CleanResume.py

import os
import sys
from pdfminer.pdfparser import PDFParser, PDFDocument
import subprocess
import re
import numpy as np
from tqdm import tqdm
import pandas as pd
from nltk.corpus import stopwords
import nltk

stop = stopwords.words("english")

def plan_text(path):
	'''
	Return in clean plane text without stop words in it  /// 
	'''
	proc = subprocess.Popen(['pdf2txt.py',path], stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
	temp=proc.communicate()[0]
	temp = temp.decode('ascii', errors='ignore') 
	cleanText = re.sub("\n", "", temp)
	document = " ".join([i for i in cleanText.split() if i not in stop])
	sentences = nltk.sent_tokenize(document)
	cleanText=" ".join(sentences)
	return cleanText



def pdf2CleanResume(directory):
	""" directory is the location of all Resume in PDF format.
	for example: ./ResumePdf/ 

	Return is the Clean Resume format as a plan text

	"""
	DEBUG =False
	directory=directory
	l = []
	for file in os.listdir(directory):
		fl = directory + file
		if DEBUG : print (fl)
		l.append(fl)
	# the os.listdir function do not give the files in the right order 
	#so we need to sort them
	l=sorted(l)
	clean_resume=[]
	for i in tqdm(range(len(l))):
		clean_resume.append(plan_text(l[i]))

	return clean_resume