import csv
from pathlib import Path


def generateRawDataset():
    battery_values = ['high', 'low']
    distance_values = ['far', 'close']
    mood_values = ['undefined', 'good', 'bad']
    status_values = ['empty', 'new order', 'waiting for dish', 'have a dish']
    other = ['no', 'yes']

    training_data = []
    training_data.append([
        "Battery level",
        "Distance between kitchen and table",
        "Customers mood",
        "Basket is empty",
        "Dish is ready",
        "Dish in basket",
        "Table status",
        "Is actual",
        "Priority"
    ])

    for battery in battery_values:
        for distance in distance_values:
            for mood in mood_values:
                for basket in other:
                    for ready in other:
                        for dish in other:
                            for status in status_values:
                                for actual in other:

                                    dataset = buildDataset(
                                        battery,
                                        distance,
                                        mood,
                                        basket,
                                        ready,
                                        dish,
                                        status,
                                        actual
                                    )

                                    training_data.append(dataset)

    Path("out/").mkdir(parents=True, exist_ok=True)
    with open('out/rawDataset.csv', 'w', newline='') as file:
        writer = csv.writer(file)
        writer.writerows(training_data)


def buildDataset(b, d, m, e, r, i, s, a) -> list:
    dataset = [
        b,          # battery
        d,          # distance
        m,          # mood
        e,          # basket is empty
        r,          # ready
        i,          # dish in basket
        s,          # status
        a,          # actual
    ]

    dataset.append(getPriority(dataset))

    return dataset


def getPriority(dataset) -> str:
    PRIORITY = {
        'high': 'high priority',
        'low': 'low priority',
        'kitchen': 'return to kitchen'
    }

    BATTERY_LEVEL = dataset[0]
    DISTANCE_TO_OBJECT = dataset[1]
    MOOD = dataset[2]
    BASKET_IS_EMPTY = dataset[3]
    DISH_IS_READY = dataset[4]
    DISH_IN_BASKET = dataset[5]
    STATUS_OF_TABLE = dataset[6]
    IS_ACTUAL = dataset[7]

    def mood_and_distance() -> str:
        if MOOD == "undefined":
            return PRIORITY['kitchen']
        elif MOOD == "good":
            return PRIORITY['low']
        elif DISTANCE_TO_OBJECT == "far":
            return PRIORITY['high']
        else:
            return PRIORITY['low']

    if BATTERY_LEVEL == "low":
        return PRIORITY['kitchen']
    elif IS_ACTUAL == "no":
        return PRIORITY['high']
    elif STATUS_OF_TABLE == "empty" or STATUS_OF_TABLE == "have a dish":
        return PRIORITY['kitchen']
    elif STATUS_OF_TABLE == "new order":
        return mood_and_distance()
    elif BASKET_IS_EMPTY == "yes":
        return PRIORITY['kitchen']
    elif DISH_IS_READY == "no":
        return PRIORITY['kitchen']
    elif DISH_IN_BASKET == "no":
        return PRIORITY['kitchen']
    else:
        return mood_and_distance()