Order of Keys in Dictionaries in Old Versions of Python

Order of keys in dictionaries in old versions of Python

You could use OrderedDict (requires Python 2.7) or higher.

Also, note that OrderedDict({'a': 1, 'b':2, 'c':3}) won't work since the dict you create with {...} has already forgotten the order of the elements. Instead, you want to use OrderedDict([('a', 1), ('b', 2), ('c', 3)]).

As mentioned in the documentation, for versions lower than Python 2.7, you can use this recipe.

How can I get the keys in a dictionary in the order that they appear in the dictionary?

Try from this source: Key Order in Python Dictionaries

OrderedDict([('a', 1), ('b', 2), ('c', 3)])

Sadly, OrderedDict({'a': 1, 'b':2, 'c':3}) won't work because The {} has already forgotten order of the elements.

Your code would be:

Dict = OrderedDict([('Name', 'Zara'), ('Age', 7), ('Class', 'First)])

Why items order in a dictionary changed in Python?

May I know why this is happening?

It is because of the way dicts are organized internally.

In short, this works via a hash-table which puts the keys into buckets according to their hash() value.

If I use dict.keys() to extract the keys from a dictionary and iterate it in an order that I suppose it to be, will that cause dismatch problem?

Depending on how you do it.

k = list(d.keys())
k.sort()
for i in k: print i, d[i]

should exactly work how you want it to work.

Are dictionaries ordered in Python 3.6+?

Are dictionaries ordered in Python 3.6+?

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 a guaranteed language feature, not merely an implementation detail. From a python-dev message by GvR:

Make it so. "Dict keeps insertion order" is the ruling. Thanks!

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.

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How does the Python 3.6 dictionary implementation perform better^[2] than the older one while preserving element order?

Essentially, by keeping two arrays.

• The first array, dk_entries, holds the entries (of type PyDictKeyEntry) 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 the dk_entries array (that is, values that indicate the position of the corresponding entry in dk_entries). This array acts as the hash table. When a key is hashed it leads to one of the indices stored in dk_indices and the corresponding entry is fetched by indexing dk_entries. Since only indices are kept, the type of this array depends on the overall size of the dictionary (ranging from type int8_t(1 byte) to int32_t/int64_t (4/8 bytes) on 32/64 bit builds)

In the previous implementation, a sparse array of type PyDictKeyEntry and size dk_size had to be allocated; unfortunately, it also resulted in a lot of empty space since that array was not allowed to be more than 2/3 * dk_size full for performance reasons. (and the empty space still had PyDictKeyEntry 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_sizes full is kept. The empty space changed from type PyDictKeyEntry to intX_t.

So, obviously, creating a sparse array of type PyDictKeyEntry is much more memory demanding than a sparse array for storing ints.

You can see the full conversation on Python-Dev regarding this feature if interested, it is a good read.

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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.

For example, the dictionary:

d = {'timmy': 'red', 'barry': 'green', 'guido': 'blue'}

is currently stored as [keyhash, key, value]:

entries = [['--', '--', '--'],
           [-8522787127447073495, 'barry', 'green'],
           ['--', '--', '--'],
           ['--', '--', '--'],
           ['--', '--', '--'],
           [-9092791511155847987, 'timmy', 'red'],
           ['--', '--', '--'],
           [-6480567542315338377, 'guido', 'blue']]

Instead, the data should be organized as follows:

indices =  [None, 1, None, None, None, 0, None, 2]
entries =  [[-9092791511155847987, 'timmy', 'red'],
            [-8522787127447073495, 'barry', 'green'],
            [-6480567542315338377, 'guido', 'blue']]

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.

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_{[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.}

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<sub>[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.</sub>

How to fix key order of a dictionary

Dictionaries are not for ordering by keys. Use OrderedDict instead:

import collections
ordered = collections.OrderedDict(sorted(dic.items()))

Order of keys in dictionary

Dictionaries are not ordered. So there is no way to do it.

If you have python2.7+, you can use collections.OrderedDict - in this case you could retrieve the item list using .items() and then reverse it and create a new OrderedDict from the reversed list:

>>> od = OrderedDict((('a', 'first'), ('b', 'second')))
>>> od
OrderedDict([('a', 'first'), ('b', 'second')])
>>> items = od.items()  # list(od.items()) in Python3
>>> items.reverse()
>>> OrderedDict(items)
OrderedDict([('b', 'second'), ('a', 'first')])

If you are using an older python version you can get a backport from http://code.activestate.com/recipes/576693/

keys() method of a Python dictionary return ordered list or not

https://docs.python.org/2/library/stdtypes.html#dict.items

CPython implementation detail: Keys and values are listed in an arbitrary order which is non-random, varies across Python implementations, and depends on the dictionary’s history of insertions and deletions.

No, you cannot rely on the ordering to be consistent.

How do you retrieve items from a dictionary in the order that they're inserted?

The standard Python dict does this by default if you're using CPython 3.6+ (or Python 3.7+ for any other implementation of Python).

On older versions of Python you can use collections.OrderedDict.

Understanding the ordering of a python dictionary

This depends upon the version of Python you are using.

Before Python 3.6

Dictionaries used the ordering of the underlying hash function. Several types have salted hashes, so this means you obtain different order on each invocation.

Python 3.6+

Dictionaries are insertion ordered, i.e., dictionaries remember the order of items inserted. From the docs:

The order-preserving aspect of this new implementation is considered an implementation detail and should not be relied upon

Python 3.7

Guido van Rossum announced on that as of Python 3.7 dicts in all Python implementations must preserve insertion order.

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