Python benchmark: is set() really fast?

perf-test.py

import sys
import random
import time

# fetch python version string
version = str(sys.version).split(" ", 2)[0]

# define get_time() function
if sys.version_info.major == 3:
    def get_time():
        return time.perf_counter()
else:
    # python 2 version
    def get_time():
        return time.time()


# benchmark
def test(size, iterations):
    # prepare data
    data_list = list()
    i = 0
    while i <= size:
        data_list.append(random.random())
        i += 1

    # convert to tuple and set
    data_tuple = tuple(data_list)
    data_set = set(data_list)

    # run tests
    t = get_time()
    j = 0
    while j <= iterations:
        x = j in data_list
        j += 1
    t1 = get_time() - t

    t = get_time()
    j = 0
    while j <= iterations:
        x = j in data_tuple
        j += 1
    t2 = get_time() - t

    t = get_time()
    j = 0
    while j <= iterations:
        x = j in data_set
        j += 1
    t3 = get_time() - t

    # print results as CSV
    print(", ".join([version, str(size), str(iterations), str(t1), str(t2), str(t3)]))


print("# Python Version, Array Size, Iterations, in list, in tuple, in set")
i = 1
while i <= 10000:
    test(i, 10000)
    i = i * 10

perf-test.sh

#!/bin/bash

for ver in 2.7 3.6 3.7 3.8; do
  echo "# running tests for version $ver"

  image=python:$ver
  docker run --rm -v "$PWD":/src $image \
    bash -c "python /src/perf-test.py"
done

Results:
Lookup for a key in set() data structure is must faster than lookup in list() or tuple() in all all major Python versions.
Also it has constant execution time.
Numbers: 0.002 sec (set) vs. 10.7 sec (list, tuple) in Python 3.x

Script output:

# running tests for version 2.7
# Python Version, Array Size, Iterations, in list, in tuple, in set
2.7.17, 1, 10000, 0.00309681892395, 0.00320911407471, 0.00244998931885
2.7.17, 10, 10000, 0.0150771141052, 0.00934600830078, 0.002032995224
2.7.17, 100, 10000, 0.0699908733368, 0.0701081752777, 0.00210094451904
2.7.17, 1000, 10000, 0.675493001938, 0.675599098206, 0.00206708908081
2.7.17, 10000, 10000, 6.70550990105, 6.68651795387, 0.00207209587097
# running tests for version 3.6
# Python Version, Array Size, Iterations, in list, in tuple, in set
3.6.9, 1, 10000, 0.004384811999898375, 0.004381762000321032, 0.002476438000030612
3.6.9, 10, 10000, 0.014039071000297554, 0.013892348000354104, 0.002434644999993907
3.6.9, 100, 10000, 0.1092279609997604, 0.10911030700026458, 0.0024445149997518456
3.6.9, 1000, 10000, 1.0666499200001454, 1.0883940899998379, 0.0024971810003080464
3.6.9, 10000, 10000, 10.876496061000125, 10.792869918000179, 0.0025605380001252342
# running tests for version 3.7
# Python Version, Array Size, Iterations, in list, in tuple, in set
3.7.5, 1, 10000, 0.004397431999677792, 0.004395890000068903, 0.0024426449999737088
3.7.5, 10, 10000, 0.014005884999733098, 0.013840296000125818, 0.0024605520002296544
3.7.5, 100, 10000, 0.11291304200040031, 0.12301392300014413, 0.0024590360003458045
3.7.5, 1000, 10000, 1.106032007000067, 1.070861749999949, 0.0025498979998701543
3.7.5, 10000, 10000, 10.704635972000233, 10.700021830999958, 0.0024611809999441903
# running tests for version 3.8
# Python Version, Array Size, Iterations, in list, in tuple, in set
3.8.0, 1, 10000, 0.004547103999811952, 0.004588472000250476, 0.0026125389999833715
3.8.0, 10, 10000, 0.014315868000267074, 0.014388877999863325, 0.002691261999643757
3.8.0, 100, 10000, 0.11120889399990119, 0.11045966400024554, 0.0026601959998515667
3.8.0, 1000, 10000, 1.079579711000406, 1.0746231389998684, 0.0026188420001744817
3.8.0, 10000, 10000, 10.719467460000033, 10.859970144999807, 0.0027028620002056414