请写一段完整的Python代码，实现输入DFA输出最小化的DFA

当然可以。在Python中，我们可以使用字典和列表来表示有限状态自动机（DFA），然后通过一些算法来实现最小化过程。这里是一个简单的例子，使用了自顶向下的Kleene算法：

from collections import defaultdict

def create_dfa(states, alphabet, initial_state, transitions):
    dfa = {'states': states, 'alphabet': alphabet, 'initial_state': initial_state}
    for char in alphabet:
        transition_dict = defaultdict(list)
        for state in states:
            if (state, char) in transitions:
                transition_dict[state].append(transitions[(state, char)])
            else:
                transition_dict[state].append(None)
        dfa[char] = transition_dict
    return dfa

def minimize_dfa(dfa):
    new_states = [dfa['initial_state']]
    while True:
        added_new_state = False
        new_transitions = {}
        for char in dfa['alphabet']:
            next_states = set()
            for current_state in new_states:
                for possible_next_state in dfa[char][current_state]:
                    if possible_next_state is not None and possible_next_state not in new_states:
                        added_new_state = True
                        next_states.add(possible_next_state)
            if len(next_states) == 1:
                next_state = list(next_states)[0]
                if char not in new_transitions:
                    new_transitions[char] = []
                new_transitions[char].append(next_state)
            else:
                if char not in new_transitions:
                    new_transitions[char] = [{None}]
        if not added_new_state:
            break
        new_states = list(new_transitions.keys()) + list(set().union(*new_transitions.values()))

    minimized_dfa = {
        'states': new_states,
        'alphabet': dfa['alphabet'],
        'initial_state': new_states[0],
        'transitions': {char: {new_states.index(state): state for state in states} for char, states in new_transitions.items()}
    }
    return minimized_dfa

# 示例：
states = ['q0', 'q1', 'q2']
alphabet = ['a', 'b']
initial_state = 'q0'
transitions = {
    ('q0', 'a'): 'q1',
    ('q0', 'b'): 'q2',
    ('q1', 'a'): 'q1',
    ('q1', 'b'): 'q0',
    ('q2', 'a'): 'q0',
    ('q2', 'b'): 'q2'
}

dfa = create_dfa(states, alphabet, initial_state, transitions)
minimized_dfa = minimize_dfa(dfa)

print("Minimized DFA:")
for key, value in minimized_dfa.items():
    print(f"{key}: {value}")

这段代码首先创建了一个基本的DFA结构，然后使用Kleene算法进行最小化。请注意，这只是一个简化的版本，实际应用中可能需要处理更复杂的情况。