While trying to implement an algorithm, I couldn't get python lists to mutate via a function. After reading up on the issue I was suggested by this StackOverflow answer to use [:] in order to mutate the array passed in the function argumemt.
However, as seen in the following code snippet, the issue still persists when trying to mutate the list l. I am expecting the output to be Before: [1,2,3,4]
After: [69, 69, 69, 69], but instead I get back the original value of l as shown below.
def mutate_list(a, b):
c = [69] * 4
a[:] = c[:2] # changed the elements, but array's still unchanged outside function
b[:] = c[2:]
if __name__ == '__main__':
l = [1, 2, 3, 4]
print("Before: {}" .format(l))
mutate_list(l[:2], l[2:])
print("After: {}" .format(l))
Output:
Before: [1, 2, 3, 4]
After : [1, 2, 3, 4]
Any insights into why this is happening?
The error is that you not pass actually the l but two slices of it. You should change it, for example:
def mutate_list(a):
c = [69] * 4
a[:2] = c[:2]
a[2:] = c[2:]
if __name__ == '__main__':
l = [1, 2, 3, 4]
print("Before: {}" .format(l))
mutate_list(l)
print("After: {}" .format(l))
its all about the scope, mutable concept is applicable on list but not to reference variable.
The variables a,b are local variables, hence the scope of the variable will be always function scope.
The operations which you have performed :
a[:]=c[:2]
b[:]=c[2:]
Note: a and b both are list now so you will get following output in the function:
[69,69],[69,69]
but if you use + operator which is use for adding operations then the out out will be like:
[69,69,69,69]
Now whatever I told you that will be a local scope, if you want that the list should be mutable across the program then you have to specify the scope of the list as global inside function and on that variable you can do changes. in this case you also dont need to pass any arguments:
def mutate_list():
global l # telling python to use this global variable in a local function
c = [69] * 4
l=c # assigning new values to actual list i.e l
Now before output will be [1,2,3,4]
and after will be [69,69,69,69]
As pointed out by others, the issue arose from the fact that the function parameters were slices of the original array and as such, the parameters were being passed by value (instead of being passed by reference).
According to #Selcuk 's suggestion, the correct way of doing such an operation would be to pass the original array along with its indices to the function and then perform any slicing inside the function.
NOTE: This concept comes in handy for (recursive) divide-and-conquer algorithms where subarrays must be mutated and combined to form the solution.
Related
I wrote a small Programm in python but it don't work like expected.
Here's the code:
puzzle = [8, 7, 5, 4, 1, 2, 3, 0, 6]
def count(p):
p[0] += 1
return p
def main(p):
print(p)
l = count(p)
print(l)
print(p)
b1 = main(puzzle)
I expect that print(p) will be different from print(l), but the result of both is the same, it's the result that print(l) should have. But p did change also, however I would need it to be unchanged… Is this a special python behavior? Is there something I missed?
I also tried to change the variable names in the functions, but that didn't help.
I restarted the Compiler, but that didn't help either.
Is there a solution to store a function output and than call the function again without let the function change the given parameters?
So that l will be the result after the calculation and p will stay the value before?
Kind Regards,
Joh.
You are passing a List parameter. Parameter passing is Call-by-Object. Since a List is a mutable object in this situation it is similar to pass by reference and changes to your List object will persist. If you were passing an immutable, such as an Integer or String, it would be akin to pass by copy/value, and changes would not persist. E.g.:
def s2asdf(s):
s = "asdf"
s = "hello world"
s2asdf(s)
print s
... results in:
$ python example.py
hello world
The reason for this is because Python passes function parameters by reference. When you call the count function it allows the function to modify the list inside the function and the changes will be applied to the original object.
If you want to have the function not modify the list but instead return a different list, you will have to make a copy of the list either by passing a copy to the function or make a copy inside the function itself. There are many ways to copy a list in Python, but I like to use the list() function to do it.
This should fix your problem:
puzzle = [8, 7, 5, 4, 1, 2, 3, 0, 6]
def count(p):
new_list = list(p) # copy values of p to new_list
new_list[0] += 1
return new_list
def main(p):
print(p)
l = count(p)
print(l) # l is the new_list returned from count
print(p) # p stays the original value
b1 = main(puzzle)
I'm still new to Python, and I've been making a small function that reverses a list of lists, both the original list and the lists inside. This is my code:
def deep_reverse(L):
L.reverse()
L = [i.reverse() for i in L]
Now this code works perfectly, but if I do a small change and rearrange the lines like this:
def deep_reverse(L):
L = [i.reverse() for i in L]
L.reverse()
suddenly it stops working! It only reverses the internal lists but not the original one. Putting some debugging print() statements inside, I can see the first code reverses the original list after the first line and it's printed, but the second code actually prints a list containing 'None' as elements after reversing the list. Can anyone please explain why this behavior and what is the difference between the two codes?
The reverse() function reverses a list in-place and returns None, that explains the weird behavior. A correct implementation would be:
def deep_reverse(L):
ans = [i[::-1] for i in L]
ans.reverse()
return ans
Also, it's a bad idea to reassign and/or mutate a parameter to a function, it can lead to unexpected results. Sometimes functions in the standard library do it for efficiency reasons (for example, sort() and reverse()), that's ok - but it can lead to confusions, like the one you just experienced. Your code doesn't have to be written in that fashion unless strictly necessary.
Your first deep_reverse function reassigned L, but it is not a global parameter and is not returned in your function. Hence this variable is lost. HOWEVER, you are mutating the list in place, hence the modifications remain which is why it still works! Your original function is equivalent to the following (note there is no final assignment):
def deep_reverse(L):
L.reverse()
[i.reverse() for i in L]
This should probably be written using a for-loop:
def deep_reverse_2(L):
L.reverse()
for i in L:
i.reverse()
L = [[1, 2, 3], [2, 3, 4]]
deep_reverse_2(L)
>>> L
[[4, 3, 2], [3, 2, 1]]
The second function does not work because you reassign L inside the function (it is now local to the function and not the same L variable you passed in to the function). They would have different memory locations if you checked using id. Given that nothing is returned, this new L list is lost, as are the modifications made to it.
I don't understand this behaviour:
def getvariable(v):
v += 1
def getlist(l):
l.append(8)
myvariable = 1
mylist = [5, 6, 7]
print myvariable, mylist
getvariable(myvariable)
getlist(mylist)
print myvariable, mylist
Output:
1 [5, 6, 7]
1 [5, 6, 7, 8]
Why list changed, but variable doesn't?
How can I change variable in function?
Many people say about passing by value, by reference, by object reference, so I am a bit confused and don't know how it is really.
In python integers are immutable. v += 1 only binds a new integer value to the name v, which is local in your function. It does not modify the integer in place.
Lists in python are mutable. You pass a list (by reference, as always in python), and the function changes it in place. That's why the change is "seen" externally to the function.
There is no such thing as "passing by value" in python.
What you probably want to do is return v+1 from your function, not to modify the value bound to the name v.
Because, lists are mutable but integers are immutable.
Read more about it here: http://docs.python.org/2/reference/datamodel.html#objects-values-and-types
Why does the variable L gets manipulated in the sorting(L) function call? In other languages, a copy of L would be passed through to sorting() as a copy so that any changes to x would not change the original variable?
def sorting(x):
A = x #Passed by reference?
A.sort()
def testScope():
L = [5,4,3,2,1]
sorting(L) #Passed by reference?
return L
>>> print testScope()
>>> [1, 2, 3, 4, 5]
Long story short: Python uses pass-by-value, but the things that are passed by value are references. The actual objects have 0 to infinity references pointing at them, and for purposes of mutating that object, it doesn't matter who you are and how you got a reference to the object.
Going through your example step by step:
L = [...] creates a list object somewhere in memory, the local variable L stores a reference to that object.
sorting (strictly speaking, the callable object pointed to be the global name sorting) gets called with a copy of the reference stored by L, and stores it in a local called x.
The method sort of the object pointed to by the reference contained in x is invoked. It gets a reference to the object (in the self parameter) as well. It somehow mutates that object (the object, not some reference to the object, which is merely more than a memory address).
Now, since references were copied, but not the object the references point to, all the other references we discussed still point to the same object. The one object that was modified "in-place".
testScope then returns another reference to that list object.
print uses it to request a string representation (calls the __str__ method) and outputs it. Since it's still the same object, of course it's printing the sorted list.
So whenever you pass an object anywhere, you share it with whoever recives it. Functions can (but usually won't) mutate the objects (pointed to by the references) they are passed, from calling mutating methods to assigning members. Note though that assigning a member is different from assigning a plain ol' name - which merely means mutating your local scope, not any of the caller's objects. So you can't mutate the caller's locals (this is why it's not pass-by-reference).
Further reading: A discussion on effbot.org why it's not pass-by-reference and not what most people would call pass-by-value.
Python has the concept of Mutable and Immutable objects. An object like a string or integer is immutable - every change you make creates a new string or integer.
Lists are mutable and can be manipulated in place. See below.
a = [1, 2, 3]
b = [1, 2, 3]
c = a
print a is b, a is c
# False True
print a, b, c
# [1, 2, 3] [1, 2, 3] [1, 2, 3]
a.reverse()
print a, b, c
# [3, 2, 1] [1, 2, 3] [3, 2, 1]
print a is b, a is c
# False True
Note how c was reversed, because c "is" a. There are many ways to copy a list to a new object in memory. An easy method is to slice: c = a[:]
It's specifically mentioned in the documentation the .sort() function mutates the collection. If you want to iterate over a sorted collection use sorted(L) instead. This provides a generator instead of just sorting the list.
a = 1
b = a
a = 2
print b
References are not the same as separate objects.
.sort() also mutates the collection.
folks, i got a question about passing mutable object to a function
with the following code, I was expecting the output to be [0,0,0], while the output is [0,1,2,3]
does it mean the argument is actually copied and then send to the inside of the function?
def lala(a):
n = [0, 0 , 0]
a = n
a = [0,1,2,3]
lala(a)
print a
if i want to fulfill the above task inside the function, how shall i write it elegantly?
thanks very much!
Python makes more sense if you think of attaching name tags to objects, rather than stuffing objects into named boxes.
def lala(a):
n = [0, 0 , 0]
a = n
Here's what's happening.
You're receiving a parameter (a list in this case) and giving it the name a.
You're creating a new list and giving it the name n.
You are giving the list you named n the additional name a.
Both names, a and n, are local to the lala function, so they "expire" when the function ends.
The list you created in the function now has no names, and Python discards it.
In other words, a is not a box into which you can put a new list. It is a name you gave a list you received. Later, you reassign that name to the list you have also named n.
Others have suggested a slice assignment, a[:] = n, which uses a reference to the items in the list rather than the list itself. When you do this, the name a still points to the same list; its contents have just been replaced. Since it is the same list that was passed into the function, any names by which it is known outside the function will "see" the new contents.
kindall provided a great explanation in my opinion, but my preferred method for doing something like this is to have the function return the change instead of messing with references.
def lala():
n = [0, 0, 0]
return n
a = [0, 1, 2, 3]
a = lala()
print a # prints [0, 0, 0]
you can use a[:] = n inside the function. this is called a slice assignment
python does not have a call-by-reference feature. There's no general way to do this.
If you know your argument is going to be a list, and you want it to take a different value, you can write it like so:
def lala(a):
a[:] = [0,0,0]
That's because a function makes new label "a" for its scope. Then this "a" overshadows the "a" you defined outside the function. So the new label a is assigned to new object [0,0,0,0]
If you would write:
def lala(a):
a.pop()
a = [0,1,2,3,4]
lala(a)
print(a)
You would see that a = [0,1,2,3] because pop() actually change the object which label 'a' points to. (while assignment just change to what object given label points to)
Note the difference between your function, and this one:
def lala(a):
a[0] = 7
a = [0,1,2,3]
lala(a)
print a # prints [7, 1, 2, 3]