If I understand correctly, in Python 2, iter(d.keys())
was the same as d.iterkeys()
. But now, d.keys()
is a view, which is in between the list and the iterator. What's the difference between a view and an iterator?
In other words, in Python 3, what's the difference between
for k in d.keys() f(k)
and
for k in iter(d.keys()) f(k)
Also, how do these differences show up in a simple for
loop (if at all)?
In Python, to iterate the dictionary ( dict ) with a for loop, use keys() , values() , items() methods. You can also get a list of all keys and values in the dictionary with those methods and list() . Use the following dictionary as an example. You can iterate keys by using the dictionary object directly in a for loop.
To iterate through the dictionary's keys, utilise the keys() method that is supplied by the dictionary. An iterable of the keys available in the dictionary is returned. Then, as seen below, you can cycle through the keys using a for loop.
You can loop through a dictionary by using a for loop. When looping through a dictionary, the return value are the keys of the dictionary, but there are methods to return the values as well.
I'm not sure if this is quite an answer to your questions but hopefully it explains a bit about the difference between Python 2 and 3 in this regard.
In Python 2, iter(d.keys())
and d.iterkeys()
are not quite equivalent, although they will behave the same. In the first, keys()
will return a copy of the dictionary's list of keys and iter
will then return an iterator object over this list, with the second a copy of the full list of keys is never built.
The view objects returned by d.keys()
in Python 3 are iterable (i.e. an iterator can be made from them) so when you say for k in d.keys()
Python will create the iterator for you. Therefore your two examples will behave the same.
The significance in the change of the return type for keys()
is that the Python 3 view object is dynamic. i.e. if we say ks = d.keys()
and later add to d
then ks
will reflect this. In Python 2, keys()
returns a list of all the keys currently in the dict. Compare:
Python 3
>>> d = { "first" : 1, "second" : 2 } >>> ks = d.keys() >>> ks dict_keys(['second', 'first']) >>> d["third"] = 3 >>> ks dict_keys(['second', 'third', 'first'])
Python 2.x
>>> d = { "first" : 1, "second" : 2 } >>> ks = d.keys() >>> ks ['second', 'first'] >>> d["third"] = 3 >>> ks ['second', 'first']
As Python 3's keys()
returns the dynamic object Python 3 doesn't have (and has no need for) a separate iterkeys
method.
Further clarification
In Python 3, keys()
returns a dict_keys
object but if we use it in a for
loop context for k in d.keys()
then an iterator is implicitly created. So the difference between for k in d.keys()
and for k in iter(d.keys())
is one of implicit vs. explicit creation of the iterator.
In terms of another difference, whilst they are both dynamic, remember if we create an explicit iterator then it can only be used once whereas the view can be reused as required. e.g.
>>> ks = d.keys() >>> 'first' in ks True >>> 'second' in ks True >>> i = iter(d.keys()) >>> 'first' in i True >>> 'second' in i False # because we've already reached the end of the iterator
Also, notice that if we create an explicit iterator and then modify the dict then the iterator is invalidated:
>>> i2 = iter(d.keys()) >>> d['fourth'] = 4 >>> for k in i2: print(k) ... Traceback (most recent call last): File "<stdin>", line 1, in <module> RuntimeError: dictionary changed size during iteration
In Python 2, given the existing behaviour of keys
a separate method was needed to provide a way to iterate without copying the list of keys whilst still maintaining backwards compatibility. Hence iterkeys()
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With