Author Profile
Mihai Maxim is a Full Stack Developer at WebScrapingAPI, contributing across the product and helping build reliable tools and features for the platform.
Published Articles
15 articles
TL;DR: Expedia relies on JavaScript rendering and anti-bot protections, so a plain requests call won't return hotel listings. This guide covers identifying CSS selectors with DevTools, building a working scraper via a scraping API, paginating across result pages, and exporting clean CSV data.
TL;DR: XPath and CSS selectors both locate DOM elements, but they solve different problems. CSS selectors are faster and more readable for straightforward selections. XPath wins when you need to traverse the DOM in any direction, match text content, or handle complex conditional logic. Most production projects benefit from using both strategically.
TL;DR: Web scraping with regex shines when you need short, predictable text patterns (prices, SKUs, emails, dates) out of HTML you already trust. Pair Python's re module with Beautiful Soup, scope your patterns to a parsed node instead of raw markup, and keep regex out of the way of full HTML tree parsing. This guide walks through a working title and price scraper, advanced regex features, and the pitfalls that bite real scrapers in production.
TL;DR: A web scraping project fails on planning long before it fails on code. These ten scraping questions walk you through legality, API alternatives, anti-bot defenses, cost, refresh cadence, data quality, and governance, so you scope the work, pick the right stack, and avoid the failure modes that quietly kill scrapers in production.
TL;DR: Discover how to use Web Stealth Proxy like a pro with our quick start guide. Get step-by-step instructions to boost your proxy game and take your online privacy to the next level. Start today!
TL;DR: Locate the failed hop before retrying a proxy request. Use status codes, CONNECT results, and safe diagnostic records to separate proxy failures from target responses.
TL;DR: First determine whether the table rows exist in the HTTP response, arrive through a data request, or require a browser to render. Then use the static Axios and Cheerio script or the focused Puppeteer path below to scrape HTML table in JavaScript, validate header-driven records, deduplicate pages, and write CSV safely. An HTML table organizes information into rows and columns, usually with <table>, <tr>, <th>, and <td> elements. To scrape HTML table in JavaScript means retrieving or rendering that markup, converting each data row into a JavaScript object, validating the result, and serializing it to a format such as CSV.
TL;DR: Jsoup is the default library for HTML parsing in Java. This guide walks the full lifecycle (Maven setup, loading a Document, CSS selectors, DOM traversal, extraction, modification, and serialization), plus a runnable scraping project, error handling, pagination, and the limits that push you toward a headless browser or scraping API.
TL;DR: To Python extract text from HTML, parse the markup with a real parser (BeautifulSoup, lxml.html, or html-text), strip scripts, styles, and site chrome, then normalize whitespace and Unicode before saving. This guide compares the main libraries, fixes the common cleanup traps, and ends with a runnable crawler that writes JSONL plus per-page .txt files.
TL;DR: This is an opinionated, end-to-end guide to web scraping with Scrapy in 2026. You will install Scrapy, prototype selectors in the shell, build a multi-page e-commerce spider, clean items with Item Loaders, persist to a database, harden settings against bans, and bolt on Scrapy-Playwright for JavaScript-rendered pages.
TL;DR: Using JavaScript with Scrapy does not always require a browser. First inspect the raw response, network requests, and embedded page state; add scrapy-playwright only when the target data truly depends on browser execution, then control waits, interactions, cleanup, and concurrency deliberately.
TL;DR: This XPath cheat sheet covers the syntax, predicates, axes, and functions you actually need for web scraping, plus a CSS-to-XPath translation table and runnable Puppeteer and Scrapy examples. Use it as a desk reference next time a CSS selector quietly breaks on a site you depend on.
TL;DR: The right choice depends on whether Scrapy's bottleneck is rendering, blocking, language fit, or operations. Keep or extend healthy spiders when possible; use browser tools for interactive pages, hosted platforms for operations, lightweight stacks for bounded static jobs, and managed APIs when request infrastructure is the constraint. Validate the shortlist with a cost model and a representative proof of concept.
TL;DR: Verify current service identity before following old Profit Scraper recommendations. Build a replacement workflow for listing data, sold-price research, and transparent cost assumptions.
TL;DR: Rust is a fast and memory-efficient language. But how does it handle web scraping? Check out this beginner-friendly guide and find out how you can use it to build a basic web scraper.
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