A Brief Introduction to lambda anonymous functions in Python

Source: Internet
Author: User

A lambda function is also called an anonymous function. That is, the function has no specific name. Let's take a look at the simplest example:

Copy codeThe Code is as follows: def f (x ):
Return x ** 2
Print f (4)

If lambda is used in Python, it is written as follows:Copy codeThe Code is as follows: g = lambda x: x ** 2
Print g (4)

Lambda expressions are implemented in many programming languages. For example, C #:

Copy codeThe Code is as follows: var g = x => x ** 2
Console. WriteLine (g (4 ))

So what is the use of lambda expressions? Many people have raised questions. lambda saves the name of a function compared to a common function, and such an anonymous function cannot be called elsewhere. Actually, it is true that lambda does not play an amazing role in a dynamic language like Python, because there are many other ways to replace lambda. At the same time, lambda statements sometimes seem less pythonic. Some even suggested that lambda should be canceled in later Python versions.

Looking back, is lambda really useless in Python? Actually not. At least I can think of the following points:

1. When using Python to write some execution scripts, using lambda can save the process of defining functions and simplify the code.

2. For some abstract functions that will not be reused elsewhere, it is also difficult to give them a name. You do not need to consider naming when using lambda.

3. Use lambda to make the code easier to understand in some cases.

Lambda Basics
In a lambda statement, there are multiple parameters before the colon, which can be separated by commas (,). return values on the right of the colon. Lambda statements are actually built as a function object. Let's see:

Copy codeThe Code is as follows: g = lambda x: x ** 2
Print g
<Function <lambda> at 0x00AFAAF0>

C #3.0 starts with lambda expressions, saving you the trouble of using delegate. In C #, the lambda expression keyword is =>. Let's look at the following example:Copy codeThe Code is as follows: var array = new int [] {2, 3, 5, 7, 9 };
Var result = array. Where (n => n> 3); // [5, 6, 9]

C # using the extension method makes the array object have a convenient method like Where and Sum. In Python, there are also several defined global functions that are easy to use. They are filter, map, and reduce.Copy codeCode: >>> foo = [2, 18, 9, 22, 17, 24, 8, 12, 27]
>>>
>>> Print filter (lambda x: x % 3 = 0, foo)
[18, 9, 24, 12, 27]
>>>
>>> Print map (lambda x: x * 2 + 10, foo)
[14, 46, 28, 54, 44, 58, 26, 34, 64]
>>>
>>> Print reduce (lambda x, y: x + y, foo)
139

Not lambda?
The role of map in the above example is the same as the Where extension method in C #, which is very simple and convenient. But does Python require lambda to be concise? In terms of object traversal processing, Python's for... in... if syntax is already very powerful, and it is better than lambda in terms of readability. For example, the preceding map example can be written as follows:

Copy codeThe Code is as follows: print [x * 2 + 10 for x in foo]

Very simple and easy to understand. The filter example can be written as follows:Copy codeThe Code is as follows: print [x for x in foo if x % 3 = 0]

It is also easier to understand than lambda.

Therefore, when lambda is used, when it is not used, and specific analysis is required, as long as the intent is clearly expressed. In general, if for... in... if can do it, I will not select lambda.

Lambda broken?
Lambda is often used in mathematics teaching. For example, a dude encountered such a problem. He wants to create a Function Array fs = [f0,..., f9] where fi (n) = I + n. Then, he defines a lambda function:

Copy codeThe Code is as follows: fs = [(lambda n: I + n) for I in range (10)]

But the strange thing is,Copy codeThe Code is as follows: >>> fs [3] (4)
13
>>> Fs [4] (4)
13
>>> Fs [5] (4)
13

The result did not meet the expectation of this dude. The expected result should be:Copy codeThe Code is as follows: >>> fs [3] (4)
7
>>> Fs [4] (4)
8
>>> Fs [5] (4)
9

The problem lies in variable I. The above code changes to a simple version that does not use lambda:Copy codeThe Code is as follows: I = 1
Def fs (n ):
Return n + I
Print fs (1) #2
I = 2
Print fs (1) #3

It can be seen that the above is not as expected because I in lambda uses global variables outside of anonymous functions. Modify:Copy codeThe Code is as follows: fs = [(lambda n, I = I: I + n) for I in range (10)]
>>> Fs [3] (4)
7
>>> Fs [4] (4)
8
>>> Fs [5] (4)
9

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