Bokeh vs. NumPy vs. Vyper vs. dbForge Query Builder for MySQL 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.

Vyper is a contract-oriented, pythonic programming language that targets the Ethereum Virtual Machine (EVM). Security: It should be possible and natural to build secure smart-contracts in Vyper. Language and compiler simplicity: The language and the compiler implementation should strive to be simple. Auditability: Vyper code should be maximally human-readable. Furthermore, it should be maximally difficult to write misleading code. Simplicity for the reader is more important than simplicity for the writer, and simplicity for readers with low prior experience with Vyper (and low prior experience with programming in general) is particularly important.