Aaronson Oracle

oracle.py

from collections import defaultdict, deque


class Model:
    def __init__(self):
        self.counts = defaultdict(lambda: {"f": 0, "d": 0})
        self.last_six = deque(maxlen=6)
        self.num_correct = 0
        self.num_predictions = 0

    def fit(self, x):
        if x in ("f", "d"):
            self.last_six.append(x)

    def predict(self, x):
        if len(self.last_six) >= 5:
            fivegram = "".join(list(self.last_six)[:5])
            m = self.counts[fivegram]
            prediction = "f" if not m or m["f"] > m["d"] else "d"

            # update counts and accuracy
            self.counts[fivegram][x[-1]] += 1
            self.num_predictions += 1
            self.num_correct += prediction == x

            return prediction

    def fit_predict(self, x):
        self.fit(x)
        return self.predict(x)

    @property
    def accuracy(self):
        return round((self.num_correct / self.num_predictions) * 100)


def cli():
    from getch import getch

    model = Model()
    print("Start typing, only 'f' or 'd' are allowed")
    while True:
        char = getch()
        prediction = model.fit_predict(char)
        msg = f"observed {char}"
        if prediction is not None:
            msg += f" predicted {prediction}"
        if model.num_predictions > 9:
            msg += f" {model.accuracy}% accurate"
        print(msg)


if __name__ == "__main__":
    cli()

Start typing, only 'f' or 'd' are allowed
observed f
observed d
observed d
observed f
observed f predicted d
observed d predicted f
observed d predicted d
observed f predicted d
observed d predicted d
observed f predicted d
observed d predicted d
observed f predicted d
observed f predicted d
observed d predicted d 40% accurate
observed f predicted d 36% accurate
observed d predicted d 42% accurate
observed d predicted d 46% accurate
observed f predicted d 43% accurate
observed d predicted d 47% accurate
observed f predicted f 50% accurate
observed d predicted d 53% accurate
observed f predicted f 56% accurate
observed d predicted f 53% accurate
observed f predicted f 55% accurate
observed f predicted d 52% accurate
observed d predicted d 55% accurate
observed f predicted f 57% accurate
observed d predicted d 58% accurate
observed d predicted d 60% accurate
observed f predicted f 62% accurate
observed f predicted d 59% accurate
observed d predicted d 61% accurate
observed f predicted d 59% accurate
observed d predicted d 60% accurate
observed f predicted d 58% accurate
observed d predicted f 56% accurate
observed f predicted f 58% accurate
observed d predicted d 59% accurate