pyahocorasick¶
pyahocorasick is a fast and memory efficient library for exact or approximate multi-pattern string search meaning that you can find multiple key strings occurrences at once in some input text. The library provides an ahocorasick Python module that you can use as a plain dict-like Trie or convert a Trie to an automaton for efficient Aho-Corasick search.
It is implemented in C and tested on Python 2.7 and 3.4+. It works on Linux, Mac and Windows.
The license is BSD-3-clause. Some utilities, such as tests and the pure Python automaton are dedicated to the Public Domain.
Download and source code¶
- You can fetch pyahocorasick from:
Quick start¶
This module is written in C. You need a C compiler installed to compile native CPython extensions. To install:
pip install pyahocorasick
Then create an Automaton:
>>> import ahocorasick
>>> A = ahocorasick.Automaton()
You can use the Automaton class as a trie. Add some string keys and their associated value to this trie. Here we associate a tuple of (insertion index, original string) as a value to each key string we add to the trie:
>>> for idx, key in enumerate('he her hers she'.split()):
... A.add_word(key, (idx, key))
Then check if some string exists in the trie:
>>> 'he' in A
True
>>> 'HER' in A
False
And play with the get()
dict-like method:
>>> A.get('he')
(0, 'he')
>>> A.get('she')
(3, 'she')
>>> A.get('cat', 'not exists')
'not exists'
>>> A.get('dog')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
KeyError
Now convert the trie to an Aho-Corasick automaton to enable Aho-Corasick search:
>>> A.make_automaton()
Then search all occurrences of the keys (the needles) in an input string (our haystack).
Here we print the results and just check that they are correct. The Automaton.iter() method return the results as two-tuples of the end index where a trie key was found in the input string and the associated value for this key. Here we had stored as values a tuple with the original string and its trie insertion order:
>>> for end_index, (insert_order, original_value) in A.iter(haystack):
... start_index = end_index - len(original_value) + 1
... print((start_index, end_index, (insert_order, original_value)))
... assert haystack[start_index:start_index + len(original_value)] == original_value
...
(1, 2, (0, 'he'))
(1, 3, (1, 'her'))
(1, 4, (2, 'hers'))
(4, 6, (3, 'she'))
(5, 6, (0, 'he'))
You can also create an eventually large automaton ahead of time and pickle it to re-load later. Here we just pickle to a string. You would typically pickle to a file instead:
>>> import cPickle
>>> pickled = cPickle.dumps(A)
>>> B = cPickle.loads(pickled)
>>> B.get('he')
(0, 'he')
- See also:
- FAQ and Who is using pyahocorasick? https://github.com/WojciechMula/pyahocorasick/wiki/FAQ#who-is-using-pyahocorasick
Documentation¶
The full documentation including the API overview and reference is published on readthedocs.
Overview
With an Aho-Corasick automaton you can efficiently search all occurrences of multiple strings (the needles) in an input string (the haystack) making a single pass over the input string. With pyahocorasick you can eventually build large automatons and pickle them to reuse them over and over as an indexed structure for fast multi pattern string matching.
One of the advantages of an Aho-Corasick automaton is that the typical worst-case and best-case runtimes are about the same and depends primarily on the size of the input string and secondarily on the number of matches returned. While this may not be the fastest string search algorithm in all cases, it can search for multiple strings at once and its runtime guarantees make it rather unique. Because pyahocorasick is based on a Trie, it stores redundant keys prefixes only once using memory efficiently.
A drawback is that it needs to be constructed and “finalized” ahead of time before you can search strings. In several applications where you search for several pre-defined “needles” in a variable “haystacks” this is actually an advantage.
Aho-Corasick automatons are commonly used for fast multi-pattern matching in intrusion detection systems (such as snort), anti-viruses and many other applications that need fast matching against a pre-defined set of string keys.
Internally an Aho-Corasick automaton is typically based on a Trie with extra data for failure links and an implementation of the Aho-Corasick search procedure.
Behind the scenes the pyahocorasick Python library implements these two data structures: a Trie and an Aho-Corasick string matching automaton. Both are exposed through the Automaton class.
In addition to Trie-like and Aho-Corasick methods and data structures, pyahocorasick also implements dict-like methods: The pyahocorasick Automaton is a Trie a dict-like structure indexed by string keys each associated with a value object. You can use this to retrieve an associated value in a time proportional to a string key length.
pyahocorasick is available in two flavors:
- a CPython C-based extension, compatible with Python 2 and 3.
- a simpler pure Python module, compatible with Python 2 and 3. This is only available in the source repository (not on Pypi) under the py/ directory and has a slightly different API.
Unicode and bytes¶
The type of strings accepted and returned by Automaton
methods are either
unicode or bytes, depending on a compile time settings (preprocessor
definition of AHOCORASICK_UNICODE
as set in setup.py).
The Automaton.unicode
attributes can tell you how the library was built.
On Python 3, unicode is the default. On Python 2, bytes is the default and only value.
Warning
When the library is built with unicode support on Python 3, an Automaton will store 2 or 4 bytes per letter, depending on your Python installation. When built for bytes, only one byte per letter is needed.
Unicode is NOT supported on Python 2 for now.
Build and install from PyPi¶
To install for common operating systems, use pip. Pre-built wheels should be available on Pypi at some point in the future:
pip install pyahocorasick
To build from sources you need to have a C compiler installed and configured which should be standard on Linux and easy to get on MacOSX.
On Windows and Python 2.7 you need the Microsoft Visual C++ Compiler for Python 2.7 (aka. Visual Studio 2008). There have been reports that pyahocorasick does not build yet with MinGW. It may build with cygwin but this has not been tested. If you get this working with these platforms, please report in a ticket!
To build from sources, clone the git repository or download and extract the source archive.
Install pip (and its setuptools companion) and then run (in a virtualenv of course!):
pip install .
If compilation succeeds, the module is ready to use.
Support¶
Support is available through the GitHub issue tracker to report bugs or ask questions.
Contributing¶
You can submit contributions through GitHub pull requests.
Authors¶
The initial author and maintainer is Wojciech Muła. Philippe Ombredanne, the current co-owner, rewrote documentation, setup CI servers and did a whole lot of work to make this module better accessible to end users.
Alphabetic list of authors:
- Andrew Grigorev
- Bogdan
- David Woakes
- Edward Betts
- Frankie Robertson
- Frederik Petersen
- gladtosee
- INADA Naoki
- Jan Fan
- Pastafarianist
- Philippe Ombredanne
- Renat Nasyrov
- Sylvain Zimmer
- Xiaopeng Xu
This library would not be possible without help of many people, who contributed in various ways. They created pull requests, reported bugs as GitHub issues or via direct messages, proposed fixes, or spent their valuable time on testing.
Thank you.
License¶
This library is licensed under very liberal BSD-3-Clause license. Some portions of the code are dedicated to the public domain such as the pure Python automaton and test code.
Full text of license is available in LICENSE file.
Other Aho-Corasick implementations for Python you can consider¶
While pyahocorasick tries to be the finest and fastest Aho Corasick library for Python you may consider these other libraries:
- py_aho_corasick by Jan
- Written in pure Python.
- Poor performance.
- ahocorapy by abusix
- Written in pure Python.
- Better performance than py-aho-corasick.
- Using pypy, ahocorapy’s search performance is only slightly worse than pyahocorasick’s.
- Performs additional suffix shortcutting (more setup overhead, less search overhead for suffix lookups).
- Includes visualization tool for resulting automaton (using pygraphviz).
- MIT-licensed, 100% test coverage, tested on all major python versions (+ pypy)
- noaho by Jeff Donner
- Written in C. Does not return overlapping matches.
- Does not compile on Windows (July 2016).
- No support for the pickle protocol.
- acora by Stefan Behnel
- Written in Cython.
- Large automaton may take a long time to build (July 2016)
- No support for a dict-like protocol to associate a value to a string key.
- ahocorasick by Danny Yoo
- Written in C.
- seems unmaintained (last update in 2005).
- GPL-licensed.
API Overview¶
This is a quick tour of the API for the C ahocorasick module. See the full API doc for more details. The pure Python module has a slightly different interface.
The module ahocorasick
contains a few constants and the main Automaton
class.
Module constants¶
ahocorasick.unicode
— see Unicode and bytesahocorasick.STORE_ANY
,ahocorasick.STORE_INTS
,ahocorasick.STORE_LENGTH
— see Automaton classahocorasick.KEY_STRING
ahocorasick.KEY_SEQUENCE
— see Automaton classahocorasick.EMPTY
,ahocorasick.TRIE
,ahocorasick.AHOCORASICK
— see Automaton Attributesahocorasick.MATCH_EXACT_LENGTH
,ahocorasick.MATCH_AT_MOST_PREFIX
,ahocorasick.MATCH_AT_LEAST_PREFIX
— see description of the keys method
Automaton class¶
Note: Automaton
instances are pickle-able
meaning that you can create ahead of time an eventually large automaton then save it to disk
and re-load it later to reuse it over and over as a persistent multi-string search index.
Internally, Automaton implements the __reduce__() magic method
.
Automaton([value_type], [key_type])
Create a new empty Automaton optionally passing a value_type to indicate what is the type of associated values (default to any Python object type). It can be one ofahocorasick.STORE_ANY
,ahocorasick.STORE_INTS
orahocorasick.STORE_LENGTH
. In the last case the length of the key will be stored in the automaton. The optional argument key_type can beahocorasick.KEY_STRING
orahocorasick.KEY_SEQUENCE
. In the latter case keys will be tuples of integers. The size of integer depends on the version and platform Python is running on, but for versions of Python >= 3.3, it is guaranteed to be 32-bits.
Automaton Trie methods¶
The Automaton class has the following main trie-like methods:
add_word(key, [value]) => bool
- Add a
key
string to the dict-like trie and associate this key with avalue
. remove_word(key) => bool
- Remove a
key
string from the dict-like trie. pop(key) => value
- Remove a
key
string from the dict-like trie and return the associatedvalue
. exists(key) => bool
orkey in ...
- Return True if the key is present in the trie.
match(key) => bool
- Return True if there is a prefix (or key) equal to
key
present in the trie.
Automaton Dictionary-like methods¶
A pyahocorasick Automaton trie behaves more or less like a Python dictionary and implements a subset of dict-like methods. Some of them are:
get(key[, default])
- Return the value associated with the
key
string. Similar to dict.get(). keys([prefix, [wildcard, [how]]]) => yield strings
- Return an iterator on keys.
values([prefix, [wildcard, [how]]]) => yield object
- Return an iterator on values associated with each keys.
items([prefix, [wildcard, [how]]]) => yield tuple (string, object)
- Return an iterator on tuples of (key, value).
Wildcard search¶
The methods keys
, values
and items
can be called with an optional
wildcard. A wildcard character is equivalent to a question mark used in glob
patterns (?) or a dot (.) in regular expressions. You can use any character you
like as a wildcard.
Note that it is not possible to escape a wildcard to match it exactly. You need instead to select another wildcard character not present in the provided prefix. For example:
automaton.keys("hi?", "?") # would match "him", "his"
automaton.keys("XX?", "X") # would match "me?", "he?" or "it?"
Aho-Corasick methods¶
The Automaton class has the following main Aho-Corasick methods:
make_automaton()
- Finalize and create the Aho-Corasick automaton.
iter(string, [start, [end]])
- Perform the Aho-Corasick search procedure using the provided input
string
. Return an iterator of tuples (end_index, value) for keys found in string. iter_long(string, [start, [end]])
- Returns iterator (object of class AutomatonSearchIterLong) that searches for longest, non-overlapping matches.
AutomatonSearchIter class¶
Instances of this class are returned by the iter
method of an Automaton
.
This iterator can be manipulated through its set() method.
set(string, [reset]) => None
Set a new string to search eventually keeping the current Automaton state to continue searching for the next chunk of a string.
For example:
>>> it = A.iter(b"") >>> while True: ... buffer = receive(server_address, 4096) ... if not buffer: ... break ... it.set(buffer) ... for index, value in it: ... print(index, '=>', value)
When
reset
isTrue
then processing is restarted. For example this code:>>> for string in string_set: ... for index, value in A.iter(string) ... print(index, '=>', value)
does the same job as:
>>> it = A.iter(b"") >>> for string in string_set: ... it.set(it, True) ... for index, value in it: ... print(index, '=>', value)
Automaton Attributes¶
The Automaton class has the following attributes:
kind
[readonly]- Return the state of the
Automaton
instance. store
[readonly]- Return the type of values stored in the Automaton as specified at creation.
Saving and loading automaton¶
There is support for two method of saving and loading an automaton:
- the standard
pickle
protocol, - custom
save
andload
methods.
While pickling is more convenient to use, it has quite high memory
requirements. The save
/load
method try to overcome this
problem.
Warning
Neither format of pickle nor save are safe. Although there are a few sanity checks, they are not sufficient to detect all possible input errors.
Pickle¶
import ahocorasick
import pickle
# build automaton
A = ahocorasick.Automaton()
# ... A.add_data, A.make_automaton
# save current state
with open(path, 'wb') as f:
pickle.dump(A, f)
# load saved state
with open(path, 'rb') as f:
B = pickle.load(f)
Save/load methods¶
import ahocorasick
import pickle
# build automaton
A = ahocorasick.Automaton()
# ... A.add_data, A.make_automaton
# save current state
A.save(path, pickle.dumps)
# load saved state
B = ahocorasick.load(path, pickle.loads)
Automaton method save
requires path
to the file which will store data.
If the automaton type is STORE_ANY
, i.e. values associated with words are
any python objects, then save
requires also another argument, a callable.
The callable serializes python object into bytes; in the example above we
use standard pickle dumps
function.
Module method load
also requires path
to file that has data previously
saved. Because at the moment of loading data we don’t know what is the store
attribute of automaton, the second argument - a callable - is required. The
callable must convert back given bytes object into python value, that will be
stored in automaton. Similarly, standard pickle.loads
function can be passed.
Other Automaton methods¶
The Automaton class has a few other interesting methods:
dump() => (list of nodes, list of edges, list of fail links)
- Return a three-tuple of lists describing the Automaton as a graph of
(nodes, edges, failure links).
The source repository and source package also contains the
dump2dot.py
script that convertsdump()
results to a graphviz dot format for convenient visualization of the trie and Automaton data structure. get_stats() => dict
- Return a dictionary containing Automaton statistics. Note that the real size occupied by the data structure could be larger because of internal memory fragmentation that can occur in a memory manager.
__sizeof__() => int
- Return the approximate size in bytes occupied by the Automaton instance. Also available by calling sys.getsizeof(automaton instance).
Examples¶
>>> import ahocorasick
>>> A = ahocorasick.Automaton()
>>> # add some key words to trie
>>> for index, word in enumerate('he her hers she'.split()):
... A.add_word(word, (index, word))
>>> # test that these key words exists in the trie all right
>>> 'he' in A
True
>>> 'HER' in A
False
>>> A.get('he')
(0, 'he')
>>> A.get('she')
(3, 'she')
>>> A.get('cat', '<not exists>')
'<not exists>'
>>> A.get('dog')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
KeyError
>>> A.remove_word('he')
True
>>> A.remove_word('he')
False
>>> A.pop('she')
(3, 'she')
>>> 'she' in A
False
>>> # convert the trie in an Aho-Corasick automaton
>>> A = ahocorasick.Automaton()
>>> for index, word in enumerate('he her hers she'.split()):
... A.add_word(word, (index, word))
>>> A.make_automaton()
>>> # then find all occurrences of the stored keys in a string
>>> for item in A.iter('_hershe_'):
... print(item)
...
(2, (0, 'he'))
(3, (1, 'her'))
(4, (2, 'hers'))
(6, (3, 'she'))
(6, (0, 'he'))
Example of the keys method behavior¶
>>> import ahocorasick
>>> A = ahocorasick.Automaton()
>>> # add some key words to trie
>>> for index, word in enumerate('cat catastropha rat rate bat'.split()):
... A.add_word(word, (index, word))
>>> # Search some prefix
>>> list(A.keys('cat'))
['cat', 'catastropha']
>>> # Search with a wildcard: here '?' is used as a wildcard. You can use any character you like.
>>> list(A.keys('?at', '?', ahocorasick.MATCH_EXACT_LENGTH))
['bat', 'cat', 'rat']
>>> list(A.keys('?at?', '?', ahocorasick.MATCH_AT_MOST_PREFIX))
['bat', 'cat', 'rat', 'rate']
>>> list(A.keys('?at?', '?', ahocorasick.MATCH_AT_LEAST_PREFIX))
['rate']
API Reference¶
Automaton(value_type=ahocorasick.STORE_ANY, [key_type])¶
Create a new empty Automaton. Both value_type
and key_type
are optional.
value_type
is one of these constants:
- ahocorasick.STORE_ANY [default] : The associated value can be any Python object.
- ahocorasick.STORE_LENGTH : The length of an added string key is automatically used as the associated value stored in the trie for that key.
- ahocorasick.STORE_INTS : The associated value must be a 32-bit integer.
key_type
defines the type of data that can be stored in an automaton; it is one of
these constants and defines type of data might be stored:
- ahocorasick.KEY_STRING [default] : string
- ahocorasick.KEY_SEQUENCE : sequences of integers; The size of integer depends the version and platform Python, but for versions of Python >= 3.3, it is guaranteed to be 32-bits.
Examples¶
>>> import ahocorasick
>>> A = ahocorasick.Automaton()
>>> A
<ahocorasick.Automaton object at 0x7f1da1bdf7f0>
>>> B = ahocorasick.Automaton(ahocorasick.STORE_ANY)
>>> B
<ahocorasick.Automaton object at 0x7f1da1bdf6c0>
>>> C = ahocorasick.Automaton(ahocorasick.STORE_INTS, ahocorasick.KEY_STRING)
>>> C
<ahocorasick.Automaton object at 0x7f1da1527f10>
add_word(key, [value]) -> boolean¶
Add a key string to the dict-like trie and associate this key with a value.
value is optional or mandatory depending how the Automaton
instance was
created. Return True if the word key is inserted and did not exists in the
trie or False otherwise. The value associated with an existing word is replaced.
The value is either mandatory or optional:
- If the Automaton was created without argument (the default) as
Automaton()
or withAutomaton(ahocorasik.STORE_ANY)
then the value is required and can be any Python object. - If the Automaton was created with
Automaton(ahocorasik.STORE_INTS)
then the value is optional. If provided it must be an integer, otherwise it defaults tolen(automaton)
which is therefore the order index in which keys are added to the trie. - If the Automaton was created with
Automaton(ahocorasik.STORE_LENGTH)
then associating a value is not allowed -len(word)
is saved automatically as a value instead.
Calling add_word() invalidates all iterators only if the new key did not exist in the trie so far (i.e. the method returned True).
Examples¶
>>> import ahocorasick
>>> A = ahocorasick.Automaton()
>>> A.add_word("pyahocorasick")
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ValueError: A value object is required as second argument.
>>> A.add_word("pyahocorasick", (42, 'text'))
True
>>> A.get("pyhocorasick")
(42, 'text')
>>> A.add_word("pyahocorasick", 12)
False
>>> A.get("pyhocorasick")
12
>>> import ahocorasick
>>> B = ahocorasick.Automaton(ahocorasick.STORE_INTS)
>>> B.add_word("cat")
True
>>> B.get()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
IndexError: tuple index out of range
>>> B.get("cat")
1
>>> B.add_word("dog")
True
>>> B.get("dog")
2
>>> B.add_word("tree", 42)
True
>>> B.get("tree")
42
>>> B.add_word("cat", 43)
False
>>> B.get("cat")
43
exists(key) -> boolean¶
Return True if the key
is present in the trie. Same as using the ‘in’ keyword.
Examples¶
>>> import ahocorasick
>>> A = ahocorasick.Automaton()
>>> A.add_word("cat", 1)
True
>>> A.exists("cat")
True
>>> A.exists("dog")
False
>>> 'elephant' in A
False
>>> 'cat' in A
True
get(key[, default])¶
Return the value associated with the key string.
Raise a KeyError
exception if the key is not in the trie and no default is provided.
Return the optional default value if provided and the key is not in the trie.
Example¶
>>> import ahocorasick
>>> A = ahocorasick.Automaton()
>>> A.add_word("cat", 42)
True
>>> A.get("cat")
42
>>> A.get("dog")
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
KeyError
>>> A.get("dog", "good dog")
'good dog'
longest_prefix(string) => integer¶
Return the length of the longest prefix of string that exists in the trie.
Examples¶
>>> import ahocorasick
>>> A = ahocorasick.Automaton()
>>> A.add_word("he", True)
True
>>> A.add_word("her", True)
True
>>> A.add_word("hers", True)
True
>>> A.longest_prefix("she")
0
>>> A.longest_prefix("herself")
4
match(key) -> bool¶
Return True if there is a prefix (or key) equal to key present in the trie.
For example if the key ‘example’ has been added to the trie, then calls to match(‘e’), match(‘ex’), …, match(‘exampl’) or match(‘example’) all return True. But exists() is True only when calling exists(‘example’).
Examples¶
>>> import ahocorasick
>>> A = ahocorasick.Automaton()
>>> A.add_word("example", True)
True
>>> A.match("e")
True
>>> A.match("ex")
True
>>> A.match("exa")
True
>>> A.match("exam")
True
>>> A.match("examp")
True
>>> A.match("exampl")
True
>>> A.match("example")
True
>>> A.match("examples")
False
>>> A.match("python")
False
len() -> integer¶
Return the number of distinct keys added to the trie.
Examples¶
>>> import ahocorasick
>>> A = ahocorasick.Automaton()
>>> len(A)
0
>>> A.add_word("python", 1)
True
>>> len(A)
1
>>> A.add_word("elephant", True)
True
>>> len(A)
2
remove_word(word) -> bool¶
Remove given word from a trie. Return True if words was found, False otherwise.
Examples¶
>>> import ahocorasick
>>> A = ahocorasick.Automaton()
>>> A.add_word("cat", 1)
True
>>> A.add_word("dog", 2)
True
>>> A.remove_word("cat")
True
>>> A.remove_word("cat")
False
>>> A.remove_word("dog")
True
>>> A.remove_word("dog")
False
>>>
pop(word)¶
Remove given word from a trie and return associated values. Raise a KeyError
if the word was not found.
Examples¶
>>> import ahocorasick
>>> A = ahocorasick.Automaton()
>>> A.add_word("cat", 1)
True
>>> A.add_word("dog", 2)
True
>>> A.pop("elephant")
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
KeyError
>>> A.pop("cat")
1
>>> A.pop("dog")
2
>>> A.pop("cat")
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
KeyError
clear()¶
Remove all keys from the trie. This method invalidates all iterators.
Examples¶
>>> import ahocorasick
>>> A = ahocorasick.Automaton()
>>> A.add_word("cat", 1)
True
>>> A.add_word("dog", 2)
True
>>> A.add_word("elephant", 3)
True
>>> len(A)
3
>>> A.clear()
>>> len(A)
0
keys([prefix, [wildcard, [how]]])¶
Return an iterator on keys.
If the optional prefix
string is provided, only yield keys starting
with this prefix.
If the optional wildcard
is provided as a single character string,
then the prefix is treated as a simple pattern using this character
as a wildcard.
The optional how
argument is used to control how strings are matched
using one of these possible values:
- ahocorasick.MATCH_EXACT_LENGTH (default) Yield matches that have the same exact length as the prefix length.
- ahocorasick.MATCH_AT_LEAST_PREFIX Yield matches that have a length greater or equal to the prefix length.
- ahocorasick.MATCH_AT_MOST_PREFIX Yield matches that have a length lesser or equal to the prefix length.
items([prefix, [wildcard, [how]]])¶
Return an iterator on tuples of (key, value). Keys are matched optionally to the prefix using the same logic and arguments as in the keys() method.
values([prefix, [wildcard, [how]]])¶
Return an iterator on values associated with each keys. Keys are matched optionally to the prefix using the same logic and arguments as in the keys() method.
make_automaton()¶
Finalize and create the Aho-Corasick automaton based on the keys already added
to the trie. This does not require additional memory. After successful creation
the Automaton.kind
attribute is set to ahocorasick.AHOCORASICK
.
iter(string, [start, [end]], ignore_white_space=False)¶
Perform the Aho-Corasick search procedure using the provided input string.
Return an iterator of tuples (end_index
, value
) for keys found in
string where:
end_index
is the end index in the input string where a trie key string was found.value
is the value associated with the found key string.
The start
and end
optional arguments can be used to limit the search
to an input string slice as in string[start:end]
.
The ignore_white_space
optional arguments can be used to ignore white
spaces from input string.
iter_long(string, [start, [end]])¶
Perform the modified Aho-Corasick search procedure which matches the longest words from set.
Return an iterator of tuples (end_index
, value
) for keys found in
string where:
end_index
is the end index in the input string where a trie key string was found.value
is the value associated with the found key string.
The start
and end
optional arguments can be used to limit the search
to an input string slice as in string[start:end]
.
Example¶
The default Aho-Corasick algorithm returns all occurrences of words stored
in the automaton, including substring of other words from string. Method
iter_long
reports only the longest match.
For set of words {“he”, “her”, “here”} and a needle “he here her” the default algorithm finds following words: “he”, “he”, “her”, “here”, “he”, “her”, while the modified one yields only: “he”, “here”, “her”.
>>> import ahocorasick
>>> A = ahocorasick.Automaton()
>>> A.add_word("he", "he")
True
>>> A.add_word("her", "her")
True
>>> A.add_word("here", "here")
True
>>> A.make_automaton()
>>> needle = "he here her"
>>> list(A.iter_long(needle))
[(1, 'he'), (6, 'here'), (10, 'her')]
>>> list(A.iter(needle))
[(1, 'he'), (4, 'he'), (5, 'her'), (6, 'here'), (9, 'he'), (10, 'her')]
find_all(string, callback, [start, [end]])¶
Perform the Aho-Corasick search procedure using the provided input string
and iterate over the matching tuples (end_index
, value
) for keys found
in string. Invoke the callback
callable for each matching tuple.
The callback callable must accept two positional arguments: - end_index is the end index in the input string where a trie key string was found. - value is the value associated with the found key string.
The start and end optional arguments can be used to limit the search to an input string slice as in string[start:end].
Equivalent to a loop on iter() calling a callable at each iteration.
__reduce__()¶
Return pickle-able data for this automaton instance.
save(path, serializer)¶
Save content of automaton in an on-disc file.
Serializer
is a callable object that is used when automaton store
type is STORE_ANY
. This method converts a python object into
bytes; it can be pickle.dumps
.
load(path, deserializer) => Automaton¶
Load automaton previously stored on disc using save
method.
Deserializer
is a callable object which converts bytes back into
python object; it can be pickle.loads
.
Return the approximate size in bytes occupied by the Automaton instance in memory excluding the size of associated objects when the Automaton is created with Automaton() or Automaton(ahocorasick.STORE_ANY).
get_stats() -> dict¶
Return a dictionary containing Automaton statistics.
- nodes_count - total number of nodes
- words_count - number of distinct words (same as
len(automaton)
) - longest_word - length of the longest word
- links_count - number of edges
- sizeof_node - size of single node in bytes
- total_size - total size of trie in bytes (about nodes_count * size_of node + links_count * size of pointer).
Examples¶
>>> import ahocorasick
>>> A = ahocorasick.Automaton()
>>> A.add_word("he", None)
True
>>> A.add_word("her", None)
True
>>> A.add_word("hers", None)
True
>>> A.get_stats()
{'nodes_count': 5, 'words_count': 3, 'longest_word': 4, 'links_count': 4, 'sizeof_node': 40, 'total_size': 232}
dump()¶
Return a three-tuple of lists describing the Automaton as a graph of nodes, edges, failure links.
- nodes: each item is a pair (node id, end of word marker)
- edges: each item is a triple (node id, label char, child node id)
- failure links: each item is a pair (source node id, node if connected by fail node)
For each of these, the node id is a unique number and a label is a number.
set(string, reset=False)¶
Set a new string to search. When the reset argument is False (default) then the Aho-Corasick procedure is continued and the internal state of the Automaton and end index of the string being searched are not reset. This allow to search for large strings in multiple smaller chunks.