# ----------Imports------------ from datetime import date from traceback import print_tb from unittest import result from urllib import response from urllib.request import Request from bs4 import BeautifulSoup from matplotlib import dates from numpy import diag_indices import requests import pandas as pd import random # List of User-Agent user_agent_list = [ 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/93.0.4577.82 Safari/537.36', 'Mozilla/5.0 (iPhone; CPU iPhone OS 14_4_2 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/14.0.3 Mobile/15E148 Safari/604.1', 'Mozilla/4.0 (compatible; MSIE 9.0; Windows NT 6.1)', 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/87.0.4280.141 Safari/537.36 Edg/87.0.664.75', 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/18.18363', ] user_agent = user_agent_list[random.randint(0, len(user_agent_list)-1)] headers = {'User-Agent': user_agent} # Array of object filteri podaci_db = [] # Pagination cross webpages # n is number of pages to crawl pages_number_to_crawl = 2 for i in range(1,pages_number_to_crawl): # if kategorija=18 - Automobili main_website = 'https://www.olx.ba/pretraga?kategorija=883&id=1&stanje=0&vrstapregleda=tabela&sort_order=desc&sort_po=datum&stranica=' + str(i) category_of_vehicle = 883 # Request to website response_for_page = requests.get(main_website, headers=headers) # Soup object soup_page = BeautifulSoup(response_for_page.content, 'html.parser') # Results results_all_items_per_page = soup_page.find_all('div',{'class':'listitem'}) # List of olx id olx_id = [] # All filters filters = { "Olx_id" : None, "Kategorija" : None, "Cijena" : None, "Stanje" : None, "Lokacija_kanton" : None, "Lokacija_grad" : None, "Brend" : None, "Godište" : None, "Kilometraža" : None, "Vrsta" : None, "Gorivo" : None, "Konjskih snaga" : None, "Kilovata (KW)" : None, "Kubikaža" : None, "Masa/Težina (kg)" : None, "Airbag" : None, "Broj prozora" : None, "Mjesta za spavanje" : None, "Pogon" : None, "Veličina felgi" : None, "Transmisija" : None, "Boja" : None, "Muzika" : None, "Otvor na krovu" : None, "Model" : None, "Alarm" : None, "Daljinsko otključavanje" : None, "Registrovan" : None, "Metalik" : None, "Servisna knjiga" : None, "El. podizači stakala" : None, "Tempomat" : None, "Servo volan" : None, "Komande na volanu" : None, "Navigacija" : None, "Ocarinjen" : None, "Strane tablice" : None, "Kuhinja" : None, "Šporet" : None, "Sudoper" : None, "Frižider" : None, "Tenda" : None, "Kupatilo (Tuš)" : None, "WC" : None, "Grijanje" : None, "Klimatizirano" : None, "Oštećen" : None, "Datum" : None, "Vrijeme" : None } # Number of all items broj_el = 0 # Getting all id's of articles for i in range(0, len(results_all_items_per_page)): if(results_all_items_per_page[i].find('p')): # Divide id from rest of link address_content = results_all_items_per_page[i].find('a')['href'] temp = address_content.split('/') artikal_number = temp[4] olx_id.append(artikal_number) broj_el = broj_el + 1 for i in range(0, broj_el): # New dictionary instance for every item podaci = filters.copy() # Add kategorija if (category_of_vehicle == 883): podaci['Kategorija'] = ('Kamperi') # Artikal olx_link artikal_link = 'https://www.olx.ba/artikal/' + olx_id[i] podaci["Olx_id"] = olx_id[i] response_item = requests.get(artikal_link, headers=headers) soup_item = BeautifulSoup(response_item.content, 'html.parser') result_item = soup_item.find('div',{'class':'artikal_lijevo'}) # Getting filters info from item # Osnovni filteri # Cijena if (result_item.find('div',{'id':'pc'})): x_cijena = result_item.find('div',{'id':'pc'}).findAll('p') item_cijena = x_cijena[1].get_text().split()[0] if(item_cijena == 'Po'): item_cijena = "Po dogovoru" podaci['Cijena'] = item_cijena # Lokacija #kanton if (result_item.find('div',{'class':'mobile-lokacija'})): x_lokacija = result_item.find('div',{'class':'mobile-lokacija'})['data-content'].split() item_kanton = x_lokacija[0].replace(',','') podaci['Lokacija_kanton'] = item_kanton #grad x_lokacija.pop(0) item_grad = x_lokacija mojstring = ' '.join(item_grad) podaci['Lokacija_grad'] = mojstring # Stanje if (result_item.find('div',{'class':'mobile-stanje'})): x_stanje = result_item.find('div',{'class':'mobile-stanje'}).get_text().split() item_stanje = x_stanje[1] podaci['Stanje'] = item_stanje # Napredni filteri # Dodatna polja if (result_item.find_all('div',{'id':'dodatnapolja1'})): dodatnapolja_all_divs = result_item.find_all('div',{'id':'dodatnapolja1'}) for i in range (0,len(dodatnapolja_all_divs)): df_pom = dodatnapolja_all_divs[i].find_all('div',{'class','df'}) for j in range (0,len(df_pom)): df_pom1 = df_pom[j].find('div',{'class','df1'}).get_text() if (df_pom[j].find('div',{'class','df2'}).find('i')): df_pom2 = True else : df_pom2 = df_pom[j].find('div',{'class','df2'}).get_text() podaci[df_pom1] = df_pom2 # Vrijeme i datum if (result_item.find('time', {'class' : 'entry-date'})): date_time_div = result_item.find('time', {'class' : 'entry-date'}).get_text().split() datum = date_time_div[0] vrijeme = date_time_div[2] podaci["Datum"] = datum podaci["Vrijeme"] = vrijeme # Insert datas to database dictionary_copy = podaci.copy() podaci_db.append(dictionary_copy) # ------------- CREATE PANDAS DATAFRAME - DICTIONARY -------------- olx_db = pd.DataFrame(podaci_db) # treba biti niz # print(olx_db) olx_db.to_excel('test_kamperi1.xlsx',index=False)