List - Copy vs. Alias

0. properties of <List>
0. memory model of list
0. List assignment
1. how to copy and make alias
2. passed as parameter (as a name only)
3. deep copy
4. as an iterator (for loop)
- looping over each element’s value (unchanged original)
- looping over list indices (changed original)

0. properties of <List>

mutable collection
mutable elements
ordered elements

0. memory model of list

Python Lists store reference to the objects.

Performance Notes
The list object consists of two internal parts; one object header, and one separately allocated array of object references. The latter is reallocated as necessary.

0. List assignment

When assign a list to a variable, the variable points the header of the list.

1. how to copy and make alias

Copy : independent (shallow copy)

mylist_copy = mylist[:]

Alias : dependent

mylist_alias = mylist

2. passed as parameter (as a name only)

Since function parameters are variables(just name), list parameters cause aliasing.

Changing the list inside the function also changes the original.

3. deep copy

If elements of copied list is mutable objects, changing one affects the other list. (shallow copy).

When a list is copied, ‘new header + new array of existing reference’ is created.
Thus if the elements of the original list is immutable, then no problem (totally independent).
But if the elements of the original list is mutable, then it’s dependent.

Thus if you need a totally independent copied list (deep copy), use copy.deepcopy. (reference)

4. as an iterator (`for` loop)

looping over each element’s value (unchanged original)

values = [10, 11, 12, 13, 14, 15]
for num in values:              # aliasing
    num = num * 2               # just reassignment
values

output :

[10, 11, 12, 13, 14, 15]        # no change

looping over list indices (changed original)

values = [10, 11, 12, 13, 14, 15]
for i in range(len(values)):
    values[i] = values[i] * 2   # direct access
values