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Python的try except：别让你的代码裸奔，异常处理才是真护身符
2026/7/27 1:19:31 网站建设 项目流程

现在, 绝大多数的编程语言, 都对异常处理予以支持, 异常处理的通行做法是, 把正常执行的代码, 放置在特定的代码块之中, 随后, 再把处理异常的代码, 放置在另外一个代码块之中, 要是正常执行的代码块里的, 某条语句抛出了异常, 那么就会直接跳到, 处理异常的代码块里面去, 继续进行执行。并且, 在正常的代码块里面, 抛出异常语句后面的, 所有代码都不会被执行。实际上, 最初的错误处理并非如此, 而是依据具体的错误类型, 通过条件来加以判断, 下面是处理错误的伪代码:

if 错误1: print('这是错误1')e1if 错误2: print('这是错误2')elif 错误3： print('这是错误3')e1if 错误4： print('这是错误4')else: print('正常执行的代码')

虽然借助条件判断错误, 要是从技术层面来讲是可行的, 然而针对一个程序所抛却出的错误数量, 又处于未知的状态, 由此可见, 凭借条件极有可能没办法处置所有的错误,为了能够尽可能地去应对所有的错误, 可以运用语言的try……语句, 该语句能够捕获诸多不同的异常, 其异常处理机制能够让程序具备相当出色的容错性能, 进而促使程序变得更加健全强壮。当程序运行过程中遭遇意外状况的时候, 系统会自动生成一个Error对象用以告知程序, 借此达成把“业务实现代码”以及“错误处理代码”区分开来, 进而提供更强的可读性。下面是 异常处理机制的语法结构：

try: # 正常的业务实现代码 ... ... except (Errorl, Error2,,.)as e: # 处理异常的代码 ... ...

倘若于执行try块以内的业务逻辑代码之际出现异常, 系统会自主生成一个异常对象, 这个异常对象会被递交予解释器, 此过程称作引发异常。当解释器接收到异常对象时, 会寻觅可以对该异常对象予以处理的块, 要是寻获适宜的块, 便会将该异常对象交付给此块处理, 这流程称为捕获异常。要是解释器寻觅不到捕获异常的块, 那么运行时环境就会终止, 解释器亦会退出。下面是一个运用try...块的例子: 示例代码: . py。

x = Nonewhile True: try: if x == None: x = int(input("请输入分子：")) y = int(input("请输入分母：")) print("x / y = {}".format(x / y)) break; except : print("分母不能为0，请重新输入分母！")

在这段代码的try语句里头, 有着用来进行分子输入之分母输入的代码。当所输入的分母成为 0 这个数值的时候, 就会引发异常从而就是执地其块 里面 的种种代码, 其过程是这样子的:

请输入分子：20请输入分母：0分母不能为0，请重新输入分母！请输入分母：12x / y = 1.6666666666666667

过往回顾: 程序编写思路方面, 存在着这样一些内容, 其一为类的实例化方法, 其二是方法深入剖析, 其三是成员变量, 还有类别的继承, 对类的动态特性加之以约束, 采用特定函数来定义类, 进一步搞定一批类所具备的特性, 详细阐释枚举类型。WWw.Shaer.Shricgs.cN/Article/details/22393.sHtML
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