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Web scraping legality depends on various factors, including the website's terms of service and local regulations. Generally, scraping public data for commercial use is more acceptable than scraping private or copyrighted information.

Web scraping involves fetching and extracting data from websites. It typically includes sending HTTP requests, parsing HTML, and extracting relevant information using programming languages like Python or Javascript.

Due too the rise of React.js or any other javascript web framework and the increase of web efficency with displaying data dynamically, the web evolves rapidly into a dynamic environement. This introduces a completly new challenge, since most of the data isn't returned with the initial HTPP GET Request anymore and a javascript interpreter is required, to completly generate the whole HTML structure with all it's data.

We have developed custom lightweight javascript interpreters, to perform so called "client sided content completions". In addition we also use web emulation to humanize our web scraping and offer automated user interactions.

Many websites have rate-limiting mechanisms or terms of service that restrict the volume and speed of requests. With our global proxy network and flexibel scalability we can offer you a very high volume of data.

Challenges include handling dynamic content, avoiding IP blocking, adapting to website changes, and maintaining ethical practices.

"High-quality data" refers to data that is accurate, relevant, up-to-date, and reliable. In the context of web scraping or any data collection process, high-quality data is free from errors, inconsistencies, and inaccuracies. It meets certain standards and criteria, making it valuable and trustworthy for various applications, analyses, and decision-making processes.