| Name | ordered-set JSON |
| Version |
4.1.0
JSON |
| download |
| home_page | |
| Summary | An OrderedSet is a custom MutableSet that remembers its order, so that every |
| upload_time | 2022-01-26 14:38:56 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.7 |
| license | |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
|
[](https://pypi.python.org/pypi/ordered-set)
An OrderedSet is a mutable data structure that is a hybrid of a list and a set.
It remembers the order of its entries, and every entry has an index number that
can be looked up.
## Installation
`ordered_set` is available on PyPI and packaged as a wheel. You can list it
as a dependency of your project, in whatever form that takes.
To install it into your current Python environment:
pip install ordered-set
To install the code for development, after checking out the repository:
pip install flit
flit install
## Usage examples
An OrderedSet is created and used like a set:
>>> from ordered_set import OrderedSet
>>> letters = OrderedSet('abracadabra')
>>> letters
OrderedSet(['a', 'b', 'r', 'c', 'd'])
>>> 'r' in letters
True
It is efficient to find the index of an entry in an OrderedSet, or find an
entry by its index. To help with this use case, the `.add()` method returns
the index of the added item, whether it was already in the set or not.
>>> letters.index('r')
2
>>> letters[2]
'r'
>>> letters.add('r')
2
>>> letters.add('x')
5
OrderedSets implement the union (`|`), intersection (`&`), and difference (`-`)
operators like sets do.
>>> letters |= OrderedSet('shazam')
>>> letters
OrderedSet(['a', 'b', 'r', 'c', 'd', 'x', 's', 'h', 'z', 'm'])
>>> letters & set('aeiou')
OrderedSet(['a'])
>>> letters -= 'abcd'
>>> letters
OrderedSet(['r', 'x', 's', 'h', 'z', 'm'])
The `__getitem__()` and `index()` methods have been extended to accept any
iterable except a string, returning a list, to perform NumPy-like "fancy
indexing".
>>> letters = OrderedSet('abracadabra')
>>> letters[[0, 2, 3]]
['a', 'r', 'c']
>>> letters.index(['a', 'r', 'c'])
[0, 2, 3]
OrderedSet implements `__getstate__` and `__setstate__` so it can be pickled,
and implements the abstract base classes `collections.MutableSet` and
`collections.Sequence`.
OrderedSet can be used as a generic collection type, similar to the collections
in the `typing` module like List, Dict, and Set. For example, you can annotate
a variable as having the type `OrderedSet[str]` or `OrderedSet[Tuple[int,
str]]`.
## OrderedSet in data science applications
An OrderedSet can be used as a bi-directional mapping between a sparse
vocabulary and dense index numbers. As of version 3.1, it accepts NumPy arrays
of index numbers as well as lists.
This combination of features makes OrderedSet a simple implementation of many
of the things that `pandas.Index` is used for, and many of its operations are
faster than the equivalent pandas operations.
For further compatibility with pandas.Index, `get_loc` (the pandas method for
looking up a single index) and `get_indexer` (the pandas method for fancy
indexing in reverse) are both aliases for `index` (which handles both cases
in OrderedSet).
## Authors
OrderedSet was implemented by Elia Robyn Lake (maiden name: Robyn Speer).
Jon Crall contributed changes and tests to make it fit the Python set API.
Roman Inflianskas added the original type annotations.
## Comparisons
The original implementation of OrderedSet was a [recipe posted to ActiveState
Recipes][recipe] by Raymond Hettiger, released under the MIT license.
[recipe]: https://code.activestate.com/recipes/576694-orderedset/
Hettiger's implementation kept its content in a doubly-linked list referenced by a
dict. As a result, looking up an item by its index was an O(N) operation, while
deletion was O(1).
This version makes different trade-offs for the sake of efficient lookups. Its
content is a standard Python list instead of a doubly-linked list. This
provides O(1) lookups by index at the expense of O(N) deletion, as well as
slightly faster iteration.
In Python 3.6 and later, the built-in `dict` type is inherently ordered. If you
ignore the dictionary values, that also gives you a simple ordered set, with
fast O(1) insertion, deletion, iteration and membership testing. However, `dict`
does not provide the list-like random access features of OrderedSet. You
would have to convert it to a list in O(N) to look up the index of an entry or
look up an entry by its index.
Raw data
{
"_id": null,
"home_page": "",
"name": "ordered-set",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.7",
"maintainer_email": "",
"keywords": "",
"author": "",
"author_email": "Elia Robyn Lake <gh@arborelia.net>",
"download_url": "https://files.pythonhosted.org/packages/4c/ca/bfac8bc689799bcca4157e0e0ced07e70ce125193fc2e166d2e685b7e2fe/ordered-set-4.1.0.tar.gz",
"platform": "",
"description": "[](https://pypi.python.org/pypi/ordered-set)\n\nAn OrderedSet is a mutable data structure that is a hybrid of a list and a set.\nIt remembers the order of its entries, and every entry has an index number that\ncan be looked up.\n\n## Installation\n\n`ordered_set` is available on PyPI and packaged as a wheel. You can list it\nas a dependency of your project, in whatever form that takes.\n\nTo install it into your current Python environment:\n\n pip install ordered-set\n\nTo install the code for development, after checking out the repository:\n\n pip install flit\n flit install\n\n## Usage examples\n\nAn OrderedSet is created and used like a set:\n\n >>> from ordered_set import OrderedSet\n\n >>> letters = OrderedSet('abracadabra')\n\n >>> letters\n OrderedSet(['a', 'b', 'r', 'c', 'd'])\n\n >>> 'r' in letters\n True\n\nIt is efficient to find the index of an entry in an OrderedSet, or find an\nentry by its index. To help with this use case, the `.add()` method returns\nthe index of the added item, whether it was already in the set or not.\n\n >>> letters.index('r')\n 2\n\n >>> letters[2]\n 'r'\n\n >>> letters.add('r')\n 2\n\n >>> letters.add('x')\n 5\n\nOrderedSets implement the union (`|`), intersection (`&`), and difference (`-`)\noperators like sets do.\n\n >>> letters |= OrderedSet('shazam')\n\n >>> letters\n OrderedSet(['a', 'b', 'r', 'c', 'd', 'x', 's', 'h', 'z', 'm'])\n\n >>> letters & set('aeiou')\n OrderedSet(['a'])\n\n >>> letters -= 'abcd'\n\n >>> letters\n OrderedSet(['r', 'x', 's', 'h', 'z', 'm'])\n\nThe `__getitem__()` and `index()` methods have been extended to accept any\niterable except a string, returning a list, to perform NumPy-like \"fancy\nindexing\".\n\n >>> letters = OrderedSet('abracadabra')\n\n >>> letters[[0, 2, 3]]\n ['a', 'r', 'c']\n\n >>> letters.index(['a', 'r', 'c'])\n [0, 2, 3]\n\nOrderedSet implements `__getstate__` and `__setstate__` so it can be pickled,\nand implements the abstract base classes `collections.MutableSet` and\n`collections.Sequence`.\n\nOrderedSet can be used as a generic collection type, similar to the collections\nin the `typing` module like List, Dict, and Set. For example, you can annotate\na variable as having the type `OrderedSet[str]` or `OrderedSet[Tuple[int,\nstr]]`.\n\n\n## OrderedSet in data science applications\n\nAn OrderedSet can be used as a bi-directional mapping between a sparse\nvocabulary and dense index numbers. As of version 3.1, it accepts NumPy arrays\nof index numbers as well as lists.\n\nThis combination of features makes OrderedSet a simple implementation of many\nof the things that `pandas.Index` is used for, and many of its operations are\nfaster than the equivalent pandas operations.\n\nFor further compatibility with pandas.Index, `get_loc` (the pandas method for\nlooking up a single index) and `get_indexer` (the pandas method for fancy\nindexing in reverse) are both aliases for `index` (which handles both cases\nin OrderedSet).\n\n\n## Authors\n\nOrderedSet was implemented by Elia Robyn Lake (maiden name: Robyn Speer).\nJon Crall contributed changes and tests to make it fit the Python set API.\nRoman Inflianskas added the original type annotations.\n\n\n## Comparisons\n\nThe original implementation of OrderedSet was a [recipe posted to ActiveState\nRecipes][recipe] by Raymond Hettiger, released under the MIT license.\n\n[recipe]: https://code.activestate.com/recipes/576694-orderedset/\n\nHettiger's implementation kept its content in a doubly-linked list referenced by a\ndict. As a result, looking up an item by its index was an O(N) operation, while\ndeletion was O(1).\n\nThis version makes different trade-offs for the sake of efficient lookups. Its\ncontent is a standard Python list instead of a doubly-linked list. This\nprovides O(1) lookups by index at the expense of O(N) deletion, as well as\nslightly faster iteration.\n\nIn Python 3.6 and later, the built-in `dict` type is inherently ordered. If you\nignore the dictionary values, that also gives you a simple ordered set, with\nfast O(1) insertion, deletion, iteration and membership testing. However, `dict`\ndoes not provide the list-like random access features of OrderedSet. You\nwould have to convert it to a list in O(N) to look up the index of an entry or\nlook up an entry by its index.\n",
"bugtrack_url": null,
"license": "",
"summary": "An OrderedSet is a custom MutableSet that remembers its order, so that every",
"version": "4.1.0",
"project_urls": {
"Home": "https://github.com/rspeer/ordered-set"
},
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "3355af02708f230eb77084a299d7b08175cff006dea4f2721074b92cdb0296c0",
"md5": "6db93c545cdb9548e7a1130ebbf80da7",
"sha256": "046e1132c71fcf3330438a539928932caf51ddbc582496833e23de611de14562"
},
"downloads": -1,
"filename": "ordered_set-4.1.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "6db93c545cdb9548e7a1130ebbf80da7",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.7",
"size": 7634,
"upload_time": "2022-01-26T14:38:48",
"upload_time_iso_8601": "2022-01-26T14:38:48.677482Z",
"url": "https://files.pythonhosted.org/packages/33/55/af02708f230eb77084a299d7b08175cff006dea4f2721074b92cdb0296c0/ordered_set-4.1.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "4ccabfac8bc689799bcca4157e0e0ced07e70ce125193fc2e166d2e685b7e2fe",
"md5": "2a9ba8d1a962c26f9a4fbe246b62ee77",
"sha256": "694a8e44c87657c59292ede72891eb91d34131f6531463aab3009191c77364a8"
},
"downloads": -1,
"filename": "ordered-set-4.1.0.tar.gz",
"has_sig": false,
"md5_digest": "2a9ba8d1a962c26f9a4fbe246b62ee77",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.7",
"size": 12826,
"upload_time": "2022-01-26T14:38:56",
"upload_time_iso_8601": "2022-01-26T14:38:56.600833Z",
"url": "https://files.pythonhosted.org/packages/4c/ca/bfac8bc689799bcca4157e0e0ced07e70ce125193fc2e166d2e685b7e2fe/ordered-set-4.1.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2022-01-26 14:38:56",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "rspeer",
"github_project": "ordered-set",
"travis_ci": false,
"coveralls": true,
"github_actions": false,
"tox": true,
"lcname": "ordered-set"
}
