Most of the actual tweets would probably be in a paragraph tag, or have a specific class or other identifying feature. In the above example, we can see that we might have a lot of information we wouldn’t want to scrape, such as the header, the logo, navigation links, etc. Secondly, a web scraper would need to know which tags to look for the information we want to scrape. At the bare minimum, each web scraping project would need to have a URL to scrape from. As you might imagine, the data that we gather from a web scraper would largely be decided by the parameters we give the program when we build it. We might limit the gathered data to tweets about a specific topic, or by a specific author.
#WEBSCRAPER OUT OF SELENIUM DRIVER#
I'm still learning :) from selenium import webdriver from import By from import WebDriverWait from import expected_conditions as EC from import TimeoutException from bs4 import BeautifulSoup from import NoSuchElementException import time import random import pprint import itertools import csv import pandas as pd start_url = "" driver = webdriver.Firefox() t_page_load_timeout(20) driver.get(start_url) #accepts cookies wait = WebDriverWait(driver, random.randint(1500,3200)/1000.0) j = random.randint(1500,3200)/1000.0 time.sleep(j) num_jobs = int(driver.find_element_by_xpath('/html/body/div/div/main/div/div/div/header/h2/span').In the above example, we might use a web scraper to gather data from Twitter. " + str(ex)) driver.close() except NoSuchElementException: continue join(text) vacature.append(text) vacatures.append(vacature) driver.close() except TimeoutException as ex: isrunning = 0 print("Exception has been thrown. I'm still learning :) from selenium import webdriver from import By from import WebDriverWait from import expected_conditions as EC from import TimeoutException from bs4 import BeautifulSoup from import NoSuchElementException import time import random import pprint import itertools import csv import pandas as pd start_url = "" driver = webdriver.Firefox() t_page_load_timeout(20) driver.get(start_url) #accepts cookies wait = WebDriverWait(driver, random.randint(1500,3200)/1000.0) j = random.randint(1500,3200)/1000.0 time.sleep(j) num_jobs = int(driver.find_element_by_xpath('/html/body/div/div/main/div/div/div/header/h2/span').text) num_pages = int(num_jobs/102) urls = list_of_links = for i in range(num_pages+1): try: elements = wait.until(EC.presence_of_all_elements_located((By.XPATH, for i in elements: list_of_links.append(i.get_attribute('href')) j = random.randint(1500,3200)/1000.0 time.sleep(j) if 'page=3' not in driver.current_url: driver.find_element_by_xpath('//html/body/div/div/main/div/div/div/paginator/div/nav/ul/li/a').click() else: driver.find_element_by_xpath('//html/body/div/div/main/div/div/div/paginator/div/nav/ul/li/a').click() url = driver.current_url if url not in urls: print(url) urls.append(url) else: break except: continue set_list_of_links = list(set(list_of_links)) print(len(set_list_of_links), "results") driver.close() def grouper(n, iterable): it = iter(iterable) while True: chunk = tuple(itertools.islice(it, n)) if not chunk: return yield chunk def remove_empty_lists(l): keep_going = True prev_l = l while keep_going: new_l = remover(prev_l) #are they identical objects? if new_l = prev_l: keep_going = False #set prev to new prev_l = new_l #return the result return new_l def remover(l): newlist = for i in l: if isinstance(i, list) and len(i) != 0: newlist.append(remover(i)) if not isinstance(i, list): newlist.append(i) return newlist vacatures = chunks = grouper(100, set_list_of_links) chunk_count = 0 for chunk in chunks: chunk_count +=1 print(chunk_count) j = random.randint(1500,3200)/1000.0 time.sleep(j) for url in chunk: driver = webdriver.Firefox() t_page_load_timeout(20) try: driver.get(url) #accepts cookies vacature = vacature.append(url) j = random.randint(1500,3200)/1000.0 time.sleep(j) elements = driver.find_elements_by_tag_name('dl') p_elements = driver.find_elements_by_tag_name('p') li_elements = driver.find_elements_by_tag_name('li') for i in elements: if "Salaris:" not in i.text: vacature.append(i.text) running_text = list() for p in p_elements: running_text.append(p.text) text= remove_ls = for li in li_elements: if li.text not in remove_ls: text.append(li.text) text = ''.
#WEBSCRAPER OUT OF SELENIUM HOW TO#
I read something about using parallel processes to process the URLs but I have no clue how to go about it and incorporate it in what I already have. I've made something that works, but it takes hours and hours to get everything I need.