Defaultdict is a container like dictionaries present in the module collections. Defaultdict is a sub-class of the dictionary class that returns a dictionary-like object. The functionality of both dictionaries and defaultdict are almost same except for the fact that defaultdict never raises a KeyError.
The main difference between defaultdict and dict is that when you try to access or modify a key that's not present in the dictionary, a default value is automatically given to that key . In order to provide this functionality, the Python defaultdict type does two things: It overrides .
defaultdict is faster for larger data sets with more homogenous key sets (ie, how short the dict is after adding elements);
Use:
from collections import defaultdict
d = defaultdict(lambda: defaultdict(int))
This will create a new defaultdict(int)
whenever a new key is accessed in d
.
Another way to make a pickleable, nested defaultdict is to use a partial object instead of a lambda:
from functools import partial
...
d = defaultdict(partial(defaultdict, int))
This will work because the defaultdict class is globally accessible at the module level:
"You can't pickle a partial object unless the function [or in this case, class] it wraps is globally accessible ... under its __name__ (within its __module__)" -- Pickling wrapped partial functions
Look at nosklo's answer here for a more general solution.
class AutoVivification(dict):
"""Implementation of perl's autovivification feature."""
def __getitem__(self, item):
try:
return dict.__getitem__(self, item)
except KeyError:
value = self[item] = type(self)()
return value
Testing:
a = AutoVivification()
a[1][2][3] = 4
a[1][3][3] = 5
a[1][2]['test'] = 6
print a
Output:
{1: {2: {'test': 6, 3: 4}, 3: {3: 5}}}
As per @rschwieb's request for D['key'] += 1
, we can expand on previous by overriding addition by defining __add__
method, to make this behave more like a collections.Counter()
First __missing__
will be called to create a new empty value, which will be passed into __add__
. We test the value, counting on empty values to be False
.
See emulating numeric types for more information on overriding.
from numbers import Number
class autovivify(dict):
def __missing__(self, key):
value = self[key] = type(self)()
return value
def __add__(self, x):
""" override addition for numeric types when self is empty """
if not self and isinstance(x, Number):
return x
raise ValueError
def __sub__(self, x):
if not self and isinstance(x, Number):
return -1 * x
raise ValueError
Examples:
>>> import autovivify
>>> a = autovivify.autovivify()
>>> a
{}
>>> a[2]
{}
>>> a
{2: {}}
>>> a[4] += 1
>>> a[5][3][2] -= 1
>>> a
{2: {}, 4: 1, 5: {3: {2: -1}}}
Rather than checking argument is a Number (very non-python, amirite!) we could just provide a default 0 value and then attempt the operation:
class av2(dict):
def __missing__(self, key):
value = self[key] = type(self)()
return value
def __add__(self, x):
""" override addition when self is empty """
if not self:
return 0 + x
raise ValueError
def __sub__(self, x):
""" override subtraction when self is empty """
if not self:
return 0 - x
raise ValueError
Late to the party, but for arbitrary depth I just found myself doing something like this:
from collections import defaultdict
class DeepDict(defaultdict):
def __call__(self):
return DeepDict(self.default_factory)
The trick here is basically to make the DeepDict
instance itself a valid factory for constructing missing values. Now we can do things like
dd = DeepDict(DeepDict(list))
dd[1][2].extend([3,4])
sum(dd[1][2]) # 7
ddd = DeepDict(DeepDict(DeepDict(list)))
ddd[1][2][3].extend([4,5])
sum(ddd[1][2][3]) # 9
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