Python vs. Slim Framework vs. scikit-image vs. yarl 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.

All URL parts, scheme, user, password, host, port, path, query, and fragment are accessible by properties. All URL manipulations produce a new URL object. Strings passed to constructor and modification methods are automatically encoded giving canonical representation as result. Regular properties are percent-decoded, use raw_ versions for getting encoded strings. Human-readable representation of URL is available as .human_repr(). PyPI contains binary wheels for Linux, Windows and MacOS. If you want to install yarl on another operating system (like Alpine Linux, which is not manylinux-compliant because of the missing glibc and therefore, cannot be used with our wheels) the tarball will be used to compile the library from the source code. It requires a C compiler and Python headers installed. Please note that the pure-Python (uncompiled) version is much slower. However, PyPy always uses a pure-Python implementation, and, as such, it is unaffected by this variable.