July 2017
Intermediate to advanced
398 pages
11h 54m
Chinese
Content preview from Python数据处理
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368
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附录
E
随着你的代码变得更高级和复杂，问题会变得越来越难办。由于你的代码更加抽象，你会
将所有的代码保存在变量中。如果一个函数或方法返回一个不符预期的类型（例如
None
而
不是列表），这个对象可能被传递到另一个函数中——可能是一个不接受
None
类型的函数，
之后抛出一个错误。很可能错误被捕获了，但代码会认为异常是因为另外的问题触发的，
并且继续执行。这会很快地脱离你的控制，并且变成一个相当难以调试的问题。
对于如何处理这些问题，最好的建议是编写非常精准又清晰的代码。你应该积极测试你的
代码（确保没有
bug
），持续关注你的脚本，并注意任何反常的行为，以此确保函数永远返
回期待的内容。你还需要添加日志来帮助确认对象包含的内容。除此之外，清楚你捕获的
异常，而不只是捕获所有的异常，这会帮助你更容易地找到和修复问题。
最后，有时
Python
会实现
PEP-484
（
https://www.python.org/dev/peps/pep-0484/
），它包含了
类型提示，允许你检查传递的变量和代码，以自我检查这些问题。这在未来
Python 3
发布
之前可能不会被合并，但是好消息是，这已经在进行当中，你可以期待在未来看到更多的
有关类型检查的结构。
E.9
捕获多个异常
随着代码的发展，你会想要在同一行代码中捕获多个异常。举个例子，你可能想要捕获一
个
TypeError
，同时还有
AttributeError
。如果你以为传递的是一个字典，而实际上传递的
是一个列表，可能就是这种情况。它可能有一些相同的属性，但是不是所有属性。如果你 ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.