Scraping Booking.com Data for Competitive Pricing Analysis - How OTAs Gain Market Advantage
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Fundamental knowledge extracting data using CSS selectors
CSS selectors state which part of markup any style applies therefore allowing to scrape data to match attributes and tags.
It’s a thing, which makes a self-determining set of libraries installed including various Python versions, which can co-occur with each other with the similar system therefore anticipation libraries or Python version fights.
📌Note: It is not a severe requirement for the given blog post.
You have to install chromium for playwright for working and operate a browser:
After doing that, if you’re using Linux, you may have to install extra things (playwright would prompt you with the terminal if anything is missing):
There’s a possibility that a request could get blocked. See how to decrease the chances of getting blocked when doing web scraping, eleven methods are there to bypass different blocks from maximum websites and a few of them would get covered in the blog post.
Import libraries
time for setting sleep() intervals among every scroll.
json just to do printing.
sync_playwright for synchronal API. playwright get asynchronous API while using an asyncio module.
Announce a function:
Prepare playwright, attach to chromium, launch() the browser new_page() and goto() the given URL:
playwright.chromiumis the connection to a Chromium browser example. launch() would launch a browser, and headless arguments will run that in a headless mode. The default is True.
new_page() makes a newer page in the new browser background.
page.goto("URL") would make the request to a given website.
After that, we had to check in case, the button accountable to show all reviews is available and click on that if available:
query_selector is a function, which accepts the CSS selectors to get searched.
click is clicking on a button and force=True would bypass auto-waits and then click directly.
Scroll to bottom of a comments window:
page.evaluate() would run the JavaScript code within a browser context, which will measure height of a .fysCi selector. scrollTop finds total pixels scrolled from the given elements, in the case of CSS selector.
time.sleep(3) would stop executing code for 3 seconds for loading more comments.
Then this would measure the new_height after scroll running similar measurement JavaScript codes.
Finally, this would check if new_height == last_height, and exit the while loop using break.
else set a last_height to new_height as well as run an iteration (scroll) once more.
Then, pass scrolled the HTML content for parsel, close a browser:
Repeat the general results after a while loop gets done:
Print this data:
Run the code with context manager:
As we help scraping review data from the Google Play App, the section shows a comparison between DIY solutions and our solutions.
The major difference is, you don’t have to utilize browser automation for scraping results, make a parser from the scratch as well as maintain that.
Remember that there’s a chance also, which request could get blocked at a few points from the Google (CAPTCHA), we deal with that on the backend.
Install google-search-results from PyPi:
Output:
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