squares = []
for num in range(10):
    squares.append(num ** 2)
my_list = []
[my_list.append(num ** 2) for num in range(10)]
[print(num ** 2) for num in range(10)]
[func(value) for value in data_source)]
[value for value in data_source if predicate(value)
my_list = [value for value in iterable]
colour = [randint(0, 255) for _ in range(3)]
my_list = [value for value, key in zip(values, keys) if predicate(keys)]
my_list = [
    transformation(elem)
    for elem in data_source
    if predicate(elem)
]
squares = []
for num in range(10):
    squares.append(num ** 2)
squares = [num ** 2 for num in range(10)]

Equivalent to a for loop with an append.

Equivalent to a for loop with an if and an append.

You don't know comprehensions.

It's ok!

Keep reading!

That's not the main advantage!

Convenient syntax to create lists.

Careful! You'll strain your eyes!!!

Builds a new list out of an existing iterable.

The list comprehension extracts important bits...

  • Shorter

  • Faster (objectively)

2 common patterns.

  • Own scope (pure)

  • IT EMPHASISES AND HIGHLIGHTS

THE CONTENTS OF THE NEW LIST.

(learn more: )

... and drops fluff:

What is a list comprehension?

Filtering

Anatomy

More examples

Tips

Advantages

Do you know list comprehensions?

Yes

What's the

main advantage

of using them?

They are fast.

They are short.

Wait!

What was that?

???

I don't know 🤷

No

[
     0,  1,  4,  9, 16,
    25, 36, 49, 64, 81,
]
[
         1,      9,    
    25,     49,     81,
]
squares = [num ** 2 for num in range(10)]
squares = []
for num in range(10):
    squares.append(num ** 2)
squares = [num ** 2 for num in range(10) if num % 2]
american_actors = [
    actor
    for actor, nationality in actors.items()
    if nationality == "USA"
]
e_word_lengths = [
    len(word)
    for word in sentence.split()
    if "e" in word
] # == ???
e_word_lengths = []
for word in sentence.split():
    if "e" in word:
        e_word_lengths.append(len(word))
print(word)
squares = [
    num ** 2
    for num in range(10)
    if num % 2
]
squares = [
    num ** 2
    for num in range(10)
    if num % 2
]
new_list = [
    func(elem)
    for elem in data_source
    if predicate(elem)
]
new_list = [
    func(elem)
    for elem in data_source
    if predicate(elem)
]

func = elem ** 2
data_source = range(10)
predicate = elem % 2


func = len(word)
data_source = sentence.split()
predicate = "e" in word

squares = []
for num in range(10):
    if num % 2:
        squares.append(num ** 2)

1. a transformation

applied to the existing data

2. a data source

to fetch the elements from

In general, list comprehensions have 3 components:

Converting to/from a list comprehension is “straightforward”.

The only thing that moves is the transformation.

General form

Specific example

3. an optional filter

to select which elements to use

new_list = [
    func(elem)
    for elem in data_source
    if predicate(elem)
]
new_list = []
for elem in data_source:
    if predicate(elem):
        new_list.append(func(elem))

1. transformation

The data transformation comes first in the comp. but last in the loop.

The loop is just a comprehension with extra steps.

  • Unused list comp?

  • Side effects are bad.

  • Don't reinvent map

    & filter!!!

  • Use list instead.

  • Repeated action.

  • Auxiliary filter.

  • It's ok to span multiple lines.