Scope of lambda functions and their parameters?

I need a callback function that is almost exactly the same for a series of gui events. The function will behave slightly differently depending on which event has called it. Seems like a simple case to me, but I cannot figure out this weird behavior of lambda functions.

So I have the following simplified code below:

def callback(msg):
    print msg

#creating a list of function handles with an iterator
funcList=[]
for m in ('do', 're', 'mi'):
    funcList.append(lambda: callback(m))
for f in funcList:
    f()

#create one at a time
funcList=[]
funcList.append(lambda: callback('do'))
funcList.append(lambda: callback('re'))
funcList.append(lambda: callback('mi'))
for f in funcList:
    f()

The output of this code is:

mi
mi
mi
do
re
mi

I expected:

do
re
mi
do
re
mi

Why has using an iterator messed things up?

I've tried using a deepcopy:

import copy
funcList=[]
for m in ('do', 're', 'mi'):
    funcList.append(lambda: callback(copy.deepcopy(m)))
for f in funcList:
    f()

But this has the same problem.

Solution

The problem here is the m variable (a reference) being taken from the surrounding scope. Only parameters are held in the lambda scope.

To solve this you have to create another scope for lambda:

def callback(msg):
    print msg

def callback_factory(m):
    return lambda: callback(m)

funcList=[]
for m in ('do', 're', 'mi'):
    funcList.append(callback_factory(m))
for f in funcList:
    f()

In the example above, lambda also uses the surounding scope to find m, but this time it's callback_factory scope which is created once per every callback_factory call.

Or with functools.partial:

from functools import partial

def callback(msg):
    print msg

funcList=[partial(callback, m) for m in ('do', 're', 'mi')]
for f in funcList:
    f()