> unintuitive arithmetic without any of its speed advantages. Using floating-point in Python is still much faster than using an exact type in Python. $ # At

> unintuitive arithmetic without any of its speed advantages. Using floating-point in Python is still much faster than using an exact type in Python. $ # At this scale, we need to be aware of and account for the timing overhead $ python -m timeit 'pass' 50000000 loops, best of 5: 8.18 nsec per loop $ # The variable assignment defeats constant folding in the very primitive optimizer $ python -m timeit --setup 'x = 0.1; y = 0.2' 'x + y' 10000000 loops, best of 5: 21.2 nsec per loop $ python -m timeit --setup 'from decimal import Decimal as d; x = d("0.1"); y = d("0.2")' 'x + y' 5000000 loops, best of 5: 62.9 nsec per loop $ python -m timeit --setup 'from fractions import Fraction as f; x = f(1, 10); y = f(2, 10)' 'x + y' 500000 loops, best of 5: 755 nsec per loop