diff --git a/config.ini b/config.ini
index fdc5e2e..49394be 100644
--- a/config.ini
+++ b/config.ini
@@ -1,58 +1,53 @@
 [thesaurus]
-input =  /home/jannis.grundmann/PycharmProjects/topicModelingTickets/deWordNet.xml
-pickle_file =  /home/jannis.grundmann/PycharmProjects/topicModelingTickets/thesaurus_dict.pkl
+input =  deWordNet.xml
+pickle_file =  thesaurus_dict.pkl
 
 
 [spellchecking]
-input = /home/jannis.grundmann/PycharmProjects/topicModelingTickets/deu_news_2015_1M-sentences.txt
-pickle_file =  /home/jannis.grundmann/PycharmProjects/topicModelingTickets/words_dict.pkl
+input = deu_news_2015_1M-sentences.txt
+pickle_file =  words_dict.pkl
 
 
 [lemmatization]
-input =  /home/jannis.grundmann/PycharmProjects/topicModelingTickets/lemmas.txt
-pickle_file =  /home/jannis.grundmann/PycharmProjects/topicModelingTickets/lemma_dict.pkl
+input =  lemmas.txt
+pickle_file =  lemma_dict.pkl
 
 
 [nouns]
-input1 =  /home/jannis.grundmann/PycharmProjects/topicModelingTickets/nomen.txt
-input2 =  /home/jannis.grundmann/PycharmProjects/topicModelingTickets/nomen2.txt
-pickle_file =  /home/jannis.grundmann/PycharmProjects/topicModelingTickets/nouns_list.pkl
+input1 =  nomen.txt
+input2 =  nomen2.txt
+pickle_file =  nouns_list.pkl
 
 
 [firstnames]
-input =  /home/jannis.grundmann/PycharmProjects/topicModelingTickets/firstnames.txt
-pickle_file =  /home/jannis.grundmann/PycharmProjects/topicModelingTickets/firstnames_list.pkl
+input =  firstnames.txt
+pickle_file =  firstnames_list.pkl
 
 
 [de_stopwords]
-input1 =  /home/jannis.grundmann/PycharmProjects/topicModelingTickets/de_stopwords_1.txt
-input2 =  /home/jannis.grundmann/PycharmProjects/topicModelingTickets/de_stopwords_2.txt
-input3 =  /home/jannis.grundmann/PycharmProjects/topicModelingTickets/de_stopwords_3.txt
-pickle_file =  /home/jannis.grundmann/PycharmProjects/topicModelingTickets/stopwords_list.pkl
+input1 =  de_stopwords_1.txt
+input2 =  de_stopwords_2.txt
+input3 =  de_stopwords_3.txt
+pickle_file = stopwords_list.pkl
 
 
 [logging]
 level = INFO
-filename = /home/jannis.grundmann/PycharmProjects/topicModelingTickets/topicModelTickets.log
+filename = topicModelTickets.log
 
 
 [de_corpus]
-#input = /home/jannis.grundmann/PycharmProjects/topicModelingTickets/M42-Export/Tickets_med.csv 
-#input =  /home/jannis.grundmann/PycharmProjects/topicModelingTickets/M42-Export/Tickets_small.csv 
-#input =  /home/jannis.grundmann/PycharmProjects/topicModelingTickets/M42-Export/Tickets_mini.csv 
-input =  /home/jannis.grundmann/PycharmProjects/topicModelingTickets/M42-Export/de_tickets.csv 
-
-path =  /home/jannis.grundmann/PycharmProjects/topicModelingTickets/corpi/ 
-raw =  de_raw_ticket
-pre =  de_pre_ticket
+#input = M42-Export/Tickets_med.csv
+#input =  M42-Export/Tickets_small.csv
+#input =  M42-Export/Tickets_mini.csv
+input =  M42-Export/de_tickets.csv
 
+path =  corpi/
 
 [en_corpus]
-input =  /home/jannis.grundmann/PycharmProjects/topicModelingTickets/M42-Export/en_tickets.csv 
+input =  M42-Export/en_tickets.csv
 
-path =  /home/jannis.grundmann/PycharmProjects/topicModelingTickets/corpi/ 
-raw =  en_raw_ticket
-pre =  en_pre_ticket
+path =  corpi/
 
 
 
diff --git a/corporization.py b/corporization.py
index c2f69f1..50cba8e 100644
--- a/corporization.py
+++ b/corporization.py
@@ -1,53 +1,20 @@
 # -*- 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 *
-
-
-
-
-
-
-
 import time
-
-
-
-
 from datetime import datetime
-import logging
-from nltk.corpus import stopwords
-import csv
-import functools
 import re
-import xml.etree.ElementTree as ET
-import spacy
 import textacy
 from scipy import *
-import sys
-csv.field_size_limit(sys.maxsize)
+import os
 
+csv.field_size_limit(sys.maxsize)
+FILEPATH = os.path.dirname(os.path.realpath(__file__)) + "/"
 
 # load config
-config_ini = "/home/jannis.grundmann/PycharmProjects/topicModelingTickets/config.ini"
+config_ini = FILEPATH + "config.ini"
 
 config = ConfigParser.ConfigParser()
 with open(config_ini) as f:
@@ -128,70 +95,61 @@ metaliste = [
 
 
 content_collumn_name = config.get("tickets","content_collumn_name")
-metaliste = config.get("tickets","metaliste")
+metaliste = config.get("tickets","metaliste").split(",")
 
 
-path2de_csv = config.get("de_corpus","input")
-corpus_de_path = config.get("de_corpus", "path")
-raw_de_name = config.get("de_corpus", "raw")
+path2de_csv = FILEPATH + config.get("de_corpus","input")
+corpus_de_path = FILEPATH + config.get("de_corpus", "path")
 
 
-path2en_csv = config.get("en_corpus","input")
-corpus_en_path = config.get("en_corpus", "path")
-raw_en_name = config.get("en_corpus", "raw")
+path2en_csv = FILEPATH + config.get("en_corpus","input")
+corpus_en_path = FILEPATH + config.get("en_corpus", "path")
 
 
 
-def main():
-    start = time.time()
-    printlog("Corporization: {0}".format(datetime.now()))
-
-
-    #print paths
-    path_csv_split = path2de_csv.split("/")
-    printlog(path_csv_split[len(path_csv_split) - 1])
-    path_csv_split = path2en_csv.split("/")
-    printlog(path_csv_split[len(path_csv_split) - 1])
+def ticketcsv2Corpus(path2_csv, corpus_path, content_collumn_name, metaliste, lang, printrandom=0):
 
 
 
-    DE_PARSER = spacy.load("de")
-    EN_PARSER = spacy.load("en")
+    # print paths
+    path_csv_split = path2_csv.split("/")
+    filename = path_csv_split[len(path_csv_split) - 1]
 
-    raw_de_corpus = textacy.Corpus(DE_PARSER)
-    raw_en_corpus = textacy.Corpus(EN_PARSER)
+    printlog("Corporization of {0} at {1}".format(filename,datetime.now()))
 
 
+    raw_corpus = textacy.Corpus(lang)
 
     ## add files to textacy-corpi,
-    printlog("Add texts to textacy-corpi")
+    printlog("Add texts to {0}_textacy-corpi".format(lang))
 
-    raw_de_corpus.add_texts(
-        ticketcsv_to_textStream(path2de_csv, content_collumn_name),
-        ticket_csv_to_DictStream(path2de_csv, metaliste)
-    )
-
-    raw_en_corpus.add_texts(
-        ticketcsv_to_textStream(path2en_csv, content_collumn_name),
-        ticket_csv_to_DictStream(path2en_csv, metaliste)
+    raw_corpus.add_texts(
+        ticketcsv_to_textStream(path2_csv, content_collumn_name),
+        ticket_csv_to_DictStream(path2_csv, metaliste)
     )
 
 
     # leere docs aus corpi kicken
-    raw_de_corpus.remove(lambda doc: len(doc) == 0)
-    raw_en_corpus.remove(lambda doc: len(doc) == 0)
+    raw_corpus.remove(lambda doc: len(doc) == 0)
+
+    #random Doc printen
+    for i in range(printrandom):
+        printRandomDoc(raw_corpus)
 
 
-    #for i in range(20):
-    #    printRandomDoc(raw_de_corpus)
-    #    printRandomDoc(raw_en_corpus)
+    # save corpus
+    raw_name = lang + "_raw_ticket"
+    save_corpus(corpus=raw_corpus, corpus_path=corpus_path, corpus_name=raw_name)
 
 
-    #save corpi
-    save_corpus(corpus=raw_de_corpus, corpus_path=corpus_de_path, corpus_name=raw_de_name)
-    save_corpus(corpus=raw_en_corpus, corpus_path=corpus_en_path, corpus_name=raw_en_name)
+def main():
+    start = time.time()
 
 
+    ticketcsv2Corpus(path2de_csv,corpus_de_path,content_collumn_name,metaliste,lang="de")
+
+    ticketcsv2Corpus(path2en_csv,corpus_en_path,content_collumn_name,metaliste,lang="en")
+
 
     end = time.time()
     printlog("Time Elapsed Corporization:{0} min".format((end - start) / 60))
diff --git a/init.py b/init.py
index 68d5f8c..596190f 100644
--- a/init.py
+++ b/init.py
@@ -1,29 +1,24 @@
 # -*- 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 *
+from stop_words import get_stop_words
+import csv
+import sys
+import xml.etree.ElementTree as ET
+
+from nltk.corpus import stopwords as nltk_stopwords
+
+from collections import Counter
+import time
+from datetime import datetime
+import os
+
+csv.field_size_limit(sys.maxsize)
+FILEPATH = os.path.dirname(os.path.realpath(__file__)) + "/"
 
 
 # load config
-config_ini = "/home/jannis.grundmann/PycharmProjects/topicModelingTickets/config.ini"
+config_ini = FILEPATH + "config.ini"
 
 config = ConfigParser.ConfigParser()
 with open(config_ini) as f:
@@ -70,7 +65,7 @@ def build_thesaurus_dict(path2wordnet,returnall=False):
 
     Result will be used as lemma_dict["word"] --> lemma
 
-    :param path2lexicalentries: str
+    :param path2wordnet: str
     :param returnall: bool    if True, also return , word2synsets, synset2Words
     :return: dictionaries:   thesaurus
     """
@@ -242,34 +237,34 @@ def build_words_for_spellchecking(path2words):
 ##################################################################################################
 
 # THESAURUS
-path2wordnet = config.get("thesaurus","input")
-path2thesaurus_dict = config.get("thesaurus","pickle_file")
+path2wordnet = FILEPATH + config.get("thesaurus","input")
+path2thesaurus_dict = FILEPATH + config.get("thesaurus","pickle_file")
 
 
 # SPELLCHECKING
-path2words_file = config.get("spellchecking","input")
-path2wordlist = config.get("spellchecking","pickle_file")
+path2words_file = FILEPATH + config.get("spellchecking","input")
+path2wordlist = FILEPATH + config.get("spellchecking","pickle_file")
 
 
 # LEMMA
-path2lemma_file = config.get("lemmatization","input")
-path2lemmadict = config.get("lemmatization","pickle_file")
+path2lemma_file = FILEPATH + config.get("lemmatization","input")
+path2lemmadict = FILEPATH + config.get("lemmatization","pickle_file")
 
 # NOMEN
-nouns1 = config.get("nouns","input1")
-nouns2 = config.get("nouns","input2")
-path2nouns_list = config.get("nouns","pickle_file")
+nouns1 = FILEPATH + config.get("nouns","input1")
+nouns2 = FILEPATH + config.get("nouns","input2")
+path2nouns_list = FILEPATH + config.get("nouns","pickle_file")
 
 
 # VORNAMEN
-firstnames_txt = config.get("firstnames","input")
-path2firstnameslist = config.get("firstnames","pickle_file")
+firstnames_txt = FILEPATH + config.get("firstnames","input")
+path2firstnameslist = FILEPATH + 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")
+stop1 = FILEPATH + config.get("de_stopwords","input1")
+stop2 = FILEPATH + config.get("de_stopwords","input2")
+stop3 = FILEPATH + config.get("de_stopwords","input3")
+path2stopwordlist = FILEPATH + config.get("de_stopwords","pickle_file")
 
 
 
diff --git a/main.py b/main.py
index 9b821d3..faa9c8e 100644
--- a/main.py
+++ b/main.py
@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 
-
+import time
 import init
 import corporization
 import preprocessing
@@ -8,7 +8,7 @@ from miscellaneous import *
 
 
 # ssh madonna "nohup /usr/bin/python3 -u /home/jannis.grundmann/PycharmProjects/topicModelingTickets/main.py &> /home/jannis.grundmann/PycharmProjects/topicModelingTickets/printout_main.log &"
-
+start = time.time()
 
 init.main()
 printlog("")
@@ -19,3 +19,5 @@ printlog("")
 preprocessing.main()
 printlog("")
 
+end = time.time()
+printlog("Total Time Elapsed: {0} min".format((end - start) / 60))
diff --git a/miscellaneous.py b/miscellaneous.py
index 92f19a0..debe414 100644
--- a/miscellaneous.py
+++ b/miscellaneous.py
@@ -1,87 +1,25 @@
 # -*- coding: utf-8 -*-
-import random
-
-import time
-
-from pathlib import Path
-
-from datetime import datetime
-import logging
-from nltk.corpus import stopwords
-import csv
-import functools
-import re
-import xml.etree.ElementTree as ET
-import spacy
-import textacy
-from scipy import *
-import sys
-
-from datetime import datetime
-
-
-import time
-start = time.time()
-
-import logging
-from nltk.corpus import stopwords
-import csv
-import functools
-import re
-import xml.etree.ElementTree as ET
-import spacy
-import textacy
-from scipy import *
-import sys
-csv.field_size_limit(sys.maxsize)
-
-
-import time
-
-import enchant
-
-start = time.time()
-
-import logging
-
-import csv
-import functools
-import os.path
-import re
-import subprocess
-import time
-import xml.etree.ElementTree as ET
-import sys
-import spacy
-import textacy
-from scipy import *
-from textacy import Vectorizer
-import warnings
 import configparser as ConfigParser
-import sys
-import hunspell
-from postal.parser import parse_address
-
-from datetime import datetime
-
-import time
-import logging
-from nltk.corpus import stopwords as nltk_stopwords
-from collections import Counter
 import csv
+import functools
+import logging
+import random
 import re
-import xml.etree.ElementTree as ET
+import sys
+from pathlib import Path
+import pickle
 import spacy
 import textacy
 from scipy import *
-import sys
+import os
+
 csv.field_size_limit(sys.maxsize)
-import pickle
+FILEPATH = os.path.dirname(os.path.realpath(__file__)) + "/"
 
 
 
 # load config
-config_ini = "/home/jannis.grundmann/PycharmProjects/topicModelingTickets/config.ini"
+config_ini = FILEPATH + "config.ini"
 
 config = ConfigParser.ConfigParser()
 with open(config_ini) as f:
@@ -90,7 +28,7 @@ with open(config_ini) as f:
 
 
 # config logging
-filename = config.get("logging","filename")
+filename = FILEPATH + config.get("logging","filename")
 level = config.get("logging","level")
 if level == "INFO":
     level = logging.INFO
@@ -188,10 +126,13 @@ def printRandomDoc(textacyCorpus):
     :param textacyCorpus:
     """
     print()
-    printlog("len(textacyCorpus) = %i" % len(textacyCorpus))
-    randIndex = int((len(textacyCorpus) - 1) * random.random())
-    printlog("Index: {0} ; Text: {1} ; Metadata: {2}\n".format(randIndex, textacyCorpus[randIndex].text,
-                                                            textacyCorpus[randIndex].metadata))
+    if len(textacyCorpus) == 0:
+        printlog("NO DOCS IN CORPUS")
+    else:
+        printlog("len(textacyCorpus) = %i" % len(textacyCorpus))
+        randIndex = int((len(textacyCorpus) - 1) * random.random())
+        printlog("Index: {0} ; Text: {1} ; Metadata: {2}\n".format(randIndex, textacyCorpus[randIndex].text,
+                                                                textacyCorpus[randIndex].metadata))
 
     print()
 
@@ -239,14 +180,14 @@ def load_corpus(corpus_path, corpus_name, lang="de"):
     Load textacy-Corpus including spacy-parser out from file
     :param corpus_path: str
     :param corpus_name: str (should content the language like "_de_")
-    :param lang: str language code)
+    :param lang: str (language code) ir spacy.Language
     :return: texracy.Corpus, spacy.language
     """
 
     #ckeck for language
-    if "_de_" in corpus_name:
+    if "de_" in corpus_name:
         lang="de"
-    elif "_en_" in corpus_name:
+    elif "en_" in corpus_name:
         lang ="en"
 
 
diff --git a/preprocessing.py b/preprocessing.py
index 6a0e5c7..c7f0d65 100644
--- a/preprocessing.py
+++ b/preprocessing.py
@@ -1,76 +1,23 @@
 # -*- coding: utf-8 -*-
 
 from datetime import datetime
-print(datetime.now())
-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 *
-
-
-
-
-
-
-
-import time
-
-
-
-
 from datetime import datetime
-import logging
-from nltk.corpus import stopwords
-import csv
-import functools
-import re
-import xml.etree.ElementTree as ET
-import spacy
-import textacy
-from scipy import *
-import sys
-csv.field_size_limit(sys.maxsize)
-
-
 import time
-
-import logging
-from nltk.corpus import stopwords
-import csv
-import functools
-import re
-import xml.etree.ElementTree as ET
-import spacy
 import textacy
 from scipy import *
-import sys
+
+import os
+
 csv.field_size_limit(sys.maxsize)
-
-
-
-import pickle
-
+FILEPATH = os.path.dirname(os.path.realpath(__file__)) + "/"
 
 
 
 # load config
-config_ini = "/home/jannis.grundmann/PycharmProjects/topicModelingTickets/config.ini"
+config_ini = FILEPATH + "config.ini"
 
 config = ConfigParser.ConfigParser()
 with open(config_ini) as f:
@@ -178,7 +125,6 @@ def getFirstSynonym(word, thesaurus=THESAURUS):
 # http://wortschatz.uni-leipzig.de/en/download
 
 import re
-from collections import Counter
 
 
 def words(text): return re.findall(r'\w+', text.lower())
@@ -250,7 +196,7 @@ def stringcleaning(stringstream):
         string = " ".join(re.compile(REGEX_SPECIALCHAR).split(string))
 
         # cut_after
-        word = "gruss"
+        word = "gruss" #idee addressen enfernen --> postal.parser
         string = string.rpartition(word)[0] if word in string else string
 
         # lemmatize
@@ -347,29 +293,23 @@ def processDictstream(dictstream, funcdict, parser):
 # ssh madonna "nohup /usr/bin/python3 -u /home/jannis.grundmann/PycharmProjects/topicModelingTickets/preprocessing.py &> /home/jannis.grundmann/PycharmProjects/topicModelingTickets/printout_preprocessing.log &"
 
 
-path2thesaurus_dict = config.get("thesaurus","pickle_file")
+path2thesaurus_dict = FILEPATH + config.get("thesaurus","pickle_file")
 
-path2wordsdict = config.get("spellchecking", "pickle_file")
+path2wordsdict = FILEPATH + config.get("spellchecking", "pickle_file")
 
-path2lemmadict = config.get("lemmatization","pickle_file")
+path2lemmadict = FILEPATH + config.get("lemmatization","pickle_file")
 
-path2nouns_list = config.get("nouns","pickle_file")
+path2nouns_list = FILEPATH + config.get("nouns","pickle_file")
 
-path2firstnameslist = config.get("firstnames","pickle_file")
+path2firstnameslist = FILEPATH + config.get("firstnames","pickle_file")
 
-path2stopwordlist = config.get("de_stopwords","pickle_file")
+path2stopwordlist = FILEPATH + config.get("de_stopwords","pickle_file")
 
 
 
-corpus_de_path = config.get("de_corpus", "path")
-raw_de_name = config.get("de_corpus", "raw")
-pre_de_name = config.get("de_corpus", "pre")
+corpus_de_path = FILEPATH + config.get("de_corpus", "path")
 
-
-
-corpus_en_path = config.get("en_corpus", "path")
-raw_en_name = config.get("en_corpus", "raw")
-pre_en_name = config.get("en_corpus", "pre")
+corpus_en_path = FILEPATH + config.get("en_corpus", "path")
 
 
 custom_words = ["geehrt", "dame", "herr", "hilfe", "problem", "lauten", "bedanken", "voraus",
@@ -383,10 +323,8 @@ custom_words = ["geehrt", "dame", "herr", "hilfe", "problem", "lauten", "bedanke
                 "funktionieren", "kollege", "pruefen", "hoffen"
                 ]
 
-
 filter_tokens = [
     # removeENT(["PERSON"]),
-    # idee addressen enfernen #bisher mit cut_after("gruss") --> postal.parser
 
     keepNouns(),
 
@@ -403,8 +341,8 @@ filter_tokens = [
 
 
 ]
-
-
+#todo filtertokens haut alle raus
+filter_tokens = None
 
 clean_in_meta = {
     "Solution": [removePOS(["SPACE"])],
@@ -412,17 +350,43 @@ clean_in_meta = {
     "categoryName": [removePOS(["SPACE", "PUNCT"])]
 }
 
+def preprocessCorpus(corpus_path, filter_tokens, clean_in_meta, lang="de", printrandom=10):
+
+    printlog("Preprocess {0}_corpus at {1}".format(lang,datetime.now()))
+
+    rawCorpus_name = lang + "_raw_ticket"
+    preCorpus_name = lang + "_pre_ticket"
+
+    #load raw corpus and create new one
+    raw_corpus, parser = load_corpus(corpus_name=rawCorpus_name, corpus_path=corpus_path)
+
+    corpus = textacy.Corpus(parser)
+
+
+    ## process and add files to textacy-corpi,
+    corpus.add_texts(
+        processContentstream(corpus2Text(raw_corpus), token_filterlist=filter_tokens, parser=parser),
+        processDictstream(corpus2Meta(raw_corpus), clean_in_meta,parser=parser)
+    )
+
+
+    # leere docs aus corpi kicken
+    corpus.remove(lambda doc: len(doc) == 0)
+
+
+    for i in range(printrandom):
+        printRandomDoc(corpus)
 
 
 
-
+    #save corpus
+    save_corpus(corpus=corpus, corpus_path=corpus_path, corpus_name=preCorpus_name)
 
 
 
 
 def main():
     start = time.time()
-    printlog("Preprocessing: {0}".format(datetime.now()))
 
 
     THESAURUS = load_obj(path2thesaurus_dict)
@@ -432,44 +396,9 @@ def main():
     NOUNS = load_obj(path2nouns_list)
     VORNAMEN = load_obj(path2firstnameslist)
 
+    preprocessCorpus(corpus_de_path,  filter_tokens, clean_in_meta, "de" )
 
-
-    #load raw corpus and create new one
-    raw_de_corpus, DE_PARSER = load_corpus(corpus_name=raw_de_name, corpus_path=corpus_de_path)
-    raw_en_corpus, EN_PARSER = load_corpus(corpus_name=raw_en_name, corpus_path=corpus_en_path)
-
-    de_corpus = textacy.Corpus(DE_PARSER)
-    en_corpus = textacy.Corpus(EN_PARSER)
-
-
-
-    ## process and add files to textacy-corpi,
-    printlog("Preprocess and add texts to textacy-corpi")
-    de_corpus.add_texts(
-        processContentstream(corpus2Text(raw_de_corpus), token_filterlist=filter_tokens, parser=DE_PARSER),
-        processDictstream(corpus2Meta(raw_de_corpus), clean_in_meta,parser=raw_de_corpus.lang)
-    )
-    en_corpus.add_texts(
-        processContentstream(corpus2Text(raw_en_corpus), token_filterlist=filter_tokens, parser=EN_PARSER),
-        processDictstream(corpus2Meta(raw_en_corpus), clean_in_meta,parser=raw_en_corpus.lang)
-    )
-
-
-    # leere docs aus corpi kicken
-    de_corpus.remove(lambda doc: len(doc) == 0)
-    en_corpus.remove(lambda doc: len(doc) == 0)
-
-
-    for i in range(20):
-        printRandomDoc(de_corpus)
-        #printRandomDoc(en_corpus)
-
-
-
-    #save corpi
-    save_corpus(corpus=de_corpus, corpus_path=corpus_de_path, corpus_name=pre_de_name)
-    save_corpus(corpus=en_corpus, corpus_path=corpus_en_path, corpus_name=pre_en_name)
-
+    preprocessCorpus(corpus_en_path,  filter_tokens, clean_in_meta, "en" )
 
 
     end = time.time()
diff --git a/testra.py b/testra.py
index f5a5b4f..843d548 100644
--- a/testra.py
+++ b/testra.py
@@ -1,10 +1,11 @@
 # -*- coding: utf-8 -*-
+
 import re
 import time
 import json
 
-import spacy
-import textacy
+#import spacy
+#import textacy
 from functools import reduce
 
 start = time.time()
@@ -15,7 +16,6 @@ from datetime import datetime
 
 import xml.etree.ElementTree as ET
 
-print(datetime.now())
 
 """
 PARSER=spacy.load("de")
@@ -55,19 +55,8 @@ print(corpi)
 """
 
 
-import pickle
-
-def save_obj(obj, path):
-    with open(path + '.pkl', 'wb') as f:
-        pickle.dump(obj, f, pickle.HIGHEST_PROTOCOL)
-
-def load_obj(path ):
-    with open(path + '.pkl', 'rb') as f:
-        return pickle.load(f)
-
-
-
 
+"""
 def load_corpus(corpus_path, corpus_name, lang="de"):
     from pathlib import Path
 
@@ -95,7 +84,7 @@ def load_corpus(corpus_path, corpus_name, lang="de"):
         corpus.add_doc(
             textacy.Doc(spacy_doc, lang=corpus.spacy_lang, metadata=metadata))
     return corpus
-
+"""
 import os
 a = "/home/jannis.grundmann/PycharmProjects/topicModelingTickets/de_stopwords_1.txt"
 b = "/home/jannis.grundmann/PycharmProjects/topicModelingTickets/de_stopwords_2.txt"
@@ -103,37 +92,16 @@ d = "/home/jannis.grundmann/PycharmProjects/topicModelingTickets/de_stopwords_3.
 
 c = "/home/jannis.grundmann/PycharmProjects/topicModelingTickets/en_stopwords_1.txt"
 
-liste = [a,b,c,d]
-de_filepaths = [path for path in liste if os.path.basename(path).split("_")[0]=='de' and os.path.basename(path).split("_")[1]=='stopwords']
-
-from nltk.corpus import stopwords as nltk_stopwords
-
-from stop_words import get_stop_words
-import spacy
-from miscellaneous import *
-# 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_stop_words_list = [list(textacy.fileio.read_file_lines(path)) for path in de_filepaths]
-de_stop_words4 = [item for sublist in de_stop_words_list for item in sublist]
-#print(de_stop_words4)
-
-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)))))
-print(len(de_stop_words))
-# ssh madonna "nohup /usr/bin/python3 -u /home/jannis.grundmann/PycharmProjects/topicModelingTickets/testra.py &> /home/jannis.grundmann/PycharmProjects/topicModelingTickets/printout_testra.log &"
 
 
 
+scriptpath = os.path.dirname(os.path.realpath(__file__))
 
 
 
 
 
+"""
 # THESAURUS
 lexicalentries = "/home/jannis.grundmann/PycharmProjects/topicModelingTickets/lexicalentries_small.xml"
 lexicalentries = "/home/jannis.grundmann/PycharmProjects/topicModelingTickets/lexicalentries.xml"
@@ -212,7 +180,7 @@ def build_thesaurus(path2lexicalentries):#, path2synsets):
             pass
     return thesaurus
 
-    """
+   
     for r in synroot:
         for element in r:
 
@@ -223,9 +191,8 @@ def build_thesaurus(path2lexicalentries):#, path2synsets):
 
                 if id not in synset2Words.keys():
                     synset2Words[id] = "WORD"
-    """
-
 
+"""
 
 """
 from postal.parser import parse_address
@@ -557,6 +524,7 @@ de_stop_words = list(map(textacy.preprocess.normalize_whitespace,de_stop_words))
 textacy.fileio.write_file_lines(de_stop_words,"german_stopwords.txt")
 
 """
+
 end = time.time()
 print("\n\n\nTime Elapsed Topic:{0}\n\n".format(end - start))
 
diff --git a/topicModeling.py b/topicModeling.py
index 3e61672..75dbe12 100644
--- a/topicModeling.py
+++ b/topicModeling.py
@@ -94,9 +94,6 @@ def printvecotorization(ngrams=1, min_df=1, max_df=1.0, weighting='tf', named_en
     printlog("doc_term_matrix: {0}".format(doc_term_matrix))
     printlog("id2term: {0}".format(id2term))
 
-
-
-
 corpus_path = "/home/jannis.grundmann/PycharmProjects/topicModelingTickets/corpi/"
 corpus_name = "de_corpus"
 
@@ -104,11 +101,6 @@ corpus_name = "de_corpus"
 de_corpus = load_corpus(corpus_name=corpus_name,corpus_path=corpus_path)
 
 
-for i in range(5):
-    printRandomDoc(de_corpus)
-
-
-
 
 # todo gescheites tf(-idf) maß finden
 ngrams = 1
@@ -128,6 +120,7 @@ printvecotorization(ngrams=(1, 2), min_df=1, max_df=0.5, weighting=weighting)
 printvecotorization(ngrams=(1, 2), min_df=1, max_df=0.8, weighting=weighting)
 """
 
+
 # build citionary of ticketcategories
 labelist = []
 
@@ -139,6 +132,7 @@ LABELDICT = {k: v for v, k in enumerate(labelist)}
 printlog(str("LABELDICT: {0}".format(LABELDICT)))
 
 
+
 def textacyTopicModeling(ngrams, min_df, max_df, topicModel='lda', n_topics=len(LABELDICT), named_entities=False,
                          corpus=de_corpus):
     printlog(