# -*- coding: utf-8 -*- from datetime import datetime import time import logging from stop_words import get_stop_words #import words as words from nltk.corpus import stopwords as nltk_stopwords from collections import Counter import csv import re import xml.etree.ElementTree as ET import spacy import textacy from scipy import * import sys csv.field_size_limit(sys.maxsize) import pickle import configparser as ConfigParser from miscellaneous import * # load config config_ini = "/home/jannis.grundmann/PycharmProjects/topicModelingTickets/config.ini" config = ConfigParser.ConfigParser() with open(config_ini) as f: config.read_file(f) def create_lemma_dict(path2lemmalist): """ Creates a dict out of a file a la: l1 w1 l1 w2 l2 w1 l2 w2 Result will be used as lemma_dict["word"] --> lemma :param path2lemmalist: str :return: dictionary """ lemmalist = list(map(textacy.preprocess.normalize_whitespace, list( textacy.fileio.read_file_lines(path2lemmalist)))) lemma_dict = {} for line in lemmalist: lem_word_pair = line.split() lemma = lem_word_pair[0].strip().lower() word = lem_word_pair[1].strip().lower() lemma_dict[word] = lemma return lemma_dict def build_thesaurus_dict(path2wordnet,returnall=False): """ Creates a dict out of the deWordNet https://raw.githubusercontent.com/hdaSprachtechnologie/odenet/master/deWordNet.xml Result will be used as lemma_dict["word"] --> lemma :param path2lexicalentries: str :param returnall: bool if True, also return , word2synsets, synset2Words :return: dictionaries: thesaurus """ lextree = ET.parse(path2wordnet, ET.XMLParser(encoding="utf-8")) lexroot = lextree.getroot() word2synsets = {} template = {"w1": ["s1", "s2"]} for ro in lexroot: for elem in ro: if elem.tag == "LexicalEntry": lex_dictlist = [subentry.attrib for subentry in elem] synlist = [] string = "WORD" for lex_dict in lex_dictlist: if "synset" in lex_dict.keys(): synset = lex_dict["synset"] synlist.append(synset) if 'writtenForm' in lex_dict.keys(): string = (lex_dict["writtenForm"]) if string == "Kennwort": pass # replaceRockDots string = re.sub(r'[ß]', "ss", string) string = re.sub(r'[ö]', "oe", string) string = re.sub(r'[ü]', "ue", string) string = re.sub(r'[ä]', "ae", string) # alle punkte raus string = re.sub(r'[.]', "", string) # alles in klammern raus string = re.sub(r"\((.*)\)", " ", string) # längeres leerzeichen normalisieren string = textacy.preprocess.normalize_whitespace(string) string = string.lower().strip() word2synsets[string] = synlist synset2Words = {} template = {"s1": ["w1","w2"]} for word,synset in word2synsets.items(): if word != '': for syn in synset: if syn not in synset2Words.keys(): synset2Words[syn] = [word] else: synset2Words[syn].append(word) # nach anzhal der wörter in den strings sortieren for synset in word2synsets.values(): synset.sort(key=lambda x: len(x.split())) thesaurus = {} thesaurus_template = {"w1" : "mainsyn"} for word,synset in word2synsets.items(): try: thesaurus[word] = synset2Words[synset[0]][0] #Ann.: erstes synonym ist das Hauptsynonym #todo nach (hauptform) suchen? except: pass if returnall: return thesaurus, word2synsets, synset2Words else: return thesaurus def create_stopword_lists(*paths): """ creates a list of stoppwords from: spacy nltk stop_words :param paths: list of additional filepaths where each file looks like w1 w2 w3 filenames must be a la de_stopwords_1.txt, en_stopwords_2.txt :return: lists: de_stopwords, en_stopwords """ ## GERMAN # from packages de_stop_words1 = list(get_stop_words("de")) de_stop_words2 = list(nltk_stopwords.words('german')) de_stop_words3 = list(__import__("spacy.de", globals(), locals(), ['object']).STOP_WORDS) #from files de_filepaths = [] for path in paths: if os.path.basename(path).split("_")[0] == 'de' and os.path.basename(path).split("_")[ 1] == 'stopwords': de_filepaths.append(path) de_stop_words4 = list_from_files(*de_filepaths) #combine everything de_stop_words = list(set(map(replaceRockDots(), list(map(textacy.preprocess.normalize_whitespace, de_stop_words1 + de_stop_words2 + de_stop_words3 + de_stop_words4))))) ## ENGLISH # from packages en_stop_words1 = list(get_stop_words("en")) en_stop_words2 = list(nltk_stopwords.words('english')) en_stop_words3 = list(__import__("spacy.en", globals(), locals(), ['object']).STOP_WORDS) # from files en_filepaths = [path for path in paths if os.path.basename(path).split("_")[0] == 'en' and os.path.basename(path).split("_")[ 1] == 'stopwords'] en_stop_words4 = list_from_files(*en_filepaths) # combine everything en_stop_words = list(set(map(replaceRockDots(), list(map(textacy.preprocess.normalize_whitespace, en_stop_words1 + en_stop_words2 + en_stop_words3 + en_stop_words4))))) return de_stop_words, en_stop_words def build_words_for_spellchecking(path2words): """ create word-Counter for spellchecking http://norvig.com/spell-correct.html http://wortschatz.uni-leipzig.de/en/download http://pcai056.informatik.uni-leipzig.de/downloads/corpora/deu_news_2015_1M.tar.gz :return: Counter """ def words(text): return re.findall(r'\w+', text.lower()) return Counter(words(open(path2words).read())) ################################################################################################## # THESAURUS path2wordnet = config.get("thesaurus","input") path2thesaurus_dict = config.get("thesaurus","pickle_file") # SPELLCHECKING path2words_file = config.get("spellchecking","input") path2wordlist = config.get("spellchecking","pickle_file") # LEMMA path2lemma_file = config.get("lemmatization","input") path2lemmadict = config.get("lemmatization","pickle_file") # NOMEN nouns1 = config.get("nouns","input1") nouns2 = config.get("nouns","input2") path2nouns_list = config.get("nouns","pickle_file") # VORNAMEN firstnames_txt = config.get("firstnames","input") path2firstnameslist = config.get("firstnames","pickle_file") # STOPWORDS stop1 = config.get("de_stopwords","input1") stop2 = config.get("de_stopwords","input2") stop3 = config.get("de_stopwords","input3") path2stopwordlist = config.get("de_stopwords","pickle_file") def main(): start = time.time() printlog("Init: {0}".format(datetime.now())) printlog("create and save lemma_dict") lemma_dict = create_lemma_dict(path2lemma_file) save_obj(lemma_dict, path2lemmadict) printlog("Build and save Wordlist for Spellchecking") words = build_words_for_spellchecking(path2words_file) save_obj(words, path2wordlist) printlog("Build and save Thesaurus") thesaurus = build_thesaurus_dict(path2wordnet) save_obj(thesaurus, path2thesaurus_dict) printlog("Build and save stoppwortliste") de_stop_words = create_stopword_lists(stop1, stop2, stop3) save_obj(de_stop_words, path2stopwordlist) printlog("Build and save nomenliste") nouns = list_from_files(nouns1,nouns2) save_obj(nouns, path2nouns_list) printlog("Build and save firstnameslist") vornamen = list_from_files(firstnames_txt) save_obj(vornamen, path2firstnameslist) end = time.time() printlog("Time Elapsed Initialization:{0} min".format((end - start) / 60)) if __name__ == "__main__": main()