"lambda"是什么?在Python中是什么意思，最简单的使用方法是什么? [英] What does "lambda" mean in Python, and what's the simplest way to use it?

问题描述

您能否提供一个示例以及其他示例来说明何时以及何时不使用Lambda? 我的书给了我一些例子，但它们令人困惑.

Can you give an example and other examples that show when and when not to use Lambda? My book gives me examples, but they're confusing.

推荐答案

Lambda，它源自 Lambda微积分和(AFAIK)最初是在 Lisp 中实现的，基本上是匿名的函数-一个没有名称的函数，该函数可在线使用，换句话说，您可以在一个表达式中为lambda函数分配一个标识符，如下所示:

Lambda, which originated from Lambda Calculus and (AFAIK) was first implemented in Lisp, is basically an anonymous function - a function which doesn't have a name, and is used in-line, in other words you can assign an identifier to a lambda function in a single expression as such:

>>> addTwo = lambda x: x+2
>>> addTwo(2)
4

这将addTwo分配给匿名函数，该函数接受1个参数x，并且在函数主体中将2加到x，它返回函数主体中最后一个表达式的最后一个值，因此没有return关键字

This assigns addTwo to the anonymous function, which accepts 1 argument x, and in the function body it adds 2 to x, it returns the last value of the last expression in the function body so there's no return keyword.

上面的代码大致等同于:

The code above is roughly equivalent to:

>>> def addTwo(x):
...     return x+2
... 
>>> addTwo(2)
4

除非您未使用函数定义，否则将为lambda分配一个标识符.

Except you're not using a function definition, you're assigning an identifier to the lambda.

使用它们的最佳位置是当您真的不想使用名称定义函数时，可能是因为该函数只会被使用一次，而不会被多次使用，在这种情况下使用函数定义会更好.

The best place to use them is when you don't really want to define a function with a name, possibly because that function will only be used one time and not numerous times, in which case you would be better off with a function definition.

使用lambda的哈希树示例:

Example of a hash tree using lambdas:

>>> mapTree = {
...     'number': lambda x: x**x,
...     'string': lambda x: x[1:]
... }
>>> otype = 'number'
>>> mapTree[otype](2)
4
>>> otype = 'string'
>>> mapTree[otype]('foo')
'oo'

在此示例中，我实际上并不想为这两个函数中的任何一个定义名称，因为我只会在哈希中使用它们，因此，我将使用lambda.

In this example I don't really want to define a name to either of those functions because I'll only use them within the hash, therefore I'll use lambdas.

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