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This guide walks you through the basics of how to run Python on Windows, setting up your environment, and running scripts in Windows. It also explains common mistakes and how to fix them.

For systematic data collection from websites, a web scraping bot is used. This is a program that automatically extracts the necessary information from pages.

A no‑code website parser (no‑code web scraper) is useful whenever you need regular access to structured data: market analysis, price monitoring, change tracking on websites, and more.

Embedding maps into your Python application is straightforward with the Google Maps API in Python. This toolkit lets you work with geospatial data directly in code without leaving your development environment.

The material covers the function’s syntax, its parameters, difference between json.dump vs json.dumps, usage examples, supported data types, as well as best practices for efficient and reliable handling of JSON in Python.

To understand what is a backconnect proxy and why they are effective for network-heavy workloads, we’ll look at their architecture, how they differ from other types, where they’re used, and how to choose a provider – with an emphasis on practical details.

Let’s analyze what an anonymous proxy is, the reasons behind this error, and methods to bypass it while retaining essential access.

Understanding the hard data vs soft data difference is essential for accurate interpretation, the selection of appropriate analytical methods, and ultimately, for making well-founded decisions and achieving objectives more effectively.

This guide presents methods for connecting HTTP(S) and SOCKS protocols, details on authentication, agent configuration, as well as common errors and ways to fix them.

Caching issues, incorrect content localization, or unexpected authorization errors are often related not to the application code, but to how HTTP headers are generated and processed during data exchange.