使用python编写完整的可以将正规式((ab)|b)(a|(ba)*)a转化成NFA的代码，并将NFA以文本的形式输出，并可以使用graphviz进行查看

好的，下面是代码实现：

import graphviz

class State:
    def __init__(self, state_id, is_final=False):
        self.state_id = state_id
        self.is_final = is_final
        self.transitions = {}

    def add_transition(self, symbol, state):
        if symbol not in self.transitions:
            self.transitions[symbol] = []
        self.transitions[symbol].append(state)

class NFA:
    def __init__(self, start_state, end_state):
        self.start_state = start_state
        self.end_state = end_state
        
    def to_dot_language(self):
        dot = graphviz.Digraph(comment='NFA')
        dot.node(str(id(self.start_state)), shape='point')
        dot.node(str(id(self.end_state)), shape='doublecircle')
        dot.edge(str(id(self.start_state)), str(id(self.end_state)), label='ε')
        visited = set()
        stack = [self.start_state]
        visited.add(self.start_state)
        while stack:
            state = stack.pop()
            for symbol, next_states in state.transitions.items():
                for next_state in next_states:
                    dot.node(str(id(next_state)))
                    dot.edge(str(id(state)), str(id(next_state)), label=symbol)
                    if next_state not in visited:
                        visited.add(next_state)
                        stack.append(next_state)
        return dot.source
        
def parse_regex(regex):
    stack = []
    state_id = 0
    for c in regex:
        if c == '(':
            stack.append(state_id)
            state_id += 1
        elif c == ')':
            end_state_id = state_id
            start_state_id = stack.pop()
            start_state = State(start_state_id)
            end_state = State(end_state_id, is_final=True)
            start_state.add_transition('ε', end_state)
            if len(stack) > 0:
                prev_start_state_id = stack[-1]
                prev_start_state = State(prev_start_state_id)
                prev_start_state.add_transition('ε', start_state)
                stack[-1] = start_state_id
            else:
                stack.append(start_state_id)
        elif c == '|':
            start_state_id = stack[-1]
            start_state = State(start_state_id)
            end_state_id = state_id
            end_state = State(end_state_id, is_final=True)
            start_state.add_transition('ε', end_state)
            prev_start_state_id = stack[-2]
            prev_start_state = State(prev_start_state_id)
            prev_start_state.add_transition('ε', end_state)
            stack[-2] = start_state_id
            state_id += 1
        elif c == '*':
            state_id += 1
            start_state_id = stack[-1]
            end_state_id = state_id
            start_state = State(start_state_id)
            end_state = State(end_state_id, is_final=True)
            start_state.add_transition('ε', end_state)
            end_state.add_transition('ε', start_state)
            if len(stack) > 1:
                prev_start_state_id = stack[-2]
                prev_start_state = State(prev_start_state_id)
                prev_start_state.add_transition('ε', start_state)
            stack[-1] = start_state_id
        else:
            state_id += 1
            start_state_id = stack[-1]
            end_state_id = state_id
            start_state = State(start_state_id)
            end_state = State(end_state_id, is_final=True)
            start_state.add_transition(c, end_state)
            stack[-1] = start_state_id
            if len(stack) > 1:
                prev_start_state_id = stack[-2]
                prev_start_state = State(prev_start_state_id)
                prev_start_state.add_transition('ε', start_state)
    start_state_id = stack[0]
    end_state_id = state_id + 1
    start_state = State(start_state_id)
    end_state = State(end_state_id, is_final=True)
    start_state.add_transition('ε', stack[-1])
    start_state.add_transition('ε', end_state)
    return NFA(start_state, end_state)

regex = '((ab)|b)(a|(ba)*)a'
nfa = parse_regex(regex)
dot_language = nfa.to_dot_language()
print(dot_language)

这段代码中，我们首先定义了一个状态类`State`，每个状态都有一个唯一的ID，表示它在NFA中的位置；还有一个`is_final`属性表示这个状态是否是终止状态；以及一个`transitions`字典表示从这个状态出发，可以通过哪些字符转移到哪些状态。

接着我们定义了一个NFA类，它包含了开始状态和结束状态两个属性，以便之后生成DOT语言并可视化。

然后我们定义了一个函数`parse_regex`，用于将正则表达式解析成NFA。具体地，我们使用一个栈来存储状态ID，遍历正则表达式中的每个字符。当遇到左括号时，我们将一个新的开始状态和结束状态加入到NFA中，并将开始状态和结束状态之间加一条ε转移；当遇到右括号时，我们弹出栈中最后一个左括号对应的开始状态ID，将之前的NFA片段与新的开始状态和结束状态连接起来，并加入到栈中；当遇到竖杠时，我们弹出栈中最后两个元素，将它们连接起来，并加入到栈中；当遇到星号时，我们将最后一个元素作为开始状态，新建一个结束状态，将开始状态与结束状态之间加一条ε转移，结束状态与开始状态之间也加一条ε转移。最后，我们将左右两端的开始和结束状态连接起来。

最后，我们可以使用DOT语言生成一个图形表示NFA，并输出DOT语言字符串。可以通过安装graphviz，并运行以下命令将DOT语言渲染成PNG图片：

# 安装graphviz
!pip install graphviz

# 渲染PNG图片
from graphviz import Source
s = Source.from_file('test.dot', format='png')
s.view()

这样就可以查看生成的NFA图像了。