singledispatch decorator for instance methods.
Project description
==============
methoddispatch 1.0.0
==============
`PEP 443 <http://www.python.org/dev/peps/pep-0443/>`_ proposed to expose
a mechanism in the ``functools`` standard library module in Python 3.4
that provides a simple form of generic programming known as
single-dispatch generic functions.
This library extends this functionality to instance methods (and works for functions too)
To define a generic method , decorate it with the ``@singledispatch``
decorator. Note that the dispatch happens on the type of the first
argument, create your function accordingly::
>>> from methoddispatch import singledispatch
>>> @singledispatch
... def fun(arg, verbose=False):
... if verbose:
... print("Let me just say,", end=" ")
... print(arg)
To add overloaded implementations to the function, use the
``register()`` attribute of the generic function. It is a decorator,
taking a type parameter and decorating a function implementing the
operation for that type::
>>> @fun.register(int)
... def _(arg, verbose=False):
... if verbose:
... print("Strength in numbers, eh?", end=" ")
... print(arg)
...
>>> @fun.register(list)
... def _(arg, verbose=False):
... if verbose:
... print("Enumerate this:")
... for i, elem in enumerate(arg):
... print(i, elem)
To enable registering lambdas and pre-existing functions, the
``register()`` attribute can be used in a functional form::
>>> def nothing(arg, verbose=False):
... print("Nothing.")
...
>>> fun.register(type(None), nothing)
<function nothing at 0x03D3FDB0>
The ``register()`` attribute returns the undecorated function which
enables decorator stacking, pickling, as well as creating unit tests for
each variant independently::
>>> from decimal import Decimal
>>> @fun.register(float)
... @fun.register(Decimal)
... def fun_num(arg, verbose=False):
... if verbose:
... print("Half of your number:", end=" ")
... print(arg / 2)
...
>>> fun_num is fun
False
When called, the generic function dispatches on the type of the first
argument::
>>> fun("Hello, world.")
Hello, world.
>>> fun("test.", verbose=True)
Let me just say, test.
>>> fun(42, verbose=True)
Strength in numbers, eh? 42
>>> fun(['spam', 'spam', 'eggs', 'spam'], verbose=True)
Enumerate this:
0 spam
1 spam
2 eggs
3 spam
>>> fun(None)
Nothing.
>>> fun(1.23)
0.615
Where there is no registered implementation for a specific type, its
method resolution order is used to find a more generic implementation.
The original function decorated with ``@singledispatch`` is registered
for the base ``object`` type, which means it is used if no better
implementation is found.
To check which implementation will the generic function choose for
a given type, use the ``dispatch()`` attribute::
>>> fun.dispatch(float)
<function fun_num at 0x1035a2840>
>>> fun.dispatch(dict) # note: default implementation
<function fun at 0x103fe0000>
To access all registered implementations, use the read-only ``registry``
attribute::
>>> fun.registry.keys()
dict_keys([<class 'NoneType'>, <class 'int'>, <class 'object'>,
<class 'decimal.Decimal'>, <class 'list'>,
<class 'float'>])
>>> fun.registry[float]
<function fun_num at 0x1035a2840>
>>> fun.registry[object]
<function fun at 0x103fe0000>
Decorating class methods requires the class have ``SingleDispatchMeta`` as
a metaclass. The metaclass ensures that the dipatch registry of
sub-classes do not affect instances of the base class::
>>> class BaseClass(metaclass=SingleDispatchMeta):
... @singledispatch
... def foo(self, bar):
... return 'default'
...
... @foo.register(int)
... def foo_int(self, bar):
... return 'int'
...
>>> b = BaseClass()
>>> b.foo('hello')
'default'
>>> b.foo(1)
'int'
Subclasses can extend the type registry of the function on the base class with their own overrides.
Because the ``foo`` function is not in scope, the ``register`` decorator must be used instead::
>>> class SubClass(BaseClass):
... @register('foo', float)
... def foo_float(self, bar):
... return 'float'
...
>>> s = SubClass()
>>> s.foo(1)
'int'
>>> s.foo(1.0)
'float'
>>> b.foo(1.0)
'default'
Method overrides do not need to provide the ``register`` decorator again::
>>> class SubClass2(BaseClass):
... def foo_int(self, bar):
... return 'my int'
...
>>> s = SubClass2()
>>> s.foo(1)
'my int'
Providing the register decorator with the same type will also work.
Decorating with a different type (not a good idea) will register the different
type and leave the base-class handler in place for the orginal type.
If your class also inhertits from an ABC interface you can use the SingleDispatchABCMeta metaclass instead.
methoddispatch 1.0.0
==============
`PEP 443 <http://www.python.org/dev/peps/pep-0443/>`_ proposed to expose
a mechanism in the ``functools`` standard library module in Python 3.4
that provides a simple form of generic programming known as
single-dispatch generic functions.
This library extends this functionality to instance methods (and works for functions too)
To define a generic method , decorate it with the ``@singledispatch``
decorator. Note that the dispatch happens on the type of the first
argument, create your function accordingly::
>>> from methoddispatch import singledispatch
>>> @singledispatch
... def fun(arg, verbose=False):
... if verbose:
... print("Let me just say,", end=" ")
... print(arg)
To add overloaded implementations to the function, use the
``register()`` attribute of the generic function. It is a decorator,
taking a type parameter and decorating a function implementing the
operation for that type::
>>> @fun.register(int)
... def _(arg, verbose=False):
... if verbose:
... print("Strength in numbers, eh?", end=" ")
... print(arg)
...
>>> @fun.register(list)
... def _(arg, verbose=False):
... if verbose:
... print("Enumerate this:")
... for i, elem in enumerate(arg):
... print(i, elem)
To enable registering lambdas and pre-existing functions, the
``register()`` attribute can be used in a functional form::
>>> def nothing(arg, verbose=False):
... print("Nothing.")
...
>>> fun.register(type(None), nothing)
<function nothing at 0x03D3FDB0>
The ``register()`` attribute returns the undecorated function which
enables decorator stacking, pickling, as well as creating unit tests for
each variant independently::
>>> from decimal import Decimal
>>> @fun.register(float)
... @fun.register(Decimal)
... def fun_num(arg, verbose=False):
... if verbose:
... print("Half of your number:", end=" ")
... print(arg / 2)
...
>>> fun_num is fun
False
When called, the generic function dispatches on the type of the first
argument::
>>> fun("Hello, world.")
Hello, world.
>>> fun("test.", verbose=True)
Let me just say, test.
>>> fun(42, verbose=True)
Strength in numbers, eh? 42
>>> fun(['spam', 'spam', 'eggs', 'spam'], verbose=True)
Enumerate this:
0 spam
1 spam
2 eggs
3 spam
>>> fun(None)
Nothing.
>>> fun(1.23)
0.615
Where there is no registered implementation for a specific type, its
method resolution order is used to find a more generic implementation.
The original function decorated with ``@singledispatch`` is registered
for the base ``object`` type, which means it is used if no better
implementation is found.
To check which implementation will the generic function choose for
a given type, use the ``dispatch()`` attribute::
>>> fun.dispatch(float)
<function fun_num at 0x1035a2840>
>>> fun.dispatch(dict) # note: default implementation
<function fun at 0x103fe0000>
To access all registered implementations, use the read-only ``registry``
attribute::
>>> fun.registry.keys()
dict_keys([<class 'NoneType'>, <class 'int'>, <class 'object'>,
<class 'decimal.Decimal'>, <class 'list'>,
<class 'float'>])
>>> fun.registry[float]
<function fun_num at 0x1035a2840>
>>> fun.registry[object]
<function fun at 0x103fe0000>
Decorating class methods requires the class have ``SingleDispatchMeta`` as
a metaclass. The metaclass ensures that the dipatch registry of
sub-classes do not affect instances of the base class::
>>> class BaseClass(metaclass=SingleDispatchMeta):
... @singledispatch
... def foo(self, bar):
... return 'default'
...
... @foo.register(int)
... def foo_int(self, bar):
... return 'int'
...
>>> b = BaseClass()
>>> b.foo('hello')
'default'
>>> b.foo(1)
'int'
Subclasses can extend the type registry of the function on the base class with their own overrides.
Because the ``foo`` function is not in scope, the ``register`` decorator must be used instead::
>>> class SubClass(BaseClass):
... @register('foo', float)
... def foo_float(self, bar):
... return 'float'
...
>>> s = SubClass()
>>> s.foo(1)
'int'
>>> s.foo(1.0)
'float'
>>> b.foo(1.0)
'default'
Method overrides do not need to provide the ``register`` decorator again::
>>> class SubClass2(BaseClass):
... def foo_int(self, bar):
... return 'my int'
...
>>> s = SubClass2()
>>> s.foo(1)
'my int'
Providing the register decorator with the same type will also work.
Decorating with a different type (not a good idea) will register the different
type and leave the base-class handler in place for the orginal type.
If your class also inhertits from an ABC interface you can use the SingleDispatchABCMeta metaclass instead.
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