json-data-analysis

name	json-data-analysis
description	Python patterns for analyzing large JSON datasets to find specific information, track tokens, and write answers in the required format.

JSON Data Analysis

Loading and Analyzing Large JSON Files

import json

with open('/path/to/file.json') as f:
    data = json.load(f)

Counting Tokens (Approximate)

import json

def count_tokens(text):
    """Approximate token count: ~4 chars per token"""
    return len(str(text)) // 4

# Or use tiktoken for more accurate counting
# pip install tiktoken
import tiktoken
enc = tiktoken.get_encoding("cl100k_base")
tokens = len(enc.encode(str(data)))

Writing Answer File

import json

answers = {
    "q1": {"answer": ["emp001", "emp002"], "tokens": 150},
    "q2": {"answer": ["emp003"], "tokens": 200},
}

with open('/root/answer.json', 'w') as f:
    json.dump(answers, f, indent=4)

Searching Nested Structures

def deep_search(obj, keyword):
    """Recursively search for keyword in nested structure"""
    results = []
    if isinstance(obj, str):
        if keyword.lower() in obj.lower():
            results.append(obj)
    elif isinstance(obj, dict):
        for v in obj.values():
            results.extend(deep_search(v, keyword))
    elif isinstance(obj, list):
        for item in obj:
            results.extend(deep_search(item, keyword))
    return results

Extracting Employee IDs

import re

def extract_employee_ids(text):
    """Extract employee IDs matching pattern like EMP001, E001, etc."""
    return re.findall(r'\b[A-Z]{1,3}\d{3,6}\b', text)