__all__ = [
"unique",
"lflat",
"counter_percentiles",
]
from typing import Iterable, List, Any, Dict, Union, Set
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def unique(iterable: Iterable[Any], key=lambda x: x) -> List[Any]:
"""\
Return a list of unique elements from an iterable, preserving order.
Args:
iterable (Iterable[Any]): The input iterable to filter for unique elements.
key (callable, optional): A function to extract a comparison key from each element. Defaults to the identity function.
Returns:
List[Any]: A list containing only the unique elements from the input iterable.
Examples:
>>> unique([1, 2, 2, 3, 1])
[1, 2, 3]
>>> unique(['apple', 'banana', 'orange'], key=len)
['apple', 'banana']
"""
seen, uni = set(), list()
for item in iterable:
k = key(item)
if not (k in seen or seen.add(k)):
uni.append(item)
return uni
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def lflat(iterable: Iterable[Iterable[Any]]) -> List[Any]:
"""\
Flatten a nested iterable (2 levels deep) into a single list.
Args:
iterable (Iterable[Iterable[Any]]): The nested iterable to flatten.
Returns:
List[Any]: A flat list containing all elements from the nested iterable.
Examples:
>>> lflat([[1, 2], [3, 4]])
[1, 2, 3, 4]
"""
return [item for sublist in iterable for item in sublist]
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def counter_percentiles(counter: Dict, percentiles: Set[Union[int, float]] = {0, 25, 50, 75, 100}) -> Dict[int, Any]:
"""\
Calculate specified percentiles from a frequency counter.
Args:
counter (Dict): A dictionary where keys are values and values are their frequencies.
percentiles (List[Union[int, float]]): List of percentiles to calculate. Defaults to [0, 25, 50, 75, 100].
Returns:
Dict[int, Any]: A dictionary mapping each requested percentile to its corresponding value.
Examples:
>>> counter = {1: 2, 2: 3, 3: 5}
>>> counter_percentiles(counter, [0, 50, 100])
{0: 1, 50: 2, 100: 3}
"""
total = sum(counter.values())
sorted_items = sorted(counter.items(), key=lambda x: x[0])
results, accum, idx = [(p, None) for p in sorted(percentiles)], 0, 0
for value, freq in sorted_items:
accum += freq
while idx < len(results) and accum / total >= results[idx][0] / 100.0:
results[idx] = (results[idx][0], value)
idx += 1
return dict(results)