mirror of
https://github.com/TheAlgorithms/Python.git
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369562a1e8
* Added more flexibility to functions, decreased amount of repeating code * Added docstrings * Updated input functions * Added doctests * removed test piece of code * black . * Updated caesar cipher standard alphabet to fit python 3.8 * Update and rename sleepsort.py to sleep_sort.py * Or 4 Co-authored-by: Christian Clauss <cclauss@me.com>
50 lines
1.4 KiB
Python
50 lines
1.4 KiB
Python
"""
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Sleep sort is probably the wierdest of all sorting functions with time-complexity of
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O(max(input)+n) which is quite different from almost all other sorting techniques.
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If the number of inputs is small then the complexity can be approximated to be
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O(max(input)) which is a constant
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If the number of inputs is large, the complexity is approximately O(n).
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This function uses multithreading a kind of higher order programming and calls n
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functions, each with a sleep time equal to its number. Hence each of function wakes
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in sorted time.
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This function is not stable for very large values.
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https://rosettacode.org/wiki/Sorting_algorithms/Sleep_sort
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"""
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from threading import Timer
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from time import sleep
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from typing import List
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def sleep_sort(values: List[int]) -> List[int]:
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"""
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Sort the list using sleepsort.
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>>> sleep_sort([3, 2, 4, 7, 3, 6, 9, 1])
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[1, 2, 3, 3, 4, 6, 7, 9]
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>>> sleep_sort([3, 2, 1, 9, 8, 4, 2])
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[1, 2, 2, 3, 4, 8, 9]
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"""
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sleep_sort.result = []
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def append_to_result(x):
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sleep_sort.result.append(x)
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mx = values[0]
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for value in values:
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if mx < value:
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mx = value
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Timer(value, append_to_result, [value]).start()
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sleep(mx + 1)
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return sleep_sort.result
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if __name__ == "__main__":
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import doctest
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doctest.testmod()
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print(sleep_sort([3, 2, 4, 7, 3, 6, 9, 1]))
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