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calculating time taken for list growth with different methods using timeit
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# List comprehensions are the fastest. | |
def test1(): | |
l = [] | |
for i in range(1000): | |
l = l + [i] | |
def test2(): | |
l = [] | |
for i in range(1000): | |
l.append(i) | |
def test3(): | |
l = [i for i in range(1000)] | |
def test4(): | |
l = list(range(1000)) | |
from timeit import Timer | |
t1 = Timer("test1()", "from __main__ import test1") | |
print("concat ",t1.timeit(number=1000), "milliseconds") | |
t2 = Timer("test2()", "from __main__ import test2") | |
print("append ",t2.timeit(number=1000), "milliseconds") | |
t3 = Timer("test3()", "from __main__ import test3") | |
print("comprehension ",t3.timeit(number=1000), "milliseconds") | |
t4 = Timer("test4()", "from __main__ import test4") | |
print("list range ",t4.timeit(number=1000), "milliseconds") | |
#> concat 8.8770373 milliseconds | |
#> append 1.4146511999999998 milliseconds | |
#> comprehension 0.819254299999999 milliseconds | |
#> list range 0.28831890000000016 milliseconds |
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