Skip to main content

Trie-search is a package for text pattern search using marisa-trie

Project description

Trie-search is a package for text pattern search using marisa-trie.

Installation

$ pip install trie-search

Usage

Create trie dictionary

Before using this package, you need to create trie dictionary, or prepare a list of patterns.

The following example simply creates trie dictionary of marisa_trie.Trie from list of article titles in English version of Wikipedia, and saves it to ./example/triedict.

$ cd ./example
$ curl https://dumps.wikimedia.org/jawiki/20170101/enwiki-20170101-all-titles-in-ns0.gz | gzcat | python create_triedict.py

NOTICE : This script will consume more than 2GB memory.

trie_search.TrieSearch

Create an instance, and load dictionary:

>>> import trie_search
>>> trie = trie_search.TrieSearch(filepath='./example/triedict')

If you have list or tuple object of patterns, you can create an instance as follows:

>>> patterns = [u'pattern1', u'pattern2', u'pattern3']
>>> trie = trie_search.TrieSearch(patterns)

TrieSearch.search_all_patterns

Search all patterns in an input text:

>>> text = (u'in computer science , a trie , also called digital tree and '
...         u'sometimes radix tree or prefix tree ( as they can be searched '
...         u'by prefixes ) , is a kind of search tree - an ordered tree data '
...         u'structure that is used to store a dynamic set or associative array '
...         u'where the keys are usually strings .')
>>> for pattern, start_idx in trie.search_all_patterns(text):
...     print pattern, start_idx
...
in 0
computer 3
computer science 3
science 12
, 20
a 22
trie 24
, 29
also 31
called 36
digital 43
... skipped ...
array 246
where 252
where the 252
the 258
the keys 258
keys 262
are 267
usually 271
strings 279
  • The text is the 1st sentence of https://en.wikipedia.org/wiki/Trie. For normalization, remove capitalizations and add single white space before/after symbols.

  • search_all_patterns returns an iterator. Each searched pattern is represented as a tuple (pattern_string, pattern_start_index). The results are sorted by the start index. If you want to get the result as a list object, use list function as follow:

    >>> patterns = list(trie.search_all_patterns(text))

TrieSearch.search_longest_patterns

Search longest patterns in an input text:

>>> for pattern, start_idx in trie.search_longest_patterns(text):
...     print pattern, start_idx
...
in 0
computer science 3
, 20
a 22
trie 24
, 29
also 31
called 36
digital tree 43
and 56
sometimes 60
radix tree 70
or 81
prefix tree 84
( 96
as 98
they 101
can 106
be 110
by 122
prefixes 125
) 134
, 136
is a 138
kind 143
of 148
search tree 151
- 163
an 165
ordered tree data structure 168
that 196
is 201
used to 204
store 212
a 218
dynamic set 220
or 232
associative array 235
where the 253
the keys 259
are 268
usually 272
strings 280
  • search_all_patterns also returns an iterator. The result sorted by the length of patterns. In the above example, the result is re-sorted by the start index.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

trie-search-0.1.5.tar.gz (4.5 kB view details)

Uploaded Source

Built Distribution

trie_search-0.1.5-py2.py3-none-any.whl (6.4 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file trie-search-0.1.5.tar.gz.

File metadata

  • Download URL: trie-search-0.1.5.tar.gz
  • Upload date:
  • Size: 4.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for trie-search-0.1.5.tar.gz
Algorithm Hash digest
SHA256 2ce3b7f2505520a15397bedd8d72b1f0e1ab77291ac6c4c1c74e543a631b60d4
MD5 7065df233af45ba8f1868ba3f18e3047
BLAKE2b-256 f0a98ba8b5fd7e5e00a23b9e79391a87f1d23ed8df139f7894bc2219e3ac1246

See more details on using hashes here.

Provenance

File details

Details for the file trie_search-0.1.5-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for trie_search-0.1.5-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 bfa48763d2fd89a141beb5652047140ff764d1bd356c5f68027ba34db11bccd0
MD5 001ebde065b929a0690280e2fa3f33ce
BLAKE2b-256 ee4e551ab20da1cb35113ba4a6a700d507d90e48c8a42d7f95d1c461951a10f6

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page