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Mastering Flask Web Development
Mastering Flask Web Development

Mastering Flask Web Development: Build enterprise-grade, scalable Python web applications , Second Edition

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Profile Icon Gaspar Profile Icon Jack Stouffer
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€17.99 €26.99
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eBook Oct 2018 332 pages 2nd Edition
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€17.99 €26.99
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€32.99
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Arrow left icon
Profile Icon Gaspar Profile Icon Jack Stouffer
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€17.99 €26.99
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2 (2 Ratings)
eBook Oct 2018 332 pages 2nd Edition
eBook
€17.99 €26.99
Paperback
€32.99
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Free Trial
Renews at €18.99p/m
eBook
€17.99 €26.99
Paperback
€32.99
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Renews at €18.99p/m

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Mastering Flask Web Development

Creating Models with SQLAlchemy

As we saw in the last chapter, models are a means of abstracting and providing a common interface to access data. In most web applications, data is stored and retrieved from a relational database management system (RDBMS), which is a database that holds data in a tabular format with rows and columns and is able to implement a relational model with data across tables. Some examples include MySQL, Postgres, Oracle, and MSSQL.

In order to create models on top of our database, we will use a Python package named SQLAlchemy. SQLAlchemy is a database API at its lowest level, and performs object relational mapping at its highest level. An ORM (object relational mapper) is a tool that allows developers to store and retrieve data using object-oriented approaches and solve object-relational mismatches—a set of conceptual and technical difficulties that...

Setting up SQLAlchemy

In order to go through the exercises in this chapter, you will need a running database, if you do not already have one. If you have never installed a database, or you do not have a preference, then SQLite is the best option for beginners, or if you want to quickly bootstrap a proof of concept.

SQLite is an SQL-embedded database engine that is fast, works without a server, and is entirely contained in one file. SQLite is also natively supported in Python, so if you choose to go with SQLite, an SQLite database will be automatically created for you during the exercise in the Our first model section.

Python packages

Flask SQLAlchemy can be used with multiple database engines, such as ORACLE, MSSQL, MySQL...

Our first model

You may have noticed that we did not actually create any tables in our database to abstract from. This is because SQLAlchemy allows us to create either models from tables or tables from our models. We will look at this after we have created the first model.

In our main.py file, SQLAlchemy must first be initialized with our app as follows:

from flask import Flask
from flask_sqlalchemy import SQLAlchemy
from config import DevConfig

app = Flask(__name__)
app.config.from_object(DevConfig)
db = SQLAlchemy(app)

SQLAlchemy will read our app's configuration and automatically connect to our database. Let's create a User model to interact with a user table in the main.py file, as follows:

class User(db.Model): 
  id = db.Column(db.Integer(), primary_key=True) 
  username = db.Column(db.String(255)) 
  password = db.Column(db.String(255)) 
 
  def __init__(self, username...

CRUD

In every storage mechanism for data, there are four basic types of functions: create, read, update, and delete (CRUD). These allow us to perform all the basic ways of manipulating and viewing the data that is needed for our web apps. To use these functions, we will use an object in the database named a session. Sessions will be explained later in the chapter, but for now, think of them as a storage location for all of our changes to the database.

Creating models

To create a new row in your database using our models, add the model to the session and commit objects. Adding an object to the session marks its changes for saving. Committing is when the session is saved to the database, as follows:

    >>> user = User...

Relationships between models

Relationships between models in SQLAlchemy are links between two or more models that allow models to reference each other automatically. This allows naturally related data, such as comments on posts, to be easily retrieved from the database with its related data. This is where the R in RDBMS comes from, and it gives this type of database a large amount of power.

Let's create our first relation. Our blogging website is going to need some blog posts. Each blog post is going to be written by one user, so it makes sense to link posts back to the user who wrote them so that we can easily get all the posts by a user. This is an example of a one-to-many relationship, as shown in the following code:

SQLite and MySQL/MyISAM engines do not enforce relationship constraints. This might cause problems if you are using SQLite on your development environment...

Constraints and indexing

Using constraints is considered a good practice. This way, you can restrict the domain of a certain model attribute and ensure data integrity and quality. There are many types of constraints that you can use; primary key and foreign key constraints were already covered in the previous sections. The other kinds of constraints that are supported by SQLAlchemy are shown in the following list:

  • Not NULL (ensures that a certain attribute contains data)
  • UNIQUE (ensures that a certain attribute value is always unique in the database table, which contains the model data)
  • DEFAULT (sets a default value for the attribute when no values were provided)
  • CHECK (used to specify range of values)

Using SQLAlchemy, you can ensure that your data's domain restrictions are explicit and all in the same place, not spread across your application code.

Let's improve...

The convenience of SQLAlchemy sessions

Now you understand the power of SQLAlchemy and what the SQLAlchemy session object is, and why web apps should never be made without them. As stated before, the session can be simply described as an object that tracks the changes in our models and commits them to the database when we tell it to. However, there is a bit more to it than this.

First, the session is also the handler for transactions. Transactions are sets of changes that are flushed to the database on commit. Transactions provide a lot of hidden functionality. For example, transactions automatically determine which objects are to be saved first when objects have relations. You might have noted this when we were saving tags in the previous section. When we added tags to the posts, the session automatically knew to save the tags first despite the fact that we did not add them to...

Database migrations with Alembic

The functionality of web apps changes all the time, and with every new functionality, we need to change the structure of our database. Whether it's adding or dropping new columns or creating new tables, our models will change throughout the life cycle of our app. However, problems quickly arise when the database changes often. When moving our changes from development to production, how can you be sure that you carried over every change without manually comparing each model and its corresponding table? Let's say that you want to go back into your Git history to see whether an earlier version of your app had the same bug that you are now encountering in production. How will you change your database back to the correct schema without a lot of extra work?

As programmers, we hate extra work. Thankfully, there is a tool called Alembic, which...

Summary

Now that we have mastered data control, we may move on to displaying our data in our application. The next chapter, Chapter 3, Creating Views with Templates, will dynamically cover creating HTML based on our models and adding models from our web interface.

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Key benefits

  • Create production-ready MVC and REST API with the dynamic features of Flask
  • Utilize the various extensions like Flask-JWT and Flask-SQLAlchemy to develop powerful applications
  • Deploy your flask application on real-world platforms like AWS and Heroku on VM’s or Docker containers

Description

Flask is a popular Python framework known for its lightweight and modular design. Mastering Flask Web Development will take you on a complete tour of the Flask environment and teach you how to build a production-ready application. You'll begin by learning about the installation of Flask and basic concepts such as MVC and accessing a database using an ORM. You will learn how to structure your application so that it can scale to any size with the help of Flask Blueprints. You'll then learn how to use Jinja2 templates with a high level of expertise. You will also learn how to develop with SQL or NoSQL databases, and how to develop REST APIs and JWT authentication. Next, you'll move on to build role-based access security and authentication using LDAP, OAuth, OpenID, and database. Also learn how to create asynchronous tasks that can scale to any load using Celery and RabbitMQ or Redis. You will also be introduced to a wide range of Flask extensions to leverage technologies such as cache, localization, and debugging. You will learn how to build your own Flask extensions, how to write tests, and how to get test coverage reports. Finally, you will learn how to deploy your application on Heroku and AWS using various technologies, such as Docker, CloudFormation, and Elastic Beanstalk, and will also learn how to develop Jenkins pipelines to build, test, and deploy applications.

Who is this book for?

The ideal target audience for this book would be Python developers who want to use Flask and its advanced features to create Enterprise grade and lightweight applications. The book is for those who have some exposure of Flask and want to take it from introductory to master level.

What you will learn

  • Develop a Flask extension using best practices
  • Implement various authentication methods: LDAP, JWT, Database, OAuth, and OpenID
  • Learn how to develop role-based access security and become an expert on Jinja2 templates
  • Build tests for your applications and APIs
  • Install and configure a distributed task queue using Celery and RabbitMQ
  • Develop RESTful APIs and secure REST API s
  • Deploy highly available applications that scale on Heroku and AWS using Docker or VMs

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Oct 31, 2018
Length: 332 pages
Edition : 2nd
Language : English
ISBN-13 : 9781788999557
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Product Details

Publication date : Oct 31, 2018
Length: 332 pages
Edition : 2nd
Language : English
ISBN-13 : 9781788999557
Languages :
Tools :

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Table of Contents

14 Chapters
Getting Started Chevron down icon Chevron up icon
Creating Models with SQLAlchemy Chevron down icon Chevron up icon
Creating Views with Templates Chevron down icon Chevron up icon
Creating Controllers with Blueprints Chevron down icon Chevron up icon
Advanced Application Structure Chevron down icon Chevron up icon
Securing Your App Chevron down icon Chevron up icon
Using NoSQL with Flask Chevron down icon Chevron up icon
Building RESTful APIs Chevron down icon Chevron up icon
Creating Asynchronous Tasks with Celery Chevron down icon Chevron up icon
Useful Flask Extensions Chevron down icon Chevron up icon
Building Your Own Extension Chevron down icon Chevron up icon
Testing Flask Apps Chevron down icon Chevron up icon
Deploying Flask Apps Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

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Veil_Lord May 01, 2019
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So the book isn't awful, it's got a lot of good info. However, it's also got unforgivable issues. For example, when setting up virtualenv it guides you through the steps. The problem being, the steps are largely wrong if you're on a Windows machine. You have to activate env/scripts/activate it is NOT actually env/bin/activate as you're told. Windows is literally the most used OS in the world, so not putting a footnote or anything is just insane. I wasted good hour trying to get it to work then hunting down on Google because of it. Makes me wonder what other surprises the book will have as I go on. Wishing I'd picked up one of the O'Reilly books. Those have always been good for me.
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Courtney Schuett Mar 22, 2020
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There is a lot of good info in here, but the instructions and steps to follow have numerous gaps. Assumptions are made and steps are skipped entirely leading to extensive time spent troubleshooting instead of learning.
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