"function" as a keyword is only used for defining functions, and cannot be used inside a loop (or inside an "if" or "switch" or other control statement.) The only kinds of functions that can be defined within loops are anonymous functions.
Python call function inside for loop A Python for loop is used to loop through an iterable object (like a list, tuple, set, etc.) and perform the same action for each entry. We can call a function from inside of for loop.
The operation of a loop function involves iterating over an R object (e.g. a list or vector or matrix), applying a function to each element of the object, and the collating the results and returning the collated results.
You're running into a problem with late binding -- each function looks up i
as late as possible (thus, when called after the end of the loop, i
will be set to 2
).
Easily fixed by forcing early binding: change def f():
to def f(i=i):
like this:
def f(i=i):
return i
Default values (the right-hand i
in i=i
is a default value for argument name i
, which is the left-hand i
in i=i
) are looked up at def
time, not at call
time, so essentially they're a way to specifically looking for early binding.
If you're worried about f
getting an extra argument (and thus potentially being called erroneously), there's a more sophisticated way which involved using a closure as a "function factory":
def make_f(i):
def f():
return i
return f
and in your loop use f = make_f(i)
instead of the def
statement.
The issue here is that the value of i
is not saved when the function f
is created. Rather, f
looks up the value of i
when it is called.
If you think about it, this behavior makes perfect sense. In fact, it's the only reasonable way functions can work. Imagine you have a function that accesses a global variable, like this:
global_var = 'foo'
def my_function():
print(global_var)
global_var = 'bar'
my_function()
When you read this code, you would - of course - expect it to print "bar", not "foo", because the value of global_var
has changed after the function was declared. The same thing is happening in your own code: By the time you call f
, the value of i
has changed and been set to 2
.
There are actually many ways to solve this problem. Here are a few options:
i
by using it as a default argumentUnlike closure variables (like i
), default arguments are evaluated immediately when the function is defined:
for i in range(3):
def f(i=i): # <- right here is the important bit
return i
functions.append(f)
To give a little bit of insight into how/why this works: A function's default arguments are stored as an attribute of the function; thus the current value of i
is snapshotted and saved.
>>> i = 0
>>> def f(i=i):
... pass
>>> f.__defaults__ # this is where the current value of i is stored
(0,)
>>> # assigning a new value to i has no effect on the function's default arguments
>>> i = 5
>>> f.__defaults__
(0,)
i
in a closureThe root of your problem is that i
is a variable that can change. We can work around this problem by creating another variable that is guaranteed to never change - and the easiest way to do this is a closure:
def f_factory(i):
def f():
return i # i is now a *local* variable of f_factory and can't ever change
return f
for i in range(3):
f = f_factory(i)
functions.append(f)
functools.partial
to bind the current value of i
to f
functools.partial
lets you attach arguments to an existing function. In a way, it too is a kind of function factory.
import functools
def f(i):
return i
for i in range(3):
f_with_i = functools.partial(f, i) # important: use a different variable than "f"
functions.append(f_with_i)
Caveat: These solutions only work if you assign a new value to the variable. If you modify the object stored in the variable, you'll experience the same problem again:
>>> i = [] # instead of an int, i is now a *mutable* object
>>> def f(i=i):
... print('i =', i)
...
>>> i.append(5) # instead of *assigning* a new value to i, we're *mutating* it
>>> f()
i = [5]
Notice how i
still changed even though we turned it into a default argument! If your code mutates i
, then you must bind a copy of i
to your function, like so:
def f(i=i.copy()):
f = f_factory(i.copy())
f_with_i = functools.partial(f, i.copy())
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