List comprehension python how to#
List comprehension python full#
List comprehension python code#

When Not to Use a List Comprehension in Python You won’t often need to use the assignment expression inside of a list comprehension in Python, but it’s a useful tool to have at your disposal when necessary. randrange ( 90, 110 ) > hot_temps = > hot_temps > import random > def get_weather_data (). The following example shows how this is possible, using get_weather_data() to generate fake weather data: It allows you to run an expression while simultaneously assigning the output value to a variable. The formula expression for member in iterable (if conditional) provides no way for the conditional to assign data to a variable that the expression can access. In this case, there’s no way to use a list comprehension in Python to solve the problem. Assume that each request will return different data.

You only want to return results that are greater than 100 degrees Fahrenheit. Say you need to make ten requests to an API that will return temperature data. To understand how you can use it, consider the following example. Python 3.8 will introduce the assignment expression, also known as the walrus operator. > squares = ) as well as a key-value pair ( i: i * i) in your expression.

List comprehension python how to#

Using Conditional LogicĮarlier, you saw this formula for how to create list comprehensions: You’ll also want to understand the changes that are coming to the list comprehension in Python 3.8.

List comprehension python full#

In order to understand the full value that list comprehensions can provide, it’s helpful to understand their range of possible functionality. With a list comprehension in Python, you can instead focus on what you want to go in the list and trust that Python will take care of how the list construction takes place. You have to manually create an empty list, loop over the elements, and add each of them to the end of the list. Loops require you to focus on how the list is created. List comprehensions are also more declarative than loops, which means they’re easier to read and understand. As an added side benefit, whenever you use a list comprehension in Python, you won’t need to remember the proper order of arguments like you would when you call map(). This is the main reason why list comprehensions are considered Pythonic, as Python embraces simple, powerful tools that you can use in a wide variety of situations. You don’t have to use a different approach for each scenario. In addition to standard list creation, list comprehensions can also be used for mapping and filtering. 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. Later on, you’ll learn about a few scenarios where the alternatives are a better choice. But rather than blindly accepting that assessment, it’s worth it to understand the benefits of using a list comprehension in Python when compared to the alternatives. List comprehensions are often described as being more Pythonic than loops or map(). Remove ads Benefits of Using List Comprehensions

List comprehension python code#

Profile your code to solve performance questions.Supercharge your comprehensions with conditional logic.Choose between comprehensions, loops, and map() calls.

Rewrite loops and map() calls as a list comprehension in Python.You’ll also gain an understanding of the trade-offs that come with using them so that you can determine when other approaches are more preferable. Some programmers even use them too much, which can lead to code that’s less efficient and harder to read.īy the end of this tutorial, you’ll understand the full power of Python list comprehensions and how to use their features comfortably. However, many developers struggle to fully leverage the more advanced features of a list comprehension in Python. 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. Python is famous for allowing you to write code that’s elegant, easy to write, and almost as easy to read as plain English. Watch it together with the written tutorial to deepen your understanding: Understanding Python List Comprehensions Watch Now This tutorial has a related video course created by the Real Python team.