# Scraping Indeed Job Data Using Python # import moduleimport requestsfrom bs4 import BeautifulSoup    # user define function# Scrape the data# and get in stringdef getdata(url):    r = requests.get(url)    return r.text  # Get Html code using parsedef html_code(url):      # pass the url    # into getdata function    htmldata = getdata(url)    soup = BeautifulSoup(htmldata, 'html.parser')      # return html code    return(soup)  # filter job data using# find_all functiondef job_data(soup):        # find the Html tag    # with find()    # and convert into string    data_str = ""    for item in soup.find_all("a", class_="jobtitle turnstileLink"):        data_str = data_str + item.get_text()    result_1 = data_str.split("\n")    return(result_1)  # filter company_data using# find_all function    def company_data(soup):      # find the Html tag    # with find()    # and convert into string    data_str = ""    result = ""    for item in soup.find_all("div", class_="sjcl"):        data_str = data_str + item.get_text()    result_1 = data_str.split("\n")      res = []    for i in range(1, len(result_1)):        if len(result_1[i]) > 1:            res.append(result_1[i])    return(res)    # driver nodes/main functionif __name__ == "__main__":      # Data for URL    job = "data+science+internship"    Location = "Noida%2C+Uttar+Pradesh"    url = "https://in.indeed.com/jobs?q="+job+"&l="+Location      # Pass this URL into the soup    # which will return    # html string    soup = html_code(url)      # call job and company data    # and store into it var    job_res = job_data(soup)    com_res = company_data(soup)      # Traverse the both data    temp = 0    for i in range(1, len(job_res)):        j = temp        for j in range(temp, 2+temp):            print("Company Name and Address : " + com_res[j])          temp = j        print("Job : " + job_res[i])        print("-----------------------------")