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This article introduces the relevant knowledge of "how to add meta-information to function parameters by python". In the operation of actual cases, many people will encounter such a dilemma, so let the editor lead you to learn how to deal with these situations. I hope you can read it carefully and be able to achieve something!

1. Method

Using function argument annotations is a good way to prompt programmers how to use this function correctly. For example, here is an annotated function:

Def add (x:int, y:int)-> int: return x + y

The python interpreter does not add any semantics to these annotations. They are not checked by type, and the runtime is no different from what it was before it was annotated. However, it is very helpful for those who read the source code. Third-party tools and frameworks may add semantics to these annotations. At the same time, they also appear in the document.

> > help (add) Help on function add in module _ main__:add (x: int, y: int)-> int >

Although you can use any type of object to annotate a function (such as numbers, strings, object instances, etc.), it is generally better to use classes or strings.

two。 Supplement

Function annotations are only stored in the _ _ annotations__ attribute of the function. For example:

> add.__annotations__ {'yearly:,' return':, 'Xerox:}

Although annotations may be used in many ways, their main use is documentation. Because python does not have a type declaration, it is usually difficult to know what parameters should be passed to this function just by reading the source code. At this point, the use of annotations can give programmers more hints so that they can use functions correctly.

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