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#!/usr/bin/env python3
from collections import Counter
from itertools import islice
from typing import Any, Iterator, List, Mapping, Sequence
def shard(lst: List[Any], size: int) -> Iterator[Any]:
"""
Yield successive size-sized shards from lst.
>>> for sublist in shard([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], 3):
... [_ for _ in sublist]
[1, 2, 3]
[4, 5, 6]
[7, 8, 9]
[10, 11, 12]
"""
for x in range(0, len(lst), size):
yield islice(lst, x, x + size)
def flatten(lst: List[Any]) -> List[Any]:
"""
Flatten out a list:
>>> flatten([ 1, [2, 3, 4, [5], 6], 7, [8, [9]]])
[1, 2, 3, 4, 5, 6, 7, 8, 9]
"""
if len(lst) == 0:
return lst
if isinstance(lst[0], list):
return flatten(lst[0]) + flatten(lst[1:])
return lst[:1] + flatten(lst[1:])
def prepend(item: Any, lst: List[Any]) -> List[Any]:
"""
Prepend an item to a list.
>>> prepend('foo', ['bar', 'baz'])
['foo', 'bar', 'baz']
"""
lst.insert(0, item)
return lst
def remove_list_if_one_element(lst: List[Any]) -> Any:
"""
Remove the list and return the 0th element iff its length is one.
>>> remove_list_if_one_element([1234])
1234
>>> remove_list_if_one_element([1, 2, 3, 4])
[1, 2, 3, 4]
"""
if len(lst) == 1:
return lst[0]
else:
return lst
def population_counts(lst: List[Any]) -> Mapping[Any, int]:
"""
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
list item in the original list.
>>> population_counts([1, 1, 1, 2, 2, 3, 3, 3, 4])
Counter({1: 3, 3: 3, 2: 2, 4: 1})
"""
return Counter(lst)
def most_common(lst: List[Any], *, count=1) -> Any:
"""
Return the most common item in the list. In the case of ties,
which most common item is returned will be random.
>>> most_common([1, 1, 1, 2, 2, 3, 3, 3, 3, 4, 4])
3
>>> most_common([1, 1, 1, 2, 2, 3, 3, 3, 3, 4, 4], count=2)
[3, 1]
"""
p = population_counts(lst)
return remove_list_if_one_element([_[0] for _ in p.most_common()[0:count]])
def least_common(lst: List[Any], *, count=1) -> Any:
"""
Return the least common item in the list. In the case of
ties, which least common item is returned will be random.
>>> least_common([1, 1, 1, 2, 2, 3, 3, 3, 4])
4
>>> least_common([1, 1, 1, 2, 2, 3, 3, 3, 4], count=2)
[4, 2]
"""
p = population_counts(lst)
mc = p.most_common()[-count:]
mc.reverse()
return remove_list_if_one_element([_[0] for _ in mc])
def dedup_list(lst: List[Any]) -> List[Any]:
"""
Remove duplicates from the list performantly.
>>> dedup_list([1, 2, 1, 3, 3, 4, 2, 3, 4, 5, 1])
[1, 2, 3, 4, 5]
"""
return list(set(lst))
def uniq(lst: List[Any]) -> List[Any]:
"""
Alias for dedup_list.
"""
return dedup_list(lst)
def contains_duplicates(lst: List[Any]) -> bool:
"""
Does the list contian duplicate elements or not?
>>> lst = [1, 2, 1, 3, 3, 4, 4, 5, 6, 1, 3, 4]
>>> contains_duplicates(lst)
True
>>> contains_duplicates(dedup_list(lst))
False
"""
seen = set()
for _ in lst:
if _ in seen:
return True
seen.add(_)
return False
def all_unique(lst: List[Any]) -> bool:
"""
Inverted alias for contains_duplicates.
"""
return not contains_duplicates(lst)
def transpose(lst: List[Any]) -> List[Any]:
"""
Transpose a list of lists.
>>> lst = [[1, 2], [3, 4], [5, 6]]
>>> transpose(lst)
[[1, 3, 5], [2, 4, 6]]
"""
transposed = zip(*lst)
return [list(_) for _ in transposed]
def ngrams(lst: Sequence[Any], n):
"""
Return the ngrams in the sequence.
>>> seq = 'encyclopedia'
>>> for _ in ngrams(seq, 3):
... _
'enc'
'ncy'
'cyc'
'ycl'
'clo'
'lop'
'ope'
'ped'
'edi'
'dia'
>>> seq = ['this', 'is', 'an', 'awesome', 'test']
>>> for _ in ngrams(seq, 3):
... _
['this', 'is', 'an']
['is', 'an', 'awesome']
['an', 'awesome', 'test']
"""
for i in range(len(lst) - n + 1):
yield lst[i:i + n]
if __name__ == '__main__':
import doctest
doctest.testmod()
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