I’m trying to pull data from an Airtable database using Python but running into some issues. The main problem is that the content loads dynamically when you scroll through the page. I’ve already attempted to use the requests library along with BeautifulSoup, but these tools don’t seem to work well with the dynamic content loading that Airtable uses.
When I try to scrape the page, I only get the initial HTML without the actual data that appears after scrolling. Has anyone successfully extracted information from Airtable using Python? What libraries or approaches would work better for handling the dynamic content? I’m looking for a reliable method that can capture all the data without having to manually scroll through the interface.
Any suggestions or code examples would be really helpful. I’m open to using different libraries like Selenium if that’s what it takes to get this working properly.
Been there! Fought with Selenium for way too long trying to scrape Airtable a couple years back before realizing I was making it harder than it needed to be.
API’s definitely the way to go like amelial said. If you can’t use it though (no base access, permission issues, whatever), then you’re stuck with Selenium and explicit waits.
This worked for me when I had to scrape:
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
# Wait for specific elements to load before trying to extract
wait = WebDriverWait(driver, 10)
wait.until(EC.presence_of_element_located((By.CLASS_NAME, "your-data-class")))
Seriously though, just use the API. JSON responses, proper errors, no browser nonsense. Takes 5 minutes vs hours debugging scroll weirdness.
why not just use airtable’s api instead of scraping? way easier and more reliable than selenium. you get an api key from your account settings and can fetch records directly with requests. no need to deal with that dynamic loading headache
Had the same issue last year with a client’s Airtable data. Started scraping but it’s a maintenance nightmare. Their dynamic loading breaks every time they update the frontend, and you’ll spend more time fixing your scraper than using the data.
The official API is actually pretty easy once you figure it out. You can grab 100 records per request and paginate through bigger datasets. If you want a wrapper instead of raw requests, pyairtable makes it even easier. Just pull your base ID from the URL and generate an API token in developer settings.
I’d only scrape if you absolutely can’t get API access to the base. Even then, ask the owner to export data periodically instead of dealing with a fragile scraper.