Why do we need tuples in Python (or any immutable data type)?

Question

I've read several python tutorials (Dive Into Python, for one), and the language reference on Python.org - I don't see why the language needs tuples.

Tuples have no methods compared to a list or set, and if I must convert a tuple to a set or list to be able to sort them, what's the point of using a tuple in the first place?

Immutability?

Why does anyone care if a variable lives at a different place in memory than when it was originally allocated? This whole business of immutability in Python seems to be over emphasized.

In C/C++ if I allocate a pointer and point to some valid memory, I don't care where the address is located as long as it's not null before I use it.

Whenever I reference that variable, I don't need to know if the pointer is still pointing to the original address or not. I just check for null and use it (or not).

In Python, when I allocate a string (or tuple) assign it to x, then modify the string, why do I care if it's the original object? As long as the variable points to my data, that's all that matters.

>>> x='hello'
>>> id(x)
1234567
>>> x='good bye'
>>> id(x)
5432167

x still references the data I want, why does anyone need to care if its id is the same or different?

Answer 1

1. immutable objects can allow substantial optimization; this is presumably why strings are also immutable in Java, developed quite separately but about the same time as Python, and just about everything is immutable in truly-functional languages.

2. in Python in particular, only immutables can be hashable (and, therefore, members of sets, or keys in dictionaries). Again, this afford optimization, but far more than just "substantial" (designing decent hash tables storing completely mutable objects is a nightmare -- either you take copies of everything as soon as you hash it, or the nightmare of checking whether the object's hash has changed since you last took a reference to it rears its ugly head).

Example of optimization issue:

$ python -mtimeit '["fee", "fie", "fo", "fum"]'
1000000 loops, best of 3: 0.432 usec per loop
$ python -mtimeit '("fee", "fie", "fo", "fum")'
10000000 loops, best of 3: 0.0563 usec per loop