How to Convert CSV Column Types While Reading in Python

import csv
from pathlib import Path
from typing import Any

def read_csv_with_types(filepath: str) -> list[dict[str, Any]]:
    """Read CSV and convert column types based on header suffixes."""
    converters = {
        "int": int,
        "float": float,
        "str": str,
        "bool": lambda v: v.strip().lower() == "true",
    }
    
    rows = []
    with Path(filepath).open(newline="") as f:
        reader = csv.DictReader(f)
        for raw_row in reader:
            typed_row = {}
            for header, value in raw_row.items():
                # If header contains a type suffix like "age:int", use it
                if ":" in header:
                    column_name, type_name = header.split(":", 1)
                    typed_row[column_name] = converters[type_name](value)
                else:
                    typed_row[header] = value
            rows.append(typed_row)
    return rows

if __name__ == "__main__":
    import tempfile
    sample = "name:str,age:int,score:float,active:bool\nAlice,30,95.5,true\nBob,25,88.0,false\n"
    with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f:
        f.write(sample)
        temp_path = f.name
    
    result = read_csv_with_types(temp_path)
    for row in result:
        print(f"{row['name']}: age={row['age']} ({type(row['age']).__name__}), "
              f"score={row['score']} ({type(row['score']).__name__}), "
              f"active={row['active']} ({type(row['active']).__name__})")