Json Data Handling

This covers the JSON fundamentals you actually need: parsing, serialization, file I/O, and pretty printing in both Python and JavaScript. It goes beyond basics with custom encoders for datetime objects, circular reference handling, and streaming large files with ijson instead of loading everything into memory. The deep merge and safe nested access patterns are genuinely useful for real API work. What I appreciate is the direct comparison between Python's json module and JavaScript's JSON object, plus the jsonschema validation example that saves you from writing manual checks. The streaming section is brief but points you in the right direction when you hit that 500MB JSON file.

skills.sh installs: 394
GitHub stars: 79
last updated: Aug 21, 2026

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Install

$ npx -y skills add bobmatnyc/claude-mpm-skills --skill json-data-handling --agent claude-code

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Files

JSON Data Handling

Working effectively with JSON data structures.

Python

Basic Operations

import json

# Parse JSON string
data = json.loads('{"name": "John", "age": 30}')

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

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

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

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

Advanced

# Custom encoder for datetime
from datetime import datetime

class DateTimeEncoder(json.JSONEncoder):
    def default(self, obj):
        if isinstance(obj, datetime):
            return obj.isoformat()
        return super().default(obj)

json_str = json.dumps({'date': datetime.now()}, cls=DateTimeEncoder)

# Handle None values
json.dumps(data, skipkeys=True)

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

JavaScript

Basic Operations

// Parse JSON string
const data = JSON.parse('{"name": "John", "age": 30}');

// Convert to JSON string
const jsonStr = JSON.stringify(data);

// Pretty print
const jsonStr = JSON.stringify(data, null, 2);

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