def agreement(request):
f = None
context = {}
try:
doc = docxpy.process('static/doc/개인정보 수집·이용 동의.docx')
except FileNotFoundError:
context['agreement1'] = '개인정보 수집·이용 약관을 불러오는데 실패했습니다.'
else:
context['agreement1'] = doc
finally:
if not (f is None):
f.close()
try:
doc = docxpy.process('static/doc/개인정보 처리 동침 동의.docx')
except FileNotFoundError:
context['agreement2'] = '개인정보 처리 동침 동의 약관을 불러오는데 실패했습니다.'
else:
context['agreement2'] = doc
finally:
if not (f is None):
f.close()
return render(request, 'account/agreement.html', context)
def word_counter(docx_path) :
text = docxpy.process(docx_path).replace(":", " ")
words = [word for word in text.split() if not word in [":", "."]]
text = " ".join(docxpy.process(docx_path).split())
return len(words), text
def filedialog(self):
#root.filename = tkFileDialog.askopenfilename(initialdir = "/",title = "Select file",filetypes = (("jpeg files","*.jpg"),("all files","*.*")))
self.filename = filedialog.askopenfilename(initialdir = "/", title = "Select file")
self.entry.insert(0,self.filename)
self.text = docxpy.process(self.filename)
print(self.text)
self.N=len(self.text)
print("length=",N)
self.dictionary=set()
self.postings=defaultdict(dict)
self.document_frequency=defaultdict(dict)
#self.length=defaultdict(float)
self.txt=ScrolledText(self.labelFrame, width=100, height=20)
self.txt.grid(row=7)
self.txt.insert(const.END,self.text)
#self.label1.config(text=self.text)
# self.entry1.insert(0,self.text)
self.terms=self.token()
print(self.terms)
self.unique_terms = set(self.terms)
print(self.unique_terms)
self.dictionary=dictionary.union(self.unique_terms)
for each term in unique_terms:
self.postings[term]=self.terms.count(term)
def TextSpeechConverter(fldr_name):
start_Time = time.time()
for filename in glob(fldr_name + "*"):
print(filename)
text = docxpy.process(filename)
path_of_output = "C:/Users/user/Documents/" #this is the path to generate file
try:
os.mkdir(os.path.join(path_of_output, "text"))
except:
pass
text_file = filename.split("\\")[-1].replace(".docx", ".txt")
with open("C:/Users/user/Documents/text/" + text_file,
"w",
encoding='utf-8') as file:
file.write(text)
try:
os.mkdir(os.path.join(path_of_output, "audio"))
except:
pass
audio_file = filename.split("\\")[-1].replace(".docx", ".mp3")
audio_obj = Text2Speech(text)
audio_obj.save(os.path.join(path_of_output, "audio/") + audio_file)
end_Time = time.time()
execution_time = (end_Time - start_Time) / 60
print("Total Execution Time: ", execution_time)
def find_files():
word = txtFrame3.get()
path = txtFrame4.get()
print(path)
all_file_names = os.listdir(
path) #returns a list of all file names present in given dir
pointer = float(result_text_word.index(INSERT))
result_text_word.insert(pointer, ("Total Files\t:\t" +
(f'{len(all_file_names)}') + "\n\n"))
pointer += 1.0
docx_file_names = []
for filename in all_file_names:
if (filename.endswith('.docx')):
docx_file_names.append(filename)
result_text_word.insert(pointer, ("Docx Files\t:\t" +
(f'{len(docx_file_names)}') + "\n\n"))
pointer = float(result_text_word.index(INSERT))
pointer += 1.0
result_file_names = []
for filename in docx_file_names:
text = docxpy.process(path + '/' + filename)
if (word in text):
result_file_names.append(filename)
result_text_word.insert(pointer, ("Matched Files\t:\t" +
(f'{len(result_file_names)}') + "\n\n"))
pointer = float(result_text_word.index(INSERT))
pointer += 1.0
for file in result_file_names:
result_text_word.insert(pointer, (f'\t{file}\n'))
def convertToText(file):
try:
if file.endswith('.pdf'):
PDF = PdfFileReader(open(file, 'rb'), strict=True)
if PDF.isEncrypted:
decrypt = PDF.decrypt('')
if decrypt == 0:
raise Exception("Nope")
elif decrypt == 1 or decrypt == 2:
pass
text = ''
r = PDF.getPage(1)
print(r.getContents())
for page in PDF.pages:
text = text + page.extractText()
#print(text)
return text
else:
text = docxpy.process(file)
return text
except Exception as e:
return e
def docx(i,o,ip,op): print 'docx' text = docxpy.process(ip+i) f=open(op+'%s'%o,'w') text=char_preprocess(text) f.write(text) f.close()
def search(dir_path, keyword):
matched_file_list = []
all_docx_files = []
all_file_list = os.listdir(dir_path)
for file in all_file_list:
if (file.endswith('.docx')):
all_docx_files.append(file)
text = dx.process(f'{dir_path}/{file}')
if (keyword.lower() in text.lower()):
matched_file_list.append(file)
return all_file_list, all_docx_files, matched_file_list
def getResumeNouns(self):
resumeNounsList = []
for file in os.listdir(self.resume):
if file.endswith(('.docx', '.pdf')):
saveNouns = []
if file.endswith('.pdf'):
PDF = PdfFileReader(open(file, 'rb'))
if PDF.isEncrypted:
decrypt = PDF.decrypt('')
if decrypt == 0:
print("Password Protected PDF: " + file)
raise Exception("Nope")
elif decrypt == 1 or decrypt == 2:
print("Successfully Decrypted PDF")
text = ''
for page in PDF.pages:
text = text + "\n" + page.extractText()
jdTokens = nltk.word_tokenize(text)
stemmer = PorterStemmer()
stemmed = [stemmer.stem(token) for token in jdTokens]
jdTagged = nltk.pos_tag(stemmed)
p = re.compile('NN|NNS|NNP|NNPS|PRP|PRP$|WP|WP$')
# store nouns from job description
for tag in jdTagged:
t = tag[1]
if p.match(t):
saveNouns.append(tag[0])
else:
text = docxpy.process(file)
jdTokens = nltk.word_tokenize(text)
stemmer = PorterStemmer()
stemmed = [stemmer.stem(token) for token in jdTokens]
jdTagged = nltk.pos_tag(stemmed)
p = re.compile('NN|NNS|NNP|NNPS|PRP|PRP$|WP|WP$')
# store nouns from job description
for tag in jdTagged:
t = tag[1]
if p.match(t):
saveNouns.append(tag[0])
resumeNounsList.append({
'filename': file,
'list': saveNouns,
'text': text
})
return resumeNounsList
def con(filenames, code, counter,subdir):
if not os.path.exists('input/'+subdir):
os.makedirs('input/'+subdir)
for file in filenames:
counter = counter+1
text = docxpy.process(file)
saveFile = open("input/"+subdir+'/'+str(code)+str(counter).zfill(4)+ ".txt", 'w', encoding="utf-8")
saveFile.write(text)
saveFile.close()
return counter
#con()
def filedialog(self):
#root.filename = tkFileDialog.askopenfilename(initialdir = "/",title = "Select file",filetypes = (("jpeg files","*.jpg"),("all files","*.*")))
self.filename = filedialog.askopenfilename(initialdir = "/", title = "Select file")
self.entry.insert(0,self.filename)
self.text = docxpy.process(self.filename)
print(self.text)
self.txt=ScrolledText(self, width=150, height=10)
self.txt.grid()
self.txt.insert(const.END,self.text)
#self.label1.config(text=self.text)
self.entry1.insert(0,self.text)
print(textwrap.fill(self.text))
def docx_extract(file, i):
delete_ppms()
j = 0
for file in sorted(os.listdir('Resumes')):
if '.docx' in file and 'file' not in file:
os.rename(PATH + file,
PATH + 'file' + str(i) + '_' + str(j) + '.docx')
j += 1
j = 0
f = open(f'result{i}.txt', 'w')
files = [f for f in os.listdir('Resumes') if '.docx' in f]
for file in sorted(files,
key=lambda x: int(x[x.index('-') + 1:x.index('.')])):
#print("extracting from:", file)
temp = docxpy.process(PATH + file)
f.write(temp)
f.close()
def filedialog(self):
#root.filename = tkFileDialog.askopenfilename(initialdir = "/",title = "Select file",filetypes = (("jpeg files","*.jpg"),("all files","*.*")))
self.filename = filedialog.askopenfilename(initialdir="/",
title="Select file")
self.entry.insert(0, self.filename)
self.text = docxpy.process(self.filename)
print(self.text)
self.txt = ScrolledText(self.labelFrame, width=100, height=20)
self.txt.grid(row=7)
self.txt.insert(const.END, self.text)
#self.label1.config(text=self.text)
# self.entry1.insert(0,self.text)
self.terms = self.token()
print(self.terms)
self.unique_terms = set(self.terms)
print(self.unique_terms)
#self.searchweb()
self.summary()
def printtext(file):
file_name, file_extension = os.path.splitext(file)
junk, filenamenopath = os.path.split(file_name)
filename = file_name + ".txt"
if (file_extension == ".docx"):
text = docxpy.process(file)
doc = docxpy.DOCReader(file)
doc.process() # process file
elif (file_extension == ".pdf"):
text = extract_text(file)
elif (file_extension == ".txt"):
text = open(file, "r").read()
else:
text = "I don't know this file type"
text = re.sub('[^A-Za-z0-9\s]+', '', text)
assignmentfile = open("../assignment.txt", "w")
assignmentfile.write(text)
#print text
return text
def convert(request, pk):
document = get_object_or_404(Document, pk=pk)
print(document.document)
translator = Translator()
parse(f"D:\\audio\\audio\\static\\" + str(document.document),
f"D:\\audio\\audio\\static\\" + str(document.document)[:-4] +
".docx",
start=0)
print("PDF --> DOCX")
# extract text
text = docxpy.process(f"D:\\audio\\audio\\static\\" +
str(document.document)[:-4] + ".docx")
print("DOCX --> TXT")
print(text)
print("Translating...")
translator = Translator()
translation = translator.translate(text, dest="hi")
print("English --> Hindi")
print(translation.text)
context = {'document': document}
return render(request, 'audio_detail.html', context)
def filedialog(self):
#root.filename = tkFileDialog.askopenfilename(initialdir = "/",title = "Select file",filetypes = (("jpeg files","*.jpg"),("all files","*.*")))
self.filename = filedialog.askopenfilename(initialdir = "/", title = "Select file")
self.entry.insert(0,self.filename)
ext=self.filename.split(".")[-1]
if ext=='doc' or ext=='docx':
self.text = docxpy.process(self.filename)
if ext=='pdf':
obj=open(self.filename,'rb')
reader=PdfFileReader(obj)
num=reader.numPages
print (num)
page=reader.getPage(0)
self.text=page.extractText()
obj.close()
print(self.text)
self.txt=ScrolledText(self.labelFrame, width=50, height=20)
self.txt.grid(row=1,column=3)
self.txt.insert(const.END,self.text)
self.button1()
def getWords(doc):
if (doc.split('.')[1] == 'txt'):
text_string = open(doc).read()
else:
text_string = docxpy.process(doc)
fullwordlist = stripNonAlphaNum(text_string)
str1 = ' '.join(fullwordlist)
match_pattern = re.findall(r'\b[a-z]{3,30}\b', str1)
wordlist = removeStopwords(match_pattern, stopwords)
dictionary = wordListToFreqDict(wordlist)
sorted_freq = [
pair[0]
for pair in sorted(dictionary.items(), key=lambda item: item[1])
]
sorted_freq.reverse()
sorted_list = []
sorted_num = []
for words in sorted_freq[:10]:
sorted_list.append(words)
sorted_num.append(dictionary.get(words))
return sorted_list, sorted_num
def grab(file_path):
text = docxpy.process(file_path)
text = filter(text)
return text
import docxpy
import os
files = os.listdir('docs')
for f in files:
print(f)
target = "docs/" + str(f)
# print(type(target))
text = docxpy.process(target, "img")
'Competence'] = extract_competencies(text, experience_list)
df.loc[i, 'competence score'] = extract_competencies_score(
text, experience_list)
df.loc[i, 'DOB'] = extract_dob(text)
else:
df.loc[i, 'Total Experience(in months)'] = 'NA'
df.loc[i, 'Last Position'] = 'NA'
df.loc[i, 'Competence'] = 'NA'
df.loc[i, 'competence score'] = 'NA'
df.loc[i, 'DOB'] = extract_dob(text)
i += 1
else:
text = docxpy.process(filename)
# print(text)
df.loc[i, 'Mobile No.'] = extract_mobile_number(text)
df.loc[i, 'Email'] = extract_email(text)
df.loc[i, 'Name'] = extract_name(text)
df.loc[i, 'Education Qualifications'] = extract_education(text)
df.loc[i, 'Skills'] = extract_skills(text)
experience_list1 = extract_entity_sections_grad(text)
if 'experience' in experience_list1:
experience_list = experience_list1['experience']
df.loc[i, 'Total Experience(in months)'] = get_total_experience(
experience_list)
df.loc[i, 'Last Position'] = extract_experience(text)
def main_docx(file):
doctext = docxpy.process(file)
doc_item = str(doctext).split()
return doc_item
Author: Milind Kumar V
"""
import re
import numpy as np
import docxpy
################### defining variables ###################
path_ts = "./38331-f80.docx"
path_out_text = "./definitions.txt"
################### process the file ###################
contents = docxpy.process(path_ts)
contents = contents.strip().split("\n")
start_tag = "-- ASN1START"
stop_tag = "-- ASN1STOP"
with open(path_out_text, "w") as file:
copy = False
for line_idx in range(len(contents)):
line = contents[line_idx]
if line.strip() == start_tag:
copy = True
continue
elif line.strip() == stop_tag:
copy = False
def resume_to_str(filename, path="saved-resumes/"):
dot_index = filename.rindex(".")
extension = filename[dot_index:]
if extension.lower() == ".pdf":
return pdf_to_str(filename, path)
return docxpy.process(path + filename)
def docx_to_text(file_path):
document = docxpy.process(file_path)
return document
import docxpy file = 'C:/Users/user/Documents/malayalam.docx' # extract text text = docxpy.process(file) # extract text and write images in /tmp/img_dir #text = docxpy.process(file, "/tmp/img_dir") print(text)
import docxpy
import pandas as pd
from bs4 import BeautifulSoup as bs
import os
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
#File Location
f='D:\Downloads\Basic-Resume-Template_Word\Word\Basic Resume Template.docx'
text=docxpy.process(f)
#soup=bs(text,'lxml')
print("---------------------")
#df=pd.read_csv("D:\Downloads\skills.csv")
#df2=df['SKILLS']
skills=['python','php','java','javascript','perl','android','c++','c','wordpress','photoshop','graphic design','cloud','asp.net','vb.net','.net','mysql','ajax','microcontroller','data structure','data mining','data warehouse','data plane','sql','selenium','qtp','web developer','bigdata','big data','ios developer','swift','flutter','hadoop','csharp','c sharp','c#','css','html','matlab','angular js','angular','nodejs','node js','node.js','angular.js','reactjs','react js','react.js','vuejs','vue js','vue.js','ui developer','jsp','jquery','rdbms','xhtml','dhtml','appdjango','vbscript','embedded c','app developer','wireless','iot','spring','pascal','javabeans','java beans','linux','azure','firebase','aws','xml','fortran','data analysis','solidity','amazon web service','redhat','alexa','cyber security','cordova','automation','drupal','machine learning','artificial intelligence','blockchain','hyperledger','ethereum','data migration','json','swing','backbone','ado','lamp','arduino','image processing','ccna','flask','mongodb','ruby','hibernate','oracle','ibm db2','teradata','ms access','joomla','indesign','acrobat','corel draw','docker','kubernetes','cobol','robotics','cyber security','augmented reality','virtual reality','autocad','solidworks','illustrator','ui/ux','ux/ui']
text2=text.replace("\n"," ")
text2=text2.lower()
#print(text2)
list1=[]
#search=''
for i in skills:
if(i in text2):
# print(i)
list1.append(i)
# search=search+' '+i
#print(list1)
s=''
s=','.join(i for i in list1)
#print("String: "+s)
#%%
import docxpy
import docx2txt
import unicodedata
# %%
text = docxpy.process('data/article one multiple topics.docx')
# %%
doc = docxpy.DOCReader('data/articletwo.docx')
# %%
text = doc.process()
# %%
import docx2txt
# %%
text = docx2txt.process('data/articletwo.docx')
# %%
from textsummarization import *
# %%
methods = ['bert_sum']
for i in methods:
print(i)
print(extract_sum(text, 0.5, i))
# %%
import torch
import json
# pa ="data/"+os.path.splitext(file)[0]+".txt"
# fw = open(pa,"w")
# fw.writelines(da)
# fw.close()
# break
# from dateutil.parser import parse
# print(parse('Jun 06'))
# import pandas as pd
# import numpy as np
# df = pd.Series([1,2,np.nan])
# print(df.head(1))
# print(df.index)
# print(np.random.randn(6,4))
# D12316
# import docx
#
# def getText(filename):
# doc = docx.Document(filename)
# fullText = []
# for para in doc.paragraphs:
# print(para.text)
# fullText.append(para.text)
# return '\n'.join(fullText)
path = "doc_file/Resume_Multiple_Email_Mobile_Rows.docx"
# print(getText(path))
import docxpy
text = docxpy.process(path)
print(text)
def get_text_from_docx(docx_path) :
file = docx_path
text = " ".join(docxpy.process(file).split())
return text
