factor_cache.py

from functools import lru_cache


@lru_cache(maxsize=128)
def compute_moving_average(symbol: str, window: int, price_data: tuple) -> float:
    """Compute the moving average of the given price data over a specified window size.

    Args:
        symbol (str): The identifier for the financial instrument.
        window (int): The number of periods over which to calculate the moving average.
        price_data (tuple): A tuple of numeric price values, with the most recent data at the end.

    Returns:
        float: The computed moving average value.

    Raises:
        ValueError: If the length of price_data is less than the specified window size.

    This function is typically used to obtain the latest moving average for a symbol to support caching or further analysis."""
    if len(price_data) < window:
        raise ValueError("Not enough data for the specified window size")
    return sum(price_data[-window:]) / window