Python JSON — Serialization & Data Exchange

JSON (JavaScript Object Notation) is the standard data interchange format. Python's json module handles encoding and decoding.

Learning Objectives

• Serialize Python objects to JSON strings
• Deserialize JSON to Python objects
• Customize JSON serialization for complex types
• Handle large JSON files with streaming

Basic Encoding and Decoding

import json

# Python dict to JSON string
data = {
    "name": "Alice",
    "age": 30,
    "scores": [95, 87, 91],
    "active": True
}

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

# JSON string to Python dict
parsed = json.loads(json_string)
print(parsed["name"])  # "Alice"

File Operations

import json

# Write JSON to file
data = {"users": [{"name": "Alice"}, {"name": "Bob"}]}
with open('data.json', 'w') as f:
    json.dump(data, f, indent=2)

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

Custom Serialization

import json
from datetime import datetime, date

class CustomEncoder(json.JSONEncoder):
    def default(self, obj):
        if isinstance(obj, (datetime, date)):
            return obj.isoformat()
        if isinstance(obj, set):
            return list(obj)
        if hasattr(obj, '__dict__'):
            return obj.__dict__
        return super().default(obj)

data = {
    "event": "Conference",
    "date": datetime.now(),
    "tags": {"python", "tech"},
    "attendees": 500
}

json_str = json.dumps(data, cls=CustomEncoder, indent=2)

Advanced Options

import json

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

# Compact output
compact = json.dumps(data, separators=(',', ':'))
# '{"name":"Alice","age":30,"city":"NYC"}'

# Sort keys
sorted_json = json.dumps(data, sort_keys=True)

# Handle non-serializable objects
def handle_non_serializable(obj):
    return str(obj)

json.dumps({"date": datetime.now()}, default=handle_non_serializable)

# Parse with object_hook for custom decoding
def as_complex(dct):
    if '__complex__' in dct:
        return complex(dct['real'], dct['imag'])
    return dct

JSON Streaming

import json

# Write large JSON arrays incrementally
def write_large_json(filename, items):
    with open(filename, 'w') as f:
        f.write('[\n')
        for i, item in enumerate(items):
            json.dump(item, f)
            if i < len(items) - 1:
                f.write(',\n')
        f.write('\n]')

# Read large JSON files
def read_large_json(filename):
    with open(filename, 'r') as f:
        for line in f:
            yield json.loads(line)

Key Takeaways

1. json.dumps() encodes Python objects to JSON strings
2. json.loads() decodes JSON strings to Python objects
3. Use indent for pretty-printing
4. Custom encoder for non-standard types
5. JSON is text — use streaming for large data