# branch_predict.py

# branch_predict.py

import random
import itertools

test_data = [p for p in itertools.permutations(range(1, 10), 4)]
test = []

def branch_predict(choices=None, ans=None):
    global tree

    if not choices:
        tree = {'choices': []}  # Reset the tree
        return None

    def predict(choices):
        current_node = tree
        for choice in choices:
            if choice not in current_node:
                current_node[choice] = {}
            current_node = current_node[choice]
        return current_node.get('prediction')

    if not ans:
        return 1 if predict(choices) else 0

    # Repair tree structure based on choices and ans
    node = tree
    for choice in choices:
        if choice not in node:
            node[choice] = {}
        node = node[choice]
    node['prediction'] = ans
branch_predict()

def test_elimination():
    global test
    def validate_list(numbers):
        contains_2_and_5 = (2 in numbers and 5 in numbers)
        contains_7_at_index_2_or_3 = 7 in (numbers[3:4])

        confidence = ''
        issue = ''
        if contains_2_and_5:
            ans = ('N', 0)
            issue = 'contains_2_and_5'
        elif contains_7_at_index_2_or_3:
            ans = ('N', 0)
            issue = 'contains_7_at_index_2_or_3'
        elif 10 < sum(chosen_numbers) < 20:
            ans = ('N', 0)
            issue = 'sum = ' + str(sum(chosen_numbers))
        else:
            ans = ('Y', 1)
            confidence = '...'
        predicted = branch_predict(numbers)
        stars = '*****'
        if predicted:
            confidence = '$$$'
        if predicted != ans[1]:
            stars = '     '
            branch_predict(numbers, ans)
        print(chosen_numbers, stars, [ans[1], predicted], confidence, '   ' + issue)

    for i in range(5000):
        if not test:
            test = test_data[:]
            random.shuffle(test)
        chosen_numbers = test.pop()
        guess = branch_predict(chosen_numbers)
        validate_list(chosen_numbers)

test_elimination()