Python JSON Tutorial – Parse, Read, Write JSON Data Easily

Python JSON

JSON (JavaScript Object Notation) is one of the most popular data formats used for storing and exchanging data.

It is widely used in:

• Web APIs
• Mobile applications
• Configuration files
• Cloud services
• Databases

Python provides a built-in module called json to work with JSON data easily.

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What is JSON?

JSON is a lightweight data format used to represent structured data.

Example JSON:

{
    "name": "John",
    "age": 30,
    "city": "New York"
}

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Why Use JSON?

• Easy to read and write
• Lightweight format
• Language independent
• Perfect for APIs
• Fast data exchange

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Python JSON Module

Python provides the built-in json module.

import json

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1. Converting Python to JSON (Serialization)

Use json.dumps().

import json

data = {
    "name": "John",
    "age": 30,
    "city": "New York"
}

json_string = json.dumps(data)

print(json_string)

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Output

{"name": "John", "age": 30, "city": "New York"}

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2. Converting JSON to Python (Deserialization)

Use json.loads().

import json

json_data = '{"name": "John", "age": 30}'

python_obj = json.loads(json_data)

print(python_obj)

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Output

{'name': 'John', 'age': 30}

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3. Reading JSON from File

import json

with open("data.json", "r") as file:
    data = json.load(file)

print(data)

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4. Writing JSON to File

import json

data = {
    "name": "Alice",
    "age": 25
}

with open("output.json", "w") as file:
    json.dump(data, file)

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5. Pretty Printing JSON

import json

data = {"name": "John", "age": 30}

print(json.dumps(data, indent=4))

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Output

{
    "name": "John",
    "age": 30
}

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6. Sorting JSON Keys

print(json.dumps(data, sort_keys=True))

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7. JSON Data Types Mapping

JSON	Python
object	dict
array	list
string	str
number	int / float
true	True
false	False
null	None

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8. Handling Complex JSON

data = {
    "users": [
        {"name": "John", "age": 30},
        {"name": "Alice", "age": 25}
    ]
}

print(json.dumps(data, indent=2))

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9. Error Handling in JSON

JSON Decode Error

json.decoder.JSONDecodeError

Solution:

• Check JSON format
• Ensure proper quotes

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10. Working with APIs

Example API response:

import json

response = '{"status": "success", "data": [1, 2, 3]}'

data = json.loads(response)

print(data["status"])

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11. JSON vs XML

Feature	JSON	XML
Readability	High	Medium
Size	Smaller	Larger
Speed	Faster	Slower
Usage	APIs	Legacy systems

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Real-World Applications

JSON is used in:

• REST APIs
• Web applications
• Mobile apps
• Configuration files
• Cloud services
• Microservices communication

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Best Practices

• Use indent for readability
• Validate JSON before parsing
• Handle exceptions properly
• Use JSON for API communication
• Avoid manual string formatting

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Common Mistakes

Using single quotes in JSON

{'name': 'John'}

Correct:

{"name": "John"}

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Forgetting json.loads()

Always convert JSON string before using.

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Summary

Python provides a powerful built-in json module for handling structured data. It allows developers to easily convert between Python objects and JSON format for storage, APIs, and data exchange.

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Conclusion

JSON is essential for modern web development and APIs. Python makes JSON processing simple, fast, and efficient. Mastering JSON will help you build better web applications, APIs, and data-driven systems.