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Source channel @githubtrending · Post #15520 · Feb 24

#python#ai#ai_scraping#automation#crawler#crawling#crawling_python#data#data_extraction#mcp#mcp_server#playwright#python#scraping#selectors#stealth#web_scraper#web_scraping#web_scraping_python#webscraping#xpath Scrapling is a fast Python web scraping tool that fetches pages, bypasses anti-bot blocks like Cloudflare, and adapts to site changes by auto-finding elements. Use simple CSS/XPath selectors, spiders for big crawls with pause/resume, proxy rotation, and CLI—no code needed sometimes. Install via pip; it's memory-light and beats others in speed. You save time fixing broken scrapers, scrape reliably at scale, cut costs with AI tools, and focus on using data for leads, prices, or research. https://github.com/D4Vinci/Scrapling

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@githubtrending · Post #14691 · 05/10/2025, 12:00 AM

#csharp#architecture#aspnetcore#clean_architecture#cqrs#ddd#dotnet#dotnetcore#event_driven_architecture#event_sourcing#kubernetes#masstransit#messaging#microservice#microservices#oauth2#opentelemetry#software_architecture#software_design#software_engineering#vertical_slice_architecture Migrating from a monolithic architecture to a cloud-native microservices architecture offers several benefits. It improves scalability, allowing different parts of the application to grow independently. This approach also enhances reliability by isolating faults, so if one service fails, others continue to work. Additionally, microservices enable faster deployment and updates, as each service can be developed and deployed separately. This flexibility allows teams to use the best technology for each service, making development more efficient and agile[2][3][5]. https://github.com/meysamhadeli/monolith-to-cloud-architecture