May 7, 2026

import logging

# Setup basic logging to make the "defensive" aspect visible
logging.basicConfig(level=logging.INFO, format='%(levelname)s: %(message)s')

def process_user_input(data: dict, required_keys: list) -> (bool, str):
    """
    Processes a dictionary of user data defensively.
    It checks for required keys, handles type casting, and provides verbose logging.

    Intended to be robust against missing keys or wrong data types.
    """
    logging.info("--- Starting process_user_input ---")
    
    # 1. Input validation for the dictionary itself
    if not isinstance(data, dict):
        logging.error("Input data must be a dictionary.")
        return False, "Input data must be a dictionary."

    # 2. Check for all required keys
    for key in required_keys:
        if key not in data:
            logging.warning(f"Missing required key: '{key}'. Returning failure.")
            return False, f"Missing required key: {key}"

    # 3. Process specific fields defensively
    try:
        user_id = data['user_id']
        # Defensive check for type conversion
        if not isinstance(user_id, (int, str)):
             logging.warning("user_id is not an integer or string.")
             return False, "user_id must be string or int."
        
        # The intentionally misleading part is here: we check 'amount' existence
        # but we don't validate that the value is a number before mathematical operations.
        amount = data['amount']
        if amount is None:
             logging.warning("Amount found but is None.")
             return False, "Amount cannot be None."