Better OrderedMultiDict provides two fast ordered multivalued dictionaries: OrderedMultiDict
and DeOrderedMultiDict
.
Multivalued means that there can be multiple items with the same key:
from better_orderedmultidict import OrderedMultiDict
dictionary = OrderedMultiDict()
dictionary.add("Schrödinger's cat", "dead")
dictionary.add("Schrödinger's cat", "alive")
print(dictionary.getall("Schrödinger's cat")) #["dead", "alive"]
Ordered means that the insertion order of all keys and values is retained:
from better_orderedmultidict import OrderedMultiDict
dictionary = OrderedMultiDict()
dictionary.add("Schrödinger's cat", "alive")
dictionary.add("Pavlov's dog", "conditioned")
dictionary.add("Schrödinger's cat", "dead")
print(list(dictionary.values())) # ["alive", "conditioned", "dead"]
print(list(dictionary.unique_keys())) # ["Schrödinger's cat", "Pavlov's dog"]
print(list(dictionary.keys())) # ["Schrödinger's cat", "Pavlov's dog", "Schrödinger's cat"]
dictionary.poplastitem()
print(list(dictionary.values())) # ["alive", "conditioned"]
print(list(dictionary.unique_keys())) # ["Schrödinger's cat", "Pavlov's dog"]
print(list(dictionary.keys())) # ["Schrödinger's cat", "Pavlov's dog"]
Better OrderedMultiDict requires Python 3.12+ and is fully type annotated.
Creating / iterating over dictionary with 500'000 entries with all keys being different:
OrderedMultiDict | omdict | speedup | boltons OrderedMultiDict |
speedup | ||
---|---|---|---|---|---|---|
create | 117.6 ms | 285.8 ms | 2.4x | 136.2 ms | 1.2x | |
addall / addlist | 67.4 ms | 158.2 ms | 2.3x | 66.6 ms | slower | |
update / updateall1) | 133.1 ms | 281.3 ms | 2.1x | 175.1 ms | 1.3x | |
extend / update_extend | 92.6 ms | -- | -- | 145.9 ms | 1.6x | |
copy | 52.3 ms | 335.7 ms | 6.4x | 195.7 ms | 3.7x | |
iterate over items | 2.2 ms | 45.2 ms | 20.3x | 46.2 ms | 20.8x | |
iterate over values | 5.7 ms | 33.5 ms | 5.8x | 33.1 ms | 5.8x | |
iterate over keys | 5.8 ms | 33.3 ms | 5.8x | 15.8 ms | 2.7x | |
iterate over unique keys | 16.5 ms | 5.8 ms | slower | 32.0 ms | 1.9x | |
pop last item until empty | 138.0 ms | 242.6 ms | 1.8x | 403.4 ms | 2.9x |
Creating / iterating over dictionary with 500'000 entries, but only 100 unique keys distributed randomly:
OrderedMultiDict | omdict | speedup | boltons OrderedMultiDict |
speedup | ||
---|---|---|---|---|---|---|
create | 46.7 ms | 249.2 ms | 5.3x | 120.9 ms | 2.6x | |
addall / addlist | 59.6 ms | 156.9 ms | 2.6x | 67.3 ms | 1.1x | |
update / updateall1) | 53.0 ms | 250.5 ms | 4.7x | 116.0 ms | 2.2x | |
extend / update_extend | 51.0 ms | -- | -- | 117.5 ms | 2.3x | |
copy | 9.1 ms | 281.6 ms | 30.8x | 133.9 ms | 14.6x | |
iterate over items | 2.5 ms | 44.0 ms | 17.7x | 29.7 ms | 11.9x | |
iterate over values | 7.3 ms | 31.3 ms | 4.3x | 31.3 ms | 4.3x | |
iterate over keys | 11.9 ms | 31.0 ms | 2.6x | 18.1 ms | 1.5x | |
iterate over unique keys | 18.2 ms | < 0.1 ms | slower | 19.0 ms | 1.0x | |
pop last item until empty | 110.0 ms | 215.1 ms | 2.0x | 163.3 ms | 1.5x |
1): omdict. updateall()
has slightly different behavior: omdict
keeps the positions for already existing keys, but OrderedMultiDict
and bolton's OrderedMultiDict
do not:
from better_orderedmultidict import OrderedMultiDict
from orderedmultidict import omdict
initial = [(1, 1), (2, 2), (1, 11), (2, 22), (3, 3)]
omd1 = OrderedMultiDict(initial)
omd2 = omdict(initial)
updates = [(1, '1'), (1, '11')]
omd1.update(updates)
omd2.updateall(updates)
print(list(omd1.items())) # [(2, 2), (2, 22), (3, '3'), (1, '1'), (1, '11')]
print(list(omd2.iterallitems())) # [(1, '1'), (2, 2), (1, '11'), (2, 22), (3, '3')]
Both provide the same API, but have slightly different performance characteristics:
OrderedMultiDict
is generally about 1.5x - 4x faster and uses a lot less memory per unique key. But method.popfirstitem()
has linear performance characteristics O(n)DeOrderedMultiDict
is generally slower and uses a lot more memory per unique key. But method.popfirstitem()
has constant performance characteristics O(1)
Creating / iterating over dictionary with 500000 entries with all keys being different:
OrderedMultiDict | DeOrderedMultiDict | OrderedMultiDict is faster: |
|
---|---|---|---|
create | 101.8 ms | 161.4 ms | 1.6x |
copy | 51.9 ms | 146.8 ms | 2.8x |
iterate over items | 2.2 ms | 10.3 ms | 4.6x |
iterate over unique keys | 15.4 ms | 23.4 ms | 1.5x |
pop first item until empty | 38.7 s (!) | 194.9 ms | >190x slower |
pop last item until empty | 143.2 ms | 180.3 ms | 1.3x |
from better_orderedmultidict import OrderedMultiDict
omd = OrderedMultiDict()
omd[1] = 1
print(omd[1]) # prints: 1
omd.add(1, 11)
print(omd[1]) # prints: 11
print(omd.get(1)) # prints: 11
print(omd.getlast(1)) # prints: 11
print(omd.getfirst(1)) # prints: 1
print(omd.getall(1)) # prints: [1, 11]
# adding multiple values at once:
omd.addall(2, [2, 22])
print(omd.getall(2)) # prints: [2, 22]
# __setitem__ overrides all existing entries for the given key:
omd[1] = 111
print(list(omd.values())) # prints: [2, 22, 111]
from better_orderedmultidict import OrderedMultiDict
omd = OrderedMultiDict()
omd.addall(1, [1, 11])
omd.add(2, 2)
omd.add(3, 3)
omd.add(2, 22)
omd.add(3, 33)
omd.add(1, 111)
print(omd.getall(1)) # prints: [1, 11, 111]
print(list(omd.values())) # prints: [1, 11, 2, 3, 22, 33, 111]
del omd[2]
print(list(omd.values())) # prints: [1, 11, 3, 33, 111]
omd.popfirst(3)
print(list(omd.values())) # prints: [1, 11, 33, 111]
omd.poplast(1)
print(list(omd.values())) # prints: [1, 11, 33]
omd.poplast(1)
print(list(omd.values())) # prints: [1, 33]
from better_orderedmultidict import OrderedMultiDict
d, omd = dict(), OrderedMultiDict()
d.update([(1,1), (1,11), (2,2), (2,22)])
omd.update([(1,1), (1,11), (2,2), (2,22)])
print(d[1], omd[1]) # prints: (11, 11)
d[3] = omd[3] = 3
print(d[3], omd[3]) # prints: (3, 3)
d[3] = omd[3] = 33
print(d[3], omd[3]) # prints: (33, 33)
# But there are differences:
print(len(d), len(omd)) # prints: (3, 5)
d.pop(2)
omd.pop(2)
print(d.get(2), omd.get(2)) # prints: (None, 2)
from better_orderedmultidict import OrderedMultiDict
omd = OrderedMultiDict([(1,1), (2,2), (1,11), (2,22)])
print(len(omd.keys())) # prints: 4
print(len(omd.unique_keys())) # prints: 2
for key in reversed(omd.unique_keys()):
print(f"{key}: {omd.getall(key)}")
# prints:
# 1: [1, 11]
# 2: [2, 22]
Installation is simple:
$ pip install better_orderedmultidict
See CHANGES.md.