[Python-3000] Updated and simplified PEP 3141: A Type Hierarchy for Numbers (original) (raw)

Jeffrey Yasskin jyasskin at gmail.com
Thu May 17 02:31:50 CEST 2007


I've updated PEP3141 to remove the algebraic classes and bring the numeric hierarchy much closer to scheme's design. Let me know what you think. Feel free to send typographical and formatting problems just to me. My schedule's a little shaky the next couple weeks, but I'll make updates as quickly as I can.

PEP: 3141 Title: A Type Hierarchy for Numbers Version: Revision:54928Revision: 54928 Revision:54928 Last-Modified: Date:2007−04−2316:37:29−0700(Mon,23Apr2007)Date: 2007-04-23 16:37:29 -0700 (Mon, 23 Apr 2007) Date:2007042316:37:290700(Mon,23Apr2007) Author: Jeffrey Yasskin <jyasskin at gmail.com> Status: Draft Type: Standards Track Content-Type: text/x-rst Created: 23-Apr-2007 Post-History: Not yet posted

Abstract

This proposal defines a hierarchy of Abstract Base Classes (ABCs) (PEP 3119) to represent number-like classes. It proposes a hierarchy of Number :> Complex :> Real :> Rational :> Integer where A :> B means "A is a supertype of B", and a pair of Exact/Inexact classes to capture the difference between floats and ints. These types are significantly inspired by Scheme's numeric tower [#schemetower]_.

Rationale

Functions that take numbers as arguments should be able to determine the properties of those numbers, and if and when overloading based on types is added to the language, should be overloadable based on the types of the arguments. For example, slicing requires its arguments to be Integers, and the functions in the math module require their arguments to be Real.

Specification

This PEP specifies a set of Abstract Base Classes with default implementations. If the reader prefers to think in terms of Roles (PEP 3133), the default implementations for (for example) the Real ABC would be moved to a RealDefault class, with Real keeping just the method declarations.

Although this PEP uses terminology from PEP 3119, the hierarchy is intended to be meaningful for any systematic method of defining sets of classes, including Interfaces. I'm also using the extra notation from PEP 3107 (Function Annotations) to specify some types.

Exact vs. Inexact Classes

Floating point values may not exactly obey several of the properties you would expect. For example, it is possible for (X + -X) + 3 == 3, but X + (-X + 3) == 0. On the range of values that most functions deal with this isn't a problem, but it is something to be aware of.

Therefore, I define Exact and Inexact ABCs to mark whether types have this problem. Every instance of Integer and Rational should be Exact, but Reals and Complexes may or may not be. (Do we really only need one of these, and the other is defined as not the first?)::

class Exact(metaclass=MetaABC): pass
class Inexact(metaclass=MetaABC): pass

Numeric Classes

We begin with a Number class to make it easy for people to be fuzzy about what kind of number they expect. This class only helps with overloading; it doesn't provide any operations. Open question: Should it specify __add__, __sub__, __neg__, __mul__, and __abs__ like Haskell's Num class?::

class Number(metaclass=MetaABC): pass

Some types (primarily float) define "Not a Number" (NaN) values that return false for any comparison, including equality with themselves, and are maintained through operations. Because this doesn't work well with the Reals (which are otherwise totally ordered by <), Guido suggested we might put NaN in its own type. It is conceivable that this can still be represented by C doubles but be included in a different ABC at runtime. Open issue: Is this a good idea?::

class NotANumber(Number):
    """Implement IEEE 754 semantics."""
    def __lt__(self, other): return false
    def __eq__(self, other): return false
    ...
    def __add__(self, other): return self
    def __radd__(self, other): return self
    ...

Complex numbers are immutable and hashable. Implementors should be careful that they make equal numbers equal and hash them to the same values. This may be subtle if there are two different extensions of the real numbers::

class Complex(Hashable, Number):
    """A ``Complex`` should define the operations that work on the
    Python ``complex`` type. If it is given heterogenous
    arguments, it may fall back on this class's definition of the
    operations. These operators should never return a
    TypeError as long as both arguments are instances of Complex
    (or even just implement __complex__).
    """
    @abstractmethod
    def __complex__(self):
        """This operation gives the arithmetic operations a fallback.
        """
        return complex(self.real, self.imag)
    @property
    def real(self):
        return complex(self).real
    @property
    def imag(self):
        return complex(self).imag

I define the reversed operations here so that they serve as the final fallback for operations involving instances of Complex. Open issue: Should Complex's operations check for isinstance(other, Complex)? Duck typing seems to imply that we should just try complex and succeed if it works, but stronger typing might be justified for the operators. TODO: analyze the combinations of normal and reversed operations with real and virtual subclasses of Complex::

    def __radd__(self, other):
        """Should this catch any type errors and return
        NotImplemented instead?"""
        return complex(other) + complex(self)
    def __rsub__(self, other):
        return complex(other) - complex(self)
    def __neg__(self):
        return -complex(self)
    def __rmul__(self, other):
        return complex(other) * complex(self)
    def __rdiv__(self, other):
        return complex(other) / complex(self)

    def __abs__(self):
        return abs(complex(self))

    def conjugate(self):
        return complex(self).conjugate()

    def __hash__(self):
        """Two "equal" values of different complex types should
        hash in the same way."""
    return hash(complex(self))

The Real ABC indicates that the value is on the real line, and supports the operations of the float builtin. Real numbers are totally ordered. (NaNs were handled above.)::

class Real(Complex, metaclass=TotallyOrderedABC):
    @abstractmethod
def __float__(self):
    """Any Real can be converted to a native float object."""
    raise NotImplementedError
    def __complex__(self):
        """Which gives us an easy way to define the conversion to
        complex."""
        return complex(float(self))
    @property
    def real(self): return self
    @property
    def imag(self): return 0

    def __radd__(self, other):
        if isinstance(other, Real):
            return float(other) + float(self)
        else:
            return super(Real, self).__radd__(other)
    def __rsub__(self, other):
        if isinstance(other, Real):
            return float(other) - float(self)
        else:
            return super(Real, self).__rsub__(other)
    def __neg__(self):
        return -float(self)
    def __rmul__(self, other):
        if isinstance(other, Real):
            return float(other) * float(self)
        else:
            return super(Real, self).__rmul__(other)
    def __rdiv__(self, other):
        if isinstance(other, Real):
            return float(other) / float(self)
        else:
            return super(Real, self).__rdiv__(other)
    def __rdivmod__(self, other):
        """Implementing divmod() for your type is sufficient to
        get floordiv and mod too.
        """
        if isinstance(other, Real):
            return divmod(float(other), float(self))
        else:
            return super(Real, self).__rdivmod__(other)
    def __rfloordiv__(self, other):
        return divmod(other, self)[0]
    def __rmod__(self, other):
        return divmod(other, self)[1]

def __trunc__(self):
        """Do we want properfraction, floor, ceiling, and round?"""
        return trunc(float(self))

    def __abs__(self):
        return abs(float(self))

There is no way to define only the reversed comparison operators, so these operations take precedence over any defined in the other type. :( ::

    def __lt__(self, other):
        """The comparison operators in Python seem to be more
        strict about their input types than other functions. I'm
        guessing here that we want types to be incompatible even
        if they define a __float__ operation, unless they also
        declare themselves to be Real numbers.
        """
        if isinstance(other, Real):
            return float(self) < float(other)
        else:
            return NotImplemented

    def __le__(self, other):
        if isinstance(other, Real):
            return float(self) <= float(other)
        else:
            return NotImplemented

    def __eq__(self, other):
        if isinstance(other, Real):
            return float(self) == float(other)
        else:
            return NotImplemented

There is no built-in rational type, but it's straightforward to write, so we provide an ABC for it::

class Rational(Real, Exact):
    """rational.numerator and rational.denominator should be in
    lowest terms.
    """
    @abstractmethod
    @property
    def numerator(self):
        raise NotImplementedError
    @abstractmethod
    @property
    def denominator(self):
        raise NotImplementedError

    def __float__(self):
        return self.numerator / self.denominator


class Integer(Rational):
@abstractmethod
def __int__(self):
    raise NotImplementedError
def __float__(self):
    return float(int(self))
    @property
    def numerator(self): return self
    @property
    def denominator(self): return 1

def __ror__(self, other):
    return int(other) | int(self)
def __rxor__(self, other):
    return int(other) ^ int(self)
def __rand__(self, other):
    return int(other) & int(self)
def __rlshift__(self, other):
    return int(other) << int(self)
def __rrshift__(self, other):
    return int(other) >> int(self)
def __invert__(self):
    return ~int(self)

    def __radd__(self, other):
        """All of the Real methods need to be overridden here too
        in order to get a more exact type for their results.
        """
        if isinstance(other, Integer):
            return int(other) + int(self)
        else:
            return super(Integer, self).__radd__(other)
    ...

    def __hash__(self):
        """Surprisingly, hash() needs to be overridden too, since
        there are integers that float can't represent."""
        return hash(int(self))

Adding More Numeric ABCs

There are, of course, more possible ABCs for numbers, and this would be a poor hierarchy if it precluded the possibility of adding those. You can add MyFoo between Complex and Real with::

class MyFoo(Complex): ...
MyFoo.register(Real)

TODO(jyasskin): Check this.

Rejected Alternatives

The initial version of this PEP defined an algebraic hierarchy inspired by a Haskell Numeric Prelude [#numericprelude]_ including MonoidUnderPlus, AdditiveGroup, Ring, and Field, and mentioned several other possible algebraic types before getting to the numbers. I had expected this to be useful to people using vectors and matrices, but the NumPy community really wasn't interested. The numbers then had a much more branching structure to include things like the Gaussian Integers and Z/nZ, which could be Complex but wouldn't necessarily support things like division. The community decided that this was too much complication for Python, so the proposal has been scaled back to resemble the Scheme numeric tower much more closely.

References

.. [#pep3119] Introducing Abstract Base Classes (http://www.python.org/dev/peps/pep-3119/)

.. [#pep3107] Function Annotations (http://www.python.org/dev/peps/pep-3107/)

.. [3] Possible Python 3K Class Tree?, wiki page created by Bill Janssen (http://wiki.python.org/moin/AbstractBaseClasses)

.. [#numericprelude] NumericPrelude: An experimental alternative hierarchy of numeric type classes (http://darcs.haskell.org/numericprelude/docs/html/index.html)

.. [#schemetower] The Scheme numerical tower (http://www.swiss.ai.mit.edu/ftpdir/scheme-reports/r5rs-html/r5rs_8.html#SEC50)

Acknowledgements

Thanks to Neil Norwitz for encouraging me to write this PEP in the first place, to Travis Oliphant for pointing out that the numpy people didn't really care about the algebraic concepts, to Alan Isaac for reminding me that Scheme had already done this, and to Guido van Rossum and lots of other people on the mailing list for refining the concept.

Copyright

This document has been placed in the public domain.



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