JSON Parsing

Handle JSON data in Python for file I/O, API communication, and data serialization.

Basic Operations

import json

# Parse JSON string
data = json.loads('{"key": "value", "count": 42}')

# Serialize to JSON string
json_str = json.dumps(data)

# Pretty printing
print(json.dumps(data, indent=2))

File I/O

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

# Write JSON file
with open('output.json', 'w') as f:
    json.dump(data, f, indent=2)

Working with Complex Types

from decimal import Decimal
from datetime import datetime

# Custom encoder
class CustomEncoder(json.JSONEncoder):
    def default(self, obj):
        if isinstance(obj, Decimal):
            return float(obj)
        if isinstance(obj, datetime):
            return obj.isoformat()
        return super().default(obj)

# Usage
data = {'price': Decimal('19.99'), 'timestamp': datetime.now()}
json_str = json.dumps(data, cls=CustomEncoder)

Safe Access Patterns

# Get with default
value = data.get('key', 'default_value')

# Nested access
email = data.get('user', {}).get('email', '')

# Check key existence
if 'key' in data:
    process(data['key'])

Validation

# Validate JSON structure
def validate_json(json_str):
    try:
        data = json.loads(json_str)
        return data
    except json.JSONDecodeError as e:
        print(f"Invalid JSON: {e}")
        return None

# Validate schema
def validate_schema(data, required_keys):
    return all(k in data for k in required_keys)

Array Handling

# Parse JSON array
records = json.loads('[{"id": 1}, {"id": 2}]')

# Process array
for record in records:
    print(record['id'])

# JSON Lines format (one JSON per line)
with open('data.jsonl', 'r') as f:
    for line in f:
        record = json.loads(line.strip())
        process(record)

Common Patterns

# Merge dictionaries
merged = {**dict1, **dict2}

# Filter keys
filtered = {k: v for k, v in data.items() if k in allowed_keys}

# Sort keys for consistent output
json.dumps(data, sort_keys=True)