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genericfuncs

genericfuncs enables you to create functions which execute different implementations depending on the arguments.

This module can be seen as a powerful improvement over Python 3's singledispatch:

  • Allows dispatch over any boolean callable, not just type checks.
  • Allows dispatch over any number of arguments, not just the first argument.

Basic usage

from genericfuncs import generic

@generic
def func(a):
    # default implementation
    raise ValueError()

@func.when(lambda a: a.startswith('foo'))
def _foo(a):
    return a.upper()

@func.when(lambda a: a.startswith('bar'))
def _bar(a):
    return a.lower()

The first predicate that returns True has its mapped implementation invoked. Predicates are checked in order of definition.

Installation

pip install genericfuncs

Advanced

Arguments are injected into predicates and implementations by their name. This means a predicate or implementation is able to specify only the arguments it needs. For example:

@generic
def multiple_params_func(a, b, c):
    return 0 # default implementation

@multiple_params_func.when(lambda b: b > 10)  # only inject argument `b` to the predicate
def _when_b_greater_than_10(a):  # only inject `a` to the implementation
    return a * 10

@multiple_params_func.when(lambda a, b: a % b == 0)  # only inject `a` and `b`
def _when_a_divisible_by_b(a, b, c):  # use all arguments
    return a / b * c

However the call site must list all mandatory arguments, as usual in Python:

multiple_params_func(10, 20, 30)  # --> 100 [_when_b_great_than_10() invoked]
multiple_params_func(4, 2, 'bla')  # --> 'blabla' [_when_a_divisible_by_b() invoked]
multiple_params_func(1, 2, 3)  # --> 0 [default implementation invoked]

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Dynamic dispatch over arbitrary predicates

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