pycedar

version python license

Python binding of cedar (implementation of efficiently-updatable double-array trie) using Cython

日本語版の README は README.ja.md にあります。

Official URL of cedar: http://www.tkl.iis.u-tokyo.ac.jp/~ynaga/cedar/

Requirements

Python 3.9 or newer
A POSIX-compatible 64-bit platform (Linux, macOS)
A C++ compiler, when building from source

The extension is tested with CPython 3.9 through 3.14 on Linux and macOS.

Installation

install from PyPI release

$ pip install --user pycedar

install from GitHub master

$ pip install --user https://github.com/akivajp/pycedar/archive/master.zip

Usage

using python-like dict class based on double array trie

>>> import pycedar

>>> d = pycedar.dict()
>>> len(d)
0
>>> bool(d)
False
>>> list(d)
[]

>>> d['nineteen'] = 19
>>> d.set('twenty', 20)
20
>>> d['twenty one'] = 21
>>> d['twenty two'] = 22
>>> d['twenty three'] = 23
>>> d['twenty four'] = 24

>>> len(d)
6
>>> bool(d)
True
>>> list(d)
['nineteen', 'twenty', 'twenty four', 'twenty one', 'twenty three', 'twenty two']
>>> list(d.keys())
['nineteen', 'twenty', 'twenty four', 'twenty one', 'twenty three', 'twenty two']
>>> list(d.values())
[19, 20, 24, 21, 23, 22]
>>> list(d.items())
[('nineteen', 19), ('twenty', 20), ('twenty four', 24), ('twenty one', 21), ('twenty three', 23), ('twenty two', 22)]
>>> d['twenty four']
24
>>> 'twenty four' in d
True
>>> del d['twenty four']
>>> 'twenty four' in d
False
>>> d['twenty four']
Traceback (most recent call last):
    ...
KeyError: 'twenty four'
>>> d.get('twenty three')
23
>>> d.get('twenty four')       # the default is base_trie.NO_VALUE
-1
>>> d.get('twenty four', None) is None
True

Prefix queries return generators:

>>> list(d.find(''))
[('nineteen', 19), ('twenty', 20), ('twenty one', 21), ('twenty three', 23), ('twenty two', 22)]
>>> list(d.find('tw'))
[('twenty', 20), ('twenty one', 21), ('twenty three', 23), ('twenty two', 22)]
>>> list(d.find('twenty t'))
[('twenty three', 23), ('twenty two', 22)]
>>> list(d.find_keys('twenty'))
['twenty', 'twenty one', 'twenty three', 'twenty two']
>>> list(d.find_values('twenty'))
[20, 21, 23, 22]

Nodes let you keep a position in the trie and search relative to it:

>>> n = d.get_node('twenty')
>>> n.key()
'twenty'
>>> n.value()
20
>>> [child.key() for child in n.find_nodes(' t')]
[' three', ' two']

>>> d.get_node('twenty ') is None    # a path without a value
True

Saving and loading:

>>> d.save('test.dat')
0
>>> d2 = pycedar.dict()
>>> d2.setdefault('eighteen', 18)
18
>>> list(d2.items())
[('eighteen', 18)]
>>> d2.load('test.dat')              # replaces the whole trie image
0
>>> list(d2.items())
[('nineteen', 19), ('twenty', 20), ('twenty one', 21), ('twenty three', 23), ('twenty two', 22)]
>>> d2.setdefault('eighteen', 18)
18
>>> list(d2.items())
[('eighteen', 18), ('nineteen', 19), ('twenty', 20), ('twenty one', 21), ('twenty three', 23), ('twenty two', 22)]

using bytes keys

pycedar.dict is parameterised by its key type, which is enforced strictly:

>>> b = pycedar.dict(bytes)
>>> b[b'cedar'] = 1
>>> b[b'cedarpp'] = 2
>>> list(b.items())
[(b'cedar', 1), (b'cedarpp', 2)]
>>> b['str key'] = 3
Traceback (most recent call last):
    ...
TypeError: Argument 'key' has incorrect type (expected bytes, got str)

str keys are encoded as UTF-8 before they reach cedar, so lengths reported by the low level API are byte lengths, not character counts.

using more primitive data structures

pycedar.dict is a thin convenience layer over the trie classes. You can use them directly when you want cedar's raw semantics.

>>> t = pycedar.str_trie()
>>> t.set('apple', 1)
1
>>> t.set('applet', 2)
2
>>> t.set('apply', 3)
3

>>> t.exact_match_search('apple')      # (value, length, node id)
(1, 5, 259)
>>> t.exact_match_search('app')[0]     # a prefix carries no value
-1

>>> t.common_prefix_search('applet')   # every key that prefixes the query
[('apple', 1, 259), ('applet', 2, 368)]
>>> [key for key, value, node_id in t.common_prefix_predict('app')]
['le', 'let', 'ly']

>>> t.erase('apply')
0
>>> t.erase('apply')                   # already gone
-1
>>> t.num_keys()
2

Note the difference between the two prefix queries:

common_prefix_search(key) returns the complete keys that are prefixes of key.
common_prefix_predict(key) returns the remaining suffixes of every key that starts with key.

Enumerating a trie (or a subtree) uses begin / next:

>>> result, from_id, pos = t.traverse('app')   # locate the subtree
>>> value, node_id, length = t.begin(from_id, pos)
>>> while value != pycedar.base_trie.NO_PATH:
...     print(t.suffix(node_id, length), value)
...     value, node_id, length = t.next(node_id, length, from_id)
apple 1
applet 2

API reference

`pycedar.base_trie`

Base class for every trie. Not meant to be instantiated directly.

Member	Description
`NO_VALUE`	`-1`. Returned when a node exists but carries no value.
`NO_PATH`	`-2`. Returned when the path does not exist, and used as the traversal terminator.
`root`	The `node` object for the trie root.
`clear(reuse=True)`	Drop all keys.
`capacity()`, `size()`, `length()`, `total_size()`, `unit_size()`, `nonzero_size()`, `nonzero_length()`, `num_keys()`	cedar's internal statistics. `num_keys()` is the number of registered keys.
`begin(from_id=0, length=0)`	Start an enumeration. Returns `(value, node_id, length)`.
`next(node_id, length, root=0)`	Advance an enumeration. Returns `(value, node_id, length)`.
`open(filepath, mode='rb', offset=0, size=0)`	Load a trie image. Returns `0` on success, `-1` on failure.
`save(filepath, mode='wb', shrink=True)`	Write a trie image. Returns `0` on success, `-1` on failure.

`pycedar.str_trie` / `pycedar.bytes_trie` / `pycedar.unicode_trie`

Specialisations of base_trie for str keys, bytes keys, and unicode keys respectively. On Python 3, unicode is str, so unicode_trie behaves identically to str_trie and is kept only for backward compatibility.

In addition to the base_trie members:

Method	Description
`set(key, value)`	Register `key` with `value`. Returns the stored value. Raises `KeyError` for an empty key.
`update(key, delta=0)`	Register `key` if needed and add `delta` to its value. Returns the new value.
`erase(key, from_id=0)`	Remove `key`. Returns `0` on success, `-1` if it was not registered.
`exact_match_search(key, from_id=0)`	Returns `(value, length, node_id)`. `value` is `NO_VALUE` / `NO_PATH` when not found.
`common_prefix_search(key, from_id=0, max_size=-1)`	Returns a list of `(key, value, node_id)` for every key that prefixes `key`.
`common_prefix_predict(key, from_id=0, max_size=-1)`	Returns a list of `(suffix, value, node_id)` for every key starting with `key`.
`traverse(key, from_id=0, pos=0)`	Follow `key` from `from_id`. Returns `(value, node_id, pos)`.
`suffix(node_id, length=0)`	Reconstruct the key ending at `node_id`.

max_size caps the number of returned results; -1 means "no limit". from_id scopes the query to a subtree.

`pycedar.node`

A cursor into a trie. Obtained from base_trie.root, dict.root, dict.get_node(), dict.nodes() or node.find_nodes().

Member	Description
`id`, `length`, `root`	Read-only position information.
`key()`	The key this node represents, relative to `root`.
`value()`	The value stored at this node.
`track()`	Returns `(id, length, root)`.
`traverse(key)`	Generator yielding `(value, node_id, length)` for the subtree under `key`.
`find_nodes(key)`	Generator yielding `node` objects for the subtree under `key`.
`get_node(key)`	The `node` for `key`, or `None` if it is absent or carries no value.

`pycedar.dict`

A dict-like façade over a trie. pycedar.dict(key_type) accepts str (the default) or bytes.

Member	Description
`trie`, `root`, `type`	The underlying trie, its root `node`, and the key type.
`d[key]`	The value, or `KeyError`.
`d[key] = value`	Register a key. `KeyError` for an empty key.
`del d[key]`	Remove a key, or `KeyError`.
`key in d`, `len(d)`, `iter(d)`	Membership, number of keys, iteration over keys.
`get(key, default=NO_VALUE)`	The value, or `default`.
`set(key, value)`	Register a key. Returns the stored value.
`setdefault(key, value=0)`	Register only if absent. Returns the effective value.
`update(key, delta=0)`	Add `delta` to a key's value, registering it if needed.
`clear()`	Drop all keys.
`keys()`, `values()`, `items()`, `nodes()`	Generators over the whole trie.
`find(prefix)`, `find_keys(prefix)`, `find_values(prefix)`	Generators scoped to `prefix`.
`get_node(key)`	The `node` for `key`, or `None`.
`save(filepath, mode='wb', shrink=True)`	Write a trie image. Returns `0` / `-1`.
`load(filepath, mode='rb')`	Replace the trie with a stored image. Returns `0` / `-1`.

pycedar.__version__ exposes the installed package version.

Limitations

Values are C `int` sized, and two of them are reserved

Values are stored as C int, so they must fit in -2**31 .. 2**31-1; anything larger raises OverflowError.

Two values collide with cedar's sentinels and must not be stored:

-1 (NO_VALUE) — the key is stored and appears during iteration, but in, get() and d[key] all report it as absent.
-2 (NO_PATH) — this value terminates traversal, so items(), keys(), values(), find() and friends silently stop at that key and never reach the rest of the trie.

Storing non-negative values avoids both problems. Every other value, including other negative numbers, round trips normally.

The serialization format is platform-dependent and unauthenticated

The native cedar .dat format depends on the pointer size and byte order of the machine that wrote it, and it carries no integrity checks. Only load files produced by pycedar on a compatible platform and obtained from a trusted source.

I/O failures are reported through return codes

save() / load() / open() return 0 on success and -1 on failure instead of raising; check the return value.

Running out of memory is the exception to that rule: save() and load() raise MemoryError rather than returning -1. A failed load() leaves the trie empty, because the previous contents are released before the new ones are allocated. The instance stays valid and can be reused. See pycedar/core/cedar/README.md.

Development

$ python -m pip install --upgrade pip
$ python -m pip install . pytest
$ pytest

To rebuild in place while iterating on pycedar.pyx:

$ python -m pip install "Cython>=3.1,<4" setuptools
$ python setup.py build_ext --inplace

./clean.sh removes build artifacts.

Benchmarks

benchmarks/bench.py times the operations pycedar is used for. Run it against two builds to check whether a change actually paid off:

$ python benchmarks/bench.py --label before
$ python benchmarks/bench.py --label after

It uses rich for the table when that is installed, and plain text otherwise. --help lists the knobs.

Releasing

The version lives in a single place, pycedar/VERSION.

Update pycedar/VERSION and CHANGELOG.md.
Commit and push to master.
Push a matching tag, e.g. git tag v0.2.0 && git push origin v0.2.0.

The release workflow verifies that the tag matches pycedar/VERSION, builds the sdist and the Linux/macOS wheels with cibuildwheel, and publishes them to PyPI via Trusted Publishing.

License

pycedar is distributed under the same terms as cedar itself: GPLv2, LGPLv2.1 and BSD-2-Clause. See the license files bundled under pycedar/core/cedar/.

Credits

cedar is written by Naoki Yoshinaga. The copy vendored under pycedar/core/cedar/ carries local modifications. pycedar/core/cedar/README.md records what was changed and why, why the 2022 upstream tarball was deliberately not re-vendored, and what has to be re-applied if anyone syncs with a newer release.

See CHANGELOG.md for the list of contributors to each release.

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BLAKE2b-256	`d12fc19c247e352ef217c0caea4e365bb444651a1154edb8428f88174867b9fe`

Algorithm	Hash digest
SHA256	`2fdd328914af092afc2af79a60897b8c2ee83798903b80eb549ddb1cb211c7bf`
MD5	`7131f8561a01d509a1035e97bba89949`
BLAKE2b-256	`17c81009952fff53a1552b3390d342515627a94115e34e7bf8c14aa5b626ff20`

Algorithm	Hash digest
SHA256	`2ac52a2d1d6d14c9dd5ef8563b2dfe64cba556013c008992fd3f6d4e7b2272bd`
MD5	`550332720f55a65fdb766752d13684e9`
BLAKE2b-256	`c54094719752b16c590fa00d4c430bfcae2aab122c96d4c98320426ac4dc856d`

Algorithm	Hash digest
SHA256	`3cf60817c4f280d742a35d4838bd91e69fe077f4cd405a2d54a5531c420d6659`
MD5	`8584dcf6c7827f64af0a715c04c7f2ea`
BLAKE2b-256	`df4730e161cc13cca180bce3fb0911deebbedfe08084ac68b1d3d91ab12b4d2a`

Algorithm	Hash digest
SHA256	`bccbc8a5bf5e0f25015ed3aa11e2dfeeb10795732db70256ba221943b877aaf7`
MD5	`ecc98f4cc2dafa457df398ea069bb683`
BLAKE2b-256	`18b9a021bc0b809ff06e6b81bbba5438cd4f07605346e88d20514d9c727cea85`

Algorithm	Hash digest
SHA256	`ce3ad2e48ed9f6b2b3b7a0c4747e6324e956beb3c45a257848a3e73380bba264`
MD5	`87ac5f52d38d84f0569f0f478f1a2861`
BLAKE2b-256	`78cb63ffacd72c1c7c6aa73c9ce9b61b5a3cdc583d2db02ad44165c7da473244`

Algorithm	Hash digest
SHA256	`27fb20ede5f3e4ee0bc0ad9e753e2d9952ddc64af1e897922586de73b20ef747`
MD5	`7e059ed62637fe1c9db9dc0c8ff712ca`
BLAKE2b-256	`e9301e9309cb74c901a2d24c993a8a0ee9345d093aa0526153639706f1d9e085`

Algorithm	Hash digest
SHA256	`24dceb82d2d6a6a9f5330664df8d6c3cd80e717694d5bb7f03ed6b1b28235355`
MD5	`a0f4e8ed520865cb5211f030034e4d5c`
BLAKE2b-256	`cf9767eda643f5c4fbaccf761b74fd8aced88977c69badb911d21dafc96b5b73`

Algorithm	Hash digest
SHA256	`486fd9280028d1d349d5bd7d8a0dec130b2f4c519a3059e42f5b3703f326f43e`
MD5	`cfe2e22ab9fa9d8c7ae1fa4ed68a6097`
BLAKE2b-256	`e069631a813cbd05719bef0463112f2fe08f2d68d0cf426f05d1bc9caa6f1189`

Algorithm	Hash digest
SHA256	`d4f1ed20e55440307d60c08ea99ea56795079653caa8d7edfeed9b1d7d754b75`
MD5	`0dfe54b24cde0659bbe676bff543b153`
BLAKE2b-256	`66fac7c0fb5c930d640335536fbf5b47d737d7e97c9ded161dc3da0a728fa798`

Algorithm	Hash digest
SHA256	`ef2ce5e5d50015cd63e033c58736f3f84ae5cb0850fd345457a252cc58038335`
MD5	`fb628bc7cff2952ccc3a92d852cbdde4`
BLAKE2b-256	`03c181a860e3a94bd6ac5110b235fc88e010ad59be071f523474ba3cebe585cd`

Algorithm	Hash digest
SHA256	`4d43ad0b4b796e5a42c09cacd81ea8218c887a695e8de6ec1b1eced5fb43078f`
MD5	`255bfa9b3677672fe44a51098855c8c7`
BLAKE2b-256	`de3a4a8e6929d87556dfdb7af2f0b0fd29ea9bed3c7c97a9e8fc99a82041d0bb`

Algorithm	Hash digest
SHA256	`7a9100e8bdb2d2576463fc3cfcb507002e0e860ad1e5d017af1982ab135d5058`
MD5	`f752ee0db85ad2c0f3ef8a95bbf57e08`
BLAKE2b-256	`541b515b1ea64d04781ce783b2d8bc57d634f57681b3c513a34099bcc5ea9cb5`

pycedar 0.2.2

pycedar

Requirements

Installation

install from PyPI release

install from GitHub master

Usage

using python-like dict class based on double array trie

using bytes keys

using more primitive data structures

API reference

pycedar.base_trie

pycedar.str_trie / pycedar.bytes_trie / pycedar.unicode_trie

pycedar.node

pycedar.dict

Limitations

Values are C int sized, and two of them are reserved

The serialization format is platform-dependent and unauthenticated

I/O failures are reported through return codes

Development

Benchmarks

Releasing

License

Credits

Project links

Key dates

1 maintainer

Credits

GitHub Statistics

License

Requires

Classifiers

Download files

Source Distribution

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`pycedar.base_trie`

`pycedar.str_trie` / `pycedar.bytes_trie` / `pycedar.unicode_trie`

`pycedar.node`

`pycedar.dict`

Values are C `int` sized, and two of them are reserved

Algorithm	Hash digest
SHA256	`1f77580db5e1fcd060696621686f6d3a61bba21694d6c0cedf2820b76eb45189`
MD5	`10bc8629bb6ab8456d6323a82f824484`
BLAKE2b-256	`de528aef3232da775be1b6b48b0c63080e5482bd05d3b9bad87808b7b9d055b0`

Algorithm	Hash digest
SHA256	`74faa45bba62d14f555bd2a9cbd35964246687acf9540c2814f97f04e3b68e42`
MD5	`43838463a1612b893fcfa510389f512b`
BLAKE2b-256	`775881c761ee35b78f595af67d98616b0124a6beeb99e0c861f3675c03c8249a`

Algorithm	Hash digest
SHA256	`8ea6a91e6d13deec85cb43b7f996d761c040cce1d2cd77a8dee21269ce5c82de`
MD5	`0e19fd64290aef8a19e54fb0a99f8ff5`
BLAKE2b-256	`a6c5ad5b492adc4f28c3995f8b44e7494bba087fafddfd8227c89a25fb45d7e4`

Algorithm	Hash digest
SHA256	`03ccf263c3f3c6adde6939070e2fcbf0305abbac6ed3d02b1764b7352554ef63`
MD5	`741cee12255b0af26c25e60ebb89476b`
BLAKE2b-256	`e030de0e7558358fe5a55c173128b6910a1a9fa8b9d372b740811e48ea0f6d10`

Algorithm	Hash digest
SHA256	`e5a24e97e7779f8ec83e0b8baef2cc4a29ab6a1dcbf2f2cc1cade749018c94ba`
MD5	`db75189c2149ab37f92a50016a198230`
BLAKE2b-256	`736d17fd603594f4fda22eb4c3899823a8df27ce2db336db3b328d9bc9b63156`

Algorithm	Hash digest
SHA256	`9a53d27f931273a91e43eb9dd9bf8dd59b1edd9912ea68c477126f3d9b17898c`
MD5	`936d4c702acae41e0618b286e3bb5961`
BLAKE2b-256	`fd20b5dffc398dcc8618461618cc5a9b72e422fcd2fe5965af36642bacec21e6`

Algorithm	Hash digest
SHA256	`0029089f9f405ed542e853ff98340aaff9757abf304ce23d180ebbda17d2bc14`
MD5	`06f89db9231d440b9dc41285f20de84d`
BLAKE2b-256	`6dc7c2a60c34fbab9d99262f94efdb7b224ac4a9bae67247f116f0f1199b36d9`

Algorithm	Hash digest
SHA256	`b1bca58db0cb071198f750083d4e47f6f02d090b9900a7b2595938361eb1374b`
MD5	`f0be9d3fd9f4f191319b4e2dfbc91ec8`
BLAKE2b-256	`5de1ea1fbbec318b114e6fc0e96926069667f1f7dae2af6df1e21b1f09c4b4f3`

Algorithm	Hash digest
SHA256	`90ad5770b51d568d81241c550b06649a1b9059e00cc81aac3f27806ff423c977`
MD5	`5b3425831810b79a0c99c34e58886e11`
BLAKE2b-256	`8aee33abfd9ba4049aac7fde66f78aeba87910fcc0e7ff73c0ca4f4461e87920`

Algorithm	Hash digest
SHA256	`e277afbb71b5dd95e96926b6a9d35251bfa4de96ef15fb1b9eb4726514db77ec`
MD5	`781e8b0f32f6e467e6439ce78370436e`
BLAKE2b-256	`12d168a3b0c63f6f2086e7e3cc3adf38517ee46bf8101d3421b23a20f01e90c7`