Dictionaries are ordered in Python 3.6 (under the CPython implementation at least) unlike in previous incarnations. This seems like a substantial change, but it's only a short paragraph in the documentation. It is described as a CPython implementation detail rather than a language feature, but also implies this may become standard in the future.
How does the new dictionary implementation perform better than the older one while preserving element order?
Here is the text from the documentation:
dict()
now uses a “compact” representation pioneered by PyPy. The memory usage of the new dict() is between 20% and 25% smaller compared to Python 3.5. PEP 468 (Preserving the order of **kwargs in a function.) is implemented by this. The order-preserving aspect of this new implementation is considered an implementation detail and should not be relied upon (this may change in the future, but it is desired to have this new dict implementation in the language for a few releases before changing the language spec to mandate order-preserving semantics for all current and future Python implementations; this also helps preserve backwards-compatibility with older versions of the language where random iteration order is still in effect, e.g. Python 3.5). (Contributed by INADA Naoki in issue 27350. Idea originally suggested by Raymond Hettinger.)
Update December 2017: dict
s retaining insertion order is guaranteed for Python 3.7
They are insertion ordered[1]. As of Python 3.6, for the CPython implementation of Python, dictionaries remember the order of items inserted. This is considered an implementation detail in Python 3.6; you need to use
OrderedDict
if you want insertion ordering that's guaranteed across other implementations of Python (and other ordered behavior[1]).As of Python 3.7, this is no longer an implementation detail and instead becomes a language feature. From a python-dev message by GvR:
This simply means that you can depend on it. Other implementations of Python must also offer an insertion ordered dictionary if they wish to be a conforming implementation of Python 3.7.
Essentially, by keeping two arrays.
The first array,
dk_entries
, holds the entries (of typePyDictKeyEntry
) for the dictionary in the order that they were inserted. Preserving order is achieved by this being an append only array where new items are always inserted at the end (insertion order).The second,
dk_indices
, holds the indices for thedk_entries
array (that is, values that indicate the position of the corresponding entry indk_entries
). This array acts as the hash table. When a key is hashed it leads to one of the indices stored indk_indices
and the corresponding entry is fetched by indexingdk_entries
. Since only indices are kept, the type of this array depends on the overall size of the dictionary (ranging from typeint8_t
(1
byte) toint32_t
/int64_t
(4
/8
bytes) on32
/64
bit builds)In the previous implementation, a sparse array of type
PyDictKeyEntry
and sizedk_size
had to be allocated; unfortunately, it also resulted in a lot of empty space since that array was not allowed to be more than2/3 * dk_size
full for performance reasons. (and the empty space still hadPyDictKeyEntry
size!).This is not the case now since only the required entries are stored (those that have been inserted) and a sparse array of type
intX_t
(X
depending on dict size)2/3 * dk_size
s full is kept. The empty space changed from typePyDictKeyEntry
tointX_t
.So, obviously, creating a sparse array of type
PyDictKeyEntry
is much more memory demanding than a sparse array for storingint
s.You can see the full conversation on Python-Dev regarding this feature if interested, it is a good read.
In the original proposal made by Raymond Hettinger, a visualization of the data structures used can be seen which captures the gist of the idea.
As you can visually now see, in the original proposal, a lot of space is essentially empty to reduce collisions and make look-ups faster. With the new approach, you reduce the memory required by moving the sparseness where it's really required, in the indices.
[1]: I say "insertion ordered" and not "ordered" since, with the existence of OrderedDict, "ordered" suggests further behavior that the
dict
object doesn't provide. OrderedDicts are reversible, provide order sensitive methods and, mainly, provide an order-sensive equality tests (==
,!=
).dict
s currently don't offer any of those behaviors/methods.[2]: The new dictionary implementations performs better memory wise by being designed more compactly; that's the main benefit here. Speed wise, the difference isn't so drastic, there's places where the new dict might introduce slight regressions (key-lookups, for example) while in others (iteration and resizing come to mind) a performance boost should be present.
Overall, the performance of the dictionary, especially in real-life situations, improves due to the compactness introduced.
Below is answering the original first question:
I think this sentence from the documentation is actually enough to answer your question
dict
is not explicitly meant to be an ordered collection, so if you want to stay consistent and not rely on a side effect of the new implementation you should stick withOrderedDict
.Make your code future proof :)
There's a debate about that here.
EDIT: Python 3.7 will keep this as a feature see
Update: Guido van Rossum announced on the mailing list that as of Python 3.7
dict
s in all Python implementations must preserve insertion order.