Tag python_Comprehensions

Python is famous for allowing you to write code that’s elegant, easy to write, and almost as easy to read as plain English. One of the language’s most distinctive features is the list comprehension, which you can use to create powerful functionality within a single line of code. However, many developers struggle to fully leverage the more advanced features of a list comprehension in Python. Some programmers even use them too much, which can lead to code that’s less efficient and harder to read.

By the end of this tutorial, you’ll understand the full power of Python list comprehensions and how to use their features comfortably.

Benefits of Using List Comprehensions

• One main benefit of using a list comprehension in Python is that it’s a single tool that you can use in many different situations.
• In addition to standard list creation, list comprehensions can also be used for mapping and filtering. You don’t have to use a different approach for each scenario.
• List comprehensions are also more declarative than loops, which means they’re easier to read and understand.

Every list comprehension in Python includes three elements:

1. expression is the member itself, a call to a method, or any other valid expression that returns a value. In the example above, the expression i * i is the square of the member value.
2. member is the object or value in the list or iterable. In the example above, the member value is i.
3. iterable is a list, set, sequence, generator, or any other object that can return its elements one at a time. In the example above, the iterable is range(10).

Let’s explore the concept through jupyter notebook.