Accuracy problems in floating-point computations: https://en.wikipedia.org/wiki/Floating_point#Accuracy_proble...

My bad, wrote rounding not accuracy. (corrected now) But my point was that it's not related to weak typing as the parent seems to suggest.

> But my point was that it's not related to weak typing as the parent seems to suggest.

And you're completely right there. Any language using floating-point numbers will have the same issue regardless of its typing discipline e.g. Rust: https://is.gd/4BNoWa

There is another snippet near that section which evaluates the following.

    >>> float > float('infinity')
    True

Bah, you're right, missed that example :(

This really makes me wish they made the decision for Python 3 to auto-convert these literals to Fraction objects like Perl 6 does.

Basically, autoconvert the above to this (and make Fraction a builtin instead of in the standard library, of course):

    >>> Fraction('2.2') * Fraction('3.0') == Fraction('3.3') * Fraction('2.0')
    True

The speed of these operations isn't on the same order of magnitude as floating-point operations. I do agree that literals for `Fraction` and `Decimal` would be interesting.

Also, I think that '2.2' is better represented as `Decimal`, as it's a decimal number (which is a subset of rational numbers, that are usually better represented using `Decimal`) (edit: that of course depends on the use case, as Decimal uses fixed-point precision).