How to Transform a List of Dictionaries with Sets in Python

def transform_data(raw_records):
    """Transform a list of dict records into normalized data with sets for unique values."""
    normalized = []
    unique_names = set()
    all_tags = set()
    
    for record in raw_records:
        # Normalize name to lowercase and strip whitespace
        name = record.get("name", "").strip().lower()
        
        # Only keep records that have a name
        if not name:
            continue
            
        # Extract and clean tags, skipping empty ones
        tags = {tag.strip().lower() for tag in record.get("tags", []) if tag.strip()}
        all_tags.update(tags)
        
        # Build a normalized record
        normalized.append({
            "id": record.get("id"),
            "name": name,
            "tags": tags,
            "active": record.get("active", False)
        })
        
        # Track unique names
        unique_names.add(name)
    
    # Add transformation summary
    result = {
        "records": normalized,
        "unique_names": len(unique_names),
        "all_tags": all_tags,
        "tags_count": len(all_tags),
        "total_records": len(normalized)
    }
    
    return result


if __name__ == "__main__":
    sample_data = [
        {"id": 1, "name": "Alice", "tags": ["Python", "Data"]},
        {"id": 2, "name": "Bob", "tags": ["SQL", "python"]},
        {"id": 3, "name": "  alice  ", "tags": ["ML"]},
        {"id": 4, "name": "", "tags": []},
        {"id": 5, "name": "Carol", "tags": ["Python", "Web"]}
    ]
    
    result = transform_data(sample_data)
    print(f"Total records: {result['total_records']}")
    print(f"Unique names: {result['unique_names']}")
    print(f"All tags: {sorted(result['all_tags'])}")
    print(f"Records: {result['records']}")