Lambda Expressions: Writing Functions on-the-go in Python!

You have learned about Python functions in the previous articles. There, you studied its working process as well as the syntax. The slight problem with functions is that each and every time you have to define it using the 'def' keyword and at times it may prove to be a tedious task especially when you are writing thousands of lines of code.

To take care of this problem, Python has a function called Lambda Expressions. Just like how keyword arguments help in defining the function more clearly, this enables you to write a function just like that without the need for defining it. This article delves deep into this topic explaining its syntax, its benefits, and its working with an example program.

Lambda expressions, also known as lambda functions, are a way to create small, anonymous functions in Python. They are called "anonymous" because they don't require a formal function definition using the 'def' keyword. Instead, lambda expressions allow you to create functions on-the-fly, directly where they are needed, without assigning them a name.

Lambda expressions are particularly useful when you need a simple function for a short duration and don't want to define a full-fledged function.

• Conciseness: Lambda expressions allow you to write small, one-line functions without the need for a formal function definition, reducing code clutter.
• Readability: Just like recursive functions, lambda expressions can make the code more readable and expressive, especially for simple and straightforward operations.
• Immediate Use: Lambda expressions are handy when you need a function for a short duration and don't want to define a separate function using def.
• Functional Programming: Lambda expressions are often used in conjunction with functional programming concepts like 'map()', 'filter()', and 'reduce()', enabling a more functional programming style.

Before understanding the working process of Lamda expression, let's first see the syntax of it:

 >>> lambda arguments: expression

Let us understand this with an example program:

1. Define the lambda expression::

 >>> square = lambda x: x ** 2

2. Using the lambda expression:

 >>> numbers = [1, 2, 3, 4, 5]
 >>> squared_numbers = list(map(square, numbers))

3. Printing the squared numbers:

 >>> print(squared_numbers)

The 'map(square, numbers)' call applies the lambda expression 'square' to each element in the 'numbers' list, resulting in a new list of squared numbers.

In the example above, the lambda expression 'square' is used with 'map()' to calculate the square of each number in a list. This provides a concise and efficient way to perform a specific operation without the need to define a separate named function.

NOTE: It's important to note that while lambda expressions offer conciseness and convenience, they have their limitations. They are best suited for simple and concise tasks, and for more complex operations, it's recommended to use regular functions defined with the 'def' keyword.

In conclusion, lambda expressions provide a convenient way to create quick, anonymous functions in Python. While they have their limitations, they are a powerful tool for concise coding and functional programming approaches that help you a great deal. Do practise more on this and if you have any doubts regarding this topic, feel free to contact us