESPath is a popular JSON query language and library available in many languages:

Quick Intro to Parsing JSON with JMESPath in Python

Introduction to JMESPath - JSON query language which is used in web scraping to parse JSON datasets for scrape data.

JSONPath is another popular JSON query language and library available in many languages:

Introduction to Parsing JSON with Python JSONPath

Intro to using Python and JSONPath library and a query language for parsing JSON datasets.

Both of these tools are a great way to parse JSON datasets within Python. As for which one is better - generally, JSONPath is more powerful by offering recursive selectors (e.g. $..book will select key book anywhere in the dataset) while Jmespath has a more intuitive syntax and better data reshaping capabilities (e.g. renaming keys and flattening nested data structures).