Practical writing on web scraping, Apify Actors, Python automation, and data science — the same techniques used in the portfolio and the scraper library.
The engineering habits that separate scrapers that last from scripts that break in a month — HTTP stack choice, anti-bot strategy, pagination, and output validation.
Your headers are perfect and you still get 403 — because the block happened during the TLS handshake. How fingerprinting works and how curl_cffi solves it.
The anatomy of a production Actor — input schema, dataset design, Dockerfile, and the marketplace lessons that separate listed Actors from used ones.
What property portals expose, why time-series beats snapshots, and how the defended targets (Zillow, Airbnb, Redfin) are collected in practice.
Numbered pages, cursors, infinite scroll — how each pattern really works, where records silently disappear, and the loop structures that don't lose data.
Five pandas stages between raw scrape and trustworthy dataset — dedup on real keys, logged type coercion, normalization, rule-based validation, delivery.
A step-by-step walkthrough of exploratory data analysis with Python and pandas.
How neural networks and data science are reshaping real-estate valuation and demand prediction.
Why predictive analytics is becoming the core tool of real-estate investment.
Scraping Airbnb listings with Python — tools, approach, and the legal boundaries.
Everything on this blog is available as a service — scrapers, Actors, pipelines, and analysis with a fixed quote.
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