Towardsdatascience Scraper
Spider read towardsdatascience.com in 1.2 s without a browser and returned 258 lines of clean markdown, including sections like "My Fall-Detection Model Scored 94%, and It Was Lying to Me", "Last Month’s Machine Learning Lessons Learned" and "Introduction to Semi-Supervised Learning".
## Matplotlib vs Plotly: Which Python Chart Tool Should You Choose?Data Science ](https://towardsdatascience.com/category/data-science/)Faster dataframe engines are nice, but they don’t reduce the amount of syntax an analyst…## My Fall-Detection Model Scored 94%, and It Was Lying to MeMachine Learning ](https://towardsdatascience.com/category/artificial-intelligence/machine-learning/)How a single evaluation choice inflated my results by 25 points, and what rebuilding honestly…## I Built an AI Data Agent Which Can Query Data and Answer Business Questions. Here’s How.Agentic AI ](https://towardsdatascience.com/category/artificial-intelligence/agentic-ai/)A step-by-step guide to building a data agent and conversational interface that let business users…## Last Month’s Machine Learning Lessons LearnedProductivity ](https://towardsdatascience.com/category/productivity/)The downside of conference travel## I Built a Tool-Calling Agent in Python. Here’s How I Debugged ItA minimal loop with real API calls, validation, compact outputs, and trace evidence before adding…## Loop Engineering for Cross-References: When RAG Answers ‘see Section 7.2’ Instead of the Actual AnswerEnterprise Document Intelligence [Vol.1 #11] – When the first answer points elsewhere in the document,…## How a Frontier Model Gets Built, Read from the Kimi K3 ReportLarge Language Models ](https://towardsdatascience.com/category/artificial-intelligence/large-language-models/)An open, 2.8-trillion-parameter model shipped with 47 pages of its own recipe. Reading it tells…## Introduction to Semi-Supervised LearningA primer about Semi-Supervised Learning, the approaches taken with different algorithms and the limitations of…## Is This Slop? Detecting AI-Generated Content Without a ModelResearch-backed cues to detect LLM-generated text along with the mathematical intuition as to ‘why’## Editor’s PicksThe same call, in code.
The capture above came back as markdown. These examples add a key, so you get browser rendering, proxies, and concurrency on towardsdatascience.com.
import { SpiderBrowser } from "spider-browser";
const spider = new SpiderBrowser({
apiKey: process.env.SPIDER_API_KEY!,
});
await spider.connect();
const page = spider.page!;
await page.goto("https://towardsdatascience.com");
// No selectors, no schema. Spider reads the page and names the fields.
const data = await page.scrape();
console.log(data);
await spider.close();import { Spider } from "@spider-cloud/spider-client";
const spider = new Spider({ apiKey: process.env.SPIDER_API_KEY! });
const result = await spider.scrapeUrl("https://www.towardsdatascience.com", {
return_format: "markdown",
});
console.log(result);Ready for volume? Get an API key →
Fields you can pull.
Spider names these from the page. The capture above came back as markdown; the same
call with return_format: "json" returns them as keys.
What towardsdatascience.com costs to scrape.
The capture above cost $0.000414 to fetch. Pricing is $1 per GB of pre-transformation bandwidth plus $0.001 per CPU minute, so a page like this one lands at a fraction of a cent. Failed requests are billed at $0.
- Free balance on signup
- No card required to test
- Balance never expires
Run it keyless, no account
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Start scraping towardsdatascience.com.
You already have the call. A key raises the rate limit and turns on browser rendering, proxies, and concurrency. Balance never expires, and top-ups go through secure checkout.