Originally published byDev.to
Web Scraping with Python in 2026: Best Libraries and Anti-Bot Strategies
Web scraping in 2026 looks very different from 2020. Sites are smarter, anti-bot systems are more aggressive, and the legal landscape has evolved. Here's what actually works now.
The 2026 Scraping Landscape
| Challenge | 2020 Solution | 2026 Solution |
|---|---|---|
| Bot detection | Rotate User-Agent | Fingerprint randomization + residential proxies |
| CAPTCHAs | Manual solving | Turnstile/hCaptcha solvers |
| JavaScript rendering | Selenium | Playwright (faster, more reliable) |
| Rate limiting | Sleep between requests | Adaptive pacing + request signing |
| IP blocking | VPN rotation | Residential proxy pools |
Best Libraries in 2026
1. Playwright (Best for JS-heavy sites)
from playwright.sync_api import sync_playwright
def scrape_with_playwright(url):
with sync_playwright() as p:
browser = p.chromium.launch(headless=True)
page = browser.new_page()
page.goto(url, wait_until="networkidle")
data = page.query_selector_all(".job-item")
results = []
for item in data:
title = item.query_selector("h2").text_content()
results.append(title)
browser.close()
return results
2. httpx + Selectolax (Fast, no JS needed)
import httpx
from selectolax.parser import HTMLParser
def scrape_static(url):
resp = httpx.get(url, headers={"User-Agent": "Mozilla/5.0"})
tree = HTMLParser(resp.text)
for node in tree.css(".listing"):
print(node.text())
3. API-First Approach (Always check first!)
Many sites have hidden or public APIs that make scraping unnecessary:
url = "https://www.freelancer.com/api/projects/0.1/projects/active/?query=python"
data = httpx.get(url).json()
Anti-Bot Strategies That Work
1. Request Fingerprint Randomization
import random
def get_random_headers():
browsers = [
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36",
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36",
]
return {
"User-Agent": random.choice(browsers),
"Accept": "text/html,application/xhtml+xml",
"Accept-Language": "en-US,en;q=0.9",
"DNT": "1",
}
2. Adaptive Rate Limiting
import time
class AdaptiveLimiter:
def __init__(self, min_delay=1.0, max_delay=5.0):
self.min_delay = min_delay
self.max_delay = max_delay
self.current_delay = min_delay
def wait(self):
time.sleep(self.current_delay)
def on_success(self):
self.current_delay = max(self.min_delay, self.current_delay * 0.9)
def on_block(self):
self.current_delay = min(self.max_delay, self.current_delay * 1.5)
Key Takeaways
- Always check for APIs first โ scraping should be the fallback
- Playwright for JS sites, httpx for static
- Randomize fingerprints โ headers, timing, viewport
- Adapt your rate โ slow down when blocked, speed up when clear
- Stay legal โ public data only, respect robots.txt
Building scraping tools? Follow for more practical guides. See my projects on GitHub.
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