Describe how lambda functions differ from regular functions in terms of syntax

Lambda functions vs. regular functions: Syntax differences

Python lambda functions and regular functions differ in syntax and usage. Here are the key differences:

Definition and syntax:

• Lambda Functions: Lambda functions are defined using the "lambda" keyword, followed by a list of arguments and a single expression.
• Regular Functions: Regular functions are defined using the "def" keyword, followed by the function name, a list of parameters in parentheses, and a block of code indented below.

Example of a lambda function:

lambda_function_result = lambda x, y: x * y

Example of a regular function:

def regular_function(x, y):
         return x *  y

Function Name:

• Lambda Functions: Lambda functions are anonymous functions, which means they have no name. As a result, they can be passed as arguments to other functions or used directly in expressions.
• Regular Functions: Regular functions have a name assigned to them, enabling them to be called and reused by that name.

Number of lines:

• Lambda Functions: Lambda functions can only contain a single expression and cannot contain multiple lines of code. They are designed for short and simple operations.
• Regular Functions: Regular functions can contain several lines of code and can be more complex, allowing for better code organization and readability.

Return Statement:

• Lambda Functions: Lambda functions return the result of evaluating an expression. There is no need to use a return statement explicitly.
• Regular Functions: Regular functions return a value explicitly using a return statement. If no return statement is used, the function returns None.

Usage:

Lambda Functions: Lambda functions are commonly used as anonymous functions for one-time or short operations. They are often used in functional programming constructs like map, filter, and sorted.

Regular Functions: These are more substantial, reusable code blocks that can be called multiple times in the program.