# How to Scrape Any Website in KNIME (Free Workflow Template)

> Source: https://scrape.do/blog/knime-web-scraper/

Published: 2026-04-16 · Updated: 2026-04-16 · Authors: Bugrahan Saka · Categories: scraping-use-cases

Building scrapers that get past anti-bot walls, CAPTCHAs, and proxy bans usually means Python scripts, constant maintenance, and a lot of broken pipelines.

That's why we packaged Scrape.do into a transparent, fully open KNIME Workflow (.knwf). Import it, feed it URLs, watch the data flow. [Download the template here](/uploads/blog/knime_scrapedo_template.knwf) and follow along.

## Step 1: Import the Engine and Add Your Key

Download the `web_scraper.knwf` file and open KNIME Analytics Platform. Go to **File → Import KNIME Workflow...**, select the file, and the node-based scraping engine appears on your canvas.

Before you run anything, authorize the workflow. Double-click the first **Table Creator** node (the one labeled for your Token) and replace `ENTER_YOUR_TOKEN_HERE` with your Scrape.do API Token from the dashboard. Click **OK**. You only have to do this once.

## Step 2: Feed the Target URLs

Double-click the second **Table Creator** node. In the URL column, paste the list of target pages you want to scrape: product pages, real estate listings, directories, whatever you need. Click **OK**.

## Step 3: Fire the Engine

Click the green **Play** button in the top toolbar (or Shift + F7) to execute all nodes.

The workflow merges your token and URLs and sends them to the **GET Request** node, which routes each request through Scrape.do's rotating residential proxies. The **Row Filter** node automatically drops any failed requests, so only clean Status 200 responses pass through.

## Step 4: Extract the Data You Actually Need

Raw HTML is useful, but you usually want specific fields. The **Regex Split** node at the end of the chain handles that. Double-click it and write a regular expression in the Pattern field.

Say you're tracking Amazon product prices. To extract the page title and unit price, use:

`(?s).*?<title>(.*?)</title>.*?class="a-price-whole">([^<]+).*`

That tells KNIME to scan the HTML body, pull the text inside `<title>` tags into one column, and extract the number inside the `a-price-whole` class into another. Right-click the node and open **Split Result** to see the clean output.

## Ready to Scrape?

No expensive scraping software. No Python libraries. A transparent, open-source engine that works inside your existing KNIME analytics environment.

[Download the Free KNIME Web Scraper Template Here](/uploads/blog/knime_scrapedo_template.knwf)

Grab your token, fire up KNIME, and let the data flow.