[python] How to implement __iter__(self) for a container object (Python)

I have written a custom container object.

According to this page, I need to implement this method on my object:

__iter__(self)

However, upon following up the link to Iterator Types in the Python reference manual, there are no examples given of how to implement your own.

Can someone post a snippet (or link to a resource), that shows how to do this?

The container I am writing, is a map (i.e. stores values by unique keys). dicts can be iterated like this:

for k, v in mydict.items()

In this case I need to be able to return two elements (a tuple?) in the iterator. It is still not clear how to implement such an iterator (despite the several answers that have been kindly provided). Could someone please shed some more light on how to implement an iterator for a map-like container object? (i.e. a custom class that acts like a dict)?

I normally would use a generator function. Each time you use a yield statement, it will add an item to the sequence.

The following will create an iterator that yields five, and then every item in some_list.

def __iter__(self):
   yield 5
   yield from some_list

Pre-3.3, yield from didn't exist, so you would have to do:

def __iter__(self):
   yield 5
   for x in some_list:
      yield x

example for inhert from dict, modify its iter, for example, skip key 2 when in for loop

# method 1
class Dict(dict):
    def __iter__(self):
        keys = self.keys()
        for i in keys:
            if i == 2:
                continue
            yield i

# method 2
class Dict(dict):
    def __iter__(self):
        for i in super(Dict, self).__iter__():
            if i == 2:
                continue
            yield i

Another option is to inherit from the appropriate abstract base class from the `collections module as documented here.

In case the container is its own iterator, you can inherit from collections.Iterator. You only need to implement the next method then.

An example is:

>>> from collections import Iterator
>>> class MyContainer(Iterator):
...     def __init__(self, *data):
...         self.data = list(data)
...     def next(self):
...         if not self.data:
...             raise StopIteration
...         return self.data.pop()
...         
...     
... 
>>> c = MyContainer(1, "two", 3, 4.0)
>>> for i in c:
...     print i
...     
... 
4.0
3
two
1

While you are looking at the collections module, consider inheriting from Sequence, Mapping or another abstract base class if that is more appropriate. Here is an example for a Sequence subclass:

>>> from collections import Sequence
>>> class MyContainer(Sequence):
...     def __init__(self, *data):
...         self.data = list(data)
...     def __getitem__(self, index):
...         return self.data[index]
...     def __len__(self):
...         return len(self.data)
...         
...     
... 
>>> c = MyContainer(1, "two", 3, 4.0)
>>> for i in c:
...     print i
...     
... 
1
two
3
4.0

NB: Thanks to Glenn Maynard for drawing my attention to the need to clarify the difference between iterators on the one hand and containers that are iterables rather than iterators on the other.

In case you don't want to inherit from dict as others have suggested, here is direct answer to the question on how to implement __iter__ for a crude example of a custom dict:

class Attribute:
    def __init__(self, key, value):
        self.key = key
        self.value = value

class Node(collections.Mapping):
    def __init__(self):
        self.type  = ""
        self.attrs = [] # List of Attributes

    def __iter__(self):
        for attr in self.attrs:
            yield attr.key

That uses a generator, which is well described here.

Since we're inheriting from Mapping, you need to also implement __getitem__ and __len__:

    def __getitem__(self, key):
        for attr in self.attrs:
            if key == attr.key:
                return attr.value
        raise KeyError

    def __len__(self):
        return len(self.attrs)

usually __iter__() just return self if you have already define the next() method (generator object):

here is a Dummy example of a generator :

class Test(object):

    def __init__(self, data):
       self.data = data

    def next(self):
        if not self.data:
           raise StopIteration
        return self.data.pop()

    def __iter__(self):
        return self

but __iter__() can also be used like this: http://mail.python.org/pipermail/tutor/2006-January/044455.html

One option that might work for some cases is to make your custom class inherit from dict. This seems like a logical choice if it acts like a dict; maybe it should be a dict. This way, you get dict-like iteration for free.

class MyDict(dict):
    def __init__(self, custom_attribute):
        self.bar = custom_attribute

mydict = MyDict('Some name')
mydict['a'] = 1
mydict['b'] = 2

print mydict.bar
for k, v in mydict.items():
    print k, '=>', v

Output:

Some name
a => 1
b => 2

To answer the question about mappings: your provided __iter__ should iterate over the keys of the mapping. The following is a simple example that creates a mapping x -> x * x and works on Python3 extending the ABC mapping.

import collections.abc

class MyMap(collections.abc.Mapping):
    def __init__(self, n):
        self.n = n

    def __getitem__(self, key): # given a key, return it's value
        if 0 <= key < self.n:
            return key * key
        else:
            raise KeyError('Invalid key')

    def __iter__(self): # iterate over all keys
        for x in range(self.n):
            yield x

    def __len__(self):
        return self.n

m = MyMap(5)
for k, v in m.items():
    print(k, '->', v)
# 0 -> 0
# 1 -> 1
# 2 -> 4
# 3 -> 9
# 4 -> 16

If your object contains a set of data you want to bind your object's iter to, you can cheat and do this:

>>> class foo:
    def __init__(self, *params):
           self.data = params
    def __iter__(self):
        if hasattr(self.data[0], "__iter__"):
            return self.data[0].__iter__()
        return self.data.__iter__()
>>> d=foo(6,7,3,8, "ads", 6)
>>> for i in d:
    print i
6
7
3
8
ads
6

The "iterable interface" in python consists of two methods __next__() and __iter__(). The __next__ function is the most important, as it defines the iterator behavior - that is, the function determines what value should be returned next. The __iter__() method is used to reset the starting point of the iteration. Often, you will find that __iter__() can just return self when __init__() is used to set the starting point.

See the following code for defining a Class Reverse which implements the "iterable interface" and defines an iterator over any instance from any sequence class. The __next__() method starts at the end of the sequence and returns values in reverse order of the sequence. Note that instances from a class implementing the "sequence interface" must define a __len__() and a __getitem__() method.

class Reverse:
    """Iterator for looping over a sequence backwards."""
    def __init__(self, seq):
        self.data = seq
        self.index = len(seq)

    def __iter__(self):
        return self

    def __next__(self):
        if self.index == 0:
            raise StopIteration
        self.index = self.index - 1
        return self.data[self.index]

>>> rev = Reverse('spam')
>>> next(rev)   # note no need to call iter()
'm'
>>> nums = Reverse(range(1,10))
>>> next(nums)
9