Bokeh vs. PyQtGraph vs. jsoup vs. python-sql Comparison Chart

Bokeh makes it simple to create common plots, but also can handle custom or specialized use-cases. Plots, dashboards, and apps can be published in web pages or Jupyter notebooks. Python has an incredible ecosystem of powerful analytics tools: NumPy, Scipy, Pandas, Dask, Scikit-Learn, OpenCV, and more. With a wide array of widgets, plot tools, and UI events that can trigger real Python callbacks, the Bokeh server is the bridge that lets you connect these tools to rich, interactive visualizations in the browser. Microscopium is a project maintained by researchers at Monash University. It allows researchers to discover new gene or drug functions by exploring large image datasets with Bokeh’s interactive tools. Panel is a tool for polished data presentation that utilizes the Bokeh server. It is created and supported by Anaconda. Panel makes it simple to create custom interactive web apps and dashboards by connecting user-defined widgets to plots, images, tables, or text.

jsoup is a Java library that simplifies working with real-world HTML and XML. It offers an easy-to-use API for URL fetching, data parsing, extraction, and manipulation using DOM API methods, CSS, and XPath selectors. jsoup implements the WHATWG HTML5 specification and parses HTML to the same DOM as modern browsers. With jsoup, you can scrape and parse HTML from a URL, file, or string; find and extract data using DOM traversal or CSS selectors; manipulate HTML elements, attributes, and text; clean user-submitted content against a safelist to prevent XSS attacks; and output tidy HTML. jsoup is designed to deal with all varieties of HTML found in the wild, from pristine and validating to invalid tag-soup, creating a sensible parse tree. For example, you can fetch the Wikipedia homepage, parse it to a DOM, and select the headlines from the "In the news" section into a list of elements.