The programming world has widely embraced Python as the language of choice for a variety of activities, including machine learning (ML), deep learning (DL), scripting, and application programming interface (API) development. Python’s capabilities in these areas have led to an increased demand for Python developers among businesses. Notable features and technologies that have furthered Python’s rise to prominence include Flask, FastAPI, and web-scraping. Although FastAPI is gaining traction in the market, the majority of ML and API developers prefer Flask for its extensive feature-set and greater years of development.
Can you explain what a web framework is?
Having a basic understanding of what a web development framework is would be helpful before delving into Flask and FastAPI.
Web applications are created using a web development framework, which is a collection of pre-constructed components such as modules, libraries, classes, and functions. This framework enables developers to focus on building their application without having to worry about the underlying protocols and thread management. Consequently, web development frameworks make the job of creating web applications significantly easier.
Django, created by the Django Software Foundation and written in the Python programming language, is an excellent example of a web development framework. In addition, the use of the AWS Lambda function, in conjunction with NodeJS, makes it possible to serve both small and large-scale applications in the cloud. This makes it an ideal solution for those who are looking for a reliable and cost-effective way to host their applications.
Flask is what?
Flask is a lightweight web application framework written in the Python programming language, designed to adhere to the Web Server Gateway Interface (WSGI) standard. It is a collection of rules that define how web servers and web applications communicate with each other. Flask enables developers to take advantage of the features of the Python language to create powerful, dynamic web applications.
Picture courtesy of DBMS Tutorial Point.
In addition to its other monikers, Flask is sometimes referred to as a “micro web framework” because of its lightweight design and emphasis on keeping a minimal, yet extensible, core. It provides the essential features required for development, including routing and request processing.
The Flask app is fantastic for newcomers since it is so simple to launch. The range of its potential uses is broad.
The Flask framework is a powerful and versatile tool used by developers to create websites, e-commerce businesses, and other similar projects. It is also frequently used to rapidly deploy machine learning models. Notable companies such as Netflix, Reddit, and Mozilla have all taken advantage of the capabilities offered by Flask.
- Includes a server and debugger for testing and development.
- Mild-mannered structure.
- Jinja2 templates are being used.
- Add-ons expand its capabilities and improve its usability.
- Built-in help for testing individual components.
- Good API.
Can you explain what FastAPI is?
Flask is a widely-recognised Python framework that has been employed for quite a while to construct RESTful services. It is an effective tool for the development of microservices, and its straightforwardness in terms of utilisation and deployment makes it a popular choice. Despite the advantages of Flask, its shortcomings inspired the emergence of the FastAPI framework.
FastAPI is an acclaimed, high-performance web framework for creating APIs in Python 3.6+. It has been demonstrated to be a rapid API, comparable to Node.js and GO in terms of performance. It has been adopted by major companies such as Uber and Netflix for the development of their applications.
To get started with FastAPI quickly and easily, it is recommended to install the core libraries and Uvicorn ASGI server using pip. Uvicorn is an ideal server for production environments.
The use of the asynchronous processing capability of FastAPI is a major benefit. When defining an endpoint, the async keyword should be placed before the function in order to take advantage of this feature. As an example, the following code snippet demonstrates the use of async def for an endpoint:
Characteristics of the FastAPI
- Often cited as the quickest Python framework available.
- The documentation is straightforward and easy to follow, and it provides excellent editing help.
- About 40 percent of all issues may be traced back to poor coding practices.
- It complies with public API and JSON schema requirements.
- Documentation of APIs that can be interacted with.
Now that we’ve discussed Flask and FastAPI in tandem, we can separate them and examine their similarities and differences.
Does anybody know whether the FastAPI framework is based on Flask?
FastAPI was developed using the Python microframework Flask and is a package for the Python programming language that facilitates the development of web applications using HTML/CSS or Python. To host a FastAPI application, an ASGI server such as Daphne or Uvicorn must be used instead of the development server that Flask provides. The rapid development time of FastAPI is largely due to its foundation on the asynchronously-supporting ASGI server.
The World Sailing Game Initiative and the Asian Sailing Game Initiative
Web Server Gateway Interface (WSGI) is a Python specification that was first introduced in 1999. Its purpose is to facilitate communication between web applications and servers, thus making it easier for developers to create web applications. Although familiarity with WSGI may be beneficial for experienced programmers, those who are new to programming may find it difficult to get started with Python. Those who have had prior experience with similar languages such as PHP or Ruby may find it easier to understand the concepts of Python.
The developers of FastAPI have introduced ASGI (Application Service Gateway Interface), which is a set of guidelines for constructing asynchronous, event-driven websites. One of the advantages of the included API framework is that it allows developers to utilise any existing framework to create an app.
The following are examples of how FastAPI and ASGI compliment one another:
- In addition, they enable you to access libraries and tools that simplify their usage.
- As a result, you may create asynchronous, event-driven programming with ease.
Validation of inputs and outputs, parameter passing
Flask does not provide any inbuilt features for validating the data that is sent. Any type of information is accepted by Flask. If a programmer attempts to execute an application that anticipates an integer value but instead it is supplied with a string, tuple or list, the application will not be able to handle it and will crash. Therefore, it is the responsibility of the developer to incorporate validation into their Flask application.
FastAPI provides developers with the ability to incorporate data validation into their projects. This feature allows developers to determine whether the arguments they are passing are valid, as well as provide any other relevant contextual information.
Mistakes will be flagged with an error message.
By default, Flask employs HTML pages to render error messages. However, when utilising FastAPI, an error message will be presented in a JSON-formatted manner.
Distantly related work
In comparison to other frameworks, Flask does not provide the capability to execute multiple processes in the background. Instead, it is deployed with the help of WSGI (Web Server Gateway Interface). On the other hand, FastAPI ASGI (Asynchronous Server Gateway Interface) permits the completion of tasks asynchronously.
Comparison between FastAPI and Flask
FastAPI is an efficient framework that provides unparalleled speed. It has been tested and found to be on par with other high-performance languages such as NodeJS and Go, which are favoured by experienced developers. Underneath the hood, FastAPI utilises Python’s asyncio library extensively, which is an essential part of Python’s capabilities when it comes to concurrent programming.
Asyncio is a powerful library that can be used for a wide range of operations that require the introduction of a delay. Examples of such operations include accessing Application Programming Interfaces (APIs), searching databases, and reading file contents. It has been established that FastAPI is compatible with the ASGI (Asynchronous Server Gateway Interface) standard, while Flask is limited to the WSGI (Web Server Gateway Interface) environment.
Help with Documentation
As you are creating your API using FastAPI, you are provided with automated documentation generation. We have found this to be exceptionally helpful. Even without writing any code for the user interface, FastAPI produces a highly refined and user-friendly interface for testing the API.
Visiting the endpoint with either the /docs or /redoc paths will provide you with access to the automatically generated documentation as well as the Swagger UI, which allows you to experiment with the API methods. Additionally, this endpoint contains a comprehensive catalogue of all requests that your application has made to external services.
Due to the lack of built-in support, the Flask framework can be cumbersome when it comes to creating documentation. This can be a major disadvantage, as constructing documentation for Flask requires a significant amount of effort and time. Fortunately, even though the framework is not equipped with the necessary tools to effectively facilitate the documentation process, it is still supported.
Help from the neighbourhood
Flask is a widely-adopted web application framework with a large user base, whereas FastAPI is still relatively new and has a smaller user base. When you experience a challenge in your development process, having a robust and extensive community to turn to may be extremely beneficial. If you are using Flask, you are likely to find solutions easily, whereas if you are using FastAPI, you may not have the same level of support.
Disadvantages and benefits of using FastAPI vs Flask
It is essential to analyse the pros and cons of both FastAPI and Flask in order to determine which one is the most suitable for your needs. Comparing the speed of FastAPI and Flask is a critical step in this process, as it can help you to make an informed decision.
So, why exactly do you recommend FastAPI?
- FastAPI is designed with robustness, safety, and user-friendliness in mind, making it a great option for those who want to quickly and conveniently create APIs, even if they don’t have any prior programming experience.
- FastAPI offers a variety of features, such as HTTP requests, OAuth authentication, XML/JSON responses, SSL/TLS encryption, and many more. This comprehensive functionality is managed through a web-based interface, enabling users to modify their preferences to suit the API’s operation.
- The built-in tools can be used to monitor the utilisation of the API. This will provide users with notifications when they are close to reaching any dangerous limits, such as those imposed on response timestamps or the number of requests.
- It is a widely accepted practice to create APIs with Flask utilising the FastAPI framework. This web application framework expansion provides all the traditional features of Flask and also offers some additional benefits.
- Rather than devoting the time and energy to writing an entire application from the ground up or relying on numerous online boilerplate generators, one should give serious consideration to adopting FastAPI’s toolkit-based approach. This library takes ideas from other libraries, so if you have any prior experience with related libraries or frameworks, you should find it relatively easy to become familiar with FastAPI.
Is there anything negative about utilising FastAPI?
- The cost of using the FastAPI framework is a major disadvantage, as it is dependent on both the user’s geographic location and the volume of API calls made each month. Unfortunately, the expense can be quite substantial.
- Scaling up a project can be a daunting task. The use of technologies such as PHP and databases such as MySQL and PostgreSQL can add complexity when attempting to expand a project from a small-scale to a larger-scale. While Python’s FastAPI can make the process a bit easier, it may not be the most appropriate architecture for long-term growth.