topicModelingTickets/init.py

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# -*- coding: utf-8 -*-
from datetime import datetime
import time
import logging
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from stop_words import get_stop_words
#import words as words
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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
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import configparser as ConfigParser
from miscellaneous import *
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# load config
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config_ini = "/home/jannis.grundmann/PycharmProjects/topicModelingTickets/config.ini"
config = ConfigParser.ConfigParser()
with open(config_ini) as f:
config.read_file(f)
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def create_lemma_dict(path2lemmalist):
"""
Creates a dict out of a file a la:
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l1 w1
l1 w2
l2 w1
l2 w2
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Result will be used as lemma_dict["word"] --> lemma
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:param path2lemmalist: str
:return: dictionary
"""
lemmalist = list(map(textacy.preprocess.normalize_whitespace, list(
textacy.fileio.read_file_lines(path2lemmalist))))
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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
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def build_thesaurus_dict(path2wordnet,returnall=False):
"""
Creates a dict out of the deWordNet
https://raw.githubusercontent.com/hdaSprachtechnologie/odenet/master/deWordNet.xml
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Result will be used as lemma_dict["word"] --> lemma
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: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"])
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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
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synset2Words = {}
template = {"s1": ["w1","w2"]}
for word,synset in word2synsets.items():
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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"}
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for word,synset in word2synsets.items():
try:
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thesaurus[word] = synset2Words[synset[0]][0] #Ann.: erstes synonym ist das Hauptsynonym #todo nach (hauptform) suchen?
except:
pass
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if returnall:
return thesaurus, word2synsets, synset2Words
else:
return thesaurus
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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
"""
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## GERMAN
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# from packages
de_stop_words1 = list(get_stop_words("de"))
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de_stop_words2 = list(nltk_stopwords.words('german'))
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de_stop_words3 = list(__import__("spacy.de", globals(), locals(), ['object']).STOP_WORDS)
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#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)
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de_stop_words4 = list_from_files(*de_filepaths)
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#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)))))
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## ENGLISH
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# from packages
en_stop_words1 = list(get_stop_words("en"))
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en_stop_words2 = list(nltk_stopwords.words('english'))
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en_stop_words3 = list(__import__("spacy.en", globals(), locals(), ['object']).STOP_WORDS)
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# 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']
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en_stop_words4 = list_from_files(*en_filepaths)
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# 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)))))
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return de_stop_words, en_stop_words
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def build_words_for_spellchecking(path2words):
"""
create word-Counter for spellchecking
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http://norvig.com/spell-correct.html
http://wortschatz.uni-leipzig.de/en/download
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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())
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return Counter(words(open(path2words).read()))
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##################################################################################################
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# THESAURUS
path2wordnet = config.get("thesaurus","input")
path2thesaurus_dict = config.get("thesaurus","pickle_file")
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# SPELLCHECKING
path2words_file = config.get("spellchecking","input")
path2wordlist = config.get("spellchecking","pickle_file")
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# LEMMA
path2lemma_file = config.get("lemmatization","input")
path2lemmadict = config.get("lemmatization","pickle_file")
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# NOMEN
nouns1 = config.get("nouns","input1")
nouns2 = config.get("nouns","input2")
path2nouns_list = config.get("nouns","pickle_file")
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# VORNAMEN
firstnames_txt = config.get("firstnames","input")
path2firstnameslist = config.get("firstnames","pickle_file")
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# 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")
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def main():
start = time.time()
printlog("Init: {0}".format(datetime.now()))
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printlog("create and save lemma_dict")
lemma_dict = create_lemma_dict(path2lemma_file)
save_obj(lemma_dict, path2lemmadict)
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printlog("Build and save Wordlist for Spellchecking")
words = build_words_for_spellchecking(path2words_file)
save_obj(words, path2wordlist)
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printlog("Build and save Thesaurus")
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thesaurus = build_thesaurus_dict(path2wordnet)
save_obj(thesaurus, path2thesaurus_dict)
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printlog("Build and save stoppwortliste")
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de_stop_words = create_stopword_lists(stop1, stop2, stop3)
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save_obj(de_stop_words, path2stopwordlist)
printlog("Build and save nomenliste")
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nouns = list_from_files(nouns1,nouns2)
save_obj(nouns, path2nouns_list)
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printlog("Build and save firstnameslist")
vornamen = list_from_files(firstnames_txt)
save_obj(vornamen, path2firstnameslist)
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end = time.time()
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printlog("Time Elapsed Initialization:{0} min".format((end - start) / 60))
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if __name__ == "__main__":
main()