Python Lambda

Python Lambda Functions are anonymous functions meaning that the function is without a name. As we already know that the def keyword is used to define a normal function in Python. Similarly, the lambda keyword is used to define an anonymous function in Python.

For Example

lambda : print(‘Hello World’)

Here, we have created a lambda function that prints ‘Hello World’.

Before you learn about lambdas, make sure to know about Python Functions.

Python Lambda Function Syntax

Syntax: lambda arguments : expression

•   This function can have any number of arguments but only one expression, which is evaluated and returned.
•   One is free to use lambda functions wherever function objects are required.
•   You need to keep in your knowledge that lambda functions are syntactically restricted to a single expression.
•   It has various uses in particular fields of programming, besides other types of expressions in functions.

The anatomy of a lambda function includes three elements:

•     The keyword lambda — an analog of def in normal functions
•     The parameters — support passing positional and keyword
  arguments, just like normal functions
•     The body — the expression for given parameters being evaluated
  with the lambda function

Note that, unlike a normal function, we don’t surround the parameters of a lambda function with parentheses. If a lambda function takes two or more parameters, we list them with a comma.

We use a lambda function to evaluate only one short expression (ideally, a single-line) and only once, meaning that we aren’t going to apply this function later. Usually, we pass a lambda function as an argument to a higher-order function (the one that takes in other functions as arguments), such as Python built-in functions like filter(), map(), or reduce().

 Examples

1. A simple lambda function

Let’s start with a basic example. We’ll create a lambda function that calculates the square of a number.

square = lambda x: x ** 2

You can call this lambda function by passing an argument like this:

result = square(5)

print(“The square is:”, result)

1. Lambda function in a list

Lambda functions are often used with built-in functions that accept a function as an argument, such as map, filter, and sorted. Here’s an example using map to apply a lambda function to a list of numbers:

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

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

The map function applies the lambda function to each element in the numbers list, producing a new list of squared numbers.

1. Lambda function for sorting

Lambda functions are handy when you need to customize the sorting order of a list of objects. In this example, we sort a list of dictionaries based on the ‘age’ key:

people = [

    {‘name’: ‘Alice’, ‘age’: 30},

    {‘name’: ‘Bob’, ‘age’: 25},

    {‘name’: ‘Charlie’, ‘age’: 35}

]

 sorted_people = sorted(people, key=lambda x: x[‘age’])

The sorted function uses the lambda function as the sorting key to sort the list of dictionaries by age.

1. Filtering with lambda

Lambda functions can be used with the filter function to create custom filters. Here’s an example that filters out even numbers from a list:

numbers = [1, 2, 3, 4, 5, 6]

filtered_numbers = list(filter(lambda x: x % 2 != 0, numbers))

The lambda function filters out numbers that are not even, resulting in a list of odd numbers.

Conclusion

Lambda functions are a powerful tool in Python for creating small, ad-hoc functions without the need for formal function definitions. They are commonly used with higher-order functions like map, filter, and sorted to perform custom operations on data. With the examples provided in this blog post, you should have a good foundation for using lambda functions effectively in your Python projects. Practice and experimentation will help you become more comfortable with this concise and versatile feature.