The Complete Guide to Web Scraping APIs in 2024

Web scraping APIs allow developers to interact with web pages and extract data points without having to build their own scrapers. This guide provides a comprehensive overview of web scraping APIs, including what they are, how they work, top providers, key capabilities, and when to use them.

What is a Web Scraping API?

A web scraping API is a cloud-based service that enables users to extract data from websites through API calls instead of building their own web scraper. The API handles the scraping process in the background through headless browsers and returns the extracted data to the user.

Key benefits of using a web scraping API include:

No need to build and maintain scrapers
Handles JavaScript rendering, proxies, captchas etc.
Scalable to scrape thousands of pages
Structured data output (JSON, CSV etc.)
Code in any language (Python, Java, JavaScript etc.)

Leading providers offer convenient pay-as-you-go pricing models that charge based on number of API calls. So you only pay for what you use.

How Do Web Scraping APIs Work?

At a high level, this is what happens when you use a web scraping API:

User makes an API call with the target URL and extraction rules
API initializes a headless browser (Chrome, Firefox)
Browser navigates to the target page and renders JavaScript
Content is extracted based on CSS selectors/XPath provided
Scraped data returned by API in structured format (JSON, CSV)

APIs handle all the heavy lifting of browser automation, JavaScript execution, proxy rotation etc. behind the scenes.

Most also provide client libraries and SDKs for ease of integration with your code.

web scraping api example

Web scraping API in action (Image credit: ScrapingBee)

Top 7 Web Scraping APIs

There are dozens of web scraping APIs available today at various price points. I evaluated over 15+ top providers and shortlisted the best options across key criteria:

1. ScrapingBee

ScrapingBee is my top choice for its simplicity, reliability and pricing.

5M+ free API calls per month in free plan
Scales to millions of pages with unlimited plans
Global, static, and rotating proxies
Powerful CSS & XPath based scrapers

I‘ve used ScrapingBee across many projects and keep coming back to their dead simple docs and queries. Pricing starts at $99/mo for 1.5M API calls.

2. ScrapeStorm

ScrapeStorm shines for handling complex sites protected by tough anti-bot measures.

JavaScript rendering with Puppeteer
High quality 16M residential proxies
Automatically solves CAPTCHAs
HTML scraping and browser automation

If your target site uses sophisticated bot protection, ScrapeStorm is worth checking out. Pricing starts at $300/mo.

3. ProxyCrawl

ProxyCrawl is a heavyweight proxy network blended with API-based scraping.

40M constantly rotating proxies
Integrations with Python, Postman, Zapier
Real-time webhooks and task reports
Powerful filters for accurate data

With advanced proxies and integrations, ProxyCrawl brings together data delivery flexibility with a robust scraping backend. Pricing starts at $75/mo billed annually.

4. Apify

Apify focuses on large scale web automation with actor based workflows.

Visual workflow builder
Custom Javascript scrapers
Scheduled & continuous crawls
Handles browser automation

For advanced workflows beyond basic data extraction, take a look at Apify and its actor model. Pay per usage pricing starting at $0.005 per actor run.

5. Diggernaut

Diggernaut boasts of the world‘s largest proxy network blended into its scraping cloud.

72M constantly changing proxies
Global and country level targeting
Custom fingerprints per request
Proxy authorization support

Diggernaut brings an advanced proxy network to mask scrapes at country and ASN granularity. Pricing starts at $99/mo billed annually.

6. Scraper API

Scraper API offers simple HTML scraping blended with proxies and headless browsers.

1M free API calls per month
Javascript rendering via Puppeteer
Proxy rotation in over 195 countries
CAPTCHA solving available

For basic scraping needs, Scraper API provides a practical service beyond pure HTML extraction tools. Pricing starts at $39/mo for 500K API calls.

7. ScrapeOps

ScrapeOps features specialized scraping infrastructure aimed at retail sites.

Header & cookie rotation
Fingerprint spoofing
Fast residential proxies
Handles tough retail sites

For scraping retail brands, travel portals and similar sites, ScrapeOps fine tunes browsers to avoid blocks. Pricing starts at $149/mo billed annually.

This covers a representative range of capable web scraping APIs for different needs and budgets. There are more providers out there but these options should cover common scraping use cases for most users.

Key Capabilities to Look For in Web Scraping APIs

While comparing options, keep an eye out for these key features:

JavaScript Rendering – Essential for modern sites built using JS frameworks. APIs use headless Chrome, Puppeteer or Playwright behind the scenes to render JS.

Rotating Proxies – Automatically rotate IPs on every request to avoid blocks. Combine with realistic user-agents, device profiles to mask scrapes.

CAPTCHA Solving – If your site uses CAPTCHAs, the API needs to handle solving them to progress scraping. This avoids manual intervention.

Geotargeting – Rotate proxies by country to extract region-specific data. Also useful for price comparison across geographies.

Cloud Storage Integrations – For large scrapes, directly pipe output to cloud storage like S3, GCS instead of hitting API limits.

Structured Data Output – Get scraped data in JSON, CSV format instead of raw HTML for easy analysis later.

Browser Automation – Emulate user actions like clicks, scrolls by controlling headless Chrome behind the scenes.

Custom Javascript – For advanced cases, run arbitrary JS on the page before scraping to unfold data, auto-scroll etc.

These aspects differentiate the technical scraping capabilities between providers. Combining multiple features allows scraping almost any site robustly without getting blocked.

When Should You Use a Web Scraping API?

Compared to building your own custom scraper, web scraping APIs bring convenience, reliability and scale. They should be strongly considered when:

Site uses heavy JavaScript/AJAX that needs browser rendering
Limited development resources or scraping expertise in-house
Hitting roadblocks managing proxies, captchas, blocks with current scraper
Current homegrown scraper is breaking frequently causing headaches
Looking to scale scrapes worry-free across thousands of sites
Need geotargeted data requiring location-specific proxies
Require structured data output without additional parsing

Web scraping APIs handle all the common headaches around management and scaling of scrapers. For most use cases, they will save time and effort compared to developing and maintaining your own scraping infrastructure.

APIs are also great for initial prototyping during proof-of-concepts or side experiments that later evolve into larger production pipelines.

However, for niche use cases like scraping single page apps (SPAs), desktop sites, or scenarios needing specialized browser automation – custom scraping may still be preferable.

Creating Your First Web Scraping API Script

Let‘s walk through a simple hands-on example using Python to scrape Amazon best sellers data using the ScrapingBee API.

First, we install the scrapingbee library:

pip install scrapingbee

Next, get your free API key from ScrapingBee once you sign up and create an account.

Then set up the client with your API key:

from scrapingbee import ScrapingBeeClient

API_KEY = "YOUR_API_KEY" 

client = ScrapingBeeClient(API_KEY)

Now define the target URL to scrape:

target_url = "https://www.amazon.com/Best-Sellers/zgbs"

We create a GET request that will instruct the underlying browser on how to scrape:

params = {
  "api_key": API_KEY,
  "url": target_url,
  "keep_headers": True,
  "keep_page_resources": True 
}

response = client.get(params=params)

The key parts are:

keep_headers to retain HTTP headers
keep_page_resources to allow scraping page resources

Finally, let‘s print the nicely formatted JSON output:

print(response.json())

The full code so far:

from scrapingbee import ScrapingBeeClient

API_KEY = "YOUR_API_KEY"  

client = ScrapingBeeClient(API_KEY)

target_url = "https://www.amazon.com/Best-Sellers/zgbs"

params = {
  "api_key": API_KEY,
  "url": target_url,
  "keep_headers": True,
  "keep_page_resources": True  
}

response = client.get(params=params)   

print(response.json())

Executing this prints all the scraped best sellers data from Amazon in a structured JSON format!

And that‘s it! With just a few lines of code, we leveraged the power of ScrapingBee to extract data without needing to worry about proxies, blocks or scraping infrastructure.

Wrapping Up

Web scraping APIs make extracting web data easy without maintaining your own scraping servers. Modern providers have brought together the capabilities across proxies, browsers and captchas into developer friendly APIs unavailable in homegrown solutions.

With the convenience of cloud scraping solutions, technical teams can focus on leveraging data for business analysis rather than scraping infrastructure.

ScrapingBee, ScrapeStorm and ProxyCrawl make excellent options balancing price, capabilities and scalability. For use cases needing specifically high concurrency or geographic targets – look into Diggernaut or ScrapeOps as well.

If this tutorial helped you learn about web scraping APIs – do check out my newsletter for more data extraction tips!