for example when available cores are not used to their full capacity. On the contrary, parallel computing can lead to performance problems. Massive downloads can be a burden for the network, the target servers or one’s own computers. However, a number of issues arise when one gets to the details of the implementation. In order to retrieve multiples web pages at once it makes sense to retrieve as many domains as possible in parallel. As such, optimizing this phase is crucial for anyone wishing to gather data from a series of websites. This part is indeed highly relevant as transmitting data over the network is very often slower than further data processing performed locally. A previous blog post addresses practical ways to perform URL selection.Īnother way is to maximize throughput by working on download speed and bandwidth capacity. One way to reach this goal is to filter the links that are to be fetched in order to maximize their adequacy to the data collection project, for example by selecting links corresponding to a series of target domains, to a target language, a topic, etc. Problem description Efficient web data collectionĪ main objective of data collection over the Internet such as web crawling is to efficiently gather as many useful web pages as possible. Here is a simple way keep an eye on all these constraints as once. However, one should respect “politeness” rules. Optimizing downloads is crucial to gather data from a series of websites.
#Python download html file from url code
Date Fri 05 November 2021 Category Tutorial Tags code snippet