Interceptar operaciones de corte en Python

methods jython

Question

Quiero imitar una lista python normal, excepto cuando los elementos se agregan o quitan mediante el corte, quiero ''guardar'' la lista. es posible? Este fue mi intento, pero nunca imprimirá ''guardar''.

class InterceptedList(list):

    def addSave(func):
        def newfunc(self, *args):
            func(self, *args)
            print ''saving''
        return newfunc

    __setslice__ = addSave(list.__setslice__)
    __delslice__ = addSave(list.__delslice__)

>>> l = InterceptedList()
>>> l.extend([1,2,3,4])
>>> l
[1, 2, 3, 4]
>>> l[3:] = [5] # note: ''saving'' is not printed
>>> l
[1, 2, 3, 5]

Esto funciona para otros métodos como append y extend , pero no para las operaciones de división.

EDITAR: El verdadero problema es que estoy usando Jython y no Python y lo olvidé. Los comentarios sobre la pregunta son correctos. Este código funciona bien en Python (2.6). Sin embargo, el código ni las respuestas funcionan en Jython.

Answer 1

"setslice" y "delslice" están en desuso, si desea hacer la intercepción que necesita para trabajar con objetos de corte de Python pasados ​​a "setitem" y "delitem". Si desea intecept tanto las divisiones como los accesos ordinarios, este código funciona perfectamente en Python 2.6.2.

class InterceptedList(list):

def addSave(func):
    def newfunc(self, *args):
        func(self, *args)
        print ''saving''
    return newfunc

def __setitem__(self, key, value):
    print ''saving''
    list.__setitem__(self, key, value)

def __delitem__(self, key):
    print ''saving''
    list.__delitem__(self, key)

Answer 2

De Python 3 documentos :

__getslice__(), __setslice__() and __delslice__() were killed. 
The syntax a[i:j] now translates to a.__getitem__(slice(i, j)) 
(or __setitem__() or __delitem__(), when used as an assignment 
or deletion target, respectively).

Answer 3

Eso es suficiente especulación. Comencemos a usar los hechos, ¿lo haremos? Por lo que puedo decir, la conclusión es que debes anular ambos conjuntos de métodos.

Si desea implementar deshacer / rehacer, probablemente debería intentar usar deshacer pila y un conjunto de acciones que pueden hacer () / deshacer () ellos mismos.

Código

import profile
import sys

print sys.version

class InterceptedList(list):

    def addSave(func):
        def newfunc(self, *args):
            func(self, *args)
            print ''saving''
        return newfunc

    __setslice__ = addSave(list.__setslice__)
    __delslice__ = addSave(list.__delslice__)


class InterceptedList2(list):

    def __setitem__(self, key, value):
        print ''saving''
        list.__setitem__(self, key, value)

    def __delitem__(self, key):
        print ''saving''
        list.__delitem__(self, key)


print("------------Testing setslice------------------")
l = InterceptedList()
l.extend([1,2,3,4])
profile.run("l[3:] = [5]")
profile.run("l[2:6] = [12, 4]")
profile.run("l[-1:] = [42]")
profile.run("l[::2] = [6,6]")

print("-----------Testing setitem--------------------")
l2 = InterceptedList2()
l2.extend([1,2,3,4])
profile.run("l2[3:] = [5]")
profile.run("l2[2:6] = [12,4]")
profile.run("l2[-1:] = [42]")
profile.run("l2[::2] = [6,6]")

Jython 2.5

C:/Users/wuu-local.pyza/Desktop>c:/jython2.5.0/jython.bat intercept.py
2.5.0 (Release_2_5_0:6476, Jun 16 2009, 13:33:26)
[Java HotSpot(TM) Client VM (Sun Microsystems Inc.)]
------------Testing setslice------------------
saving
         3 function calls in 0.035 CPU seconds

   Ordered by: standard name

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    0.000    0.000 <string>:0(<module>)
        1    0.000    0.000    0.000    0.000 intercept.py:9(newfunc)
        1    0.034    0.034    0.035    0.035 profile:0(l[3:] = [5])
        0    0.000             0.000          profile:0(profiler)


saving
         3 function calls in 0.005 CPU seconds

   Ordered by: standard name

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    0.001    0.001 <string>:0(<module>)
        1    0.001    0.001    0.001    0.001 intercept.py:9(newfunc)
        1    0.004    0.004    0.005    0.005 profile:0(l[2:6] = [12, 4])
        0    0.000             0.000          profile:0(profiler)


saving
         3 function calls in 0.012 CPU seconds

   Ordered by: standard name

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    0.000    0.000 <string>:0(<module>)
        1    0.000    0.000    0.000    0.000 intercept.py:9(newfunc)
        1    0.012    0.012    0.012    0.012 profile:0(l[-1:] = [42])
        0    0.000             0.000          profile:0(profiler)


         2 function calls in 0.004 CPU seconds

   Ordered by: standard name

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    0.000    0.000 <string>:0(<module>)
        1    0.004    0.004    0.004    0.004 profile:0(l[::2] = [6,6])
        0    0.000             0.000          profile:0(profiler)


-----------Testing setitem--------------------
         2 function calls in 0.004 CPU seconds

   Ordered by: standard name

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    0.000    0.000 <string>:0(<module>)
        1    0.004    0.004    0.004    0.004 profile:0(l2[3:] = [5])
        0    0.000             0.000          profile:0(profiler)


         2 function calls in 0.006 CPU seconds

   Ordered by: standard name

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    0.000    0.000 <string>:0(<module>)
        1    0.006    0.006    0.006    0.006 profile:0(l2[2:6] = [12,4])
        0    0.000             0.000          profile:0(profiler)


         2 function calls in 0.004 CPU seconds

   Ordered by: standard name

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    0.000    0.000 <string>:0(<module>)
        1    0.004    0.004    0.004    0.004 profile:0(l2[-1:] = [42])
        0    0.000             0.000          profile:0(profiler)


saving
         3 function calls in 0.007 CPU seconds

   Ordered by: standard name

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    0.002    0.002 <string>:0(<module>)
        1    0.001    0.001    0.001    0.001 intercept.py:20(__setitem__)
        1    0.005    0.005    0.007    0.007 profile:0(l2[::2] = [6,6])
        0    0.000             0.000          profile:0(profiler)

Python 2.6.2

C:/Users/wuu-local.pyza/Desktop>python intercept.py
2.6 (r26:66721, Oct  2 2008, 11:35:03) [MSC v.1500 32 bit (Intel)]
------------Testing setslice------------------
saving
         4 function calls in 0.002 CPU seconds

   Ordered by: standard name

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.002    0.002    0.002    0.002 :0(setprofile)
        1    0.000    0.000    0.000    0.000 <string>:1(<module>)
        1    0.000    0.000    0.000    0.000 intercept.py:9(newfunc)
        1    0.000    0.000    0.002    0.002 profile:0(l[3:] = [5])
        0    0.000             0.000          profile:0(profiler)


saving
         4 function calls in 0.000 CPU seconds

   Ordered by: standard name

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    0.000    0.000 :0(setprofile)
        1    0.000    0.000    0.000    0.000 <string>:1(<module>)
        1    0.000    0.000    0.000    0.000 intercept.py:9(newfunc)
        1    0.000    0.000    0.000    0.000 profile:0(l[2:6] = [12, 4])
        0    0.000             0.000          profile:0(profiler)


saving
         4 function calls in 0.000 CPU seconds

   Ordered by: standard name

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    0.000    0.000 :0(setprofile)
        1    0.000    0.000    0.000    0.000 <string>:1(<module>)
        1    0.000    0.000    0.000    0.000 intercept.py:9(newfunc)
        1    0.000    0.000    0.000    0.000 profile:0(l[-1:] = [42])
        0    0.000             0.000          profile:0(profiler)


         3 function calls in 0.000 CPU seconds

   Ordered by: standard name

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    0.000    0.000 :0(setprofile)
        1    0.000    0.000    0.000    0.000 <string>:1(<module>)
        1    0.000    0.000    0.000    0.000 profile:0(l[::2] = [6,6])
        0    0.000             0.000          profile:0(profiler)


-----------Testing setitem--------------------
         3 function calls in 0.000 CPU seconds

   Ordered by: standard name

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    0.000    0.000 :0(setprofile)
        1    0.000    0.000    0.000    0.000 <string>:1(<module>)
        1    0.000    0.000    0.000    0.000 profile:0(l2[3:] = [5])
        0    0.000             0.000          profile:0(profiler)


         3 function calls in 0.000 CPU seconds

   Ordered by: standard name

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    0.000    0.000 :0(setprofile)
        1    0.000    0.000    0.000    0.000 <string>:1(<module>)
        1    0.000    0.000    0.000    0.000 profile:0(l2[2:6] = [12,4])
        0    0.000             0.000          profile:0(profiler)


         3 function calls in 0.000 CPU seconds

   Ordered by: standard name

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    0.000    0.000 :0(setprofile)
        1    0.000    0.000    0.000    0.000 <string>:1(<module>)
        1    0.000    0.000    0.000    0.000 profile:0(l2[-1:] = [42])
        0    0.000             0.000          profile:0(profiler)


saving
         4 function calls in 0.003 CPU seconds

   Ordered by: standard name

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    0.000    0.000 :0(setprofile)
        1    0.000    0.000    0.003    0.003 <string>:1(<module>)
        1    0.002    0.002    0.002    0.002 intercept.py:20(__setitem__)
        1    0.000    0.000    0.003    0.003 profile:0(l2[::2] = [6,6])
        0    0.000             0.000          profile:0(profiler)

Answer 4

las circunstancias donde __getslice__ y __setslice__ se llaman son bastante estrechas. Específicamente, el corte solo se produce cuando utiliza un corte regular, donde los elementos primero y final se mencionan exactamente una vez. para cualquier otra sintaxis de sector, o ninguna __setitem__ en absoluto, se llama __getitem__ o __setitem__ .