def testInitWithCorrectDictWorks(self):
self.voikko.terminate()
self.voikko = Voikko(u"fi-x-standard")
self.failIf(self.voikko.spell(u"amifostiini"))
self.voikko.terminate()
self.voikko = Voikko(u"fi-x-medicine")
self.failUnless(self.voikko.spell(u"amifostiini"))
def initVoikko():
global _voikko
for allowedDict in ALLOWED_DICTS:
v = Voikko(allowedDict)
v.setIgnoreDot(False)
v.setAcceptUnfinishedParagraphsInGc(True)
_voikko[allowedDict] = v
for d in Voikko.listDicts():
tag = d.language + u"-x-" + d.variant
if tag in ALLOWED_DICTS:
_dictInfo[tag] = d
def __openHandleWithVariant(self, language, fullVariant):
logging.debug("VoikkoHandlePool.__openHandleWithVariant")
try:
voikkoHandle = Voikko(fullVariant, self.getDictionaryPath())
self.__handles[language] = voikkoHandle
for booleanOpt, booleanValue in self.__globalBooleanOptions.items(
):
voikkoHandle.setBooleanOption(booleanOpt, booleanValue)
for integerOpt, integerValue in self.__globalIntegerOptions.items(
):
voikkoHandle.setIntegerOption(integerOpt, integerValue)
return voikkoHandle
except VoikkoException as e:
self.__initializationErrors[language] = e.args[0]
return None
def testAnotherObjectCanBeCreatedUsedAndDeletedInParallel(self):
medicalVoikko = Voikko(u"fi-x-medicine")
self.failUnless(medicalVoikko.spell(u"amifostiini"))
self.failIf(self.voikko.spell(u"amifostiini"))
del medicalVoikko
self.failIf(self.voikko.spell(u"amifostiini"))
def setUp(self):
self.voikko = Voikko(u"fi")
def testInitWithPathWorks(self):
# TODO: better test
self.voikko.terminate()
self.voikko = Voikko(u"fi", path=u"/path/to/nowhere")
self.failUnless(self.voikko.spell(u"kissa"))
def tryInit():
self.voikko = Voikko(u"fi-x-non-existent-variant")
"""Contains functions for retrieving pre-processed words from one teletext frontpage image.
See instructions in words_from_image()
"""
import re
from typing import List, Tuple
import pytesseract
from PIL import Image, ImageOps
from libvoikko import Voikko
# these settings only work in Windows environment
Voikko.setLibrarySearchPath("C:/python37/DLLs")
voikko = Voikko("fi-x-morphoid")
pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files (x86)\Tesseract-OCR\tesseract.exe'
def words_from_image(filename: str) -> List[List[str]]:
"""Retrieve pre-processed words from given 'filename' containing teletext frontpage image.
Return value is a list of lists
e.g. [['word1', 'word2'], ['word1', 'word2', 'word3']]
"""
# make image black and white
image = Image.open(filename).convert('1').convert('RGB')
# invert black and white
image = ImageOps.invert(image)
import re
from libvoikko import Voikko
# v = Voikko('fi-x-morphoid')
v = Voikko("fi")
# Replace all non letter characters with space
RE_WS_REPLACE = re.compile(r"[^\w]", re.UNICODE)
RE_FIND_COMPOUNDS = re.compile(r"\(([\w+]+)\)", re.UNICODE)
def voikko_analyze(text):
text = RE_WS_REPLACE.sub(" ", text)
words = text.split(" ")
# Strip spaces
words = [x.strip() for x in words]
# Remove empty items
words = filter(None, words)
# Loop all words and analyze them
analyzed = []
for word in words:
aword = v.analyze(word)
if aword:
i = 0
for f in aword:
i += 1
f["found"] = True
f["original"] = word
wordbases = RE_FIND_COMPOUNDS.findall(f.get("WORDBASES", ""))
f["wordbase_list"] = [
def __init__(self, attributes, langtag="fi"): self.input = input self.attributes = attributes self.voikko = Voikko(langtag) self.__init_feature_names()
def __init__(self, langtag="fi", binary=False, stop_word_classes=[]): self.voikko = Voikko(langtag) self.stop_word_classes = set(stop_word_classes) super().__init__(binary=binary)
locale.setlocale(locale.LC_ALL, "FI_fi")
weekday = datetime.datetime.now().strftime("%A") # e.g. Tiistai
if len(sys.argv) > 1:
weekday = sys.argv[1]
pattern = re.compile(".*{}.*".format(weekday))
URL = "http://pompier.fi/espa/lounas/"
text = get_html(URL)
soup = BeautifulSoup(text)
# columns = soup.find_all('strong')
todays_lunch = soup.find(text=pattern)
print(todays_lunch.parent.parent.text)
from libvoikko import Voikko, Token
v = Voikko(u"fi-x-morphoid")
ttt = (todays_lunch.parent.parent.text.replace("-",
" ").replace("\r", " ").replace(
"\n", " "))
all_words = []
for word in ttt.split(" "):
word = word.strip("\n\r,.")
foo = v.analyze(word)
print("-- " + word + "--")
if foo and "BASEFORM" in foo[0]:
base = foo[0]["BASEFORM"]
else:
base = word
all_words.append(base)
print(": " + base)
from libvoikko import Voikko
voikko = Voikko("fi")
# from https://stackoverflow.com/a/1988826/95357
class Memoize:
def __init__(self, f):
self.f = f
self.memo = {}
def __call__(self, *args):
if not args in self.memo:
self.memo[args] = self.f(*args)
# Warning: You may wish to do a deepcopy here if returning objects
return self.memo[args]
@Memoize
def analyze_word(form):
return voikko.analyze(form)
from flask import Flask, request
from flask_restful import Resource, Api
from flask import jsonify
import sys
from libvoikko import Voikko
app = Flask(__name__)
api = Api(app)
v = Voikko('fi')
class Finnish_text_analysis(Resource):
def get(self):
word = request.args.get('word')
return (jsonify(self.process(word)))
class Analyze(Finnish_text_analysis):
def process(self, word):
return v.analyze(word)
class Spell(Finnish_text_analysis):
def process(self, word):
return {"spelling": v.spell(word)}
class Suggest(Finnish_text_analysis):
def process(self, word):
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from libvoikko import Voikko
AUTHOR = 'Viljami Venekoski'
AUTHOR_EMAIL = "*****@*****.**"
VERSION = '0.1'
VOIKKO = Voikko("fi")
