Question on passing function as argument

xtian xtian at
Tue Apr 1 07:21:31 CEST 2003

matthew <matthew at> wrote in message news:<b6abiv$b6t$1 at>...
> Hi,
> Howto pass a func as an argument to a list?
> event.add_listener('linear', [calc_position(params)])
> the function seems to execute 'in-place' and the event_list[event] shows 
> None.

calc_position(params) is calling calc_position with params before
calling event.add_listener with the result (which is None, in this

To pass a one element list containing the function object named
calc_position to your add_listener method (you might want to rename
that to add_listeners, by the way), you'd do the following:

event.add_listener('linear', [calc_position])

Leaving off the () means that the function isn't called, it's just
passed in.
Now, this isn't quite what you want - it doesn't pass the parameters.

If params is accessible from your notify method, you could just pass
it in when calling the function (guessing at the implementation of the
notify method...):

def notify(self, event, params):
    for listener in self.event_list[event]:

If you won't be able to access params from notify, you'll need to
package the arguments with the function . You could do this in a
number of ways:

1) defining a local function:

def local_calc():
event.add_listener('linear', [local_calc])

2) defining a local anonymous function:

event.add_listener('linear', [lambda: calc_position(params)])

3) by currying the function:

class SimpleCurry:
    def __init__(self, func, *args, **kw):
        self.func = func
        self.args = args = kw
    def __call__(self):
        return self.func(*self.args, **

event.add_listener('linear', [SimpleCurry(calc_position, params)])

If you use one of these, the notify method changes to:

def notify(self, event):
    for listener in self.event_list[event]:

Note - the first two options use nested scopes - I'm not sure whether
they're on by default in 2.1, but I don't think so. And the
func(*args, **kw) syntax used in 3 isn't available until then either.
If you're using an earlier version of Python (before 2.1), these
options will be spelt slightly differently, although using the same
basic concepts.

Hope that helps!

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