Python has lots of amazing features, but to me, list comprehensions are #1.

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This is a list comprehension that allows you to define 1 list in terms of another list and is reminiscent of set notation from mathematics.

The elegance, simplicity, and power of this notation makes it, in my opinion, the best feature of Python.

Now what does it mean to be a best feature of a programming language?

To me it's a feature that makes you fall in love with the language and the feature that makes you enjoy programming in the language for many years.

So the basic notation is a for loop over some input list nums and a function like f of x that computes something for each element x in nums.

In addition, there's a filter conditional like if g of x, some function, some expression that filters the elements of nums and only keeps the ones that pass this conditional.

Let's look at an example, input list nums 1, 2, 3, 4.

The list comprehension squares each element of nums, so x times x for x in nums.

And so that creates a list that contains 1, 4, 9, and 16.

And now to add a filter to keep just the even numbers, we can add into the filter conditional of the list comprehension x modulo 2 equals 0.

And then the result is the squaring of the elements that pass the filter, which is 4 and 16.

Now some would argue that you can achieve the same kind of results with for loops, or more direct comparison is the map and filter functions, which are also available in Python.

To square each element in the list, you can have a lambda function that does the squaring and a map that applies that lambda function to each element of nums.

And the third line, you can add a filter to that.

So first apply a filter with a lambda function that does the module 2 equals 0 conditional and then on top of that on the elements that pass the filter you again do the map function of the lambda that squares each element.

Now I believe this is also beautiful and powerful notation, but to me it's not nearly as elegant and Pythonic and readable as the list comprehension notation.

Now I already did a video on the most controversial Python feature, which in my opinion is the walrus operator.

It comes into play nicely with list comprehensions.

Now if we take some difficult to compute function like fibo here, which computes the nth element of the Fibonacci sequence, The 1 line ternary operator recursive implementation of the function written by me, untested.

I'll leave it to you as homework to test if this actually works.

And I threw it in there to give a shout out to 2 other things I enjoy, which is recursion and the ternary operator.

The if-else notation of which, in Python, I think is another beautiful design choice that makes an otherwise cryptic-looking ternary operator actually readable to our human brains.

And so if we take then another definition of nums that goes from 1 to 6, we can create a basic list comprehension that applies the fibo function to each element of nums, resulting in the familiar Fibonacci sequence of 1, 1, 2, 3, 5, 8.

Now if we wanted to also add a conditional, which is where the walrus operator comes in, we can compute fibo x and assign it to the variable y via the walrus operator's assignment expression and then do the modules 2 equals 0 check to keep just the even elements of the Fibonacci sequence.

And then in the actual output of the list comprehension, we can just use the variable Y as opposed to re-computing the Fibbo function.

So the result of this list comprehension that uses the Wallace operator is 2 and 8.

So list comprehension actually creates a list objects, computes all the elements in the list, and stores the entire list in memory while the generator expression stores just the iterable object and computes every element in the list 1 at a time as it's being queried.

So for most people, list comprehension is probably the default choice.

It's used when the size of the list is not crazy large, especially when you want to reiterate over the list multiple times.

It is faster than generator expressions depending on the context, it could be 2 to 3 times faster.

So speed is essential, you want to use these.

And if you need different list methods like especially the slicing notation, you should be using list comprehension.

On the other hand, you should use generator expressions when the range of the sequence is large or infinite, or if you want to construct iteratable generator objects, which are great to impress your friends with.

I should mention I'm really grateful for the sponsors that support these videos and the podcast, in this case, 8sleep.

So if you enjoy these, click the links in the description to get a discount and to support my efforts.

Thanks for listening, and Remember, try to learn something new every day.


Speaker 0: This is a list comprehension that allows you to define 1 list in terms of another list and is reminiscent of set notation from mathematics. The elegance, simplicity, and power of this notation makes it, in my opinion, the best feature of Python. Now what does it mean to be a best feature of a programming language? To me it's a feature that makes you fall in love with the language and the feature that makes you enjoy programming in the language for many years. So the basic notation is a for loop over some input list nums and a function like f of x that computes something for each element x in nums.

In addition, there's a filter conditional like if g of x, some function, some expression that filters the elements of nums and only keeps the ones that pass this conditional. Let's look at an example, input list nums 1, 2, 3, 4. The list comprehension squares each element of nums, so x times x for x in nums. And so that creates a list that contains 1, 4, 9, and 16. Simple, beautiful.

And now to add a filter to keep just the even numbers, we can add into the filter conditional of the list comprehension x modulo 2 equals 0. And then the result is the squaring of the elements that pass the filter, which is 4 and 16. Now some would argue that you can achieve the same kind of results with for loops, or more direct comparison is the map and filter functions, which are also available in Python. So what would that look like? To square each element in the list, you can have a lambda function that does the squaring and a map that applies that lambda function to each element of nums.

That's the second line in the code here. And the third line, you can add a filter to that. So first apply a filter with a lambda function that does the module 2 equals 0 conditional and then on top of that on the elements that pass the filter you again do the map function of the lambda that squares each element. Now I believe this is also beautiful and powerful notation, but to me it's not nearly as elegant and Pythonic and readable as the list comprehension notation. Now I already did a video on the most controversial Python feature, which in my opinion is the walrus operator.

It comes into play nicely with list comprehensions. Now if we take some difficult to compute function like fibo here, which computes the nth element of the Fibonacci sequence, The 1 line ternary operator recursive implementation of the function written by me, untested. I'll leave it to you as homework to test if this actually works. And I threw it in there to give a shout out to 2 other things I enjoy, which is recursion and the ternary operator. The if-else notation of which, in Python, I think is another beautiful design choice that makes an otherwise cryptic-looking ternary operator actually readable to our human brains.

And so if we take then another definition of nums that goes from 1 to 6, we can create a basic list comprehension that applies the fibo function to each element of nums, resulting in the familiar Fibonacci sequence of 1, 1, 2, 3, 5, 8. Now if we wanted to also add a conditional, which is where the walrus operator comes in, we can compute fibo x and assign it to the variable y via the walrus operator's assignment expression and then do the modules 2 equals 0 check to keep just the even elements of the Fibonacci sequence. And then in the actual output of the list comprehension, we can just use the variable Y as opposed to re-computing the Fibbo function. So the result of this list comprehension that uses the Wallace operator is 2 and 8. So list comprehension actually creates a list objects, computes all the elements in the list, and stores the entire list in memory while the generator expression stores just the iterable object and computes every element in the list 1 at a time as it's being queried.

So for most people, list comprehension is probably the default choice. It's used when the size of the list is not crazy large, especially when you want to reiterate over the list multiple times. It is faster than generator expressions depending on the context, it could be 2 to 3 times faster. So speed is essential, you want to use these. And if you need different list methods like especially the slicing notation, you should be using list comprehension.

On the other hand, you should use generator expressions when the range of the sequence is large or infinite, or if you want to construct iteratable generator objects, which are great to impress your friends with. I should mention I'm really grateful for the sponsors that support these videos and the podcast, in this case, 8sleep. So if you enjoy these, click the links in the description to get a discount and to support my efforts. Thanks for listening, and Remember, try to learn something new every day. You

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Best feature of Python | List Comprehensions