Python Lambda expressions: abbreviated, concise, powerful

python Lambda expressions are a powerful and flexible tool for creating concise, readable, and easy-to-use code. They are great for quickly creating anonymous functions that can be passed as arguments to other functions or stored in variables.

The basic syntax of Lambda expression is as follows:

lambda arguments : expression

For example, the following Lambda expression adds two numbers:

lambda x, y: x + y

This Lambda expression can be passed to another function as a parameter, as shown below:

def sum(x, y):
return x + y

result = sum(lambda x, y: x + y, 1, 2)

In this example, the Lambda expression is passed as a parameter to the sum() function. sum()The function calls the Lambda expression twice, once with 1 and 2 as parameters, and another time with 3 and 4 as parameters. It then adds the two results and stores it in the result variable.

Lambda expressions can also be used to create anonymous functions that can be stored in variables and called later. For example, the following Lambda expression creates an anonymous function that multiplies two numbers:

multiply = lambda x, y: x * y

This anonymous function can be called later, as shown below:

result = multiply(3, 4)

In this example, the anonymous function multiply() is called with 3 and 4 as parameters. The result (12) is stored in the result variable.

Lambda expressions are ideal for situations where you need to quickly create anonymous functions. For example, they are great for mapping or filtering lists or dictionaries. The following example shows how to use Lambda expressions to map lists:

numbers = [1, 2, 3, 4, 5]

squared_numbers = list(map(lambda x: x ** 2, numbers))

print(squared_numbers)

In this example, the map() function is used to map the numbers list. map()The function passes the Lambda expression lambda x: x ** 2 to each list item. This Lambda expression squares each list item and stores it in the squared_numbers list.

Lambda expressions are a powerful tool for creating concise, readable, and easy-to-use code. They are great for quickly creating anonymous functions that can be passed as arguments to other functions or stored in variables. Understanding how to use lambda expressions can help you write more efficient and maintainable Python code.

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