mirror of
https://github.com/TheAlgorithms/Python.git
synced 2024-12-18 01:00:15 +00:00
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
"""
|
|
Sleep sort is probably the wierdest of all sorting functions with time-complexity of
|
|
O(max(input)+n) which is quite different from almost all other sorting techniques.
|
|
If the number of inputs is small then the complexity can be approximated to be
|
|
O(max(input)) which is a constant
|
|
|
|
If the number of inputs is large, the complexity is approximately O(n).
|
|
|
|
This function uses multithreading a kind of higher order programming and calls n
|
|
functions, each with a sleep time equal to its number. Hence each of function wakes
|
|
in sorted time.
|
|
|
|
This function is not stable for very large values.
|
|
|
|
https://rosettacode.org/wiki/Sorting_algorithms/Sleep_sort
|
|
"""
|
|
from threading import Timer
|
|
from time import sleep
|
|
from typing import List
|
|
|
|
|
|
def sleep_sort(values: List[int]) -> List[int]:
|
|
"""
|
|
Sort the list using sleepsort.
|
|
>>> sleep_sort([3, 2, 4, 7, 3, 6, 9, 1])
|
|
[1, 2, 3, 3, 4, 6, 7, 9]
|
|
>>> sleep_sort([3, 2, 1, 9, 8, 4, 2])
|
|
[1, 2, 2, 3, 4, 8, 9]
|
|
"""
|
|
sleep_sort.result = []
|
|
|
|
def append_to_result(x):
|
|
sleep_sort.result.append(x)
|
|
|
|
mx = values[0]
|
|
for value in values:
|
|
if mx < value:
|
|
mx = value
|
|
Timer(value, append_to_result, [value]).start()
|
|
sleep(mx + 1)
|
|
return sleep_sort.result
|
|
|
|
|
|
if __name__ == "__main__":
|
|
import doctest
|
|
|
|
doctest.testmod()
|
|
|
|
print(sleep_sort([3, 2, 4, 7, 3, 6, 9, 1]))
|