110 lines
2.6 KiB
Python
110 lines
2.6 KiB
Python
# -*- coding: utf-8 -*-
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import time
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start = time.time()
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import corenlp as corenlp
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import os
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import re
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import spacy
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import textacy
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import nltk
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from textblob_de import TextBlobDE
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from textblob_de import PatternParser
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#from polyglot.text import Text
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import hunspell
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from postal.parser import parse_address
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print(parse_address(str(textacy.fileio.read_file("teststring.txt"))))
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"""
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regex_specialChars = r'[`\-=~!#@,.$%^&*()_+\[\]{};\'\\:"|</>?]'
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def stringcleaning(stringstream, funclist):
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for string in stringstream:
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for f in funclist:
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string = f(string)
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yield string
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def seperate_words_on_regex(regex=regex_specialChars):
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return lambda string: " ".join(re.compile(regex).split(string))
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words = [
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"uniaccount",
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"nr54065467",
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"nr54065467",
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"455a33c5,"
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"tvt?=",
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"tanja.saborowski@tu-dortmund.de",
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"-",
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"m-sw1-vl4053.itmc.tu-dortmund.de",
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"------problem--------"
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]
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topLVLFinder = re.compile(r'\.[a-z]{2,3}(\.[a-z]{2,3})?', re.IGNORECASE)
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specialFinder = re.compile(r'[`\-=~!@#$%^&*()_+\[\]{};\'\\:"|<,./>?]', re.IGNORECASE)
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for s in stringcleaning((w for w in words),[seperate_words_on_regex()]):
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print(s.strip())
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#print(stringcleaning(w,string_comp))
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#print(bool(re.search(r'\.[a-z]{2,3}(\.[a-z]{2,3})?',w)))
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#print(bool(re.search(r'[`\-=~!@#$%^&*()_+\[\]{};\'\\:"|<,./>?]',w)))
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#result = specialFinder.sub(" ", w)
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#print(re.sub(r'[`\-=~!@#$%^&*()_+\[\]{};\'\\:"|<,./>?]'," ",w))
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#print(re.sub(r'\.[a-z]{2,3}(\.[a-z]{2,3})?', " ", w))
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"""
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"""
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de_stop_words= set(
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list(__import__("spacy." + DE_PARSER.lang, globals(), locals(), ['object']).STOP_WORDS) +
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list(textacy.fileio.read_file_lines("stopwords-de.txt"))
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)
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LEMMAS = list(textacy.fileio.read_file_lines(filepath="lemmatization-de.txt"))
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VORNAMEN = list(textacy.fileio.read_file_lines("vornamen.txt"))
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#blob = Text(str(textacy.fileio.read_file("teststring.txt")))#,parser=PatternParser(pprint=True, lemmata=True))
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#print(blob.entities)
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de_stop_words = list(map(replaceRockDots(),de_stop_words))
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LEMMAS = list(map(replaceRockDots(),LEMMAS))
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VORNAMEN = list(map(replaceRockDots(),VORNAMEN))
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de_stop_words = list(map(textacy.preprocess.normalize_whitespace,de_stop_words))
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LEMMAS = list(map(textacy.preprocess.normalize_whitespace,LEMMAS))
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VORNAMEN = list(map(textacy.preprocess.normalize_whitespace,VORNAMEN))
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textacy.fileio.write_file_lines(LEMMAS,"lemmas.txt")
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textacy.fileio.write_file_lines(VORNAMEN,"firstnames.txt")
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textacy.fileio.write_file_lines(de_stop_words,"de_stop_words.txt")
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"""
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end = time.time()
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print("\n\n\nTime Elapsed Topic:{0}\n\n".format(end - start))
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