Python vs. Slim Framework vs. Vyper vs. scikit-image Comparison Chart

Slim is an ideal tool to create APIs that consume, repurpose, or publish data. Slim is also a great tool for rapid prototyping. Heck, you can even build full-featured web applications with user interfaces. More importantly, Slim is super fast and has very little code. You don’t always need a kitchen-sink solution like Symfony or Laravel. These are great tools, for sure. But they are often overkill. Instead, Slim provides only a minimal set of tools that do what you need and nothing else. First, you need a web server like Nginx or Apache. A Slim app contains routes that respond to specific HTTP requests. Each route invokes a callback and returns an HTTP response. To get started, you first instantiate and configure the Slim application. Next, you define your application routes.

scikit-image is a collection of algorithms for image processing. It is available free of charge and free of restriction. We pride ourselves on high-quality, peer-reviewed code, written by an active community of volunteers. scikit-image provides a versatile set of image processing routines in Python. This library is developed by its community, and contributions are most welcome! scikit-image aims to be the reference library for scientific image analysis in Python. We accomplish this by being easy to use and install. We are careful in taking on new dependencies, and sometimes cull existing ones, or make them optional. All functions in our API have thorough docstrings clarifying expected inputs and outputs. Conceptually identical arguments have the same name and position in a function signature. Test coverage is close to 100% and code is reviewed by at least two core developers before being included in the library.