Good evening Bill,
If I have a list defined as my_list = ['a','b','c'], what is the
is differnce between refering to it as my_list or my_list[:]?
These seem equivalent to me. Is that the case? Is there any
nuance I am missing here? Situations where one form should be
used as opposed to the other?
Yes, there is a difference. It can (conceivably) by subtle, but it
is simple.
Let's start with the following. I will call the list by the
variable name l. So, Python ('the computer') has stored the list in
memory. After executing this command, if I want to retrieve that
data, I can call it by the variable named 'l':
l = ['a', 'b', 'c']
Now consider the following two statements.
case A: k = l
case B: m = l[:]
These perform two different operations. The first simply says "Hey,
when I refer to variable k, I want it to behave exactly like I had
used the variable named l." The second says "Please give me a COPY
of everything contained in the variable named l and let me refer to
that as the variable named m."
What is the nuance of difference? Where are the data stored in
memory? Let's take case A:
>>> l = ['a', 'b', 'c']
>>> k = l
>>> k == l
True
>>> k is l
True
So, you see, not only are k and l refer to the same list contents,
but they point to the same place in computer memory where the list
is stored. The variables named l and k are just different names for
the same thing (data).
Now, let's see what happens when we use case B, copying the list
(strictly speaking you are slicing the entire list, see Python
documentation).
>>> m = l[:]
>>> m == l
True
>>> m is l
False
What's different here? Well, the variables m and l have the same
contents, and are therefore equal (this will compare all elements of
the list for equality). But, m and l are not the same thing (data)!
Though they contain the same data, the list contents are stored in
different places in computer memory.
This subtlety means that you probably do not want to say my_list[:]
unless you really want to use up all the memory to store the same
data twice. You may wish to do that, but given your question about
nuance, I would point out that this is no nuance but a significant
feature which can surprise you later if you do not understand what
is happening with the slicing notation.
Best of luck and enjoy a fried slice of Python!
-Martin
[0]
https://docs.python.org/3/library/stdtypes.html#sequence-types-list-tuple-range
--
Martin A. Brown
http://linux-ip.net/
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