Using list as the default_factory, it is easy to group a sequence of key-value pairs into a dictionary of lists:
>>> s = [('yellow', 1), ('blue', 2), ('yellow', 3), ('blue', 4), ('red', 1)] >>> d = defaultdict(list) >>> for k, v in s: d[k].append(v) >>> d.items() [('blue', [2, 4]), ('red', [1]), ('yellow', [1, 3])]
When each key is encountered for the first time, it is not already in the mapping; so an entry is automatically created using the default_factory function which returns an empty list. The list.append() operation then attaches the value to the new list. When keys are encountered again, the look-up proceeds normally (returning the list for that key) and the list.append() operation adds another value to the list. This technique is simpler and faster than an equivalent technique using dict.setdefault():
>>> d = {} >>> for k, v in s: d.setdefault(k, []).append(v) >>> d.items() [('blue', [2, 4]), ('red', [1]), ('yellow', [1, 3])]
Setting the default_factory to int makes the defaultdict useful for counting (like a bag or multiset in other languages):
>>> s = 'mississippi' >>> d = defaultdict(int) >>> for k in s: d[k] += 1 >>> d.items() [('i', 4), ('p', 2), ('s', 4), ('m', 1)]
When a letter is first encountered, it is missing from the mapping, so the default_factory function calls int() to supply a default count of zero. The increment operation then builds up the count for each letter. This technique makes counting simpler and faster than an equivalent technique using dict.get():
>>> d = {} >>> for k in s: d[k] = d.get(k, 0) + 1 >>> d.items() [('i', 4), ('p', 2), ('s', 4), ('m', 1)]
Setting the default_factory to set makes the defaultdict useful for building a dictionary of sets:
>>> s = [('red', 1), ('blue', 2), ('red', 3), ('blue', 4), ('red', 1), ('blue', 4)] >>> d = defaultdict(set) >>> for k, v in s: d[k].add(v) >>> d.items() [('blue', set([2, 4])), ('red', set([1, 3]))]