Top Web Scraping APIs with Python SDK Support in 2026

Top Web Scraping APIs with Python SDK Support in 2026

A good Python SDK makes or breaks a scraping API. You want clean installation via pip, sensible defaults, async support, and error handling that doesn't require reading three pages of docs. This roundup covers the web scraping APIs with the best Python developer experience in 2026.

Key Takeaways

• SearchHive ScrapeForge combines the cheapest pricing ($9/5K) with native markdown output and a clean Python SDK
• Firecrawl has a strong SDK but costs 8x more per credit than SearchHive at scale
• ScrapingBee and ScraperAPI have reliable SDKs but return raw HTML — no LLM-ready output
• Apify offers the most Python SDK features (actors, datasets, scheduling) but the learning curve is steep

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What Makes a Good Scraping API SDK

Before diving into specific tools, here's what matters in a Python scraping SDK:

• Single-command install (pip install <package>)
• Synchronous + async support
• Typed responses (not raw dicts everywhere)
• Built-in retry logic for rate limits and transient failures
• Batch operations (scrape multiple URLs in one call)
• Clear error messages that tell you what went wrong and what to do about it
• Pagination helpers for scraping multiple pages of the same site

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1. SearchHive ScrapeForge

SearchHive's Python SDK covers all three products — SwiftSearch, ScrapeForge, and DeepDive — under one package. The scraping SDK returns markdown by default, which is what most Python developers working with LLMs actually want.

Install: pip install searchhive

Pricing: 500 free credits/month, Starter $9/5K, Builder $49/100K, Unicorn $199/500K.

Code example:

from searchhive import ScrapeForge

client = ScrapeForge(api_key="your-key")

# Single page scrape
result = client.scrape("https://example.com/article")
print(result["markdown"])

# Batch scrape with JS rendering
pages = client.batch_scrape(
    urls=[
        "https://example.com/products/1",
        "https://example.com/products/2",
        "https://example.com/products/3"
    ],
    render_js=True,
    format="markdown"
)

for page in pages:
    print(page["url"], len(page["content"]))

# Extract structured data
product = client.scrape(
    "https://example.com/product/123",
    extract={"name": "h1", "price": ".price-value", "description": ".product-desc"}
)
print(product["extracted"])

SDK quality: Clean API with type hints. Batch operations built in. Error handling returns structured error objects, not raw HTTP exceptions.

Learn more: /compare/firecrawl

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2. Firecrawl

Firecrawl's Python SDK is well-designed and widely adopted in the AI community. It integrates directly with LangChain and LlamaIndex.

Install: pip install firecrawl-py

Pricing: Free 500 credits, Hobby $16/3K, Standard $83/100K, Growth $333/500K, Scale $599/1M.

Code example:

from firecrawl import FirecrawlApp

app = FirecrawlApp(api_key="your-key")

# Scrape to markdown
result = app.scrape_url("https://example.com", params={"formats": ["markdown"]})
print(result["markdown"])

# Crawl a site
crawl = app.crawl_url("https://example.com/docs", params={
    "limit": 50,
    "scrapeOptions": {"formats": ["markdown"]}
})

for result in crawl:
    print(result["markdown"][:200])

SDK quality: Solid SDK with good LangChain integration. The crawl function handles recursion automatically. Downside: at $83/100K, it's one of the more expensive options.

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3. ScrapingBee

ScrapingBee's Python SDK is straightforward — it's essentially a wrapper around their HTTP API. Simple, but effective.

Install: pip install scrapingbee

Pricing: Freelance $49/250K, Startup $99/1M, Business $249/3M. JavaScript rendering costs 5 credits per request.

Code example:

from scrapingbee import ScrapingBeeClient

client = ScrapingBeeClient(api_key="your-key")

# Static page
response = client.get("https://example.com/data-page")
print(response.status_code)

# JavaScript rendering
response = client.get(
    "https://example.com/dynamic-page",
    params={"render_js": "true", "wait": 2000}
)

# Extract specific elements
response = client.get(
    "https://example.com/products",
    params={"extract_rules": '{"title": "h1", "price": ".price"}'}
)
print(response.json())

SDK quality: Simple and functional. No async support in the official SDK (you'd need to wrap it). Returns HTML — you handle parsing.

See our ScrapingBee alternatives guide.

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4. ScraperAPI

ScraperAPI's Python SDK is minimal — install, set API key, make requests. It handles retries and proxy rotation internally.

Install: pip install scraperapi-sdk

Pricing: Hobby $49/100K, Startup $149/500K, Business $349/2M.

Code example:

from scraperapi import ScraperAPIClient

client = ScraperAPIClient("your-key")

# Basic request
html = client.get("https://example.com", render_js=True)
print(len(html))

# With parameters
html = client.get(
    "https://example.com/search?q=python",
    render_js=True,
    premium=True,
    country_code="us"
)

SDK quality: Dead simple. Good for getting started quickly. No batch operations in the SDK — you'd loop manually. Returns raw HTML only.

See our ScraperAPI alternatives.

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5. Apify

Apify has the most feature-rich Python SDK on this list. It includes dataset management, actor scheduling, and webhook integrations.

Install: pip install apify-client

Pricing: Free tier ($5 credit/month), Starter $49/month, Business $149/month.

Code example:

from apify_client import ApifyClient

client = ApifyClient("your-token")

# Run a pre-built scraper
run = client.actor("apify/web-scraper").call(run_input={
    "startUrls": [{"url": "https://example.com/listings"}],
    "selectors": {"title": "h2.listing-title", "price": ".price"}
})

# Read results from dataset
dataset = client.dataset(run["defaultDatasetId"])
items = list(dataset.iterate_items())
print(f"Scraped {len(items)} items")

# Paginated result access
for i in range(0, len(items), 100):
    batch = items[i:i+100]
    # Process batch

SDK quality: Most complete SDK — datasets, actors, scheduling, webhooks, pagination. But the learning curve is steep. You need to understand Apify's platform concepts (actors, datasets, key-value stores) to use it effectively.

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6. ZenRows

ZenRows focuses on anti-bot bypass. The Python SDK is a thin wrapper around their REST API.

Install: pip install zenrows

Pricing: Starts at $49/month for 250K requests.

Code example:

from zenrows import ZenRows

client = ZenRows("your-key")

# Basic scrape
response = client.get("https://example.com")
print(response.status_code)

# Anti-bot bypass with premium proxies
response = client.get(
    "https://cloudflare-protected.com",
    params={
        "js_render": "true",
        "antibot": "true",
        "premium_proxies": "true"
    }
)

SDK quality: Functional but minimal. No batch operations, no structured extraction. Returns HTML — you parse it. Good async support available.

See our ZenRows alternatives.

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7. BeautifulSoup + Requests (DIY)

Not an API, but worth mentioning because many Python developers start here. Beautiful Soup is a parsing library — it doesn't handle proxies, rate limits, or JavaScript rendering.

Install: pip install beautifulsoup4 requests

Code example:

import requests
from bs4 import BeautifulSoup

resp = requests.get("https://example.com/products", headers={"User-Agent": "Mozilla/5.0"})
soup = BeautifulSoup(resp.text, "html.parser")

products = []
for item in soup.select(".product-card"):
    products.append({
        "name": item.select_one("h3").text.strip(),
        "price": item.select_one(".price").text.strip(),
        "url": item.select_one("a")["href"]
    })

print(products)

When to use: Learning, prototyping, or scraping simple static sites with no anti-bot protection. For anything production-grade, use a scraping API — the proxy rotation and retry logic alone justify the cost.

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SDK Comparison Table

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Our Recommendation

For Python developers building AI/LLM applications, SearchHive ScrapeForge delivers the best combination of SDK quality, pricing, and output format. Native markdown output means you skip the parsing step entirely.

For teams that need pre-built scrapers for specific platforms (LinkedIn, Amazon, Google Maps), Apify has the largest actor marketplace. The SDK is more complex but more capable.

For traditional scraping of simple sites, ScrapingBee or ScraperAPI work fine if you don't need markdown output.

Start with SearchHive's free tier — 500 credits, install the Python SDK with one pip command, and scrape your first page in under five minutes.