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Home > Web Development > Server Side Web Development > Learning Flask Framework
Learning Flask Framework
Learning Flask Framework

Learning Flask Framework: Build dynamic, data-driven websites and modern web applications with Flask

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Learning Flask Framework

Chapter 2. Relational Databases with SQLAlchemy

Relational databases are the bedrock upon which almost every modern Web application is built. Learning to think about your application in terms of tables and relationships is one of the keys to a clean, well-designed project. As you will see in this chapter, the data model you choose early on will affect almost every facet of the code that follows. We will be using SQLAlchemy, a powerful object relational mapper that allows us to abstract away the complexities of multiple database engines, to work with the database directly from within Python.

In this chapter, we shall:

  • Present a brief overview of the benefits of using a relational database
  • Introduce SQLAlchemy, the Python SQL Toolkit and Object Relational Mapper
  • Configure our Flask application to use SQLAlchemy
  • Write a model class to represent blog entries
  • Learn how to save and retrieve blog entries from the database
  • Perform queries – sorting, filtering, and aggregation
  • Build a tagging...

Why use a relational database?

Our application's database is much more than a simple record of things that we need to save for future retrieval. If all we needed to do was save and retrieve data, we could easily use flat text files. The fact is, though, that we want to be able to perform interesting queries on our data. What's more, we want to do this efficiently and without reinventing the wheel. While non-relational databases (sometimes known as NoSQL databases) are very popular and have their place in the world of the web, relational databases long ago solved the common problems of filtering, sorting, aggregating, and joining tabular data. Relational databases allow us to define sets of data in a structured way that maintains the consistency of our data. Using relational databases also gives us, the developers, the freedom to focus on the parts of our app that matter.

In addition to efficiently performing ad hoc queries, a relational database server will also do the following...

Introducing SQLAlchemy

SQLAlchemy is an extremely powerful library for working with relational databases in Python. Instead of writing SQL queries by hand, we can use normal Python objects to represent database tables and execute queries. There are a number of benefits to this approach, as follows:

  • Your application can be developed entirely in Python.
  • Subtle differences between database engines are abstracted away. This allows you to do things just like a lightweight database, for instance, use SQLite for local development and testing, then switch to the databases designed for high loads (such as PostgreSQL) in production.
  • Database errors are less common because there are now two layers between your application and the database server: the Python interpreter itself (this will catch the obvious syntax errors), and SQLAlchemy, which has well-defined APIs and its own layer of error-checking.
  • Your database code may become more efficient, thanks to SQLAlchemy's unit-of-work model that helps...

Creating the Entry model

A model is the data representation of a table of data that we want to store in the database. These models have attributes called columns that represent the data items in the data. So, if we were creating a Person model, we might have columns for storing the first and last name, date of birth, home address, hair color, and so on. Since we are interested in creating a model to represent blog entries, we will have columns for things like the title and body content.

Note

Note that we don't say a People model or Entries model – models are singular even though they commonly represent many different objects.

With SQLAlchemy, creating a model is as easy as defining a class and specifying a number of attributes assigned to that class. Let's start with a very basic model for our blog entries. Create a new file named models.py in the blog project's app/ directory and enter the following code:

import datetime, re
from app import db

def slugify(s):
    return...

Retrieving blog entries

While creating, updating, and deleting are fairly straightforward operations, the real fun starts when we look at ways to retrieve our entries. We'll start with the basics, and then work our way up to more interesting queries.

We will use a special attribute on our model class to make queries: Entry.query. This attribute exposes a variety of APIs for working with the collection of entries in the database.

Let's simply retrieve a list of all the entries in the Entry table:

In []: entries = Entry.query.all()
In []: entries  # What are our entries?
Out[]: [<Entry u'First entry'>, <Entry u'Second entry'>, <Entry u'Third entry'>, <Entry u'Fourth entry'>]

As you can see, in this example the query returns a list of Entry instances that we created. When no explicit ordering is specified, the entries are returned to us in an arbitrary order chosen by the database. Let's specify that we want the entries...

Building a tagging system

Tags are a lightweight taxonomy system that is perfect for blogs. Tags allow you to apply multiple categories to a blog post and allow multiple posts to be related to one another outside their category. On my own blog I use tags to organize the posts, so that people interested in reading my posts about Flask need only look under the "Flask" tag and find all the relevant posts. As per the spec that we discussed in Chapter 1, Creating Your First Flask Application, each blog entry can have as few or as many tags as you want, so a post about Flask might be tagged with both Flask and Python. Similarly, each tag (for example, Python) can have multiple entries associated with it. In database parlance, this is called a many-to-many relationship.

In order to model this, we must first create a model to store tags. This model will store the names of tags we use, so after we've added a few tags the table might look something like the following one:

id

tag

1...

Why use a relational database?

Our application's database is much more than a simple record of things that we need to save for future retrieval. If all we needed to do was save and retrieve data, we could easily use flat text files. The fact is, though, that we want to be able to perform interesting queries on our data. What's more, we want to do this efficiently and without reinventing the wheel. While non-relational databases (sometimes known as NoSQL databases) are very popular and have their place in the world of the web, relational databases long ago solved the common problems of filtering, sorting, aggregating, and joining tabular data. Relational databases allow us to define sets of data in a structured way that maintains the consistency of our data. Using relational databases also gives us, the developers, the freedom to focus on the parts of our app that matter.

In addition to efficiently performing ad hoc queries, a relational database server will also do the following:

  • Ensure that...

Introducing SQLAlchemy

SQLAlchemy is an extremely powerful library for working with relational databases in Python. Instead of writing SQL queries by hand, we can use normal Python objects to represent database tables and execute queries. There are a number of benefits to this approach, as follows:

  • Your application can be developed entirely in Python.

  • Subtle differences between database engines are abstracted away. This allows you to do things just like a lightweight database, for instance, use SQLite for local development and testing, then switch to the databases designed for high loads (such as PostgreSQL) in production.

  • Database errors are less common because there are now two layers between your application and the database server: the Python interpreter itself (this will catch the obvious syntax errors), and SQLAlchemy, which has well-defined APIs and its own layer of error-checking.

  • Your database code may become more efficient, thanks to SQLAlchemy's unit-of-work model that helps reduce...

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Description

Flask is a small and powerful web development framework for Python. It does not presume or force a developer to use a particular tool or library. Flask supports extensions that can add application features as if they were implemented in Flask itself. Flask’s main task is to build web applications quickly and with less code. With its lightweight and efficient web development framework, Flask combines rapid development and clean, simple design. This book will take you through the basics of learning how to apply your knowledge of Python to the web. Starting with the creation of a “Hello world” Flask app, you will be introduced to the most common Flask APIs and Flask’s interactive debugger. You will learn how to store and retrieve blog posts from a relational database using an ORM and also to map URLs to views. Furthermore, you will walk through template blocks, inheritance, file uploads, and static assets. You will learn to authenticate users, build log in/log out functionality, and add an administrative dashboard for the blog. Moving on, you will discover how to make Ajax requests from the template and see how the Mock library can simplify testing complex interactions. Finally, you will learn to deploy Flask applications securely and in an automated, repeatable manner, and explore some of the most popular Flask resources on the web.

Who is this book for?

This book is for anyone who wants to develop their knowledge of Python into something that can be used on the web. Flask follows the Python design principles and can be easily understood by anyone who knows Python, and even by those who do not.

What you will learn

  • Create your web pages to add modularity and flexibility to your web app using templates
  • Store and retrieve relational data using SQLAlchemy
  • Develop schema migrations with Alembic
  • Produce an admin section using flaskadmin
  • Build RESTful APIs using FlaskRestless
  • Simulate requests and sessions using the Flask test client
  • Make Ajax requests from Jinja2 templates

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Publication date : Nov 26, 2015
Length: 250 pages
Edition : 1st
Language : English
ISBN-13 : 9781783983377
Category :
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Languages :
Python
Concepts :
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Flask

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Publication date : Nov 26, 2015
Length: 250 pages
Edition : 1st
Language : English
ISBN-13 : 9781783983377
Category :
Web Development
Languages :
Python
Concepts :
Server Side Web Development
Tools :
Flask

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Learning Flask Framework
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Table of Contents

11 Chapters
1. Creating Your First Flask Application Chevron down icon Chevron up icon
1. Creating Your First Flask Application
What is Flask?
Setting up a development environment
Installing Python packages
Creating your first Flask app
Introducing the blog project
Summary
2. Relational Databases with SQLAlchemy Chevron down icon Chevron up icon
2. Relational Databases with SQLAlchemy
Why use a relational database?
Introducing SQLAlchemy
Creating the Entry model
Retrieving blog entries
Building a tagging system
Making changes to the schema
Summary
3. Templates and Views Chevron down icon Chevron up icon
3. Templates and Views
Introducing Jinja2
Creating a base template for the blog
Creating a URL scheme
Adding pagination links
Enhancing the blog app
Summary
4. Forms and Validation Chevron down icon Chevron up icon
4. Forms and Validation
Getting started with WTForms
Using flash messages
Saving and modifying tags on posts
Serving static files
Summary
5. Authenticating Users Chevron down icon Chevron up icon
5. Authenticating Users
Creating a user model
Installing Flask-Login
Creating user objects
Login and logout views
Accessing the current user
Restricting access to views
Sessions
Summary
6. Building an Administrative Dashboard Chevron down icon Chevron up icon
6. Building an Administrative Dashboard
Installing Flask-Admin
Exposing models through the Admin
Managing static assets via the Admin
Securing the admin website
Reading more
Summary
7. AJAX and RESTful APIs Chevron down icon Chevron up icon
7. AJAX and RESTful APIs
Creating a comment model
Installing Flask-Restless
Creating comments using AJAX
Loading comments using AJAX
Reading more
Summary
8. Testing Flask Apps Chevron down icon Chevron up icon
8. Testing Flask Apps
Unit testing
Flask and unit testing
Test-friendly configuration
Mocking objects
Logging and error reporting
Read more
Summary
9. Excellent Extensions Chevron down icon Chevron up icon
9. Excellent Extensions
SeaSurf and CSRF protection of forms
Creating Atom feeds
Syntax highlighting using Pygments
Simple editing with Markdown
Caching with Flask-Cache and Redis
Creating secure, stable versions of your site by creating static content
Asynchronous tasks with Celery
Creating command line instructions with Flask-script
References
Summary
10. Deploying Your Application Chevron down icon Chevron up icon
10. Deploying Your Application
Running Flask with a WSGI server
Securing your site with SSL
Automating deployment using Ansible
Read more
Summary
Index Chevron down icon Chevron up icon
Index

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Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5
(2 Ratings)
5 star 50%
4 star 50%
3 star 0%
2 star 0%
1 star 0%
James Anderson Jun 01, 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5
A good book to learn from, but needs to updated to the latest Flask software.
Amazon Verified review Amazon
Zweibier Jul 09, 2016
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
I read few books on Flask, and this is one is quite good.The book walks through, step by step, building of a moderately complex Flask application, a blog engine.Many important aspects are discussed in detail, including model persistence with SQLAlchemy, login subsystem with Flask-login, building REST API with Flask-Restless and so on.By working through this book, I have learned how to design, structure, and build a real-world Flask application with all bells and whistles.Why not 5 stars then?Editing is quite subpar, there are many mistakes which should've be easily uncovered by a diligent editor, there is no errata (at least I didn't find it), no github repository with chapter by chapter source code; all I was able to find, was a source code of the completed application, on the publisher's Web site,
Amazon Verified review Amazon

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