"""
Spellchecker.
Useful to check several dictionaries at once.
To avoid iterating over a pile of dictionaries, it is assumed that 3 are enough:
- the main dictionary, bundled with the package
- the extended dictionary
- the community dictionary, added by an organization
- the personal dictionary, created by the user for its own convenience
"""
import importlib
import traceback
from . import ibdawg
from . import tokenizer
dDefaultDictionaries = {
"fr": "fr-allvars.bdic",
"en": "en.bdic"
}
class SpellChecker ():
"SpellChecker: wrapper for the IBDAWG class"
def __init__ (self, sLangCode, sfMainDic="", sfCommunityDic="", sfPersonalDic=""):
"returns True if the main dictionary is loaded"
self.sLangCode = sLangCode
if not sfMainDic:
sfMainDic = dDefaultDictionaries.get(sLangCode, "")
self.oMainDic = self._loadDictionary(sfMainDic, True)
self.oCommunityDic = self._loadDictionary(sfCommunityDic)
self.oPersonalDic = self._loadDictionary(sfPersonalDic)
self.bCommunityDic = bool(self.oCommunityDic)
self.bPersonalDic = bool(self.oPersonalDic)
self.oTokenizer = None
# Default suggestions
self.dDefaultSugg = None
self.loadSuggestions(sLangCode)
# storage
self.bStorage = False
self._dMorphologies = {} # key: flexion, value: list of morphologies
self._dLemmas = {} # key: flexion, value: list of lemmas
def _loadDictionary (self, source, bNecessary=False):
"returns an IBDAWG object"
if not source:
return None
try:
return ibdawg.IBDAWG(source)
except Exception as e:
if bNecessary:
raise Exception(str(e), "Error: <" + str(source) + "> not loaded.")
print("Error: <" + str(source) + "> not loaded.")
traceback.print_exc()
return None
def _loadTokenizer (self):
self.oTokenizer = tokenizer.Tokenizer(self.sLangCode)
def getTokenizer (self):
"load and return the tokenizer object"
if not self.oTokenizer:
self._loadTokenizer()
return self.oTokenizer
def setMainDictionary (self, source):
"returns True if the dictionary is loaded"
self.oMainDic = self._loadDictionary(source, True)
return bool(self.oMainDic)
def setCommunityDictionary (self, source, bActivate=True):
"returns True if the dictionary is loaded"
self.oCommunityDic = self._loadDictionary(source)
self.bCommunityDic = False if not bActivate else bool(self.oCommunityDic)
return bool(self.oCommunityDic)
def setPersonalDictionary (self, source, bActivate=True):
"returns True if the dictionary is loaded"
self.oPersonalDic = self._loadDictionary(source)
self.bPersonalDic = False if not bActivate else bool(self.oPersonalDic)
return bool(self.oPersonalDic)
def activateCommunityDictionary (self):
"activate community dictionary (if available)"
self.bCommunityDic = bool(self.oCommunityDic)
def activatePersonalDictionary (self):
"activate personal dictionary (if available)"
self.bPersonalDic = bool(self.oPersonalDic)
def deactivateCommunityDictionary (self):
"deactivate community dictionary"
self.bCommunityDic = False
def deactivatePersonalDictionary (self):
"deactivate personal dictionary"
self.bPersonalDic = False
# Default suggestions
def loadSuggestions (self, sLangCode):
"load default suggestion module for <sLangCode>"
try:
suggest = importlib.import_module("."+sLangCode, "grammalecte.graphspell")
except ImportError:
print("No suggestion module for language <"+sLangCode+">")
return
self.dDefaultSugg = suggest.dSugg
# Storage
def activateStorage (self):
"store all lemmas and morphologies retrieved from the word graph"
self.bStorage = True
def deactivateStorage (self):
"stop storing all lemmas and morphologies retrieved from the word graph"
self.bStorage = False
def clearStorage (self):
"clear all stored data"
self._dLemmas.clear()
self._dMorphologies.clear()
# parse text functions
def parseParagraph (self, sText, bSpellSugg=False):
"return a list of tokens where token value doesn’t exist in the word graph"
if not self.oTokenizer:
self._loadTokenizer()
aSpellErrs = []
for dToken in self.oTokenizer.genTokens(sText):
if dToken['sType'] == "WORD" and not self.isValidToken(dToken['sValue']):
if bSpellSugg:
dToken['aSuggestions'] = []
for lSugg in self.suggest(dToken['sValue']):
dToken['aSuggestions'].extend(lSugg)
aSpellErrs.append(dToken)
return aSpellErrs
def countWordsOccurrences (self, sText, bByLemma=False, bOnlyUnknownWords=False, dWord={}):
"""count word occurrences.
<dWord> can be used to cumulate count from several texts."""
if not self.oTokenizer:
self._loadTokenizer()
for dToken in self.oTokenizer.genTokens(sText):
if dToken['sType'] == "WORD":
if bOnlyUnknownWords:
if not self.isValidToken(dToken['sValue']):
dWord[dToken['sValue']] = dWord.get(dToken['sValue'], 0) + 1
else:
if not bByLemma:
dWord[dToken['sValue']] = dWord.get(dToken['sValue'], 0) + 1
else:
for sLemma in self.getLemma(dToken['sValue']):
dWord[sLemma] = dWord.get(sLemma, 0) + 1
return dWord
# IBDAWG functions
def isValidToken (self, sToken):
"checks if sToken is valid (if there is hyphens in sToken, sToken is split, each part is checked)"
if self.oMainDic.isValidToken(sToken):
return True
if self.bCommunityDic and self.oCommunityDic.isValidToken(sToken):
return True
if self.bPersonalDic and self.oPersonalDic.isValidToken(sToken):
return True
return False
def isValid (self, sWord):
"checks if sWord is valid (different casing tested if the first letter is a capital)"
if self.oMainDic.isValid(sWord):
return True
if self.bCommunityDic and self.oCommunityDic.isValid(sWord):
return True
if self.bPersonalDic and self.oPersonalDic.isValid(sWord):
return True
return False
def lookup (self, sWord):
"checks if sWord is in dictionary as is (strict verification)"
if self.oMainDic.lookup(sWord):
return True
if self.bCommunityDic and self.oCommunityDic.lookup(sWord):
return True
if self.bPersonalDic and self.oPersonalDic.lookup(sWord):
return True
return False
def getMorph (self, sWord):
"retrieves morphologies list, different casing allowed"
if self.bStorage and sWord in self._dMorphologies:
return self._dMorphologies[sWord]
lMorph = self.oMainDic.getMorph(sWord)
if self.bCommunityDic:
lMorph.extend(self.oCommunityDic.getMorph(sWord))
if self.bPersonalDic:
lMorph.extend(self.oPersonalDic.getMorph(sWord))
if self.bStorage:
self._dMorphologies[sWord] = lMorph
self._dLemmas[sWord] = set([ s[1:s.find("/")] for s in lMorph ])
return lMorph
def getLemma (self, sWord):
"retrieves lemmas"
if self.bStorage:
if sWord not in self._dLemmas:
self.getMorph(sWord)
return self._dLemmas[sWord]
return set([ s[1:s.find("/")] for s in self.getMorph(sWord) ])
def suggest (self, sWord, nSuggLimit=10):
"generator: returns 1, 2 or 3 lists of suggestions"
if self.dDefaultSugg:
if sWord in self.dDefaultSugg:
yield self.dDefaultSugg[sWord].split("|")
elif sWord.istitle() and sWord.lower() in self.dDefaultSugg:
lRes = self.dDefaultSugg[sWord.lower()].split("|")
yield list(map(lambda sSugg: sSugg[0:1].upper()+sSugg[1:], lRes))
else:
yield self.oMainDic.suggest(sWord, nSuggLimit)
else:
yield self.oMainDic.suggest(sWord, nSuggLimit)
if self.bCommunityDic:
yield self.oCommunityDic.suggest(sWord, nSuggLimit)
if self.bPersonalDic:
yield self.oPersonalDic.suggest(sWord, nSuggLimit)
def select (self, sFlexPattern="", sTagsPattern=""):
"generator: returns all entries which flexion fits <sFlexPattern> and morphology fits <sTagsPattern>"
yield from self.oMainDic.select(sFlexPattern, sTagsPattern)
if self.bCommunityDic:
yield from self.oCommunityDic.select(sFlexPattern, sTagsPattern)
if self.bPersonalDic:
yield from self.oPersonalDic.select(sFlexPattern, sTagsPattern)
def drawPath (self, sWord):
"draw the path taken by <sWord> within the word graph: display matching nodes and their arcs"
self.oMainDic.drawPath(sWord)
if self.bCommunityDic:
print("-----")
self.oCommunityDic.drawPath(sWord)
if self.bPersonalDic:
print("-----")
self.oPersonalDic.drawPath(sWord)
def getSimilarEntries (self, sWord, nSuggLimit=10):
"return a list of tuples (similar word, stem, morphology)"
lResult = self.oMainDic.getSimilarEntries(sWord, nSuggLimit)
if self.bCommunityDic:
lResult.extend(self.oCommunityDic.getSimilarEntries(sWord, nSuggLimit))
if self.bPersonalDic:
lResult.extend(self.oPersonalDic.getSimilarEntries(sWord, nSuggLimit))
return lResult