# Jak liczby zmiennoprzecinkowe wpływają na testy wydajnościowe list składanych w CPythonie i PyPy
# PyPy spowalnia nieco dla liczb zmiennoprzecinkowych w porównaniu z liczbami całkowitymi, ale mniej niż CPython


$ python3
Python 3.12.2 (v3.12.2:6abddd9f6a, Feb  6 2024, 17:02:06) [Clang 13.0.0 (clang-1300.0.29.30)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import timeit
>>> min(timeit.repeat(stmt='[x ** 2 for x in range(1000)]', number=1000, repeat=5))
0.052329765632748604
>>> min(timeit.repeat(stmt='[x ** 2.0 for x in range(1000)]', number=1000, repeat=5))
0.08080639503896236
>>> min(timeit.repeat(stmt='[float(x) ** 2 for x in range(1000)]', number=1000, repeat=5))
0.1009976901113987
>>> min(timeit.repeat(stmt='[float(x) ** 2.0 for x in range(1000)]', number=1000, repeat=5))
0.09676378173753619

$ pypy3
Python 3.10.14 (75b3de9d9035, Apr 21 2024, 10:56:19)
[PyPy 7.3.16 with GCC Apple LLVM 15.0.0 (clang-1500.1.0.2.5)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>>> import timeit
>>>> min(timeit.repeat(stmt='[x ** 2 for x in range(1000)]', number=1000, repeat=5))
0.0022287541069090366
>>>> min(timeit.repeat(stmt='[x ** 2.0 for x in range(1000)]', number=1000, repeat=5))
0.0028824331238865852
>>>> min(timeit.repeat(stmt='[float(x) ** 2 for x in range(1000)]', number=1000, repeat=5))
0.0029041911475360394
>>>> min(timeit.repeat(stmt='[float(x) ** 2.0 for x in range(1000)]', number=1000, repeat=5))
0.002913380041718483
