Best Python Frameworks for Web Development in 2020

What are the frameworks for? They make developers' lives easier by offering ready-made structures for application development. What's more, frameworks automate processes that a while back required a code approach and were time-consuming.

With frameworks in general and Python frameworks in particular, developers' work has been simplified and accelerated. Professionals are not distracted by routine tasks and can focus on the main thing - the logic of the application, as well as how to increase its value for users.

The goal of this article is to give you an overview of the overall capabilities of Python and its frameworks so that you can understand how powerful these tools are.

Why Python frameworks rather than others

Python is considered one of the most prominent programming languages for its adaptivity and diversity. Even leading market players such as Spotify, Instagram, and YouTube also prefer this programming language.

And here are the main reasons for choosing Python:

• It’s open-source;
• Scalable and integrated;
• Object-oriented;
• It has extensive libraries;
• Simple syntax;
• Automated development and testing.

Having emerged in the late 1980s as an unremarkable language designed to automate routine development tasks, Python has gradually taken a leading position among all programming languages.

Today it is the undisputed leader in data analysis and infrastructure management. Python is also a driving force in processes such as web system management, machine intelligence, and data science.

What is the secret to the success of this programming language? It increases productivity:

• No compilation phase. As a result, the edit-test-debug process is accelerated;
• If an interpreter detects an error or a bug, an exception is requested instead of a more complex stage, namely a segmentation fault.

These and other Python features contribute to its simplicity and ease of use.

This programming language is growing rapidly, which is also facilitated by the development of machine intelligence and data science. There is no industry where that language wouldn't fit; Python is widely used to develop solutions for both banking and travel services. When it comes to the complexity of solutions that can be built with Python, it is both a simple website and an application based on machine learning algorithms. Want an API? API can be created as well.

Types of Python frameworks

These frameworks offer developers seamless structures for application development, automate the implementation of common solutions, and reduce product development time. Isn't the optimization of time, development process and budget with the guarantee to get a scalable multifunctional product the goal of the software development service itself?

All Python frameworks can be broken down into three categories:

1. Full stack frameworks.

2. Microframeworks.

3. Asynchronous frameworks.

Full stack frameworks

They are already pre-packaged and equipped with everything you need to create an application:

• ORM (object-relational mapping) technology;
• MVC (model-view-controller) architecture;
• routers;
• template engine.

Full stack frameworks are most commonly used for large projects, although they are suitable for developing applications of any level of complexity.

Below the full stack Python frameworks are listed:

• Django;
• Pyramid;
• Turbogears;
• Web2Py;
• CubicWeb.

Microframeworks

The name itself - microframeworks - already indicates that this type of framework is used to create small applications with minimal coding required. The functionality of such applications may be limited (no form validation or database abstraction level). But it is noteworthy that some microframeworks can be complemented by template engines or databases and scaled to the full stack level.

The Python microframeworks are the following:

• CherryPy;
• Bottle;
• Falcon;
• Dash;
• Flask;
• Hug;
• MorePath.

Asynchronous frameworks

Asynchronous encoding is not something new, and yet not all asynchronous frameworks support it. What is the point of asynchronous programming? Asynchronous programming is the process of coding when several tasks can be performed simultaneously without a specific sequence. Python asynchronous programming frameworks can handle huge sets of simultaneous connections, which is possible thanks to asyncio library.

The asynchronous frameworks are listed below:

• AIOHTTP;
• Sanic;
• Tornado.

Top 15 Python frameworks

Let's consider the most useful and frequently used Python frameworks from all three categories. This article is intended to give you an idea of which frameworks can be beneficial for your project.

1. Django

Django is a high-level full stack web development framework. It is designed to save stakeholders’ time and money. The main focus of Django is to minimize code and speed up the development process.

Django features:

• URL routing;
• Template engine;
• Database version control;
• Object-relational mapper (ORM);
• Great variety of ready-to-use libraries;
• Support for web servers, authentication, and internationalization.

Advantages of Django

Built-in packages to save time.

Basic functionality is pre-installed. No need to spend time checking if everything is working properly. Functionality can be imported into the project as soon as it is launched. Some of the packages include session management, authentication, including Google site map authentication.

Strong community and comprehensive documentation.

The Django community brings together professionals of all levels, from beginners to experts. Its members actively help each other and thus work to improve and enhance the framework. In addition to a community where all questions can be answered, Django provides developers with detailed documentation.

Scalability.

Django functionality allows you to scale even a small startup if needed. It can handle large amounts of data and a huge number of user requests even at the scalability stage.

Administration panel.

Data can be managed using basic CRUD operations. This function is one of the so-called "out of the box". It simplifies the work on any project: you don't need to write code for this functionality, you can start a project right away.

Disadvantages of Django

• This framework does not support WebSockets, so it is not a suitable solution for creating real-time apps.
• The framework comes with ready-to-use features, so it may seem monolithic rather than flexible, providing the only way to work with it. But it’s not.

How useful Django Framework can be is demonstrated by such large-scale projects created with its help as Spotify and Instagram.

2. Flask

This is a WSGI microframework that allows you to switch from a simple application to a complex platform. Developers are free to choose the libraries, tools, and extensions created by the Flask community.

Flask features:

• It’s unicode-based;
• Built-in quick debugger;
• HTTP request processing;
• Built-in development server;
• Jinja2 templating;
• RESTful request dispatching;
• ORM support;
• Support for secure cookies;
• Support for module testing;
• WSGI 1.0 compliance.

Advantages of Flask

It’s easy to use.

Flask is easy to learn even after updating or adding new components. It brings clarity to what is happening in the development process.

User-friendly.

Flask has all the necessary tools to prototype a web application.

All the necessary components are pre-installed.

Disadvantages of Flask

Only highly qualified Flask developers will be able to handle this framework, as it requires increased attention to detail and a greater understanding of their interconnections.

To get a clear picture of the scope of Flask and how useful it is, take a look at the name of the project created with its help - Netflix.

3. Pyramid

This full stack framework is suitable for working with projects of any complexity. It is particularly suitable for stakeholders who prefer minimalism. By using Pyramid, it is possible to scale a small project or start with a big one right away.

Pyramid features:

• URL generation;
• Predicates and renderers;
• Specification of asset location in the package.

Advantages of Pyramid

It’s easy to configure and flexible.

Any framework component can be replaced by any other one. Besides, two different components (two different databases or two different URL display methods) can be used within the same application or to implement the same functionality.

Easy use of Ajax requests.

Sending Ajax requests is easy with XHR views and decorators.

SQLAlchemy support.

This is good news for SQL-based projects. SQLAlchemy is a powerful database that makes it easy to create complex queries.

Disadvantages of Pyramid

• The Pyramid needs advanced tool preparation, which is time-consuming;
• Only highly experienced technicians can properly configure the Pyramid elements;
• SQLAlchemy is not necessary or even useless in case of simple projects.

4. Web2Py

Web2Py is a full stack framework, fully scalable through the web-based Integrated Development Environment (IDE). It has a built-in system for issuing tickets to users in case of an error in the system.

Web2Py features:

• Role-based access control;
• Backward compatibility;
• Built-in data protection;
• MVC architecture support;
• Support for internationalization;
• Multiple protocol readability.

Advantages of Web2Py

Flexible, powerful, and extensible.

Web2Py is great for large-scale projects as well as for simple ones and can be handled even by beginners. Despite the sufficient number of built-in features, Web2Py can be extended with external libraries.

Supported and easily adaptable to the needs of any team.

With Web2Py, there will be no situation when it’s necessary to understand and adapt the code written by the previous team. Even if the code is outdated, it will be compatible with updates and the latest version of the framework.

Supportive community.

The Web2Py framework has a lively community that provides its members with answers to the challenging work-related issues.

Disadvantages of Web2Py

• Inflexible plug-in system;
• Difficulties in managing the system for loading data models;
• No Python 3 support.

5. TurboGears

TurboGears is an open-source full stack Python framework for the fast creation of data-driven web applications. It is especially suitable if you need a database connection to develop an application. Such tools as SQLAlchemy, Genshi, Repoze, and WebOb serve this purpose.

TurboGears features:

• MochiKit JavaScript library integration;
• Horizontal data split;
• Function decorators;
• PasteScript templates;
• Support for several databases;
• MVC architecture support;
• ToscaWidgets;
• Validation support using FormEncode.

Advantages of TurboGears

Universality.

TurboGears is in fact a microframework, but with the ability to brilliantly transform into a full stack solution. It’s enough to start with a simple prototype and gradually scale it to a more complex project.

Scalability due to built-in functionality.

You can create your own plug-in modules or modify existing ones. All these processes are under your control.

Disadvantages of TurboGears

The need to expand the framework if necessary.

6. CubicWeb

It is a semantic web framework based on the application data model. There are no models and views, but there are configuration files, a database and cubes that can be combined through a web server.

CubicWeb features:

• Multiple databases support;
• RDF (Resource Description Framework) support;
• Subversion and Mercurial backend storage;
• Web Ontology Language (OWL);
• Semi-automatic generation of text, JSON, XML or XHTML using the selection + view mechanism;
• Reusable components.

Advantages of CubicWeb

Reusable components.

Like almost all Python frameworks, CubicWeb consists of reusable components (cubes). Using off-the-shelf elements leads to significant time-reducing.

RQL queries.

Relation Query Language (RQL) was created to provide a clear syntax for relationship queries, allowing developers to manage data repositories and view attributes and relationships.

Disadvantages of CubicWeb

A large number of functions that can potentially make it difficult to work with projects.

7. CherryPy

This is the best option for developing data access technologies or templates. It is easy to use, fast, and offers a wide range of ready-made solutions for working with projects of any complexity.

CherryPy features:

• Built-in plugins;
• Built-in coverage, testing and profiling support;
• Support for multiple, simultaneous HTTP servers;
• HTTP/1.1 compliant and thread-pooled WSGI Web Server;
• Configuration system.

Advantages of CherryPy

Production-ready server.

Available to use the production-ready WSGI server instead of "gunicorn" or both.

Dispatch templates.

CherryPy brings order to code and provides a lot of functionality with dispatching templates.

Disadvantages of CherryPy

The biggest disadvantage of the framework so far is the lack of comprehensive documentation, which can make it difficult for beginners to work.

8. Bottle

This framework is suitable for creating simple applications or APIs. It is also the best choice if you need to develop an application for personal use or a prototype. The whole development process takes place in one file called bottle.py. On the one hand, it is convenient for developers, but in the end, it can lead to a mess in the code.

Bottle features:

• Built-in HTTP server;
• URL-parameter, WSGI support;
• Support for external template engines;
• Plugins for different database support.

Advantages of Bottle

Flexibility.

This microframework is an optimal solution for working with small websites (templates, routing). It can be implemented through plug-ins.

Disadvantages of Bottle

Since the framework is small, it is suitable only for small applications and can only rely on the standard Python library.

The framework community is also narrow and lacks documentation and use cases.

9. Falcon

This microframework is widely used to create the REST API and provides clean code. It does not require many dependencies to create an HTTP API.

Falcon features:

• Cython support;
• Highly optimized and extensible codebase;
• Idiomatic responses to HTTP errors;
• RESTful resource classes;
• Prehandling exceptions;
• Intuitive routing;
• Testing modules using WSGI helpers and mocking.

Advantages of Falcon

It focuses on very narrowly defined tasks.

Falcon is configured to create a REST API, so it gives developers more options than more general-purpose frameworks.

It’s lightweight and requires minimal dependencies.

Falcon uses only the standard library and the mimeparse module, which makes it lightweight.

Disadvantages of Falcon

The inability to scale and the focus only on REST APIs narrows down the scope of this framework.

10. Dash

This microframework is used to create analytical and data science-driven web applications.

Dash features:

• Error processing, LDAP integration, URL routing (Dash Deployment Server);
• High level of customization;
• Plugin support;
• A simple interface to bind user interface controls, including drop-down lists, charts, and sliders.

Advantages of Dash

Scalability.

The framework allows you to create web applications with the ability to increase the number of users that the application can serve. This is possible due to the fact that a large number of work processes are involved in the processing of requests.

Dash components with React.js.

Dash has a plugin system to build your own components using React.

Multi-user access.

Applications built with Dash provide multi-user access: many users can have independent sessions simultaneously.

Disadvantages of Dash

• In addition to the default Dash components, you may need other, more complex components;
• You'll have to plug in the React components or write your own;
• The structure may be complex, as you will have to encode the function for each output separately.

11. Hug

Hug is a microframework used to develop the Python3 API, designed for minimal resource consumption, and aimed at simple and fast local development using the CLI HTTP.

Hug features:

• Annotation-based validation;
• Built-in version control;
• Auto-documentation support;
• It is based on the philosophy of "encode once, use everywhere".

Advantages of Hug

It simplifies API development.

The API developed with its use can be reused. A large number of interfaces are also available, which in turn simplifies the development process.

Automated generation of documentation.

The Hug framework has built-in functionality that provides automatic generation of API documentation. It is a time-saving solution as there is no need to write the documentation manually.

Disadvantages of Hug

Problems may arise in the pre-processing of requests, especially when it is necessary to obtain the specified parameters from the flow.

12. MorePath

This is a model-driven framework that requires minimal effort to install. Its main task is to ensure code scalability and reuse. It is involved in creating REST web services.

MorePath features:

• Standard views and UI;
• Hyperlink generation;
• Routing to models;
• RESTful architecture;
• Flexible extension and redefinition mechanism.

Advantages of MorePath

Comprehensive documentation.

This microframework provides a clear and comprehensive user guide, backed up by examples. The documentation also contains many articles and tutorials explaining how to solve a particular issue.

Application reuse.

Another framework that supports code reuse, thus saving developers' time and effort. Besides, applications can be extended, isolated, and overridden without additional effort.

Disadvantages of MorePath

This is a relatively new Python framework, and therefore there are not many professionals who know it well. Its knowledge base is also not yet comprehensive.

13. AIOHTTP

This is a Python 3.5+ asynchronous framework, which can also act as a client and server web framework.

AIOHTTP features:

• Forwarding requests to functions;
• WebSocket support;
• Plug-in routing;
• Middleware support.

14. Sanic

This is an open-source asynchronous framework that is used to handle asynchronous requests for fast HTTP responses. It is compatible with the standby and asynchronous functions of Python 3.5, which increases development speed and provides non-blocking capabilities.

Sanic features:

• Support for sub-routing within an application;
• Different types of logging, including errors and access;
• Dot-notation for modifying the configuration object;
• Handlers with easy-to-use decorator support;
• Class-based views;
• Plug-in support.

15. Tornado

Tornado is both an asynchronous framework and a network library. With a non-blocking network I/O, it is able to scale multiple connections. The Tornado framework is suitable for applications where long-term user connections are required.

Tornado features:

• Support for third-party authorization and authentication schemes;
• User authentication;
• Localization and translation support;
• Web template creation;
• Real-time services.

Bottom line

There are many Python frameworks. However, they are all different:

• Some of them are more flexible and provide more development opportunities than others;
• Some of the frameworks are only suitable for large projects and very heavy for simple sites, and vice versa;
• They all make it easy to create projects of any complexity.

And yet, if among your tasks is to get a ready-to-use product in the shortest possible time, you should focus on full stack Python frameworks. To be more precise, you should find the right subject-matter experts.

The Python developers of the DDI Development team have relevant experience, so we can offer you our proven expertise.

In addition to Python development frameworks, we also provide our customers with such Python-related services:

• Python-based product development;
• Enterprise application development;
• Python integration;
• Python support services;
• Python web development.

Sometimes all that your project needs to succeed is to use the right frameworks. In this article, we tried to explain the value of each of the Python frameworks to give you an idea of how beneficial they can be for your project.