-
Notifications
You must be signed in to change notification settings - Fork 4
/
Copy pathtask-assignment.py
69 lines (60 loc) · 2.04 KB
/
task-assignment.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
# Task Assignment
# 🟠 Medium
#
# https://www.algoexpert.io/questions/task-assignment
#
# Tags: Array - Greedy - Sorting
import timeit
from collections import deque
from operator import itemgetter
# Sort the tasks on ascending order by cost, use a double ended queue
# to be able to pop from both ends, assign to each worker the next
# easiest and hardest job, that way we optimize the time that each
# worker needs and get the best overall runtime.
#
# Time complexity: O(n*log(n)) - Sorting the jobs has the highest cost.
# Space complexity: O(n) - The queue that contains the sorted jobs.
class UseQueue:
def taskAssignment(self, k, tasks):
# Sorted list of tasks and their indexes.
q = deque(sorted([(tasks[i], i) for i in range(len(tasks))]))
res = [None] * k
for i in range(k):
res[i] = (q.popleft()[1], q.pop()[1])
return res
class UseIndexes:
def taskAssignment(self, k, tasks):
t = sorted(
[(i, task) for i, task in enumerate(tasks)], key=itemgetter(1)
)
return [(t[i][0], t[-i - 1][0]) for i in range(k)]
def test():
executors = [
UseQueue,
UseIndexes,
]
tests = [
[3, [1, 3, 5, 3, 1, 4], [(0, 2), (4, 5), (1, 3)]],
[
5,
[3, 7, 5, 4, 4, 3, 6, 8, 3, 3],
[(0, 7), (5, 1), (8, 6), (9, 2), (3, 4)],
],
]
for executor in executors:
start = timeit.default_timer()
for _ in range(1):
for col, t in enumerate(tests):
sol = executor()
result = sol.taskAssignment(t[0], t[1])
exp = t[2]
assert result == exp, (
f"\033[93m» {result} <> {exp}\033[91m for"
+ f" test {col} using \033[1m{executor.__name__}"
)
stop = timeit.default_timer()
used = str(round(stop - start, 5))
cols = "{0:20}{1:10}{2:10}"
res = cols.format(executor.__name__, used, "seconds")
print(f"\033[92m» {res}\033[0m")
test()