A brief introduction and detailed usage of lambda expressions in Python

Introduction and detailed usage of lambda function in Python

In Python, lambda function is a special anonymous function that can be used anywhere a function object is required use. Lambda functions are usually used to define simple functions that can have only one expression and return a result. This article will introduce you to the basic usage and common application scenarios of lambda functions, and provide specific code examples.

1. Basic syntax of lambda function:
   The syntax of lambda function is simpler and clearer than ordinary functions. The basic form is as follows:
   lambda parameters: expression

Among them, lambda is the keyword, the parameters are the input parameters of the function, and the expression is the function implementation and return result of the function.

2. Characteristics of the lambda function:
3. The lambda function is an anonymous function and has no function name. Therefore, when it needs to be used, it can be assigned to a variable or called as another function. parameter.
4. The lambda function can accept any number of parameters, but can only have one expression.
5. The lambda function returns a function object rather than the result of executing the function.
6. Usage examples of lambda function:

3.1 Simple lambda function example:
For example, if we need a function to calculate the sum of two numbers, we can use the lambda function to achieve the following ：

add = lambda x, y: x + y
print(add(1, 2))  # 输出3

In this example, we use lambda to define an anonymous function add, which has two parameters x and y, and returns the result x y. Then we call this function and pass in parameters 1 and 2, and get the result 3.

3.2 The lambda function is passed as a parameter to other functions:
lambda function is often used as a parameter to be passed to other functions. The following is an example of using the sorted function and the lambda function to sort the list:

fruits = ['apple', 'banana', 'cherry', 'durian']

# 按照字母顺序排序
sorted_fruits = sorted(fruits, key=lambda x: x)
print(sorted_fruits)  # 输出['apple', 'banana', 'cherry', 'durian']

# 按照字符串长度排序
sorted_fruits = sorted(fruits, key=lambda x: len(x))
print(sorted_fruits)  # 输出['apple', 'banana', 'cherry', 'durian']

In this example, we use the sorted function to sort the fruit list, and the sorting rules are defined through the lambda function. In the first example, we use key=lambda x: x to sort alphabetically. In the second example, we use key=lambda x: len(x) Sort by string length.

3.3 The lambda function is used in combination with the map and filter functions:
The map function can operate on each element in the sequence and return a new list, and the filter function can filter the sequence according to a certain condition. . Here is an example of using the lambda function combined with the map and filter functions to operate on a list:

numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

# 将列表中的每个元素平方
squared_numbers = list(map(lambda x: x ** 2, numbers))
print(squared_numbers)  # 输出[1, 4, 9, 16, 25, 36, 49, 64, 81, 100]

# 过滤出列表中的偶数
even_numbers = list(filter(lambda x: x % 2 == 0, numbers))
print(even_numbers)  # 输出[2, 4, 6, 8, 10]

In this example, we use the map function and the lambda function to square each element in the list, using the filter function and lambda function to filter out even numbers in the list.

Through the above examples, we can see the flexible application of lambda functions in Python programming. The lambda function is a concise and powerful way to define functions, especially suitable for some simple functional requirements. When needed, you can always use lambda functions to improve the readability and efficiency of your code.

Summary:
This article details the basic usage and common application scenarios of lambda functions in Python, and provides specific code examples. Through lambda functions, you can easily define simple functions and apply them to various scenarios such as list sorting, parameter passing, and sequence operations. In daily Python programming, the flexible use of lambda functions can improve the readability and efficiency of the code, while simplifying the structure and logic of the program.

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