⚙️JavaScript Rendering
Web Scraping API for Python
Beautiful Soup is lovely. Scrapy is powerful. Both require you to write parsers. denkbot.dog returns structured JSON so you can skip straight to the data science part. The dog does the fetching. You do the pandas.
What you'd use this for
Python data pipelines, Jupyter notebooks, Django/Flask applications, automation scripts, and ML data collection workflows.
How it works
example
import requests
API_KEY = "your_api_key_here"
def scrape(url, render_js=False):
response = requests.post(
"https://api.denkbot.dog/scrape",
headers={
"Authorization": f"Bearer {API_KEY}",
"Content-Type": "application/json",
},
json={"url": url, "renderJs": render_js, "format": "json"},
)
response.raise_for_status()
return response.json()
data = scrape("https://example.com")
print(data["title"])
print(data["text"][:500])Questions & Answers
Does it work with httpx?+
Yes. Any HTTP library works — requests, httpx, aiohttp, urllib. It's just HTTP.
Can I use it in async Python?+
Yes. Use httpx or aiohttp with async/await.
Does it replace Scrapy?+
For simple use cases, yes. For complex crawling with custom middleware and pipelines, Scrapy might still be more appropriate.
Related topics
Web Scraping API for Developers
A simple, fast web scraping API. Send a URL, get back HTML, text, metadata, and links. No proxies, no headless browser setup, no headaches.
Web Scraping API for Node.js
Add web scraping to your Node.js app in minutes. No npm dependencies, no browser binaries. Just fetch().
Web Scraping via REST API
A clean REST API for web scraping. POST a URL, GET structured data. Works from any language, any platform, any runtime.
Collect Web Data for AI Training
Build AI training datasets from web content. Scrape thousands of pages and collect clean text at scale with denkbot.dog.
Ready to start fetching?
€19/year. Unlimited requests. API key ready in 30 seconds.