JetBrains DataSpell vs. JupyterLab vs. Python vs. hug Comparison Chart

Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. JupyterLab is a web-based interactive development environment for Jupyter notebooks, code, and data. JupyterLab is flexible, configure and arrange the user interface to support a wide range of workflows in data science, scientific computing, and machine learning. JupyterLab is extensible and modular, write plugins that add new components and integrate with existing ones. The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include, data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more. Jupyter supports over 40 programming languages, including Python, R, Julia, and Scala.

Drastically simplify API development over multiple interfaces. With hug, design and develop your API once, then expose it however your clients need to consume it. Be it locally, over HTTP, or through the command line - hug is the fastest and most modern way to create APIs on Python3. hug has been built from the ground up with performance in mind. It is built to consume resources only when necessary and is then compiled with Cython to achieve amazing performance. As a result, hug consistently benchmarks as one of the fastest Python frameworks and without question takes the crown as the fastest high-level framework for Python 3. hug makes it easy to expose multiple versions of your API. With hug you can simply specify what version or range of versions an endpoint supports and then automatically have that enforced and communicated to your API's users.