Lesson 20: Working with JSON in Python

🎯 Lesson Objective

To learn how to read, write, and manipulate JSON data in Python using the built-in json module.

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🧩 1. What Is JSON?

JSON (JavaScript Object Notation) is a lightweight format for storing and exchanging data.

• It is text-based and human-readable.
• Supports objects (dict), arrays (list), strings, numbers, booleans, and null.

✅ Example JSON

{
    "name": "Sameer",
    "age": 25,
    "skills": ["Python", "Excel", "Web Scraping"]
}

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⚙️ 2. Importing the JSON Module

import json

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🔄 3. Converting Python to JSON (Serialization)

• Use json.dumps() to convert Python objects to JSON string.

data = {"name": "Sameer", "age": 25, "skills": ["Python", "Excel"]}
json_str = json.dumps(data)
print(json_str)

Output:

{"name": "Sameer", "age": 25, "skills": ["Python", "Excel"]}

• Save JSON to a file using json.dump():

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

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🧰 4. Converting JSON to Python (Deserialization)

• Load JSON string to Python dict:

json_str = '{"name": "Sameer", "age": 25, "skills": ["Python", "Excel"]}'
data = json.loads(json_str)
print(data["name"])

Output:

Sameer

• Load JSON from a file:

with open("data.json", "r") as f:
    data = json.load(f)
print(data["skills"])

Output:

['Python', 'Excel']

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🧱 5. Working with Nested JSON

nested_json = {
    "person": {
        "name": "Ali",
        "age": 22,
        "address": {"city": "Warangal", "country": "India"}
    }
}

# Access nested data
print(nested_json["person"]["address"]["city"])

Output:

Warangal

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🔄 6. Pretty Printing JSON

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

Output:

{
    "name": "Sameer",
    "age": 25,
    "skills": [
        "Python",
        "Excel"
    ]
}

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🛠️ 7. Updating JSON Data

data["age"] = 26
data["skills"].append("Web Scraping")

with open("data.json", "w") as f:
    json.dump(data, f, indent=4)

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🌍 8. Real-Life Example – Storing Contact Book

contacts = {
    "Ali": {"phone": "9876543210", "email": "ali@example.com"},
    "Sara": {"phone": "9123456789", "email": "sara@example.com"}
}

# Save to file
with open("contacts.json", "w") as f:
    json.dump(contacts, f, indent=4)

# Load from file
with open("contacts.json", "r") as f:
    data = json.load(f)

print(data["Sara"]["phone"])

Output:

9123456789