retrie
retrie offers fast methods to match and replace (sequences of) strings based on efficient Trie-based regex unions.
Trie
Instead of matching against a simple regex union, which becomes slow for large sets of words, a more efficient regex pattern can be compiled using a Trie structure:
from retrie.trie import Trie
trie = Trie()
for term in ["abc", "foo", "abs"]:
trie.add(term)
assert trie.pattern() == "(?:ab[cs]|foo)" # equivalent to but faster than "(?:abc|abs|foo)"
trie.add("absolute")
assert trie.pattern() == "(?:ab(?:c|s(?:olute)?)|foo)"
trie.add("abx")
assert trie.pattern() == "(?:ab(?:[cx]|s(?:olute)?)|foo)"
trie.add("abxy")
assert trie.pattern() == "(?:ab(?:c|s(?:olute)?|xy?)|foo)"Installation
This pure-Python, OS independent package is available on PyPI:
$ pip install retrieUsage
The following objects are all subclasses of retrie.retrie.Retrie, which handles filling the Trie and compiling the corresponding regex pattern.
Blacklist
The Blacklist object can be used to filter out bad occurences in a text or a sequence of strings:
from retrie.retrie import Blacklist
# check out docstrings and methods
help(Blacklist)
blacklist = Blacklist(["abc", "foo", "abs"], match_substrings=False)
blacklist.compiled
# re.compile(r'(?<=\b)(?:ab[cs]|foo)(?=\b)', re.IGNORECASE|re.UNICODE)
assert not blacklist.is_blacklisted("a foobar")
assert tuple(blacklist.filter(("good", "abc", "foobar"))) == ("good", "foobar")
assert blacklist.cleanse_text(("good abc foobar")) == "good foobar"
blacklist = Blacklist(["abc", "foo", "abs"], match_substrings=True)
blacklist.compiled
# re.compile(r'(?:ab[cs]|foo)', re.IGNORECASE|re.UNICODE)
assert blacklist.is_blacklisted("a foobar")
assert tuple(blacklist.filter(("good", "abc", "foobar"))) == ("good",)
assert blacklist.cleanse_text(("good abc foobar")) == "good bar"Whitelist
Similar methods are available for the Whitelist object:
from retrie.retrie import Whitelist
# check out docstrings and methods
help(Whitelist)
whitelist = Whitelist(["abc", "foo", "abs"], match_substrings=False)
whitelist.compiled
# re.compile(r'(?<=\b)(?:ab[cs]|foo)(?=\b)', re.IGNORECASE|re.UNICODE)
assert not whitelist.is_whitelisted("a foobar")
assert tuple(whitelist.filter(("bad", "abc", "foobar"))) == ("abc",)
assert whitelist.cleanse_text(("bad abc foobar")) == "abc"
whitelist = Whitelist(["abc", "foo", "abs"], match_substrings=True)
whitelist.compiled
# re.compile(r'(?:ab[cs]|foo)', re.IGNORECASE|re.UNICODE)
assert whitelist.is_whitelisted("a foobar")
assert tuple(whitelist.filter(("bad", "abc", "foobar"))) == ("abc", "foobar")
assert whitelist.cleanse_text(("bad abc foobar")) == "abcfoo"Replacer
The Replacer object does a fast single-pass search & replace for occurrences of replacement_mapping.keys() with corresponding values.
from retrie.retrie import Replacer
# check out docstrings and methods
help(Replacer)
replacement_mapping = dict(zip(["abc", "foo", "abs"], ["new1", "new2", "new3"]))
replacer = Replacer(replacement_mapping, match_substrings=True)
replacer.compiled
# re.compile(r'(?:ab[cs]|foo)', re.IGNORECASE|re.UNICODE)
assert replacer.replace("ABS ...foo... foobar") == "new3 ...new2... new2bar"
replacer = Replacer(replacement_mapping, match_substrings=False)
replacer.compiled
# re.compile(r'\b(?:ab[cs]|foo)\b', re.IGNORECASE|re.UNICODE)
assert replacer.replace("ABS ...foo... foobar") == "new3 ...new2... foobar"
replacer = Replacer(replacement_mapping, match_substrings=False, re_flags=None)
replacer.compiled # on py3, re.UNICODE is always enabled
# re.compile(r'\b(?:ab[cs]|foo)\b')
assert replacer.replace("ABS ...foo... foobar") == "ABS ...new2... foobar"
replacer = Replacer(replacement_mapping, match_substrings=False, word_boundary=" ")
replacer.compiled
# re.compile(r'(?<= )(?:ab[cs]|foo)(?= )', re.IGNORECASE|re.UNICODE)
assert replacer.replace(". ABS ...foo... foobar") == ". new3 ...foo... foobar"Development
Run make help for options like installing for development, linting and testing.