Iterable Objects of Built-in Data Types

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∟Iterable Objects of Built-in Data Types

This section lists all built-in data types that can be used to create iterable objects.

As of Python 3.10, objects created from many built-in data types are iterable objects.

Here is an example Python code showing you iterable built-in data types. It uses the "collections" module to help testing whether an object is iterable or not.

herong$ more built-in-iterable.py
#  built-in-iterable.py
#- Copyright 2022 (c) HerongYang.com. All Rights Reserved.
#
from collections.abc import Iterable

o = bytes(b'\x41\x42\x43\x44')
print('bytes is iterable:', isinstance(o, Iterable))

o = bytearray(b'\x41\x42\x43\x44')
print('bytearray is iterable:', isinstance(o, Iterable))

o = memoryview(b'\x41\x42\x43\x44')
print('memoryview is iterable:', isinstance(o, Iterable))

o = str('ABCD')
print('str is iterable:', isinstance(o, Iterable))

o = tuple(['apple', 'orange'])
print('tuple is iterable:', isinstance(o, Iterable))

o = list(('apple', 'orange'))
print('list is iterable:', isinstance(o, Iterable))

o = dict(foo=100, bar=200)
print('dict is iterable:', isinstance(o, Iterable))

o = set(['apple', 'orange'])
print('set is iterable:', isinstance(o, Iterable))

o = frozenset(['apple', 'orange'])
print('frozenset is iterable:', isinstance(o, Iterable))


herong$ python built-in-iterable.py

bytes is iterable: True
bytearray is iterable: True
memoryview is iterable: True
str is iterable: True
tuple is iterable: True
list is iterable: True
dict is iterable: True
set is iterable: True
frozenset is iterable: True

"tuple" is a commonly used iterable data type. So let's see how it supports the iterable interface.

>>> t = tuple(range(5))
>>> i = iter(t)

>>> print("object t: id and type =", id(t), type(t))
object t: id and type = 4402847552 <class 'tuple'>

>>> print("object i: id and type =", id(i), type(i))
object i: id and type = 4402522912 <class 'tuple_iterator'>

>>> n = 0
>>> for x in t:
...    n += 1
...    print(x)
...    if n == 3: break
...
0
1
2

>>> n = 0
>>> for x in t:
...    n += 1
...    print(x)
...    if n == 3: break
...
0
1
2

Above output tells me that:

"tuple" object, t, is an iterable object. It supports the next(iterable) function.
next(tuple) returns an iterator object, i, of the "tuple_iterator" type.
You can use the "tuple" object, t, in a "for" loop directly.
Each time you use t in a "for" loop, a new iterator object will be created to let you iterate from the first element.

As an iterable object, "tuple" also has a less known behavior. Its iterator object is also an iterable object, see the example code below.

>>> t = tuple(range(5)
>>> i = iter(t)
>>> j = iter(i)

>>> print("object i: id and type =", id(i), type(i))
object i: id and type = 4402522912 <class 'tuple_iterator'>

>>> print("object j: id and type =", id(j), type(j))
object j: id and type = 4402522912 <class 'tuple_iterator'>

>>> i = iter(t)
>>> n = 0
>>> for x in i:
...    n += 1
...    print(x)
...    if n == 3: break
...
0
1
2

>>> n = 0
>>> for x in i:
...    n += 1
...    print(x)
...    if n == 3: break
...
3
4

Above output tells me that:

"tuple_iterator" object, i, is also an iterable object. It supports the next(iterable) function.
However, next(tuple_iterator) returns itself: i and j are referring to the same object.
You can use the "tuple_iterator" object, i, in a "for" loop directly.
Each time you use i in a "for" loop, the same iterator is used to iterate from the last item where the iterator was stopped.

By the way, Python standard actually requires that all "iterator" objects to implement the __iter__() method and return themselves. In other words, all "iterator" objects are special "iterable" objects. They can be used to iterate all items only in one round.