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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def calculate_query_times(**kwargs):
 """ Calculates aggregate query times from all iteration times Kwargs: total_times(list):
 List of total time calculations execution_times(list):
 List of execution_time calculations results_iter_times(list):
 List of results_iter_time calculations connect_times(list):
 List of connect_time calculations Returns: query_execution(dict):
 Query times False(bool):
 The query failed. Exception should be logged. """

    return {
        "total_time_avg": round(numpy.mean(kwargs["total_times"]), 1),
        "total_time_min": round(numpy.min(kwargs["total_times"]), 1),
        "total_time_max": round(numpy.max(kwargs["total_times"]), 1),
        "total_time_85": round(numpy.percentile(kwargs["total_times"], 85), 1),
        "execution_time_avg": round(numpy.mean(kwargs["execution_times"]), 1),
        "execution_time_min": round(numpy.min(kwargs["execution_times"]), 1),
        "execution_time_max": round(numpy.max(kwargs["execution_times"]), 1),
        "execution_time_85": round(
            numpy.percentile(kwargs["execution_times"], 85), 1
        ),
        "execution_time_25": round(
            numpy.percentile(kwargs["execution_times"], 25), 1
        ),
        "execution_time_std": round(numpy.std(kwargs["execution_times"]), 1),
        "connect_time_avg": round(numpy.mean(kwargs["connect_times"]), 1),
        "connect_time_min": round(numpy.min(kwargs["connect_times"]), 1),
        "connect_time_max": round(numpy.max(kwargs["connect_times"]), 1),
        "connect_time_85": round(
            numpy.percentile(kwargs["connect_times"], 85), 1
        ),
        "results_iter_time_avg": round(
            numpy.mean(kwargs["results_iter_times"]), 1
        ),
        "results_iter_time_min": round(
            numpy.min(kwargs["results_iter_times"]), 1
        ),
        "results_iter_time_max": round(
            numpy.max(kwargs["results_iter_times"]), 1
        ),
        "results_iter_time_85": round(
            numpy.percentile(kwargs["results_iter_times"], 85), 1
        ),
    }