Python Flask (or just Flask) is a web development framework created in Python language. It was created by Armin Ronacher in 2010, based both on the robust foundation of Jinja2 templates engine and Werkzeug comprehensive WSGI web application library.
Developed nowadays as a part of the Pallets Projects, Flask is considered relatively new if compared to other Python frameworks. However, since it is a micro web framework (and therefore it does not require any particular tools or libraries) and was designed to be simple to use and to extend, it has a promising future. As an example of its application, Flask is part of popular platforms such as Pinterest or LinkedIn.
If you are looking forward to getting a job related to this framework, we have selected the most commonly asked Flask interview questions and the respective answers, at both basic and advanced levels. We also had included several Flask Code Challenges that will help you to be more prepared for your interview ahead. So when you had mastered our selection, you will be ready to excel in your Flask interview.
Basic Flask questions
Mention the features that distinguish the Flask framework from others
Being one of the newest frameworks of Python, Flask has some outstanding features, such as:
Comes with a built-in development server and a fast debugger
It contains the integrated support required for unit testing
The feature of restful request dispatching is included
It is built-in with Jinja2 templating technique
It supports secure cookies, in client-side sessions, for instance
It has the WSGI 1.0 compliant feature.
Flask is based on Unicode, to be more universally available.
It has vast and growing documentation.
What are the main advantages of using Flask Python?
Along with all the advantages of Python, Flask has some additional advantages:
Since it is lightweight and modular by design, it is easy to transform it into web applications when very few extensions are needed.
It is ORM-agnostic, so we can plug in Flask apps in ORMs like SqlAlchemy
Flask is designed to be coherent with the basic foundation of API.
There is a wealth of Flask documentation, well-structured and packed with examples of its implementation in numerous cases.
Flask comes with 100% WSGI 1.0 compliant, so it is very easy to deploy Flask apps in production
Flask handle HTTP request easily
Due to its simplicity, Flask is highly flexible and easily configurable
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One code challenge.
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What is the difference between Django and Flask?
Django is a Python full-featured web development framework, with a lot of built-in modules such as the Admin backend or an ORM with migration capability. It was been developed for quite some time, so could be considered a more mature framework.
On the other hand, Flask is more appropriate for quick development and prototyping. Due to its simple conception, is more suitable for quickly developing lightweight web applications with a small codebase, like microservices or serverless applications.
Even when Django is a more mature and complex framework, Flask is easier to learn and has fewer API’s when compared to Django. Using one or the other depends on the complexity of the problem ahead, so in theory, the best solution is to keep both in our web development toolkit.
What are the major differences between Pyramid and Flask?
As when compared to Django, Flask is considered a ready-to-use micro framework for a small application with simple requirements that uses external libraries.
On the other hand, Pyramid has been built for a larger application, providing flexibility. Pyramid allows the developer to use the right features for each project, choosing the database, templating style URL structure, and more. Pyramid is therefore heavy configurable and complex, while Flask provides a fast solution to easier projects.
Why is Flask called a Microframework? What are the benefits of using this kind of framework?
Flask has been called a micro framework since it only provides core, simple features to develop web applications. Flask only implements requests, routing, and blueprints. Other features like caching, forms, ORM, etc. require the use of Flask-Extensions.
However, working with a micro-framework like Flask gives to the developer some powerful advantages, such as:
The development server is built-in.
Flask works with lots of third-party extensions.
The micro framework has a tiny API that can be quickly learned by any web developer.
Flask is WSGI compliant and supports Unicode.
What are template engines in the Python Flask micro framework?
A template engine is a file that contains two types of data: static and dynamic. In Flask, the framework makes use of Jinja2 template engine to create HTML templates with placeholders for dynamic data to be populated during run time. Those placeholders are filled during run time by using Flask’s render_template method, providing the required parameters and values.
The use of these templates helps with the issue to keep the consistency of the website style. Therefore, the user does not need to write multiple times the same text when personalizing the style of the website. It is particularly useful on websites that contain lots of pages like web stores with lots of products.
Using templates allows us to set a basic layout that will remain consistent on all the pages of the website. If we need to change an element, it will replicate to all the components of the site, saving a lot of time and effort and reducing the possibility of human error, and providing a fast and reliable method for updating and maintaining the website.
What do you mean by Thread local object in Flask?
Thread-safety has been provided out of the box in Flask, so we are able to use objects such as current_app, g, and request without taking into account issues related to locking and concurrency. In Flask we do not need to pass objects from method to method, since these objects are readily available within a valid request context.
What is the g object in Flask? How does it differ from the session object?
The letter g, in this context, stands for global. The g object in Flask is used as a global namespace that will hold any data during the application context. This g object is not appropriate for storing the data between requests. When we need to keep global variables during an application context, rather than creating a global variable, it is best to use the g object as each request in Flask has a separate g object.
In this sense, Flask’s g object is an easy way to prevent accidental modifications of self-defined global variables.
What is the application context in Flask?
The application context in Flask is linked to the idea of a complete request/response cycle. It is used to keep a track of application-level data during a request or a CLI command. It makes use of g and current_app proxies to achieve the same.
If it is difficult to directly import the Flask app, like in the case of a Flask extension or a Blueprint or introducing applications may raise the problem of circular imports; Flask pushes the application context with each request. During a request, functions are given access to g and current_app in order to overcome the problem highlighted above.
How we can enable debugging in Flask Python?
There are two ways to enable debugging in Flask:
By setting the flag on the applications object
By passing the flag as a parameter to run.
If the user is enabling debug support, the server will reload when the code change. In that way, we don’t need to restart manually each time a change in the code is made.
Advanced Flask interview questions
How static files are served in Flask?
What kind of applications can be created with Flask?
We can create almost all types of web applications using Flask: microservices, RESTful API based Applications, SAS applications, serverless apps, single-page applications, small to medium size websites, or static websites.
Also, the versatility and flexibility of Flask allow us to integrate with other technologies such as NodeJS serverless, AWS lambda, and similar third-party services to build more complex systems.
What is NumPy and why it is better than a list?
NumPy is one of the Flask packages to deal with large data sizes, and also contains a powerful N dimensional array object along with a set of advanced functions. This NumPy array is much better than a list since it is more compact, convenient, efficient, and simpler to read and write than a list.
What is the maximum length of an identifier in Flask?
An identifier in Flask can be of any length, within certain rules. An identifier should begin with a character or an underscore or from A-Z or a-z, and it can contain anything from the following: A-Z or a-z or 0-9 or _. Keep in mind that Flask is case-sensitive, so it will treat upper case and lower case letters in a different way.
Also, there are certain words reserved in Python that cannot be used as identifiers. Some of them are:
and, as, assert, break, class, continue, def, del, else, elseif, except, exec, false, finally, for, from, global, if, import, in, is, lambda, none, nonlocal, not, or, pass, print, raise, return, true, try, while, with, yield.
What are pickling and unpickling?
To make portable and serialized representations of objects, we need to use the module known as pickle. Basically, it accepts a Python object and converts it into a string type. After that, it uses the dump () function to dump it into a file. That is pickling. On the contrary, retrieving objects from the stored string forms is called unpickling.
How is memory managed in Flask?
Flask is a collection of private heap spaces, which holds all objects and data structures together, managed by the interpreter. In the core API, users can access some of these tools using the memory manager. Also, there is an inbuilt garbage collector for recycling all unused memory to make available memory for the heap space.
Explain how can we structure a large Flask application
To structure a large flask application, some steps are required:
First, we connect the functions and move them to various files
Then we use blueprints to assign the views to various categories such as auth, backend, profile, etc.
Finally, we use the hidden Werkzeug URL map and register functions on a central URL map.
What are the requirements to create a database in Flask?
Flask supports all kinds of database-powered applications like RDBS, as long as we create a schema in the form of a schema.sql file. This schema requires to be connected to a sqlite3 command, that must be installed in order to create or start the database in Flask.
Is the SQLite database built-in Flask?
Yes, SQLite is in-built. To use it in Flask, no additional Flask-Extension is needed: we can import SQLite and write SQL queries for interacting with the database directly.
However, Flask developers generally make use of Flask-SQLAlchemy, an ORM to interact with the SQLite database. Using it, we don’t need to write complex SQL queries.
How can we connect to a database in Flask?
Flask works with most of the RDBMSs, like PostgreSQL, SQLite, and MySQL. However, the Flask-SQLAlchemy extension is the preferred way to interact with a database in Flask. It makes database interaction and management easier during development. For No-SQL data stores, several extensions are available for each type of database.
Flask Code Challenges
With these challenges, we have reached the end of this article on Flask Interview Questions. We hope that you feel now more confident and remember: make sure you study and practice as much as possible. Good luck with that interview ahead!
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