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  2. Data scraping - Wikipedia

    en.wikipedia.org/wiki/Data_scraping

    Because of this, tool kits that scrape web content were created. A web scraper is an API or tool to extract data from a website. [6] Companies like Amazon AWS and Google provide web scraping tools, services, and public data available free of cost to end-users. Newer forms of web scraping involve listening to data feeds from web servers.

  3. Search engine scraping - Wikipedia

    en.wikipedia.org/wiki/Search_engine_scraping

    PHP is a commonly used language to write scraping scripts for websites or backend services, since it has powerful capabilities built-in (DOM parsers, libcURL); however, its memory usage is typically 10 times the factor of a similar C/C++ code. Ruby on Rails as well as Python are also frequently used to automated scraping jobs.

  4. Beautiful Soup (HTML parser) - Wikipedia

    en.wikipedia.org/wiki/Beautiful_Soup_(HTML_parser)

    Beautiful Soup is a Python package for parsing HTML and XML documents, including those with malformed markup. It creates a parse tree for documents that can be used to extract data from HTML, [3] which is useful for web scraping. [2] [4]

  5. Web scraping - Wikipedia

    en.wikipedia.org/wiki/Web_scraping

    Web scraping is the process of automatically mining data or collecting information from the World Wide Web. It is a field with active developments sharing a common goal with the semantic web vision, an ambitious initiative that still requires breakthroughs in text processing, semantic understanding, artificial intelligence and human-computer interactions.

  6. Data retrieval - Wikipedia

    en.wikipedia.org/wiki/Data_retrieval

    In order to retrieve the desired data the user presents a set of criteria by a query. Then the database management system selects the demanded data from the database. The retrieved data may be stored in a file, printed, or viewed on the screen. A query language, like for example Structured Query Language (SQL), is used to prepare the queries.

  7. Extract, transform, load - Wikipedia

    en.wikipedia.org/wiki/Extract,_transform,_load

    A common use case for ETL tools include converting CSV files to formats readable by relational databases. A typical translation of millions of records is facilitated by ETL tools that enable users to input csv-like data feeds/files and import them into a database with as little code as possible.

  8. Wikipedia:Database download - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:Database_download

    pages-articles-multistream.xml.bz2 – Current revisions only, no talk or user pages; this is probably what you want, and is over 19 GB compressed (expands to over 86 GB when decompressed). pages-meta-current.xml.bz2 – Current revisions only, all pages (including talk) abstract.xml.gz – page abstracts

  9. Web crawler - Wikipedia

    en.wikipedia.org/wiki/Web_crawler

    The latest generation of "visual scrapers" remove the majority of the programming skill needed to be able to program and start a crawl to scrape web data. The visual scraping/crawling method relies on the user "teaching" a piece of crawler technology, which then follows patterns in semi-structured data sources.