List VS Tuple, When to Use Each

List vs tuple, when to use each?

There's a strong culture of tuples being for heterogeneous collections, similar to what you'd use structs for in C, and lists being for homogeneous collections, similar to what you'd use arrays for. But I've never quite squared this with the mutability issue mentioned in the other answers. Mutability has teeth to it (you actually can't change a tuple), while homogeneity is not enforced, and so seems to be a much less interesting distinction.

Lists vs. Tuples - What to use and when?

You've already given a pretty good summary of the differences, so in any conditions where one of those things is important it should help you decide on which to use.

The way to think about it is that Lists are open-ended data structures and their size can vary at runtime while Tuples have a constant size set at compile time.

For example if you wanted to store all the commands the user has given during an iex session you would want a list - the length of that list will depend on the number of commands given in that session. Contrast this with a typical use-case for tuples - returning {:ok, result} or {:error, reason} from a method - here the number of elements is known up-front and so you don't pay an unacceptable price for the performance improvements of Tuples.

As for enumeration - Tuples conceptually aren't collections and every element's position is supposed to also denote its role. Consider an {:ok, #PID<0.336.0>} Tuple - iterating over it would first give you an :ok and then a #PID<0.336.0>, it would be very strange to write a function acting in a uniform way on those things.

What's the difference between lists and tuples?

Apart from tuples being immutable there is also a semantic distinction that should guide their usage. Tuples are heterogeneous data structures (i.e., their entries have different meanings), while lists are homogeneous sequences. Tuples have structure, lists have order.

Using this distinction makes code more explicit and understandable.

One example would be pairs of page and line number to reference locations in a book, e.g.:

my_location = (42, 11)  # page number, line number

You can then use this as a key in a dictionary to store notes on locations. A list on the other hand could be used to store multiple locations. Naturally one might want to add or remove locations from the list, so it makes sense that lists are mutable. On the other hand it doesn't make sense to add or remove items from an existing location - hence tuples are immutable.

There might be situations where you want to change items within an existing location tuple, for example when iterating through the lines of a page. But tuple immutability forces you to create a new location tuple for each new value. This seems inconvenient on the face of it, but using immutable data like this is a cornerstone of value types and functional programming techniques, which can have substantial advantages.

There are some interesting articles on this issue, e.g. "Python Tuples are Not Just Constant Lists" or "Understanding tuples vs. lists in Python". The official Python documentation also mentions this

"Tuples are immutable, and usually contain an heterogeneous sequence ...".

In a statically typed language like Haskell the values in a tuple generally have different types and the length of the tuple must be fixed. In a list the values all have the same type and the length is not fixed. So the difference is very obvious.

Finally there is the namedtuple in Python, which makes sense because a tuple is already supposed to have structure. This underlines the idea that tuples are a light-weight alternative to classes and instances.

When to use Lists, Sets, Dictionaries, or tuples in python?

Lists are used when you have data you want to further modify, alter like sorting and all.

Dictionary is used when you have to sets of data where data of the first set corresponds to data of other set. And the position of the data doesn't matter only the relation of the two sets matters.

A tuple is used when position of the data is very important and you don't want to alter the position throughout.

in list VS in tuple condition in python

list and tuple both have an O(n) time complexity for x in container checks.

However, set have an O(1) for this check (most of the time, the worst case scenario will have a worse time complexity due to hash collisions).

See these timings for a list, tuple and a set with 1 million elements:

from timeit import Timer

li = list (range(1, 1000000))
t =  tuple(range(1, 1000000))
s =  set  (range(1, 1000000))

def x_in_list():
    999999 in li

def x_in_tuple():
    999999 in t

def x_in_set():
    999999 in s

print(min(Timer(x_in_list).repeat(5, 5)))
print(min(Timer(x_in_tuple).repeat(5, 5)))
print(min(Timer(x_in_set).repeat(5, 5)))

Outputs

0.08769642199999961
0.09637485699999981
9.329999999252436e-07

Are tuples more efficient than lists in Python?

The dis module disassembles the byte code for a function and is useful to see the difference between tuples and lists.

In this case, you can see that accessing an element generates identical code, but that assigning a tuple is much faster than assigning a list.

>>> def a():
...     x=[1,2,3,4,5]
...     y=x[2]
...
>>> def b():
...     x=(1,2,3,4,5)
...     y=x[2]
...
>>> import dis
>>> dis.dis(a)
  2           0 LOAD_CONST               1 (1)
              3 LOAD_CONST               2 (2)
              6 LOAD_CONST               3 (3)
              9 LOAD_CONST               4 (4)
             12 LOAD_CONST               5 (5)
             15 BUILD_LIST               5
             18 STORE_FAST               0 (x)

  3          21 LOAD_FAST                0 (x)
             24 LOAD_CONST               2 (2)
             27 BINARY_SUBSCR
             28 STORE_FAST               1 (y)
             31 LOAD_CONST               0 (None)
             34 RETURN_VALUE
>>> dis.dis(b)
  2           0 LOAD_CONST               6 ((1, 2, 3, 4, 5))
              3 STORE_FAST               0 (x)

  3           6 LOAD_FAST                0 (x)
              9 LOAD_CONST               2 (2)
             12 BINARY_SUBSCR
             13 STORE_FAST               1 (y)
             16 LOAD_CONST               0 (None)
             19 RETURN_VALUE

Is there a difference between a list and a tuple?

A tuple is just a finite list. All tuples are lists. All finite lists are tuples. Infinite lists are not tuples. All differences of typing and semantics are purely language dependent considerations.

Why is tuple faster than list in Python?

The reported "speed of construction" ratio only holds for constant tuples (ones whose items are expressed by literals). Observe carefully (and repeat on your machine -- you just need to type the commands at a shell/command window!)...:

$ python3.1 -mtimeit -s'x,y,z=1,2,3' '[x,y,z]'
1000000 loops, best of 3: 0.379 usec per loop
$ python3.1 -mtimeit '[1,2,3]'
1000000 loops, best of 3: 0.413 usec per loop

$ python3.1 -mtimeit -s'x,y,z=1,2,3' '(x,y,z)'
10000000 loops, best of 3: 0.174 usec per loop
$ python3.1 -mtimeit '(1,2,3)'
10000000 loops, best of 3: 0.0602 usec per loop

$ python2.6 -mtimeit -s'x,y,z=1,2,3' '[x,y,z]'
1000000 loops, best of 3: 0.352 usec per loop
$ python2.6 -mtimeit '[1,2,3]'
1000000 loops, best of 3: 0.358 usec per loop

$ python2.6 -mtimeit -s'x,y,z=1,2,3' '(x,y,z)'
10000000 loops, best of 3: 0.157 usec per loop
$ python2.6 -mtimeit '(1,2,3)'
10000000 loops, best of 3: 0.0527 usec per loop

I didn't do the measurements on 3.0 because of course I don't have it around -- it's totally obsolete and there is absolutely no reason to keep it around, since 3.1 is superior to it in every way (Python 2.7, if you can upgrade to it, measures as being almost 20% faster than 2.6 in each task -- and 2.6, as you see, is faster than 3.1 -- so, if you care seriously about performance, Python 2.7 is really the only release you should be going for!).

Anyway, the key point here is that, in each Python release, building a list out of constant literals is about the same speed, or slightly slower, than building it out of values referenced by variables; but tuples behave very differently -- building a tuple out of constant literals is typically three times as fast as building it out of values referenced by variables! You may wonder how this can be, right?-)

Answer: a tuple made out of constant literals can easily be identified by the Python compiler as being one, immutable constant literal itself: so it's essentially built just once, when the compiler turns the source into bytecodes, and stashed away in the "constants table" of the relevant function or module. When those bytecodes execute, they just need to recover the pre-built constant tuple -- hey presto!-)

This easy optimization cannot be applied to lists, because a list is a mutable object, so it's crucial that, if the same expression such as [1, 2, 3] executes twice (in a loop -- the timeit module makes the loop on your behalf;-), a fresh new list object is constructed anew each time -- and that construction (like the construction of a tuple when the compiler cannot trivially identify it as a compile-time constant and immutable object) does take a little while.

That being said, tuple construction (when both constructions actually have to
occur) still is about twice as fast as list construction -- and that discrepancy can be explained by the tuple's sheer simplicity, which other answers have mentioned repeatedly. But, that simplicity does not account for a speedup of six times or more, as you observe if you only compare the construction of lists and tuples with simple constant literals as their items!_)

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