Top 5 Python Frameworks To Opt For
Building the backend for a web application or service?
It doesn’t matter if it’s simple or complex, there’s a Python framework that can address your needs. Choosing the right one can make tedious implementations like user management, data design, form submissions, and security, less of a headache.
If your project is simple you can opt for something implicit and minimal rather than explicit and complex. Whereas, if you’re working on a big project then you’d need all the firepower a framework can pack. Here are 5 Python backend frameworks that you might want to consider for the backend of your web application.
Undoubtedly one of the most known and deployed frameworks, Django has been the go-to choice for enterprises for building web applications for years. With its 3 stable releases, Django has come far in terms of deployment speed. It is now equipped with the new asynchronous ASGI standard for Python web applications.
One of the reasons that Django is so popular is that it comes with batteries-included, meaning all the components that you’d need to develop a generic web application. For instance – user management features like tracking, sessions, passwords, and admin permissions, etc. are common to most web applications. Django provides these features natively.
This Python framework sure is powerful but it comes at the cost of unnecessary complexity; even simpler applications need a lot of configuring to install and run. Django applications are heavy and come with many moving parts. Django is monolithic, meaning apps are chunky and tightly coupled, so everything gets deployed together.
CubicWeb is an object-oriented semantic web app framework. It uses reusable building blocks of code called “cubes”. Cubes are made up of a schema, logic, and views. These components can be utilized as in any other modular framework, each having its function. It lets you build apps by reusing your code and of others.
It’s a powerful Python framework featuring the fundamental building blocks of a modern web application. In CubicWeb, you set up and manage instances with a command-line tool and its built-in templates let you generate HTML output conveniently.
Since CubicWeb doesn’t support the native async functionality some workarounds are required. One of which is to use the cubicweb-worker cube to perform tasks asynchronously. Moreover, it also comes with a lot of dependencies which translates to a daunting list of manual tweaking on the local environment. You can use pip install instead to get them all in one go or you could also use a Docker container to set up shop.
The CubicWeb development has been slow and is not the most promising but it still powers some of the large-scale semantic web and linked open data applications.
Inspired by the simplicity of Rails, Professor Massimo di Pierro created a simple and easy to set up framework called Web2py. It’s a scalable, open-source full-stack framework for Python which comes with its web-based development environment and features like Role-Based Access Control (RBAC), Database Abstraction Layer (DAL), and support for internationalization.
The data abstraction system in Web2py is a bit different from Django’s ORM, which uses Python classes to define models, whereas Web2py uses constructor functions like define_table to instantiate models.
Just like CubicWeb, Web2py doesn’t explicitly use Python’s Async functionality, but it makes up for it with a scheduler for handling long-running tasks.
Looking at features like data layers and authentication, Weppy will remind you of Django. But when you look at the code it starts looking like Flask, with minimal instruction to get a basic single route setup ready.
Weppy is a lightweight framework and comes with convenience functions, which makes it great for building RESTful APIs. You just have to use @service on a route to get data that is automatically formatted in the format of your choices like JSON or XML. Though lightweight, it packs some big framework features sans the weight and complexity. Validation mechanisms, form handling, response caching, internationalization, and user validation among others are such features.
The not so complex ‘Just enough’ features come with some trade-offs. Weppy extensions try to make up for these trade-offs but unfortunately the list of official add-ons is not that long.
The upcoming Weppy 2.0 will support async and sockets as low-level first-class entities. Also, all the upcoming versions will require Python 3.7 and above to run.
In contrast to every framework mentioned in the list (except for Django) Zope is meant to be a full-blown, enterprise-grade application server stack. For templating, Zope uses a flexible Zope Page Templates (ZPT) system or a basic DTML markup system. While ZPT can be a powerful way to design templates but the syntax takes some getting used to.
While the complexity can be beneficial for enterprise-grade applications, when it comes to installation Zope can be a bit difficult. So much so that it also offers a specialized setup tool called zc.buildout for installation .
If there are no resource constraints and you can look past the unnecessarily complex setup then Zope might prove to be the best for a large undertaking.
One thing to note is that there is no direct support for Python’s async. However, Zope utilizes the zc.async package to distribute tasks across machines and synchronize them in a ZODB instance.
There are a host of choices to base your backend on. It boils down to how much functionality and freedom to tweak are you looking for? All of these frameworks offer something that makes it a unique offering. You just need to truly understand what your solution needs and your choice will be easy and best suited.
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