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