Телеграм канал «ProxySeller»

Parsing Wikipedia Data with Python — Step-by-Step Guide In our latest video, we show how to scrape and structure Wikipedia data using Python, Requests, and BeautifulSoup — safely and at scale. You’ll learn how to: - extract text and metadata from Wikipedia pages; - configure proxies for stable, multi-IP scraping; - and integrate results into your data workflows. For engineers and analysts building AI pipelines, data enrichment, or research automation — this guide walks through practical setup, code, and proxy configuration examples. 🎥 Watch the full video on our YouTube channel: How to Parse Wikipedia Data with Python

No-Code Web Scraping in 2025 — 11 Tools That Simplify Data Access Not every team needs a custom scraper — sometimes, speed and scalability matter more than code. In our new guide, we review 11 no-code scraping platforms that help marketing, data, and R&D teams collect structured web data without writing a single line of code. Inside: - Which tools work best for e-commerce, analytics, or content tracking; - What to check before choosing — API access, scheduling, proxy support; - And how to stay compliant and stable under heavy scraping loads. Whether you’re building dashboards, monitoring prices, or feeding AI pipelines — this article helps you pick the right no-code scraper for your workflow. 👉 Read the full guide

In 2025, proxies moved beyond “bypass tools.” They’ve become a core layer of AI, automation, and DevOps ecosystems. In our latest video, we explain: — Why mobile and residential proxies now power data pipelines and AI workloads; — How adaptive proxies integrate with antidetect browsers to stay undetectable; — And why API-first, SaaS-level proxy systems redefine scalability and observability. Modern teams treat proxies as infrastructure — not accessories. From load balancing to AI routing, they’ve become essential for reliability and compliance. 🎥 Watch the full video on our YouTube channel

Python is a core language for automation, data pipelines, and QA — but even experienced teams face setup issues on Windows Our latest guide shows how to configure a stable Python environment for smooth execution across business workflows. Inside: - proper interpreter setup and PATH configuration; - secure script execution via CMD, IDLE, or VS Code; - troubleshooting common launch and network errors; - and how proxy settings impact performance and data access. For DevOps, analysts, and R&D teams — it’s a practical starting point to standardize Python across workstations. 👉 Read the full article: Running Python Scripts on Windows — Beginner’s Guide

Managing hundreds of proxies across campaigns or client accounts? Proxy Checker helps teams instantly validate proxy performance and reliability — before deployment In this video, we cover: - how to verify proxy uptime, latency, and GEO accuracy; - protocol and anonymity checks (HTTP / SOCKS4 / SOCKS5); - how to export results in TXT or CSV for workflow automation; - and why our tool can test up to 💯 proxies simultaneously — fast and free. For marketing, data, or SaaS teams — Proxy Checker ensures your infrastructure stays stable, efficient, and ready to scale 👉 Watch the full video on our YouTube channel

Financial data moves fast — markets, currencies, corporate reports. But manual collection can’t keep up. Our new guide explains how to automate financial data extraction using modern tools and Python libraries. You’ll learn: - where to safely collect stock, forex, and corporate data; - how proxies and header rotation help avoid blocks; - the best scraping methods for finance projects; - and key legal aspects you must know. ⚙️ Read the full article: Guide to Financial Data Web Scraping — and see how automation turns data chaos into clear insights.