Das deutsche Python-Forum

Code: Alles auswählen

Hersteller=soup.find('h1',class_='col-xs-8')
    if Hersteller is not None:
        Hersteller=Herstellert.text.strip()
    else:
        Hersteller='N/A'
    print(Hersteller)
    
    amount=soup.find('div',class_='col-xs-8')
    if len (amount) >0:
        amount = amount[0].text.strip() 
    else:
        amount='N/A'
    print(amount)

Code: Alles auswählen

from bs4 import BeautifulSoup
import requests


HEADERS = {"User-Agent":"Mozilla/5.0 (Windows NT 6.1; WOW64; rv:44.0) Gecko/20100101 Firefox/44.0"}


def main():
    url = "https://www.apo-rot.de/details/baldriparan-zur-beruhigung-ueberzogene-tabletten/10124803.html?_menuid=7685764&_nav=nervensystem_stress__beruhigun.beruhigung_stress__schlaf.beruhigungs__schlafmittel"
    page = requests.get(url, headers=HEADERS)
    soup = BeautifulSoup(page.content, "html.parser")
    info = soup.find('div',{'data-sourcefile':'details_info-standard-details.jsp'}).find_all('div',{'class':'col-xs-4 bold'})
    for element in info:
        if "Hersteller:" in element.text:
            hersteller = element.find_next('div',{'class':'col-xs-8'}).text.strip()
        elif "Menge:" in element.text:
            menge = element.find_next('div',{'class':'col-xs-8'}).text.strip()
    print(f"Hersteller: {hersteller}")
    print(f"Menge: {menge}")


        
main()

Code: Alles auswählen

import requests
from bs4 import BeautifulSoup
import csv
import pandas as pd
from time import sleep


def connect():
    try:
        requests.get('http://google.com') #Python 3.x
        return True
    except:
        return False
def gernate_file():
    headers_text = []
    headers_text.append('Article Number')
    headers_text.append('Title')
    headers_text.append('menge')
    headers_text.append('hersteller')
    headers_text.append('Price')
    headers_text.append('Categorie')
    headers_text.append('Link')
    headers_text.append('Image Url')
    headers_text.append('Article Number')

    df = pd.DataFrame([], columns=headers_text)
    df.to_csv('Results.csv', index=False, encoding='utf-8-sig')
def hasNumbers(inputString):
    return any(char.isdigit() for char in inputString)
# url='https://produkte.migros.ch/milch-extra-12x100g'
# url='https://produkte.migros.ch/les-adorables-marc-de-champagne'
def profileScraper(url,index):
    while(not connect()):
        print('no internet')
        sleep(5)
    res= requests.get(url)
    soup=BeautifulSoup(res.content,features='html.parser')
    
    
    title=soup.find('span',class_='hidden-xs')
    if title is not None:
        title=title.text.strip()
    else:
        return 0
    print(title)
    
    
    Hersteller=soup.find('div',class_='col-xs-8')
    if Hersteller is not None:
        Hersteller=Hersteller.text.strip()
    else:
        Hersteller='N/A'
    print(Hersteller)
    
    
    Price=soup.find('span',class_='')
    if Price is not None:
        Price = Price.text.strip() 
    else:
        Price='N/A'
    print(Price)
    
    Categories=soup.find_all('a',class_='overflow-hidden')
    if len(Categories) >0:
        # print(Categories[2].text.strip())
        Categories = Categories[0].text.strip()
    else:
        # print(Categories[-2].text.strip())
        Categories = Categories[-2].text.strip()
    print(url)
    
    
    
    menge=soup.find_next('div',class_='col-xs-8')
    if menge is not None:
        menge=menge.text.strip()
    else:
        menge='N/A'
    print(menge)
    

    img_tag1=soup.find('div',class_='details_image')
    if img_tag1 is not None:
        img_tag = img_tag1.find('img',class_='img-responsive')
        if img_tag is not None:   
            img_url=img_tag['src']
            img_url_text=img_url.replace('//','')
    print(img_url_text)
        
        
    
    article_no = soup.find('div',class_='col-xs-8')
    if article_no is not None:
        article_no=article_no.text.strip()
    print(article_no)
    
    return[index,title,'`'+Hersteller,menge,Price,Categories,url,img_url_text,article_no]
#Migrolist.csv
with open('Ikea.csv', 'r', encoding='utf-8') as readFile:
    reader = csv.reader(readFile)
    file_lines = list(reader)

# print(file_lines[1][8])
gernate_file()
for index, row in enumerate(file_lines[1:]): 
    print(index)
    # print(row[7])
    record=[]
    record =  profileScraper(row[6],index+1)
    df = pd.DataFrame([record])
    df.to_csv('Ikea1.csv', index=False, mode='a',  encoding='utf-8-sig', header=False)
    # break
print()
print()
# print(record)