Python - Lambda Functions

In Python, a lambda function is a small, anonymous function defined using the keyword lambda. Lambda functions are often used for short-term operations where a full function is not necessary. They are also known as anonymous functions because they don't require a formal name like regular functions defined using def.

The syntax for a lambda function is:

lambda arguments: expression

Here is an example program that uses a lambda function to calculate the square of a number:

# Using a lambda function to calculate the square of a number
square = lambda x: x**2
result = square(5)
print(result)

The output of the program will be:

25

This example demonstrates the use of a lambda function to create a function that calculates the square of a given number. The lambda function is assigned to the variable square, and then we call this lambda function with the argument 5 and print the result.

When comparing lambda functions and regular functions in Python, there are several key differences. Let's explore these differences with an example program:

Regular Function:

# Regular function to calculate the square of a number
def square_regular(x):
    return x**2

result_regular = square_regular(5)
print(result_regular)

Lambda Function:

# Lambda function to calculate the square of a number
square_lambda = lambda x: x**2
result_lambda = square_lambda(5)
print(result_lambda)

Differences:

1. Syntax:

The regular function is defined using the def keyword, followed by a function name, parameters, and a code block. On the other hand, the lambda function uses the lambda keyword, followed by parameters and an expression.

2. Name:

A regular function has a name (in this case, square_regular), while a lambda function is anonymous and typically assigned to a variable (in this case, square_lambda).

3. Readability:

Regular functions are generally more readable and can include multiple statements and documentation. Lambda functions are suitable for short, one-liner expressions.

Outputs:

25
25

This example illustrates the differences between a regular function and a lambda function. The regular function is named, has a defined structure using def, and uses a code block. The lambda function, on the other hand, is anonymous, more concise, and uses a single expression. The outputs of both functions, when called with the argument 5, result in the same value of 25.

In Python, a lambda function is defined using the lambda keyword. The syntax for a lambda function is simple and concise:

# Syntax of a lambda function
lambda arguments: expression

Here's an example program that demonstrates how to define a lambda function:

# Define a lambda function to calculate the square of a number
square = lambda x: x**2

# Call the lambda function with an argument
result = square(5)

# Print the result
print(result)

The output of the program will be:

25

In this example, the lambda function is defined to calculate the square of a number. The lambda keyword is followed by the parameter x and the expression x**2. The lambda function is then assigned to the variable square, and we call this lambda function with the argument 5 to calculate the square and print the result.

In Python, the lambda keyword is used to create anonymous functions, also known as lambda functions. The primary purpose of the lambda keyword is to allow the quick and concise creation of small, one-time-use functions without the need to formally define them using def.

Here's an example program that illustrates the purpose of the lambda keyword:

# Using lambda to create a function that adds two numbers
add_numbers = lambda x, y: x + y

# Using the lambda function to add two numbers
result = add_numbers(3, 5)

# Print the result
print(result)

The output of the program will be:

8

In this example, the lambda keyword is used to create an anonymous function that adds two numbers. The lambda function is assigned to the variable add_numbers. The advantage of using lambda in this scenario is the brevity and simplicity of creating a small function without the need for a formal function definition using def.