Bokeh vs. NumPy vs. WTForms 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.

WTForms is a flexible forms validation and rendering library for Python web development. It can work with whatever web framework and template engine you choose. It supports data validation, CSRF protection, internationalization (I18N), and more. There are various community libraries that provide closer integration with popular frameworks. WTForms tries to provide as usable an API as possible. We’ve listed here some of the known libraries to work with WTForms, but if it’s not listed, it doesn’t mean it won’t work. Pretty much any ORM or object-DB should work, as long as data objects allow attribute access to their members. WTForms uses unicode strings throughout the source code and assumes that form input has already been coerced to unicode by your framework. WTForms fields render to unicode strings by default, and therefore as long as your templating engine can work with that, you should have no unicode issues.