[Izkata]

This is why Decimal exists:

  Python 3.8.10 (default, Nov 22 2023, 10:22:35) 
  [GCC 9.4.0] on linux
  Type "help", "copyright", "credits" or "license" for more information.
  >>> from decimal import Decimal
  >>> Decimal('100000.000000000017')
  Decimal('100000.000000000017')

For example:

  >>> import json
  >>> json.loads('{"a": 100000.000000000017}')
  {'a': 100000.00000000001}
  >>> json.loads('{"a": 100000.000000000017}', parse_float=Decimal)
  {'a': Decimal('100000.000000000017')}

[dhosek]

And not every programming language offers a Decimal type and on most of those, there’s usually a performance penalty associated with it not to mention issues of interoperability and developer knowledge of its existence. For financial calculations, usually using integers with an implicit decimal offset (e.g., US currency amounts being expressed in cents rather than dollars), while other contexts will often determine that the inherent inaccuracy of IEEE floating types is a non-issue. The biggest potential problem lies in treating values that act kind of like numbers and look like numbers as numbers, e.g., Dewey Decimal classification numbers or the topic in a Library of Congress classification.¹

⸻

1. This is a bit on my mind lately as I discovered that LibraryThing’s sort by LoC classification seems to be broken so I exported my library (discovering that they export as ISO8859-1 with no option for UTF-8) and wrote a custom sorter for LOC classification codes for use in finally arranging the books on my shelves after my move last year.

[Retr0id]

Decimal is not arbitrary precision, though. It has many of the same issues, you'll just see them in different places.

  >>> Decimal('100000.00000000000000000000017') + Decimal('1')
  Decimal('100001.0000000000000000000002')

[cerved]

but serializing/deserializing decimal using the json module is futile

[yawaramin]

Why is it futile? It can be serialized/deserialized perfectly through its string representation.