#!/usr/bin/env python3
+# © Copyright 2021-2022, Scott Gasch
+
+"""A fast word unscrambler library."""
+
import logging
from typing import Dict, Mapping, Optional
logger = logging.getLogger(__name__)
letters_bits = 32
-letters_mask = 2 ** letters_bits - 1
+letters_mask = 2**letters_bits - 1
fprint_bits = 52
-fprint_mask = (2 ** fprint_bits - 1) << letters_bits
+fprint_mask = (2**fprint_bits - 1) << letters_bits
fprint_feature_bit = {
'e': 0,
lookup methods support a "fuzzy match" argument that can be set to
request similar words that do not match exactly in addition to any
exact matches.
-
"""
def __init__(self, indexfile: Optional[str] = None):
+ """
+ Constructs an unscrambler.
+
+ Args:
+ indexfile: overrides the default indexfile location if provided
+ """
+
# Cached index per instance.
self.sigs = []
self.words = []
- filename = self.get_indexfile(indexfile)
+ filename = Unscrambler.get_indexfile(indexfile)
with open(filename, 'r') as rf:
lines = rf.readlines()
for line in lines:
self.sigs.append(isig)
self.words.append(word)
- def get_indexfile(self, indexfile: Optional[str]) -> str:
+ @staticmethod
+ def get_indexfile(indexfile: Optional[str]) -> str:
+ """Returns the current indexfile location."""
if indexfile is None:
if 'unscrambler_default_indexfile' in config.config:
- indexfile = config.config['unscramble_indexfile']
+ indexfile = config.config['unscrambler_default_indexfile']
else:
indexfile = "/usr/share/dict/sparse_index"
else:
# 52 bits
@staticmethod
- def _compute_word_fingerprint(word: str, population: Mapping[str, int]) -> int:
+ def _compute_word_fingerprint(population: Mapping[str, int]) -> int:
fp = 0
for pair in sorted(population.items(), key=lambda x: x[1], reverse=True):
letter = pair[0]
if letter in fprint_feature_bit:
- count = pair[1]
- if count > 3:
- count = 3
+ count = min(pair[1], 3)
shift = fprint_feature_bit[letter]
s = count << shift
fp |= s
# 32 bits
@staticmethod
def _compute_word_letter_sig(
- letter_sigs: Mapping[str, int],
+ lsigs: Mapping[str, int],
word: str,
population: Mapping[str, int],
) -> int:
sig = 0
for pair in sorted(population.items(), key=lambda x: x[1], reverse=True):
letter = pair[0]
- if letter not in letter_sigs:
+ if letter not in lsigs:
continue
- s = letter_sigs[letter]
+ s = lsigs[letter]
count = pair[1]
if count > 1:
s <<= count
s |= count
s &= letters_mask
sig ^= s
- length = len(word)
- if length > 31:
- length = 31
+ length = min(len(word), 31)
sig ^= length << 8
sig &= letters_mask
return sig
the word and their frequencies. We try to cluster "similar"
words close to each other in the signature space.
+ Args:
+ word: the word to compute a signature for
+
+ Returns:
+ The word's signature.
+
>>> train = Unscrambler.compute_word_sig('train')
>>> train
23178969883741
"""
population = list_utils.population_counts(word)
- fprint = Unscrambler._compute_word_fingerprint(word, population)
+ fprint = Unscrambler._compute_word_fingerprint(population)
letter_sig = Unscrambler._compute_word_letter_sig(letter_sigs, word, population)
assert fprint & letter_sig == 0
sig = fprint | letter_sig
@staticmethod
def repopulate(
- letter_sigs: Dict[str, int],
dictfile: str = '/usr/share/dict/words',
indexfile: str = '/usr/share/dict/sparse_index',
) -> None:
- """Before calling this method, change letter_sigs from the default above
- unless you want to populate the same exact files.
+ """
+ Repopulates the indexfile.
+
+ .. warning::
+ Before calling this method, change letter_sigs from the
+ default above unless you want to populate the same exact
+ files.
"""
words_by_sigs: Dict[int, str] = {}
seen = set()
for word in f:
word = word.replace('\n', '')
word = word.lower()
- sig = Unscrambler.compute_word_sig(letter_sigs, word)
- logger.debug("%s => 0x%x" % (word, sig))
+ sig = Unscrambler.compute_word_sig(word)
+ logger.debug("%s => 0x%x", word, sig)
if word in seen:
continue
seen.add(word)
if sig in words_by_sigs:
- words_by_sigs[sig] += ",%s" % word
+ words_by_sigs[sig] += f",{word}"
else:
words_by_sigs[sig] = word
with open(indexfile, 'w') as f:
"""Looks up a potentially scrambled word optionally including near
"fuzzy" matches.
+ Args:
+ word: the word to lookup
+ window_size: the number of nearby fuzzy matches to return
+
+ Returns:
+ A dict of word -> bool containing unscrambled words with (close
+ to or precisely) the same letters as the input word. The bool
+ values in this dict indicate whether the key word is an exact
+ or near match. The count of entries in this dict is controlled
+ by the window_size param.
+
>>> u = Unscrambler()
>>> u.lookup('eanycleocipd', window_size=0)
{'encyclopedia': True}
-
"""
sig = Unscrambler.compute_word_sig(word)
return self.lookup_by_sig(sig, window_size=window_size)
a previous call to Unscrambler.compute_word_sig. Optionally returns
near "fuzzy" matches.
+ Args:
+ sig: the signature of the word to lookup (see :meth:`compute_word_sig`
+ to generate these signatures).
+ window_size: the number of nearby fuzzy matches to return
+
+ Returns:
+ A dict of word -> bool containing unscrambled words with (close
+ to or precisely) the same letters as the input word. The bool
+ values in this dict indicate whether the key word is an exact
+ or near match. The count of entries in this dict is controlled
+ by the window_size param.
+
>>> sig = Unscrambler.compute_word_sig('sunepsapetuargiarin')
>>> sig
18491949645300288339
>>> u = Unscrambler()
>>> u.lookup_by_sig(sig)
{'pupigerous': False, 'pupigenous': False, 'unpurposing': False, 'superpurgation': False, 'unsupporting': False, 'superseptuaginarian': True, 'purpurogallin': False, 'scuppaug': False, 'purpurigenous': False, 'purpurogenous': False, 'proppage': False}
-
"""
ret = {}
- (exact, location) = list_utils.binary_search(self.sigs, sig)
+ (_, location) = list_utils.binary_search(self.sigs, sig)
start = location - window_size
- if start < 0:
- start = 0
+ start = max(start, 0)
end = location + 1 + window_size
- if end > len(self.words):
- end = len(self.words)
+ end = min(end, len(self.words))
for x in range(start, end):
word = self.words[x]
projects / python_utils.git / blobdiff