ChatGPT解决这个技术问题 Extra ChatGPT

Does Python have an ordered set?

Python has an ordered dictionary. What about an ordered set?

what about the converse, a bag of things? (unordered and non-unique)
@wim collections.Counter is Python's bag.
What if something gets added twice? What should the position be?
@McKay - if it were to follow the behavior of collections.OrderDict it would still be in the position of the initial addition
Warning: several answers here are outdated. E.g., dict is now insertion-ordered (guaranteed since Python 3.7)

A
Asclepius

The answer is no, but you can use collections.OrderedDict from the Python standard library with just keys (and values as None) for the same purpose.

Update: As of Python 3.7 (and CPython 3.6), standard dict is guaranteed to preserve order and is more performant than OrderedDict. (For backward compatibility and especially readability, however, you may wish to continue using OrderedDict.)

Here's an example of how to use dict as an ordered set to filter out duplicate items while preserving order, thereby emulating an ordered set. Use the dict class method fromkeys() to create a dict, then simply ask for the keys() back.

>>> keywords = ['foo', 'bar', 'bar', 'foo', 'baz', 'foo']

>>> list(dict.fromkeys(keywords))
['foo', 'bar', 'baz']

Maybe worth mentioning that this also works (faster) with vanilla dict.fromkeys(). But in that case, key order is only preserved in CPython 3.6+ implementations, so OrderedDict is a more portable solution when order matters.
@AnwarHossain keys = (1,2,3,1,2,1) list(OrderedDict.fromkeys(keys).keys()) -> [1, 2, 3], python-3.7. It works.
Can we infer that Set in Python 3.7+ preserve order too ?
@user474491 Unlike dict, set in Python 3.7+ unfortunately does not preserve order.
@DavidEhrmann Keep reading a little further on the same link: "Update December 2017: dicts retaining insertion order is guaranteed for Python 3.7"
L
LondonRob

There is an ordered set (possible new link) recipe for this which is referred to from the Python 2 Documentation. This runs on Py2.6 or later and 3.0 or later without any modifications. The interface is almost exactly the same as a normal set, except that initialisation should be done with a list.

OrderedSet([1, 2, 3])

This is a MutableSet, so the signature for .union doesn't match that of set, but since it includes __or__ something similar can easily be added:

@staticmethod
def union(*sets):
    union = OrderedSet()
    union.union(*sets)
    return union

def union(self, *sets):
    for set in sets:
        self |= set

I selected my own answer because the reference from the documentation makes this close to an official answer
The interface is NOT exactly the same as the normal set object, many essential methods are missing such as update, union, intersection.
FYI, I noticed that a slightly modified version of the recipe cited in this answer has been added to PyPi as "ordered-set"
I'm pretty sure you're not allowed to have two methods both called union in the same class. The last one will "win" and the first one will fail to exist at runtime. This is because OrderedSet.union (no parens) has to refer to a single object.
There is also "orderedset" package which is based on the same recipe but implemented in Cython -- pypi.python.org/pypi/orderedset .
S
Stephan202

Update: This answer is obsolete as of Python 3.7. See jrc's answer above for a better solution. Will keep this answer here only for historical reasons.

An ordered set is functionally a special case of an ordered dictionary.

The keys of a dictionary are unique. Thus, if one disregards the values in an ordered dictionary (e.g. by assigning them None), then one has essentially an ordered set.

As of Python 3.1 and 2.7 there is collections.OrderedDict. The following is an example implementation of an OrderedSet. (Note that only few methods need to be defined or overridden: collections.OrderedDict and collections.MutableSet do the heavy lifting.)

import collections

class OrderedSet(collections.OrderedDict, collections.MutableSet):

    def update(self, *args, **kwargs):
        if kwargs:
            raise TypeError("update() takes no keyword arguments")

        for s in args:
            for e in s:
                 self.add(e)

    def add(self, elem):
        self[elem] = None

    def discard(self, elem):
        self.pop(elem, None)

    def __le__(self, other):
        return all(e in other for e in self)

    def __lt__(self, other):
        return self <= other and self != other

    def __ge__(self, other):
        return all(e in self for e in other)

    def __gt__(self, other):
        return self >= other and self != other

    def __repr__(self):
        return 'OrderedSet([%s])' % (', '.join(map(repr, self.keys())))

    def __str__(self):
        return '{%s}' % (', '.join(map(repr, self.keys())))
    
    difference = property(lambda self: self.__sub__)
    difference_update = property(lambda self: self.__isub__)
    intersection = property(lambda self: self.__and__)
    intersection_update = property(lambda self: self.__iand__)
    issubset = property(lambda self: self.__le__)
    issuperset = property(lambda self: self.__ge__)
    symmetric_difference = property(lambda self: self.__xor__)
    symmetric_difference_update = property(lambda self: self.__ixor__)
    union = property(lambda self: self.__or__)

@Casebash: yes, one may want to define a class OrderedSet which subclasses OrderedDict and abc.Set and then define __len__, __iter__ and __contains__.
This is true, but you do have a lot of wasted space as a result, which leads to suboptimal performance.
An addition; collections.OrderedDict is also available in python 2.7.
Doing OrderedSet([1,2,3]) raises a TypeError. How does the constructor even work? Missing usage example.
This answer needs to be rewritten to: (1) support initialization using a list of tuple, (2) use dict (since it is now ordered) via composition rather than inheritance, and (3) use collections.abc.MutableSet.
M
Mahmoud Hashemi

Implementations on PyPI

While others have pointed out that there is no built-in implementation of an insertion-order preserving set in Python (yet), I am feeling that this question is missing an answer which states what there is to be found on PyPI.

There are the packages:

ordered-set (Python based)

orderedset (Cython based)

collections-extended

boltons (under iterutils.IndexedSet, Python-based)

oset (last updated in 2012)

Some of these implementations are based on the recipe posted by Raymond Hettinger to ActiveState which is also mentioned in other answers here.

Some differences

ordered-set (version 1.1)

advantage: O(1) for lookups by index (e.g. my_set[5])

oset (version 0.1.3)

advantage: O(1) for remove(item)

disadvantage: apparently O(n) for lookups by index

Both implementations have O(1) for add(item) and __contains__(item) (item in my_set).


A new contender is collections_extended.setlist. Functions like set.union don't work on it though, even though it inherits collections.abc.Set.
OrderedSet now supports remove
There is also SortedSet from sortedcontainers 2.3.0 with a bunch of other sorted stuff.
N
NOhs

I can do you one better than an OrderedSet: boltons has a pure-Python, 2/3-compatible IndexedSet type that is not only an ordered set, but also supports indexing (as with lists).

Simply pip install boltons (or copy setutils.py into your codebase), import the IndexedSet and:

>>> from boltons.setutils import IndexedSet
>>> x = IndexedSet(list(range(4)) + list(range(8)))
>>> x
IndexedSet([0, 1, 2, 3, 4, 5, 6, 7])
>>> x - set(range(2))
IndexedSet([2, 3, 4, 5, 6, 7])
>>> x[-1]
7
>>> fcr = IndexedSet('freecreditreport.com')
>>> ''.join(fcr[:fcr.index('.')])
'frecditpo'

Everything is unique and retained in order. Full disclosure: I wrote the IndexedSet, but that also means you can bug me if there are any issues. :)


Indexing does not work when negative indexes are supplied. For instance, this s[-4:-1] returns IndexedSet([]) on a very non-empty set.
@darlove Not sure what version you're on but negative indexes are supported and your supplied case does not reproduce on the issue you opened: github.com/mahmoud/boltons/issues/274
G
GrantJ

If you're using the ordered set to maintain a sorted order, consider using a sorted set implementation from PyPI. The sortedcontainers module provides a SortedSet for just this purpose. Some benefits: pure-Python, fast-as-C implementations, 100% unit test coverage, hours of stress testing.

Installing from PyPI is easy with pip:

pip install sortedcontainers

Note that if you can't pip install, simply pull down the sortedlist.py and sortedset.py files from the open-source repository.

Once installed you can simply:

from sortedcontainers import SortedSet
help(SortedSet)

The sortedcontainers module also maintains a performance comparison with several alternative implementations.

For the comment that asked about Python's bag data type, there's alternatively a SortedList data type which can be used to efficiently implement a bag.


Note that the SortedSet class there requires members to be comparable and hashable.
@gsnedders The builtins set and frozenset also require elements to be hashable. The comparable constraint is the addition for SortedSet, but it's also an obvious constraint.
As the name suggests, this does not maintain order. It is nothing but sorted(set([sequence])) which makes better?
@ldmtwo I'm not sure which you're referring to but just to be clear, SortedSet as part of Sorted Containers does maintain sorted order.
@GrantJ - It is the difference between whether it maintains insertion order or sort order. Most of the other answers are regarding insertion order. I think you are already aware of this based on your first sentence, but it's probably what ldmtwo is saying.
b
bustawin

As other answers mention, as for python 3.7+, the dict is ordered by definition. Instead of subclassing OrderedDict we can subclass abc.collections.MutableSet or typing.MutableSet using the dict's keys to store our values.

import itertools
import typing

T = typing.TypeVar("T")

class OrderedSet(typing.MutableSet[T]):
    """A set that preserves insertion order by internally using a dict."""

    def __init__(self, iterable: typing.Iterator[T]):
        self._d = dict.fromkeys(iterable)

    def add(self, x: T) -> None:
        self._d[x] = None

    def discard(self, x: T) -> None:
        self._d.pop(x, None)

    def __contains__(self, x: object) -> bool:
        return self._d.__contains__(x)

    def __len__(self) -> int:
        return self._d.__len__()

    def __iter__(self) -> typing.Iterator[T]:
        return self._d.__iter__()

    def __str__(self):
        return f"{{{', '.join(str(i) for i in self)}}}"

    def __repr__(self):
        return f"<OrderedSet {self}>"

Then just:

x = OrderedSet([1, 2, -1, "bar"])
x.add(0)
assert list(x) == [1, 2, -1, "bar", 0]

I added this code, with some tests, in a small library, so anyone can just pip install it.


Don't use this as-is. discard should never ever raise a KeyError. Also note that this doesn't provide a sensible __repr__
@JasonForbes You are right —in fact we addressed your comments in the linked repo. So I just brought those fixes in this answer. Thank you for pointing it out! :-)
B
Berislav Lopac

In case you're already using pandas in your code, its Index object behaves pretty like an ordered set, as shown in this article.

Examples from the article:

indA = pd.Index([1, 3, 5, 7, 9])
indB = pd.Index([2, 3, 5, 7, 11])

indA & indB  # intersection
indA | indB  # union
indA - indB  # difference
indA ^ indB  # symmetric difference

Can you include an example in this answer? Links tend to be broken after some time.
for the difference between sets, you actually need to use indA.difference(indB), the minus sign performs standard subtraction
It's important to note that pd.Index allows for duplicate elements, which one would not expect from an actual Python set.
M
Michael Lenzen

A little late to the game, but I've written a class setlist as part of collections-extended that fully implements both Sequence and Set

>>> from collections_extended import setlist
>>> sl = setlist('abracadabra')
>>> sl
setlist(('a', 'b', 'r', 'c', 'd'))
>>> sl[3]
'c'
>>> sl[-1]
'd'
>>> 'r' in sl  # testing for inclusion is fast
True
>>> sl.index('d')  # so is finding the index of an element
4
>>> sl.insert(1, 'd')  # inserting an element already in raises a ValueError
ValueError
>>> sl.index('d')
4

GitHub: https://github.com/mlenzen/collections-extended

Documentation: http://collections-extended.lenzm.net/en/latest/

PyPI: https://pypi.python.org/pypi/collections-extended


f
fhdrsdg

There's no OrderedSet in official library. I make an exhaustive cheatsheet of all the data structure for your reference.

DataStructure = {
    'Collections': {
        'Map': [
            ('dict', 'OrderDict', 'defaultdict'),
            ('chainmap', 'types.MappingProxyType')
        ],
        'Set': [('set', 'frozenset'), {'multiset': 'collection.Counter'}]
    },
    'Sequence': {
        'Basic': ['list', 'tuple', 'iterator']
    },
    'Algorithm': {
        'Priority': ['heapq', 'queue.PriorityQueue'],
        'Queue': ['queue.Queue', 'multiprocessing.Queue'],
        'Stack': ['collection.deque', 'queue.LifeQueue']
        },
    'text_sequence': ['str', 'byte', 'bytearray']
}

Some odd things in this cheatsheet: according to collections.abc, Sequences are Collections, not a sibling. And iterator does not support indexing, so shouldn't be on the same group as lists and tuples. Also, all text_sequences are also Sequence
D
David Ehrmann

As others have said, OrderedDict is a superset of an ordered set in terms of functionality, but if you need a set for interacting with an API and don't need it to be mutable, OrderedDict.keys() is actually an implementation abc.collections.Set:

import random
from collections import OrderedDict, abc

a = list(range(0, 100))
random.shuffle(a)

# True
a == list(OrderedDict((i, 0) for i in a).keys())

# True
isinstance(OrderedDict().keys(), abc.Set)   

The caveats are immutability and having to build up the set like a dict, but it's simple and only uses built-ins.


R
RichardB

The ParallelRegression package provides a setList( ) ordered set class that is more method-complete than the options based on the ActiveState recipe. It supports all methods available for lists and most if not all methods available for sets.


T
Tutorialwing.com

Note: a extension to jrc answer since how to use OrderDict is not included in that answer.

A nice explanation with proper example explained at Create OrderedSet in Python 3.7 and Before

We have two ways for this - (1) collections.OrderedDict and (2) dict

First is used for python prior to 3.7 and later is used for python 3.7 and above.

Create ordered set in python 3.7 and above as shown below -

keywords = ['hello', 'aurav', 'hello', 'narendra', 'foo', 'foo']
sampleList = list(dict.fromkeys(keywords))

print(type(sampleList))

for item in sampleList:
    print(item)

When above program is run output is -

<class 'list'>
hello
aurav
narendra
foo

Checkout on how to create OrderedSet using OrderDict from collections


W
Watchdog101

There is a pip library that does this:

pip install ordered-set

Then you can use it:

from ordered_set import OrderedSet

h
hwrd

For many purposes simply calling sorted will suffice. For example

>>> s = set([0, 1, 2, 99, 4, 40, 3, 20, 24, 100, 60])
>>> sorted(s)
[0, 1, 2, 3, 4, 20, 24, 40, 60, 99, 100]

If you are going to use this repeatedly, there will be overhead incurred by calling the sorted function so you might want to save the resulting list, as long as you're done changing the set. If you need to maintain unique elements and sorted, I agree with the suggestion of using OrderedDict from collections with an arbitrary value such as None.


The purpose for OrderedSet is to be able to get the items in the order which they where added to the set. You example could maybe called SortedSet...
L
Loïc N.

So i also had a small list where i clearly had the possibility of introducing non-unique values.

I searched for the existence of a unique list of some sort, but then realized that testing the existence of the element before adding it works just fine.

if(not new_element in my_list):
    my_list.append(new_element)

I don't know if there are caveats to this simple approach, but it solves my problem.


The main issue with this approach is that adding runs in O(n). Meaning it gets slower with big lists. Python's built-in sets are very good at making adding elements faster. But for simple use-cases, it certainly does work!