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Using Selenium

Selenium is a tool for web automation and testing that can also be used for web scraping. It allows you to control a web browser programmatically and interact with web pages just as a human would.

Some of the key features of Selenium for web scraping include:

  • Cross-browser support - Selenium supports the latest versions of major browsers like Chrome, Firefox, and Safari, so you can choose the one that suits your needs the best.
  • Headless mode - Selenium can run in headless mode, meaning that the browser window is not visible on your screen while it is scraping, which can be useful for running scraping tasks in the background or in containers without a display.
  • Powerful selectors - Selenium provides a variety of powerful selectors that allow you to target specific elements on a web page, including CSS selectors, XPath, and text matching.
  • Emulation of user interactions - Selenium allows you to emulate user interactions like clicking, scrolling, filling out forms, and even typing in text, which can be useful for scraping websites that have dynamic content or require user input.

Using Selenium in Actors

To create Actors which use Selenium, start from the Selenium & Python Actor template.

On the Apify platform, the Actor will already have Selenium and the necessary browsers preinstalled in its Docker image, including the tools and setup necessary to run browsers in headful mode.

When running the Actor locally, you'll need to install the Selenium browser drivers yourself. Refer to the Selenium documentation for installation instructions.

Example Actor

This is a simple Actor that recursively scrapes titles from all linked websites, up to a maximum depth, starting from URLs in the Actor input.

It uses Selenium ChromeDriver to open the pages in an automated Chrome browser, and to extract the title and anchor elements after the pages load.

from urllib.parse import urljoin

from apify import Actor
from selenium import webdriver
from import Options as ChromeOptions
from import By

async def main():
async with Actor:
# Read the Actor input
actor_input = await Actor.get_input() or {}
start_urls = actor_input.get('start_urls', [{ 'url': '' }])
max_depth = actor_input.get('max_depth', 1)

if not start_urls:'No start URLs specified in actor input, exiting...')
await Actor.exit()

# Enqueue the starting URLs in the default request queue
default_queue = await Actor.open_request_queue()
for start_url in start_urls:
url = start_url.get('url')'Enqueuing {url} ...')
await default_queue.add_request({ 'url': url, 'userData': { 'depth': 0 }})

# Launch a new Selenium Chrome WebDriver'Launching Chrome WebDriver...')
chrome_options = ChromeOptions()
if Actor.config.headless:
driver = webdriver.Chrome(options=chrome_options)

assert driver.title == 'Example Domain'

# Process the requests in the queue one by one
while request := await default_queue.fetch_next_request():
url = request['url']
depth = request['userData']['depth']'Scraping {url} ...')

# Open the URL in the Selenium WebDriver

# If we haven't reached the max depth,
# look for nested links and enqueue their targets
if depth < max_depth:
for link in driver.find_elements(By.TAG_NAME, 'a'):
link_href = link.get_attribute('href')
link_url = urljoin(url, link_href)
if link_url.startswith(('http://', 'https://')):'Enqueuing {link_url} ...')
await default_queue.add_request({
'url': link_url,
'userData': {'depth': depth + 1 },

# Push the title of the page into the default dataset
title = driver.title
await Actor.push_data({ 'url': url, 'title': title })
Actor.log.exception(f'Cannot extract data from {url}.')
await default_queue.mark_request_as_handled(request)