These frameworks act as a one-stop shop for all of a developer's requirements. A typical full-stack framework will often include form generators, form validation, and template layouts.
These are simple frameworks that don't include any extra features or functionalities, such as a database abstraction layer, form validation, or particular tools and libraries. Developers that use a microframework must manually add a lot of code and requirements.
Any asynchronous framework is a microframework that provides for the management of a high number of concurrent connections, and it has lately gained prominence. An asynchronous framework written in Python often makes use of the asyncio package.
Best Python Frameworks
Asynchronous framework is a type of framework. AIOHTTP is a Python framework that largely relies on capabilities from Python 3.5+, such as async and awaits. Because it makes use of Python's asyncio library, the Python framework is an asynchronous framework. AIOHTTP is a web framework that may be used both as a server and as a client. It has a request object and a router that routes requests to functions that have been built to handle them.
· Supports both client and server WebSockets while avoiding Callback Hell
· Middlewares support
· Pluggable routing
Microframework is a kind of framework. Bottle generates a single source file for each application it is used to develop. It is a top-notch Python web framework. The Python microframework was created with the goal of creating APIs. Bottle does not require any dependencies other than the Python Standard Library to create tiny web apps. Bottle has a number of advantages, one of which is that it allows engineers to work closer to the hardware. Bottle is a good match for learning how to organise web frameworks and prototyping, in addition to constructing simple personal-use apps.
· Allows simple access from cookies, data, file uploads, and other HTTP-related information
· Built-in HTTP server
· Plugin support for various databases
· Support for third-party template engines and WSGI/HTTP servers through adapters
· Provides URL-parameter support for request dispatching routes.
Microframework is a kind of framework. CherryPy is a popular open-source Python object-oriented framework with a minimalistic approach. The micro-framework is one of the oldest Python frameworks, having been released in June 2002.
Any CherryPy-powered web application is stand-alone Python software with its own integrated multi-threaded web server that works on any operating system that supports Python. A program like this can run anyplace that a regular Python app can.
Running CherryPy applications does not necessitate the use of an Apache server. For data access, templating, and so on, the micro-framework allows the developer(s) to employ any sort of technology.
· A variety of pre-installed utilities for authentication, caching, encoding, sessions, static content, and more.
· A powerful configuration system
· Runs on Android
· HTTP/1.1-compliant WSGI thread-pooled web server
· Support for coverage, profiling, and testing is built-in.
· Offers simplicity for operating several HTTP servers concurrently
Full-stack framework is the type of framework. CubicWeb is a free-to-use, semantic, open-source, Python-based web framework developed and maintained by Logilab. CubicWeb demands that the data model be established in order to construct a working application based on it.
CubicWeb uses cube instead of other popular Python frameworks that employ distinct views and models. With the aid of a database, a web server, and some configuration files, many cubes are then connected together to create an instance.
· RDF (Resource Description Framework) and OWL (Web Ontology Language) support
· Components those are reusable
· Workflows for security
· Data-related searches are made easier using RQL (Relational Query Language) embedding.
· Multi-database compatibility
Microframework is a kind of framework. Dash is an open-source framework for building analytical web applications based on Python. It's a great Python framework for data scientists who aren't used to working with the web.
Dash applications are Flask-based web servers that communicate with JSON packets via HTTP requests. ReactJS is used to render components in its frontend. Flask plugins may be used to increase Dash's functionality.
Dash apps are cross-platform and mobile-ready since they are rendered in a web browser and can be distributed to servers. The underlying Flask instance, as well as all of its adjustable settings, are available to Dash developers.
· Error handling (Dash Deployment Server)
· High degree of customization
· LDAP integration (Dash Deployment Server)
· Plugin support
· Simple interface for linking UI components, such as dropdowns, graphs, and sliders
· URL routing (Dash Deployment Server)