Detailed explanation of anonymous functions in Python

Detailed explanation of anonymous functions in Python

Python is a high-level programming language, object-oriented, highly scalable, and has been widely used in mathematical calculations, data processing and other fields. Python supports functional programming, in which anonymous functions are an important part of functional programming. This article will introduce anonymous functions in Python in detail.

What is an anonymous function?

Anonymous function, also called lambda function, is a function without a function name. It is a one-time function that is defined when needed and discarded after use. For example, we can define a simple anonymous function like this:

lambda x: x**2

The meaning of the above anonymous function is to pass in a parameter x and return the square of x. Notice that there is no function name here, and the lambda keyword is used to represent the anonymous function.

The grammatical structure of lambda function

The grammatical structure of lambda function is:

lambda arguments: expression

Among them, arguments represent the parameters passed in, and expression is the expression. As in the previous example, the arguments are x and the expression is the square of x.

In addition, the lambda function can have multiple parameters, separated by commas, for example:

lambda x, y: x + y

The meaning of the above lambda function is to pass in two parameters x and y and return Their sum.

Using lambda functions

There are many ways to use anonymous functions in Python. Here are some common methods.

1. Assign the lambda function to a variable

We can assign a lambda function to a variable, and then call the anonymous function through the variable name. For example:

f = lambda x: x**2
print(f(4)) # 输出16

The above code defines a lambda function, assigns it to the variable f, and then calls f(4), returns the square value of 4, 16.

2. Pass in other functions as parameters

When calling other functions, we can pass the lambda function as a parameter to perform different functions. For example:

def apply(func, n):
    return func(n)

print(apply(lambda x: x**2, 5)) # 输出25

In the above code, the apply function accepts two parameters, the first parameter is a function, and the second parameter is a number. When the second parameter (here the number 5) is passed in, this function will be called as the first parameter, passing the number 5 as the parameter. The lambda function expression x**2 is passed to the apply function as the first argument, so 25 is output.

3. Use in combination with other functions

lambda function is often used in combination with other functions, such as filter function and map function. The filter function takes a list (or other iterable object) as the first parameter and returns a new list containing only elements that meet the condition. The map function takes a list (or other iterable object) as the first parameter and returns a new list processed by the function.

For example, the following code demonstrates the use of combining the filter function and the lambda function:

my_list = [1, 3, 5, 6, 8, 9]
filtered_list = list(filter(lambda x: x % 3 == 0, my_list))
print(filtered_list) # 输出[3, 6, 9]

In the above code, the filter function is used to filter the list my_list, and the lambda function is used to return a value divisible by 3 elements, and finally assign the result to filtered_list.

Conclusion

This article introduces the definition, grammatical structure and usage of anonymous functions in Python. Anonymous functions are often used in combination with other functions to simplify code and improve code readability. Proficient in the use of anonymous functions can help improve code quality and work efficiency.

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