Python — Comprehensions, iterators & generators

Las preguntas del cuestionario

1. 1. What does [x * x for x in range(5) if x % 2] evaluate to?
   1. [0, 1, 4, 9, 16]
   2. [1, 9]
   3. [1, 4, 9]
   4. [1, 9, 25]
2. 2. Difference between (x for x in r) and [x for x in r]?
   1. None
   2. First is a generator (lazy); second is a list (eager)
   3. First returns a tuple
   4. First is faster but uses more memory
3. 3. What protocol must an iterator implement?
   1. __iter__ and __next__
   2. __getitem__ only
   3. __call__
   4. __index__
4. 4. What does this print?

   def gen():
       yield 1
       yield 2
       yield 3
   
   print(sum(gen()))

   1. 3
   2. 6
   3. [1, 2, 3]
   4. TypeError
5. 5. What is the output?

   def gen():
       x = yield 1
       yield x + 10
   
   g = gen()
   print(next(g))
   print(g.send(5))

   1. 1 then 15
   2. 1 then 11
   3. 5 then 15
   4. StopIteration
6. 6. Which itertools function chains iterables together?
   1. chain
   2. zip_longest
   3. product
   4. tee
7. 7. What does this print?

   g = (i*i for i in range(3))
   print(list(g))
   print(list(g))

   1. [0, 1, 4] then [0, 1, 4]
   2. [0, 1, 4] then []
   3. [] then []
   4. Error
8. 8. How do you delegate to another iterable in a generator?
   1. yield from iterable
   2. yield *iterable
   3. return iterable
   4. raise iterable
9. 9. Complexity of any(x < 0 for x in big_list)?
   1. Always O(n)
   2. Best O(1) if early match, worst O(n) — short-circuits
   3. O(n log n)
   4. O(1) memory, O(0) time
10. 10. What does this print?

    d = {k: v for k, v in [('a',1),('b',2),('a',3)]}
    print(d)

    1. {'a': 1, 'b': 2}
    2. {'a': 3, 'b': 2}
    3. {'a': [1, 3], 'b': 2}
    4. Error
11. 11. What does list(zip([1,2,3], ['a','b'])) return?
    1. [(1, 'a'), (2, 'b')]
    2. [(1, 'a'), (2, 'b'), (3, None)]
    3. Error
    4. [1, 2, 3, 'a', 'b']
12. 12. What does this produce?

    from itertools import islice, count
    for x in islice(count(10, 2), 4):
        print(x, end=' ')

    1. 10 11 12 13
    2. 10 12 14 16
    3. 10 12 14
    4. Error
13. 13. How do you implement a lazy chunks of n generator?
    1. for c in chunks: yield list(c) with itertools.islice in a loop until empty
    2. map(chunked, lst)
    3. list(zip(lst, lst, lst))
    4. Impossible without numpy
14. 14. What is the output?

    def g():
        try:
            yield 1
        finally:
            print("end")
    
    for x in g():
        print(x)
        break

    1. 1
    2. 1 then end
    3. end then 1
    4. Generator does not call finally on break
15. 15. Which expression is a set comprehension?
    1. {x for x in r}
    2. {x: 0 for x in r}
    3. (x for x in r)
    4. [x for x in r]
16. 16. What does enumerate(seq, start=10) yield for seq=['a','b']?
    1. (0, 'a'), (1, 'b')
    2. (10, 'a'), (11, 'b')
    3. (1, 'a'), (2, 'b')
    4. Error
17. 17. What is the output?

    from itertools import groupby
    data = sorted("AaBbAa", key=str.lower)
    result = [(k, len(list(g))) for k, g in groupby(data, key=str.lower)]
    print(result)

    1. [('a', 4), ('b', 2)]
    2. [('A', 2), ('a', 2), ('B', 1), ('b', 1)]
    3. [('a', 6)]
    4. Error
18. 18. What is special about itertools.tee?
    1. Splits one iterator into n independent iterators (with memory cost if they advance at different rates)
    2. Reverses an iterator
    3. Joins two iterators
    4. Filters an iterator
19. 19. What's the result of next(iter([]), 'def')?
    1. StopIteration
    2. None
    3. 'def'
    4. Error
20. 20. Which generator pattern correctly streams a large file by line and uppercases each line lazily?
    1. (line.upper() for line in open(p))
    2. open(p).read().upper().splitlines()
    3. [l.upper() for l in open(p)]
    4. map(str.upper, open(p).readlines())