Okay, bear with me on this, I know it's going to look horribly convoluted, but please help me understand what's happening.
from functools import partial
class Cage(object):
def __init__(self, animal):
self.animal = animal
def gotimes(do_the_petting):
do_the_petting()
def get_petters():
for animal in ['cow', 'dog', 'cat']:
cage = Cage(animal)
def pet_function():
print "Mary pets the " + cage.animal + "."
yield (animal, partial(gotimes, pet_function))
funs = list(get_petters())
for name, f in funs:
print name + ":",
f()
Gives:
cow: Mary pets the cat.
dog: Mary pets the cat.
cat: Mary pets the cat.
So basically, why am I not getting three different animals? Isn't the cage
'packaged' into the local scope of the nested function? If not, how does a call to the nested function look up the local variables?
I know that running into these kind of problems usually means one is 'doing it wrong', but I'd like to understand what happens.
The nested function looks up variables from the parent scope when executed, not when defined.
The function body is compiled, and the 'free' variables (not defined in the function itself by assignment), are verified, then bound as closure cells to the function, with the code using an index to reference each cell. pet_function
thus has one free variable (cage
) which is then referenced via a closure cell, index 0. The closure itself points to the local variable cage
in the get_petters
function.
When you actually call the function, that closure is then used to look at the value of cage
in the surrounding scope at the time you call the function. Here lies the problem. By the time you call your functions, the get_petters
function is already done computing it's results. The cage
local variable at some point during that execution was assigned each of the 'cow'
, 'dog'
, and 'cat'
strings, but at the end of the function, cage
contains that last value 'cat'
. Thus, when you call each of the dynamically returned functions, you get the value 'cat'
printed.
The work-around is to not rely on closures. You can use a partial function instead, create a new function scope, or bind the variable as a default value for a keyword parameter.
Partial function example, using functools.partial()
:
from functools import partial
def pet_function(cage=None):
print "Mary pets the " + cage.animal + "."
yield (animal, partial(gotimes, partial(pet_function, cage=cage)))
Creating a new scope example:
def scoped_cage(cage=None):
def pet_function():
print "Mary pets the " + cage.animal + "."
return pet_function
yield (animal, partial(gotimes, scoped_cage(cage)))
Binding the variable as a default value for a keyword parameter:
def pet_function(cage=cage):
print "Mary pets the " + cage.animal + "."
yield (animal, partial(gotimes, pet_function))
There is no need to define the scoped_cage
function in the loop, compilation only takes place once, not on each iteration of the loop.
My understanding is that cage is looked for in the parent function namespace when the yielded pet_function is actually called, not before.
So when you do
funs = list(get_petters())
You generate 3 functions which will find the lastly created cage.
If you replace your last loop with :
for name, f in get_petters():
print name + ":",
f()
You will actually get :
cow: Mary pets the cow.
dog: Mary pets the dog.
cat: Mary pets the cat.
This stems from the following
for i in range(2):
pass
print(i) # prints 1
after iterating the value of i
is lazily stored as its final value.
As a generator the function would work (i.e. printing each value in turn), but when transforming to a list it runs over the generator, hence all calls to cage
(cage.animal
) return cats.
Let's simplify the question. Define:
def get_petters():
for animal in ['cow', 'dog', 'cat']:
def pet_function():
return "Mary pets the " + animal + "."
yield (animal, pet_function)
Then, just like in the question, we get:
>>> for name, f in list(get_petters()):
... print(name + ":", f())
cow: Mary pets the cat.
dog: Mary pets the cat.
cat: Mary pets the cat.
But if we avoid creating a list()
first:
>>> for name, f in get_petters():
... print(name + ":", f())
cow: Mary pets the cow.
dog: Mary pets the dog.
cat: Mary pets the cat.
What's going on? Why does this subtle difference completely change our results?
If we look at list(get_petters())
, it's clear from the changing memory addresses that we do indeed yield three different functions:
>>> list(get_petters())
[('cow', <function get_petters.<locals>.pet_function at 0x7ff2b988d790>),
('dog', <function get_petters.<locals>.pet_function at 0x7ff2c18f51f0>),
('cat', <function get_petters.<locals>.pet_function at 0x7ff2c14a9f70>)]
However, take a look at the cell
s that these functions are bound to:
>>> for _, f in list(get_petters()):
... print(f(), f.__closure__)
Mary pets the cat. (<cell at 0x7ff2c112a9d0: str object at 0x7ff2c3f437f0>,)
Mary pets the cat. (<cell at 0x7ff2c112a9d0: str object at 0x7ff2c3f437f0>,)
Mary pets the cat. (<cell at 0x7ff2c112a9d0: str object at 0x7ff2c3f437f0>,)
>>> for _, f in get_petters():
... print(f(), f.__closure__)
Mary pets the cow. (<cell at 0x7ff2b86b5d00: str object at 0x7ff2c1a95670>,)
Mary pets the dog. (<cell at 0x7ff2b86b5d00: str object at 0x7ff2c1a952f0>,)
Mary pets the cat. (<cell at 0x7ff2b86b5d00: str object at 0x7ff2c3f437f0>,)
For both loops, the cell
object remains the same throughout the iterations. However, as expected, the specific str
it references varies in the second loop. The cell
object refers to animal
, which is created when get_petters()
is called. However, animal
changes what str
object it refers to as the generator function runs.
In the first loop, during each iteration, we create all the f
s, but we only call them after the generator get_petters()
is completely exhausted and a list
of functions is already created.
In the second loop, during each iteration, we are pausing the get_petters()
generator and calling f
after each pause. Thus, we end up retrieving the value of animal
at that moment in time that the generator function is paused.
As @Claudiu puts in an answer to a similar question:
Three separate functions are created, but they each have the closure of the environment they're defined in - in this case, the global environment (or the outer function's environment if the loop is placed inside another function). This is exactly the problem, though -- in this environment,
animal
is mutated, and the closures all refer to the sameanimal
.[Editor note:
i
has been changed toanimal
.]
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With