110 lines
2.9 KiB
Python
110 lines
2.9 KiB
Python
from threading import Thread
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import json
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import os
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import shelve
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from bs4 import BeautifulSoup
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from time import perf_counter
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import time
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import re
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#Data process
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from nltk.tokenize import word_tokenize
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from nltk.stem import PorterStemmer
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from sklearn.feature_extraction.text import TfidfVectorizer
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import pandas as pd
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import numpy as np
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from collections import Counter
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from posting import Posting
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import sys
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class Worker(Thread):
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def __init__(self,indexer,target):
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self.file = target
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self.indexer = indexer
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super().__init__(daemon=True)
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def run(self):
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print("Target: " + str(self.file))
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ticker = perf_counter()
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tic = perf_counter()
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file_load = open(self.file)
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data = json.load(file_load)
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soup = BeautifulSoup(data["content"],features="lxml")
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words = word_tokenize(soup.get_text())
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toc = perf_counter()
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if toc - tic > 1 :
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print("Took " + str(toc - tic) + "seconds to tokenize text !")
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tokenized_words = list()
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stemmed_words = list()
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important = {'b' : [], 'h1' : [], 'h2' : [], 'h3' : [], 'title' : []}
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for key_words in important.keys():
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for i in soup.findAll(key_words):
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for word in word_tokenize(i.text):
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important[key_words].append(self.indexer.stemmer.stem(word))
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tic = perf_counter()
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for word in words:
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if word != "" and re.fullmatch('[A-Za-z0-9]+',word):
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#So all the tokenized words are here,
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tokenized_words.append(word)
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toc = perf_counter()
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if toc - tic > 1 :
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print("Took " + str(toc - tic) + "seconds to isalnum text !")
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#YOUR CODE HERE
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tic = perf_counter()
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for word in tokenized_words:
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stemmed_words.append(self.indexer.stemmer.stem(word))
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#stemming,
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#tf_idf
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#get_tf_idf(stemmed_words,word)
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#post = Posting()
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toc = perf_counter()
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if toc - tic > 1 :
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print("Took " + str(toc - tic) + "seconds to stemmed text !")
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counts = Counter(stemmed_words)
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size = len(stemmed_words)
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for word in counts:
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#posting = Posting(data["url"],self.get_tf_idf(list(' '.join(stemmed_words)),word))
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tic = perf_counter()
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weight = 1.0
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index = 0
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"""
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for group in important:
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for word_important in group:
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if word_important.lower() == word.lower():
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if index == 0:
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weight = 1.2
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elif index == 1:
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weight = 1.8
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elif index == 2:
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weight = 1.5
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elif index == 3:
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weight = 1.3
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elif index == 4:
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weight = 2.0
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index = index + 1
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"""
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posting = Posting(data["url"],counts[word]/size*weight)
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toc = perf_counter()
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if toc - tic > 1 :
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print("Took " + str(toc - tic) + "seconds to tf_idf text !")
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tic = perf_counter()
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self.indexer.save_index(word,posting)
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toc = perf_counter()
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if toc - tic > 1 :
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print("Took " + str(toc - tic) + "seconds to save text !")
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tocker = perf_counter()
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print("Finished " + data['url'] + "\n" + str(tocker-ticker))
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