return lst
-def population_counts(lst: List[Any]) -> Mapping[Any, int]:
+def population_counts(lst: List[Any]) -> Counter:
"""
Return a population count mapping for the list (i.e. the keys are
list items and the values are the number of occurrances of that
['an', 'awesome', 'test']
"""
for i in range(len(lst) - n + 1):
- yield lst[i:i + n]
+ yield lst[i : i + n]
-def permute(seq: Sequence[Any]):
+def permute(seq: str):
"""
- Returns all permutations of a sequence; takes O(N^2) time.
+ Returns all permutations of a sequence; takes O(N!) time.
>>> for x in permute('cat'):
... print(x)
yield from _permute(seq, "")
-def _permute(seq: Sequence[Any], path):
- if len(seq) == 0:
+def _permute(seq: str, path: str):
+ seq_len = len(seq)
+ if seq_len == 0:
yield path
- for i in range(len(seq)):
+ for i in range(seq_len):
car = seq[i]
left = seq[0:i]
- right = seq[i + 1:]
+ right = seq[i + 1 :]
cdr = left + right
yield from _permute(cdr, path + car)
-def binary_search(lst: Sequence[Any], target: Any) -> Tuple[bool, int]:
+def binary_search(
+ lst: Sequence[Any], target: Any, *, sanity_check=False
+) -> Tuple[bool, int]:
"""Performs a binary search on lst (which must already be sorted).
Returns a Tuple composed of a bool which indicates whether the
target was found and an int which indicates the index closest to
>>> binary_search(a, 2)
(False, 1)
+ >>> a.append(9)
+ >>> binary_search(a, 4, sanity_check=True)
+ Traceback (most recent call last):
+ ...
+ AssertionError
+
"""
+ if sanity_check:
+ last = None
+ for x in lst:
+ if last is not None:
+ assert x >= last # This asserts iff the list isn't sorted
+ last = x # in ascending order.
return _binary_search(lst, target, 0, len(lst) - 1)
-def _binary_search(lst: Sequence[Any], target: Any, low: int, high: int) -> Tuple[bool, int]:
+def _binary_search(
+ lst: Sequence[Any], target: Any, low: int, high: int
+) -> Tuple[bool, int]:
if high >= low:
mid = (high + low) // 2
if lst[mid] == target:
if __name__ == '__main__':
import doctest
+
doctest.testmod()