# 5.2. Protocol Iterator¶

## 5.2.1. Rationale¶

• Used for iterating in a for loop

## 5.2.2. Protocol¶

• __iter__(self) -> self

• __next__(self) -> raise StopIteration

• iter(obj) -> obj.__iter__()

• next(obj) -> obj.__next__()

>>> class Iterator:
...     def __iter__(self):
...         self._current = 0
...         return self
...
...     def __next__(self):
...         if self._current >= len(self.values):
...             raise StopIteration
...         element = self.values[self._current]
...         self._current += 1
...         return element


## 5.2.3. Example¶

>>> class Crew:
...     def __init__(self):
...         self.members = list()
...
...         self.members.append(other)
...         return self
...
...     def __iter__(self):
...         self._current = 0
...         return self
...
...     def __next__(self):
...         if self._current >= len(self.members):
...             raise StopIteration
...         result = self.members[self._current]
...         self._current += 1
...         return result
>>>
>>>
>>> crew = Crew()
>>> crew += 'Mark Watney'
>>> crew += 'Jose Jimenez'
>>> crew += 'Melissa Lewis'
>>>
>>> for member in crew:
...     print(member)
Mark Watney
Jose Jimenez
Melissa Lewis


## 5.2.4. Loop and Iterators¶

For loop:

>>> DATA = [1, 2, 3]
>>>
>>> for current in DATA:
...     print(current)
1
2
3


Intuitive implementation of the for loop:

>>> DATA = [1, 2, 3]
>>> iterator = iter(DATA)
>>>
>>> try:
...     current = next(iterator)
...     print(current)
...
...     current = next(iterator)
...     print(current)
...
...     current = next(iterator)
...     print(current)
...
...     current = next(iterator)
...     print(current)
... except StopIteration:
...     pass
1
2
3


Intuitive implementation of the for loop:

>>> DATA = [1, 2, 3]
>>> iterator = DATA.__iter__()
>>>
>>> try:
...     current = iterator.__next__()
...     print(current)
...
...     current = iterator.__next__()
...     print(current)
...
...     current = iterator.__next__()
...     print(current)
...
...     current = iterator.__next__()
...     print(current)
... except StopIteration:
...     pass
1
2
3


## 5.2.5. Built-in Type Iteration¶

Iterating str:

>>> for character in 'hello':
...     print(character)
h
e
l
l
o


Iterating sequences:

>>> for number in [1, 2, 3]:
...     print(number)
1
2
3


Iterating dict:

>>> DATA = {'a': 1, 'b': 2, 'c': 3}
>>>
>>> for element in DATA:
...     print(element)
a
b
c


Iterating dict:

>>> for key, value in DATA.items():
...     print(f'{key} -> {value}')
a -> 1
b -> 2
c -> 3


Iterating nested sequences:

>>> for key, value in [('a',1), ('b',2), ('c',3)]:
...     print(f'{key} -> {value}')
a -> 1
b -> 2
c -> 3


## 5.2.6. Use Cases¶

Iterator implementation:

>>> class Parking:
...     def __init__(self):
...         self._parked_cars = list()
...
...     def park(self, car):
...         self._parked_cars.append(car)
...
...     def __iter__(self):
...         self._current = 0
...         return self
...
...     def __next__(self):
...         if self._current >= len(self._parked_cars):
...             raise StopIteration
...         element = self._parked_cars[self._current]
...         self._current += 1
...         return element
>>>
>>>
>>> parking = Parking()
>>> parking.park('Mercedes')
>>> parking.park('Maluch')
>>> parking.park('Toyota')
>>>
>>> for car in parking:
...     print(car)
Mercedes
Maluch
Toyota


## 5.2.7. Standard Library Itertools¶

itertools.count(start=0, step=1):

>>> from itertools import count
>>>
>>>
>>> data = count(3, 2)
>>>
>>> next(data)
3
>>> next(data)
5
>>> next(data)
7


itertools.cycle(iterable):

>>> from itertools import cycle
>>>
>>>
>>> data = cycle(['white', 'gray'])
>>>
>>> next(data)
'white'
>>> next(data)
'gray'
>>> next(data)
'white'
>>> next(data)
'gray'


itertools.cycle(iterable):

>>> from itertools import cycle
>>>
>>>
>>> for i, status in enumerate(cycle(['even', 'odd'])):  # doctest + SKIP
...     print(i, status)
...     if i == 3:
...         break
0 even
1 odd
2 even
3 odd


itertools.repeat(object[, times]):

>>> from itertools import repeat
>>>
>>>
>>> data = repeat('Beetlejuice', 3)
>>>
>>> next(data)
'Beetlejuice'
>>> next(data)
'Beetlejuice'
>>> next(data)
'Beetlejuice'
>>> next(data)
Traceback (most recent call last):
StopIteration


itertools.accumulate(iterable[, func, *, initial=None]):

>>> from itertools import accumulate
>>>
>>>
>>> data = accumulate([1, 2, 3, 4])
>>>
>>> next(data)
1
>>> next(data)
3
>>> next(data)
6
>>> next(data)
10
>>> next(data)
Traceback (most recent call last):
StopIteration


itertools.chain(*iterables):

>>> from itertools import chain
>>>
>>>
>>> keys = ['a', 'b', 'c']
>>> values = [1, 2, 3]
>>>
>>> for x in chain(keys, values):
...     print(x)
a
b
c
1
2
3


itertools.chain(*iterables):

>>> from itertools import chain
>>>
>>>
>>> class Iterator:
...     def __iter__(self):
...         self._current = 0
...         return self
...
...     def __next__(self):
...         if self._current >= len(self.values):
...             raise StopIteration
...         element = self.values[self._current]
...         self._current += 1
...         return element
>>>
>>>
>>> class Character(Iterator):
...     def __init__(self, *values):
...         self.values = values
>>>
>>>
>>> class Number(Iterator):
...     def __init__(self, *values):
...         self.values = values
>>>
>>>
>>> chars = Character('a', 'b', 'c')
>>> nums = Number(1, 2, 3)
>>> data = chain(chars, nums)
>>> next(data)
'a'
>>> next(data)
'b'
>>> next(data)
'c'
>>> next(data)
1
>>> next(data)
2
>>> next(data)
3


itertools.compress(data, selectors):

>>> from itertools import compress
>>>
>>>
>>> # data = compress('ABCDEF', [1,0,1,0,1,1])
>>> data = compress('ABCDEF', [True, False, True, False, True, True])
>>>
>>> next(data)
'A'
>>> next(data)
'C'
>>> next(data)
'E'
>>> next(data)
'F'
>>> next(data)
Traceback (most recent call last):
StopIteration


itertools.islice(iterable, start, stop[, step]):

>>> from itertools import islice
>>>
>>>
>>> data = islice('ABCDEFG', 2, 6, 2 )
>>>
>>> next(data)
'C'
>>> next(data)
'E'
>>> next(data)
Traceback (most recent call last):
StopIteration


itertools.starmap(function, iterable):

>>> from itertools import starmap
>>>
>>>
>>> data = starmap(pow, [(2,5), (3,2), (10,3)])
>>>
>>> next(data)
32
>>> next(data)
9
>>> next(data)
1000
>>> next(data)
Traceback (most recent call last):
StopIteration


itertools.product(*iterables, repeat=1):

>>> from itertools import product
>>>
>>>
>>> data = product(['a', 'b', 'c'], [1,2])
>>>
>>> next(data)
('a', 1)
>>> next(data)
('a', 2)
>>> next(data)
('b', 1)
>>> next(data)
('b', 2)
>>> next(data)
('c', 1)
>>> next(data)
('c', 2)
>>> next(data)
Traceback (most recent call last):
StopIteration


itertools.permutations(iterable, r=None):

>>> from itertools import permutations
>>>
>>>
>>> data = permutations([1,2,3])
>>>
>>> next(data)
(1, 2, 3)
>>> next(data)
(1, 3, 2)
>>> next(data)
(2, 1, 3)
>>> next(data)
(2, 3, 1)
>>> next(data)
(3, 1, 2)
>>> next(data)
(3, 2, 1)
>>> next(data)
Traceback (most recent call last):
StopIteration


itertools.combinations(iterable, r):

>>> from itertools import combinations
>>>
>>>
>>> data = combinations([1, 2, 3, 4], 2)
>>>
>>> next(data)
(1, 2)
>>> next(data)
(1, 3)
>>> next(data)
(1, 4)
>>> next(data)
(2, 3)
>>> next(data)
(2, 4)
>>> next(data)
(3, 4)
>>> next(data)
Traceback (most recent call last):
StopIteration


itertools.combinations_with_replacement(iterable, r):

>>> from itertools import combinations_with_replacement
>>>
>>>
>>> data = combinations_with_replacement([1,2,3], 2)
>>>
>>> next(data)
(1, 1)
>>> next(data)
(1, 2)
>>> next(data)
(1, 3)
>>> next(data)
(2, 2)
>>> next(data)
(2, 3)
>>> next(data)
(3, 3)
>>> next(data)
Traceback (most recent call last):
StopIteration


itertools.groupby(iterable, key=None). Make an iterator that returns consecutive keys and groups from the iterable. Generally, the iterable needs to already be sorted on the same key function. The operation of groupby() is similar to the uniq filter in Unix. It generates a break or new group every time the value of the key function changes. That behavior differs from SQL’s GROUP BY which aggregates common elements regardless of their input order:

>>> from itertools import groupby
>>>
>>>
>>> data = groupby('AAAABBBCCDAABBB')
>>>
>>> next(data)
('A', <itertools._grouper object at 0x...>)
>>> next(data)
('B', <itertools._grouper object at 0x...>)
>>> next(data)
('C', <itertools._grouper object at 0x...>)
>>> next(data)
('D', <itertools._grouper object at 0x...>)
>>> next(data)
('A', <itertools._grouper object at 0x...>)
>>> next(data)
('B', <itertools._grouper object at 0x...>)
>>> next(data)
Traceback (most recent call last):
StopIteration
>>> [k for k, g in groupby('AAAABBBCCDAABBB')]
['A', 'B', 'C', 'D', 'A', 'B']
>>> [list(g) for k, g in groupby('AAAABBBCCD')]
[['A', 'A', 'A', 'A'], ['B', 'B', 'B'], ['C', 'C'], ['D']]


## 5.2.8. Assignments¶

"""
* Assignment: Protocol Iterator Implementation
* Complexity: easy
* Lines of code: 14 lines
* Time: 8 min

English:
1. Modify classes to implement iterator protocol
2. Iterator should return instances of Mission
3. Run doctests - all must succeed

Polish:
1. Zmodyfikuj klasy aby zaimplementować protokół iterator
2. Iterator powinien zwracać instancje Mission
3. Uruchom doctesty - wszystkie muszą się powieść

Tests:
>>> import sys; sys.tracebacklimit = 0
>>> from inspect import isclass, ismethod

>>> assert isclass(Astronaut)

>>> astro = Astronaut('Mark', 'Watney')
>>> assert hasattr(astro, 'firstname')
>>> assert hasattr(astro, 'lastname')
>>> assert hasattr(astro, 'missions')
>>> assert hasattr(astro, '__iter__')
>>> assert hasattr(astro, '__next__')
>>> assert ismethod(astro.__iter__)
>>> assert ismethod(astro.__next__)

>>> astro = Astronaut('Jan', 'Twardowski', missions=(
...     Mission(1969, 'Apollo 11'),
...     Mission(2024, 'Artemis 3'),
...     Mission(2035, 'Ares 3'),
... ))

>>> for mission in astro:
...     print(mission)
Mission(year=1969, name='Apollo 11')
Mission(year=2024, name='Artemis 3')
Mission(year=2035, name='Ares 3')
"""

from dataclasses import dataclass

@dataclass
class Astronaut:
firstname: str
lastname: str
missions: tuple = ()

@dataclass
class Mission:
year: int
name: str


"""
* Assignment: Protocol Iterator Range
* Complexity: medium
* Lines of code: 14 lines
* Time: 8 min

English:
1. Modify class Range to write own implementation
of a built-in range(start, stop, step) function
2. Assume, that user will never give only one argument;
it will always be either two or three arguments
3. Use Iterator protocol
4. Run doctests - all must succeed

Polish:
1. Zmodyfikuj klasę Range aby napisać własną implementację
wbudowanej funkcji range(start, stop, step)
2. Przyjmij, że użytkownik nigdy nie poda tylko jednego argumentu;
zawsze będą to dwa lub trzy argumenty
3. Użyj protokołu Iterator
4. Uruchom doctesty - wszystkie muszą się powieść

Tests:
>>> import sys; sys.tracebacklimit = 0
>>> from inspect import isclass, ismethod

>>> assert isclass(Range)

>>> r = Range(0, 0, 0)
>>> assert hasattr(r, '__iter__')
>>> assert hasattr(r, '__next__')
>>> assert ismethod(r.__iter__)
>>> assert ismethod(r.__next__)

>>> list(Range(0, 10, 2))
[0, 2, 4, 6, 8]

>>> list(Range(0, 5))
[0, 1, 2, 3, 4]
"""
from dataclasses import dataclass

@dataclass
class Range:
start: int = 0
stop: int = None
step: int = 1