How to Work with JSON in Python

JSON (JavaScript Object Notation) is a common data format for APIs and configuration files. Python’s built-in json module makes working with JSON easy.

Importing the JSON Module

import json

Converting Python to JSON (Serialization)

json.dumps() - Python to JSON String

import json

# Dictionary to JSON string
data = {
    "name": "Alice",
    "age": 30,
    "city": "New York",
    "active": True,
    "skills": ["Python", "SQL", "JavaScript"]
}

json_string = json.dumps(data)
print(json_string)
# {"name": "Alice", "age": 30, "city": "New York", "active": true, "skills": ["Python", "SQL", "JavaScript"]}

# Pretty print with indentation
json_pretty = json.dumps(data, indent=2)
print(json_pretty)

json.dump() - Write to File

import json

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

# Write to file
with open("data.json", "w") as f:
    json.dump(data, f, indent=2)

Converting JSON to Python (Deserialization)

json.loads() - JSON String to Python

import json

json_string = '{"name": "Alice", "age": 30, "active": true}'

# Parse JSON string
data = json.loads(json_string)
print(data["name"])  # Alice
print(data["age"])   # 30
print(type(data))    # <class 'dict'>

json.load() - Read from File

import json

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

print(data)

Type Conversions

Python to JSON type mappings:

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

import json

python_data = {
    "string": "hello",
    "number": 42,
    "float": 3.14,
    "boolean": True,
    "null_value": None,
    "list": [1, 2, 3],
    "nested": {"key": "value"}
}

json_string = json.dumps(python_data, indent=2)
print(json_string)

Working with APIs

import json
import urllib.request

# Fetch JSON from API
url = "https://api.example.com/users/1"
with urllib.request.urlopen(url) as response:
    data = json.loads(response.read().decode())
    print(data["name"])

# Using requests library (recommended)
import requests

response = requests.get("https://api.example.com/users/1")
data = response.json()  # Built-in JSON parsing
print(data["name"])

Handling Errors

import json

# Handle invalid JSON
invalid_json = "{'name': 'Alice'}"  # Single quotes are invalid

try:
    data = json.loads(invalid_json)
except json.JSONDecodeError as e:
    print(f"Invalid JSON: {e}")

# Check if file exists
import os

if os.path.exists("data.json"):
    with open("data.json") as f:
        data = json.load(f)
else:
    data = {}  # Default value

Custom Serialization

Handling Non-Serializable Types

import json
from datetime import datetime

data = {
    "name": "Event",
    "date": datetime.now()  # Not JSON serializable
}

# This will raise TypeError:
# json.dumps(data)

# Solution 1: Custom encoder
class DateTimeEncoder(json.JSONEncoder):
    def default(self, obj):
        if isinstance(obj, datetime):
            return obj.isoformat()
        return super().default(obj)

json_string = json.dumps(data, cls=DateTimeEncoder)
print(json_string)

# Solution 2: Convert before serializing
data["date"] = data["date"].isoformat()
json_string = json.dumps(data)

Custom Object Serialization

import json

class User:
    def __init__(self, name, email):
        self.name = name
        self.email = email
    
    def to_dict(self):
        return {"name": self.name, "email": self.email}

user = User("Alice", "alice@example.com")

# Convert to dict first
json_string = json.dumps(user.to_dict())
print(json_string)

# Or use __dict__
json_string = json.dumps(user.__dict__)
print(json_string)

Practical Examples

Configuration File

import json

# Load config
def load_config(filepath="config.json"):
    try:
        with open(filepath) as f:
            return json.load(f)
    except FileNotFoundError:
        return {"debug": False, "port": 8000}  # Defaults

# Save config
def save_config(config, filepath="config.json"):
    with open(filepath, "w") as f:
        json.dump(config, f, indent=2)

# Usage
config = load_config()
config["debug"] = True
save_config(config)

Data Processing

import json

# Process JSON array
json_data = '''
[
    {"name": "Alice", "score": 85},
    {"name": "Bob", "score": 92},
    {"name": "Charlie", "score": 78}
]
'''

students = json.loads(json_data)

# Calculate average
average = sum(s["score"] for s in students) / len(students)
print(f"Average score: {average:.2f}")

# Filter and transform
passed = [s["name"] for s in students if s["score"] >= 80]
print(f"Passed: {passed}")

Summary

• Use json.dumps() to convert Python to JSON string
• Use json.loads() to convert JSON string to Python
• Use json.dump() to write JSON to file
• Use json.load() to read JSON from file
• Handle JSONDecodeError for invalid JSON
• Use custom encoder for non-serializable types