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

Complete introduction to using JMESPath in Python for JSON parsing and an example web scraping project.

Quick Intro to Parsing JSON with JMESPath in Python

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

Quick Intro to Parsing JSON with JSONPath in Python

Complete introduction to JSONPath and how to use it in Python through an example web scraping project.

Quick Intro to Parsing JSON with JSONPath in Python

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).

Question tagged: Python, Data Parsing

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