Scraping dynamic pages with Python, Playwright and AWS Lambda
The article discusses how to scrape dynamic web pages using Python, Playwright, and AWS Lambda. It focuses on a practical example involving the Dev IT Jobs portal, highlighting the challenges of extracting data from modern job boards. The author provides a detailed walkthrough of setting up a serverless scraper that efficiently handles dynamic content loading.
- ▪Scraping dynamic pages often requires handling JavaScript-rendered content that loads in chunks.
- ▪The article outlines a method using Playwright and AWS Lambda to extract job listings from a job board.
- ▪Key components of the setup include using headless Chromium, managing temporary files, and ensuring efficient data storage in S3.
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | DEV.to (Top) |
| Canonical URL | https://dev.to/lukzmu/scraping-dynamic-pages-with-python-playwright-and-aws-lambda-54f1 |
| Publication time | Sun, 17 May 2026 21:41:13 +0000 |
| Retrieval time | 2026-05-17T22:03:21.003Z |
| Last seen | 2026-05-17T22:03:21.003Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | rehxAu7JbP7P |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 2960141) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Łukasz Żmudziński Posted on May 17 • Originally published at zmudzinski.me Scraping dynamic pages with Python, Playwright and AWS Lambda #data #python #scraping #aws If you have ever pointed BeautifulSoup at a modern job board and then wondered why you got only a fraction of the visible listings, welcome to the club. Many of these pages behave like mini frontends: data appears in chunks, the DOM keeps changing, and scrolling is effectively part of the API contract.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV.to (Top).
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