[Python-Dev] Mini-Pep: Simplifying the Integral ABC (original) (raw)

Raymond Hettinger python at rcn.com
Wed Jun 4 10:54:25 CEST 2008

The only comment so far was to keep the index method.

Other than that, is this good to go?

Raymond

----- Original Message -----

Target: Py2.6 and Py3.0 Author: Raymond Hettinger Date: May 31, 2008

Motivation ---------- The principal purpose of an abstract base class is to support multiple implementations of an API; thereby allowing one concrete class to be substitutable for another. This purpose is defeated when useful substitutions are precluded because the ABC is too aggressive in its behavioral requirements -- mandating too many methods, mandating methods that are difficult to implement, or too closely following the full API of a single concrete type. The Integral ABC is somewhat extensive and requires essentially every behavior exhibited by the int concrete class. Usefully, it provides for basic integer behaviors like simple arithmetic and ordering relations. However, the current ABC goes beyond that and requires bit-flipping and other operations that are not fundamental to the notion of being an integer. That makes it challenging to define a new Integral class that isn't already an int. Proposal -------- Remove non-essential abstract methods like index, three argument pow, lshift, rlshift, rshift, rrshift, and, rand, xor, rxor, or, ror, and invert, numerator, and denominator. Discussion ---------- The only known use cases for variants of int are types that limit the range of values to those that fit in a fixed storage width. One existing implementation is in numpy which has types like int0, int8, int16, int32, and int16. The numpy integral types implement all the methods present in Integral except for the new methods like trunc, index, real, imag, conjugate, numerator, and denominator. For the most part, they are fully substitutable into code that expects regular ints; however, they do have wrap-around behaviors such as int8(200)+int8(100) --> int8(44). The wrap-around behaviors make the numpy types totally unsuitable for some applications of Integral such as the fractions module which accepts any integral numerator and denominator.

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