topicModelingTickets/testra.py

# -*- coding: utf-8 -*-
import re
import time

import textacy

start = time.time()


from datetime import datetime

import xml.etree.ElementTree as ET

print(datetime.now())


path2xml="/home/jannis.grundmann/PycharmProjects/topicModelingTickets/deWordNet.xml"

tree = ET.parse(path2xml, ET.XMLParser(encoding="utf-8"))
root = tree.getroot()

regex_specialChars = r'[`\-=~!#@,.$%^&*()_+\[\]{};\'\\:"|</>?]'

nomen=[]





### extract from deWordNet.xml

#https://github.com/hdaSprachtechnologie/odenet

for r in root:
    for element in r:

            if element.tag == "LexicalEntry":
                for i,subentry in enumerate(element):
                    if subentry.tag == "Lemma" and subentry.attrib["partOfSpeech"] == "n":
                            string = (subentry.attrib["writtenForm"])
                            # 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)

                            # seperate_words_on_regex:
                            string = " ".join(re.compile(regex_specialChars).split(string))
                            string_list=string.split()
                            if len(string_list) == 1:
                                nomen.append(string.lower().strip())


textacy.fileio.write_file_lines(nomen,"nomen.txt")













































"""
### extract from derewo

#http://www1.ids-mannheim.de/kl/projekte/methoden/derewo.html


raw = textacy.fileio.read_file_lines("DeReKo-2014-II-MainArchive-STT.100000.freq")

for line in raw:
    line_list=line.split()
    if line_list[2] == "NN":
        string = line_list[1].lower()

        # 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)


        nomen.append(string.lower().strip())


textacy.fileio.write_file_lines(nomen,"nomen2.txt")
"""















"""
stream = textacy.fileio.read_csv("/home/jannis.grundmann/PycharmProjects/topicModelingTickets/M42-Export/Tickets_2017-09-13.csv", delimiter=";")
content_collumn_name = "Description"
content_collumn = 9  # standardvalue

de_tickets=[]
en_tickets=[]
misc_tickets=[]

error_count = 0
for i, lst in enumerate(stream):
    if i == 0:
        de_tickets.append(lst)
        en_tickets.append(lst)
        misc_tickets.append(lst)
    else:
        try:
            content_collumn_ = lst[content_collumn]
            if detect(content_collumn_) == "de":
                de_tickets.append(lst)
            elif detect(content_collumn_) == "en":
                en_tickets.append(lst)
            else:
                misc_tickets.append(lst)

        except:
            misc_tickets.append(lst)
            error_count += 1

print(error_count)

textacy.fileio.write_csv(de_tickets,"M42-Export/de_tickets.csv", delimiter=";")
textacy.fileio.write_csv(en_tickets,"M42-Export/en_tickets.csv", delimiter=";")
textacy.fileio.write_csv(misc_tickets,"M42-Export/misc_tickets.csv", delimiter=";")


"""



"""
regex_specialChars = r'[`\-=~!#@,.$%^&*()_+\[\]{};\'\\:"|</>?]'


def stringcleaning(stringstream, funclist):
    for string in stringstream:
        for f in funclist:
            string = f(string)
        yield string


def seperate_words_on_regex(regex=regex_specialChars):
    return lambda string: " ".join(re.compile(regex).split(string))


words = [
    "uniaccount",
    "nr54065467",
    "nr54065467",
    "455a33c5,"
    "tvt?=",
    "tanja.saborowski@tu-dortmund.de",
    "-",
    "m-sw1-vl4053.itmc.tu-dortmund.de",
    "------problem--------"
]



topLVLFinder = re.compile(r'\.[a-z]{2,3}(\.[a-z]{2,3})?', re.IGNORECASE)
specialFinder = re.compile(r'[`\-=~!@#$%^&*()_+\[\]{};\'\\:"|<,./>?]', re.IGNORECASE)

for s in stringcleaning((w for w in words),[seperate_words_on_regex()]):
    print(s.strip())

    #print(stringcleaning(w,string_comp))
    #print(bool(re.search(r'\.[a-z]{2,3}(\.[a-z]{2,3})?',w)))
    #print(bool(re.search(r'[`\-=~!@#$%^&*()_+\[\]{};\'\\:"|<,./>?]',w)))
    #result = specialFinder.sub(" ", w)
    #print(re.sub(r'[`\-=~!@#$%^&*()_+\[\]{};\'\\:"|<,./>?]'," ",w))

    #print(re.sub(r'\.[a-z]{2,3}(\.[a-z]{2,3})?', " ", w))
"""



"""
def replaceRockDots():
    return lambda string: re.sub(r'[ß]', "ss", (re.sub(r'[ö]', "oe", (re.sub(r'[ü]', "ue", (re.sub(r'[ä]', "ae", string.lower())))))))



de_stop_words = list(textacy.fileio.read_file_lines(filepath="german_stopwords_full.txt"))


#blob = Text(str(textacy.fileio.read_file("teststring.txt")))#,parser=PatternParser(pprint=True, lemmata=True))

#print(blob.entities)

de_stop_words = list(map(replaceRockDots(),de_stop_words))
#LEMMAS = list(map(replaceRockDots(),LEMMAS))
#VORNAMEN = list(map(replaceRockDots(),VORNAMEN))

de_stop_words = list(map(textacy.preprocess.normalize_whitespace,de_stop_words))
#LEMMAS = list(map(textacy.preprocess.normalize_whitespace,LEMMAS))
#VORNAMEN = list(map(textacy.preprocess.normalize_whitespace,VORNAMEN))




#textacy.fileio.write_file_lines(LEMMAS,"lemmas.txt")
#textacy.fileio.write_file_lines(VORNAMEN,"firstnames.txt")
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))