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Extended Comprehension Syntax for Sets and Dictionaries

Like list comprehensions and generator expressions, both set and dictionary comprehensions support nested associated if clauses to filter items out of the result—the following collect squares of even items (i.e., items having no remainder for division by 2) in a range:

>>> [x * x for x in range(10) if x % 2 == 0]           # Lists are ordered
[0, 4, 16, 36, 64]
>>> {x * x for x in range(10) if x % 2 == 0}           # But sets are not
{0, 16, 4, 64, 36}
>>> {x: x * x for x in range(10) if x % 2 == 0}        # Neither are dict keys
{0: 0, 8: 64, 2: 4, 4: 16, 6: 36}

Nested for loops work as well, though the unordered and no-duplicates nature of both types of objects can make the results a bit less straightforward to decipher:

>>> [x + y for x in [1, 2, 3] for y in [4, 5, 6]]      # Lists keep duplicates
[5, 6, 7, 6, 7, 8, 7, 8, 9]
>>> {x + y for x in [1, 2, 3] for y in [4, 5, 6]}      # But sets do not
{8, 9, 5, 6, 7}
>>> {x: y for x in [1, 2, 3] for y in [4, 5, 6]}       # Neither do dict keys
{1: 6, 2: 6, 3: 6}

Like list comprehensions, the set and dictionary varieties can also iterate over any type of iterator—lists, strings, files, ranges, and anything else that supports the iteration protocol:

>>> {x + y for x in 'ab' for y in 'cd'}
{'bd', 'ac', 'ad', 'bc'}

>>> {x + y: (ord(x), ord(y)) for x in 'ab' for y in 'cd'}
{'bd': (98, 100), 'ac': (97, 99), 'ad': (97, 100), 'bc': (98, 99)}

>>> {k * 2 for k in ['spam', 'ham', 'sausage'] if k[0] == 's'}
{'sausagesausage', 'spamspam'}

>>> {k.upper(): k * 2 for k in ['spam', 'ham', 'sausage'] if k[0] == 's'}
{'SAUSAGE': 'sausagesausage', 'SPAM': 'spamspam'}

For more details, experiment with these tools on your own. They may or may not have a performance advantage over the generator or for loop alternatives, but we would have to time their performance explicitly to be sure—which seems a natural segue to the next section.