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Your Quick Guide to Using JSON in Python
Learn how to easily work with JSON in Python. Here's how to read and write files and between JSON and Python objects.
In today’s world of APIs, web apps, and data-driven projects, JSON (JavaScript Object Notation) is everywhere. And if you’re working in Python, knowing how to handle JSON is a must.
This week, we’re giving you a quick, practical guide to working with JSON in Python. You’ll see how to read, write, parse, and convert JSON data with just a few simple lines of code.
How JSON Works in Python
Python has a built-in json
module that makes it easy to work with JSON data. You can think of JSON as a lightweight format for storing and transporting data, similar to Python dictionaries and lists.
Here’s how to load a JSON string into a Python object:
import json
json_data = '{"name": "Gandalf", "age": 42}'
python_obj = json.loads(json_data)
print(python_obj["name"]) # Output: Gandalf
And here’s how to write a Python object to a JSON string:
python_obj = {"name": "Gandalf", "age": 30}
json_data = json.dumps(python_obj)
print(json_data)
If you are working with files instead of strings, you can use json.load() and json.dump():
Reading a JSON file:
with open('data.json', 'r') as file:
data = json.load(file)
print(data)
Writing a JSON file:
with open('data.json', 'w') as file:
json.dump(python_obj, file, indent=4)
Indentation helps keep your JSON files human-readable. This might seem like a small skill, but that’s one of the reasons it’s vital. Learning to handle JSON in Python is a small investment that pays off fast. Whether you are building APIs, processing data, or connecting with web services, JSON is everywhere.
And Python makes it easy to work with.
Common Use Cases:
Parsing API responses
Saving settings or preferences
Reading configuration files
Building data-driven applications
Storing lightweight structured data
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