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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 .
Scrapy (/ ˈ s k r eɪ p aɪ / [2] SKRAY-peye) is a free and open-source web-crawling framework written in Python. Originally designed for web scraping, it can also be used to extract data using APIs or as a general-purpose web crawler. [3] It is currently maintained by Zyte (formerly Scrapinghub), a web-scraping development and services company.
Beautiful Soup may refer to: "Beautiful Soup", ... Beautiful Soup (HTML parser), an HTML parser written in the Python programming language; See also
Pip's command-line interface allows the install of Python software packages by issuing a command: pip install some-package-name. Users can also remove the package by issuing a command: pip uninstall some-package-name. pip has a feature to manage full lists of packages and corresponding version numbers, possible through a "requirements" file. [14]
Gensim is implemented in Python and Cython for performance. Gensim is designed to handle large text collections using data streaming and incremental online algorithms, which differentiates it from most other machine learning software packages that target only in-memory processing.
The techniques above can be freely mixed and embedded in any HTML document.. Any legal Python code can be embedded and any Python module can be imported, which makes it especially suited for writing very robust applications (using exception handling and unit testing single modules individually).
Data journalism trainer and writer Paul Bradshaw describes the process of data-driven journalism in a similar manner: data must be found, which may require specialized skills like MySQL or Python, then interrogated, for which understanding of jargon and statistics is necessary, and finally visualized and mashed with the aid of open-source tools.
Word2vec is a group of related models that are used to produce word embeddings.These models are shallow, two-layer neural networks that are trained to reconstruct linguistic contexts of words.