Can you tell about a unique or important feature you have implemented in your practice?

In one of the projects, I implemented a function for automatic processing and normalization of data from different sources for subsequent analysis. This function accepted data in various formats (JSON, CSV, XML), automatically determined the structure, converted the data to a unified format, and filtered based on specified criteria.

An example of a simplified implementation in Python:

import json
import csv
from xml.etree import ElementTree as ET

def normalize_data(data, data_type):
    if data_type == 'json':
        parsed = json.loads(data)
    elif data_type == 'csv':
        reader = csv.DictReader(data.splitlines())
        parsed = list(reader)
    elif data_type == 'xml':
        root = ET.fromstring(data)
        parsed = [{child.tag: child.text for child in elem} for elem in root]
    else:
        raise ValueError('Unsupported data type')
    
    # Example normalization: convert all keys to lowercase
    normalized = []
    for item in parsed:
        normalized.append({k.lower(): v for k, v in item.items()})
    return normalized

This significantly simplified integration with different systems and accelerated data preparation for analytics.