Is there any performance difference between tuples and lists when it comes to instantiation and retrieval of elements?
Tuples tend to perform better than lists in almost every category:
1) Tuples can be constant folded.
2) Tuples can be reused instead of copied.
3) Tuples are compact and don't over-allocate.
4) Tuples directly reference their elements.
Tuples of constants can be precomputed by Python's peephole optimizer or AST-optimizer. Lists, on the other hand, get built-up from scratch:
>>> from dis import dis
>>> dis(compile("(10, 'abc')", '', 'eval'))
1 0 LOAD_CONST 2 ((10, 'abc'))
3 RETURN_VALUE
>>> dis(compile("[10, 'abc']", '', 'eval'))
1 0 LOAD_CONST 0 (10)
3 LOAD_CONST 1 ('abc')
6 BUILD_LIST 2
9 RETURN_VALUE
Running tuple(some_tuple)
returns immediately itself. Since tuples are immutable, they do not have to be copied:
>>> a = (10, 20, 30)
>>> b = tuple(a)
>>> a is b
True
In contrast, list(some_list)
requires all the data to be copied to a new list:
>>> a = [10, 20, 30]
>>> b = list(a)
>>> a is b
False
Since a tuple's size is fixed, it can be stored more compactly than lists which need to over-allocate to make append() operations efficient.
This gives tuples a nice space advantage:
>>> import sys
>>> sys.getsizeof(tuple(iter(range(10))))
128
>>> sys.getsizeof(list(iter(range(10))))
200
Here is the comment from Objects/listobject.c that explains what lists are doing:
/* This over-allocates proportional to the list size, making room
* for additional growth. The over-allocation is mild, but is
* enough to give linear-time amortized behavior over a long
* sequence of appends() in the presence of a poorly-performing
* system realloc().
* The growth pattern is: 0, 4, 8, 16, 25, 35, 46, 58, 72, 88, ...
* Note: new_allocated won't overflow because the largest possible value
* is PY_SSIZE_T_MAX * (9 / 8) + 6 which always fits in a size_t.
*/
References to objects are incorporated directly in a tuple object. In contrast, lists have an extra layer of indirection to an external array of pointers.
This gives tuples a small speed advantage for indexed lookups and unpacking:
$ python3.6 -m timeit -s 'a = (10, 20, 30)' 'a[1]'
10000000 loops, best of 3: 0.0304 usec per loop
$ python3.6 -m timeit -s 'a = [10, 20, 30]' 'a[1]'
10000000 loops, best of 3: 0.0309 usec per loop
$ python3.6 -m timeit -s 'a = (10, 20, 30)' 'x, y, z = a'
10000000 loops, best of 3: 0.0249 usec per loop
$ python3.6 -m timeit -s 'a = [10, 20, 30]' 'x, y, z = a'
10000000 loops, best of 3: 0.0251 usec per loop
Here is how the tuple (10, 20)
is stored:
typedef struct {
Py_ssize_t ob_refcnt;
struct _typeobject *ob_type;
Py_ssize_t ob_size;
PyObject *ob_item[2]; /* store a pointer to 10 and a pointer to 20 */
} PyTupleObject;
Here is how the list [10, 20]
is stored:
PyObject arr[2]; /* store a pointer to 10 and a pointer to 20 */
typedef struct {
Py_ssize_t ob_refcnt;
struct _typeobject *ob_type;
Py_ssize_t ob_size;
PyObject **ob_item = arr; /* store a pointer to the two-pointer array */
Py_ssize_t allocated;
} PyListObject;
Note that the tuple object incorporates the two data pointers directly while the list object has an additional layer of indirection to an external array holding the two data pointers.