List and dictionary comprehensions

In the lesson on lists we built new lists like this: create an empty list, write a loop, append on every step. That takes three or four lines. Python has a special syntax that does the same in one line — the comprehension. Professional Python programmers use it every day.

List comprehension

Inside square brackets you first write the expression to calculate for each item, followed by an ordinary for part. Both ways give the same result — compare them:

squares = []
for n in range(1, 6):
    squares.append(n * n)
print(squares)

squares = [n * n for n in range(1, 6)]
print(squares)

[1, 4, 9, 16, 25]
[1, 4, 9, 16, 25]

[expression for item in iterable if condition]
{key: value for item in iterable if condition}
{expression for item in iterable}

The real power of a comprehension is the filter: an if at the end keeps only the items that match the condition. The expression can be anything — a method call, a function, a calculation:

numbers = [12, 7, 30, 5, 18, 21]
evens = [n for n in numbers if n % 2 == 0]
print(evens)

names = ['aysel', 'tural', 'ali']
print([name.title() for name in names])
print([len(name) for name in names])

[12, 30, 18]
['Aysel', 'Tural', 'Ali']
[5, 5, 3]

If you don't want to drop items but to transform them in two different ways, use a conditional expression: A if condition else B. Note that this goes before the for, while a filter if goes after it.

numbers = [3, 8, 11, 14]
labels = ['even' if n % 2 == 0 else 'odd' for n in numbers]
print(labels)

['odd', 'even', 'odd', 'even']

Dictionary comprehension

Write curly braces and a key: value pair, and you get a dictionary instead of a list. This is very handy for building a dictionary from a list, changing values or filtering pairs. The shop has started a 10% sale:

names = ['Aysel', 'Tural', 'Ali']
lengths = {name: len(name) for name in names}
print(lengths)

prices = {'bread': 0.8, 'milk': 1.9, 'cheese': 6.5}
sale = {item: round(price * 0.9, 2) for item, price in prices.items()}
print(sale)

scores = {'Aysel': 91, 'Murad': 48, 'Leyla': 76}
passed = {name: s for name, s in scores.items() if s >= 50}
print(passed)

{'Aysel': 5, 'Tural': 5, 'Ali': 3}
{'bread': 0.72, 'milk': 1.71, 'cheese': 5.85}
{'Aysel': 91, 'Leyla': 76}

Set comprehensions and generator expressions

Write a single expression in curly braces and you get a set — duplicates are removed automatically. If you drop the brackets and pass the comprehension straight to a function, you get a generator expression: it produces the items one by one without building a separate list, which saves memory.

words = ['sun', 'moon', 'star', 'sky', 'planet']
lengths = {len(w) for w in words}
print(sorted(lengths))

total = sum(n * n for n in range(1, 11))
print(total)

table = [[1, 2, 3], [4, 5, 6]]
flat = [n for row in table for n in row]
print(flat)

[3, 4, 6]
385
[1, 2, 3, 4, 5, 6]

Generator expressions are especially useful with the any() and all() functions. any() returns True when at least one item matches the condition, and all() when every item does. This lets you answer questions like “Did anyone fail the test?” or “Did everyone score above 40?” in one line.

scores = [72, 45, 88, 91]
print(any(s < 50 for s in scores))
print(all(s > 40 for s in scores))
print(max(len(w) for w in ['sun', 'planet', 'sky']))

True
True
6

temps = [24, 27, 31, 29, 33, 26, 30]
hot = [t for t in temps if t >= 30]
print('Hot days:', len(hot))
print([t * 9 / 5 + 32 for t in hot])

Hot days: 3
[87.8, 91.4, 86.0]

numbers = [4, 7, 10, 3, 8, 5]
words = ['sun', 'Baku', 'python', 'sea', 'tea', 'Caspian']
# 1) odd_squares: squares of the odd numbers
# 2) long_words: words longer than 3 letters, in capitals
# print both lists

[49, 9, 25]
['BAKU', 'PYTHON', 'CASPIAN']

scores = {'Aysel': 91, 'Murad': 48, 'Leyla': 76, 'Elvin': 55}
# 1) results: name -> 'pass' or 'fail'
# 2) print results
# 3) print the sum of the scores that are at least 50

{'Aysel': 'pass', 'Murad': 'fail', 'Leyla': 'pass', 'Elvin': 'pass'}
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