Accessing indexes & Performance Benchmarking of approaches
#Accessing indexes & Performance Benchmarking of approaches TheThe fastest way to access indexes of list within loop in Python 3.7 is to use the enumerate method for small, medium and huge lists.
Please see different approaches which can be used to iterate over list and access index value and their performance metrics (which I suppose would be useful for you) in code samples below:
# Using range
def range_loop(iterable):
for i in range(len(iterable)):
1 + iterable[i]
# Using enumerate
def enumerate_loop(iterable):
for i, val in enumerate(iterable):
1 + val
# Manual indexing
def manual_indexing_loop(iterable):
index = 0
for item in iterable:
1 + item
index += 1
See performance metrics for each method below:
from timeit import timeit
def measure(l, number=10000):
print("Measure speed for list with %d items" % len(l))
print("range: ", timeit(lambda :range_loop(l), number=number))
print("enumerate: ", timeit(lambda :enumerate_loop(l), number=number))
print("manual_indexing: ", timeit(lambda :manual_indexing_loop(l), number=number))
# Measure speed for list with 1000 items
measure(range(1000))
# range: 1.161622366
# enumerate: 0.5661940879999996
# manual_indexing: 0.610455682
# Measure speed for list with 100000 items
measure(range(10000))
# range: 11.794482958
# enumerate: 6.197628574000001
# manual_indexing: 6.935181098000001
# Measure speed for list with 10000000 items
measure(range(10000000), number=100)
# range: 121.416859069
# enumerate: 62.718909123
# manual_indexing: 69.59575057400002
As the result, using enumerate method is the fastest method for iteration when the index needed.
Adding some useful links below:
