Python defaultdict and lambda

In someone else's code I read the following two lines:

x = defaultdict(lambda: 0)
y = defaultdict(lambda: defaultdict(lambda: 0))

As the argument of defaultdict is a default factory, I think the first line means that when I call x[k] for a nonexistent key k (such as a statement like v=x[k]), the key-value pair (k,0) will be automatically added to the dictionary, as if the statement x[k]=0 is first executed. Am I correct?

And what about y? It seems that the default factory will create a defaultdict with default 0. But what does that mean concretely? I tried to play around with it in Python shell, but couldn't figure out what it is exactly.

> I think the first line means that when I call x[k] for a nonexistent key k (such as a statement like v=x[k]), the key-value pair (k,0) will be automatically added to the dictionary, as if the statement x[k]=0 is first executed.

That's right. This is more idiomatically written

x = defaultdict(int)

In the case of y, when you do y["ham"]["spam"], the key "ham" is inserted in y if it does not exist. The value associated with it becomes a defaultdict in which "spam" is automatically inserted with a value of 0.

I.e., y is a kind of "two-tiered" defaultdict. If "ham" not in y, then evaluating y["ham"]["spam"] is like doing

y["ham"] = {}
y["ham"]["spam"] = 0

in terms of ordinary dict.

You are correct for what the first one does. As for y, it will create a defaultdict with default 0 when a key doesn't exist in y, so you can think of this as a nested dictionary. Consider the following example:

y = defaultdict(lambda: defaultdict(lambda: 0))
print y['k1']['k2']   # 0
print dict(y['k1'])   # {'k2': 0}

To create an equivalent nested dictionary structure without defaultdict you would need to create an inner dict for y['k1'] and then set y['k1']['k2'] to 0, but defaultdict does all of this behind the scenes when it encounters keys it hasn't seen:

y = {}
y['k1'] = {}
y['k1']['k2'] = 0

The following function may help for playing around with this on an interpreter to better your understanding:

def to_dict(d):
    if isinstance(d, defaultdict):
        return dict((k, to_dict(v)) for k, v in d.items())
    return d

This will return the dict equivalent of a nested defaultdict, which is a lot easier to read, for example:

>>> y = defaultdict(lambda: defaultdict(lambda: 0))
>>> y['a']['b'] = 5
>>> y
defaultdict(<function <lambda> at 0xb7ea93e4>, {'a': defaultdict(<function <lambda> at 0xb7ea9374>, {'b': 5})})
>>> to_dict(y)
{'a': {'b': 5}}

defaultdict takes a zero-argument callable to its constructor, which is called when the key is not found, as you correctly explained.

lambda: 0 will of course always return zero, but the preferred method to do that is defaultdict(int), which will do the same thing.

As for the second part, the author would like to create a new defaultdict(int), or a nested dictionary, whenever a key is not found in the top-level dictionary.

All answers are good enough still I am giving the answer to add more info:

"defaultdict requires an argument that is callable. That return result of that callable object is the default value that the dictionary returns when you try to access the dictionary with a key that does not exist."

Here's an example

SAMPLE= {'Age':28, 'Salary':2000}
SAMPLE = defaultdict(lambda:0,SAMPLE)

>>> SAMPLE
defaultdict(<function <lambda> at 0x0000000002BF7C88>, {'Salary': 2000, 'Age': 28})

>>> SAMPLE['Age']----> This will return 28
>>> SAMPLE['Phone']----> This will return 0   # you got 0 as output for a non existing key inside SAMPLE

y = defaultdict(lambda:defaultdict(lambda:0))

will be helpful if you try this y['a']['b'] += 1