Practical Python Backend Programming: Build Flask and FastAPI applications, asynchronous programming, containerization and deploy apps on cloud

By Tim Peters

"Practical Python Backend Programming" is a quick pragmatic book that teaches both new and experienced developers the fundamentals of backend development with Python. 

• Language: English
• Publisher: GitforGits
• Release date: Jan 31, 2024
• ISBN: 9788119177776

Book preview

Practical Python Backend Programming

Build Flask and FastAPI applications, asynchronous programming, containerization and deploy apps on cloud

Tim Peters

Preface

Practical Python Backend Programming is a quick pragmatic book that teaches both new and experienced developers the fundamentals of backend development with Python. All sorts of developers, from Python programmers to non-Python programmers, full stack developers, and web developers, will find what they need to know to become experts in backend programming in this entire book.

The book covers key topics in backend development, including how to set up stable development environments and how to use virtual environments for better dependency management. With this book, readers will have a firm grasp of Python programming with an emphasis on backend tasks by learning the language's syntax, data structures, and functions.

The book teaches you to create and launch dynamic web apps by providing an in-depth look at web frameworks such as Flask and FastAPI. It teaches SQLAlchemy for efficient data handling and advanced database integration, and it shows to improve applications with databases like PostgreSQL, MySQL, and MongoDB. Strategies for managing concurrent operations and improving performance are also covered in the book, along with asynchronous programming in Python.

Ensuring security is of utmost importance in backend development. This book delves into various authentication methods, secure communication protocols such as HTTPS, and techniques to secure REST APIs. For efficient management of asynchronous tasks and real-time data processing, it also introduces message brokers such as RabbitMQ and Kafka.

The book teaches its readers how to containerize apps and manage them on a large scale by integrating technologies like Docker and Kubernetes. It goes on to talk about how to use serverless architectures, how to use modern tools for continuous integration and deployment, and how to deploy apps to cloud platforms like AWS.

This book claims to teach its readers how to write efficient and readable Python code for robust backend systems and how to build, deploy, and maintain such systems.

In this book you will learn how to:

Build dynamic web apps with strong backend logic using Flask and FastAPI.

Write efficient, well-structured backend code by learning Python's syntax, functions, and best practices.

Make your apps more efficient and scalable by using asynchronous programming techniques.

Investigate Kubernetes and Docker to orchestrate and containerize apps for improved deployment and scalability.

Use AWS's cloud services to deploy apps with guaranteed uptime and lightning-fast performance.

Improve efficiency and compatibility by setting up and managing Python development environments.

Enhance your data handling capabilities by learning to integrate and manipulate databases using SQLAlchemy.

Protect online apps with OAuth and JWT's sophisticated authorization and authentication features.

Efficiently process data in real-time and broker messages with RabbitMQ and Kafka.

Streamline processes, cut down on mistakes, and implement continuous integration and deployment by following best practices.

Prologue

Welcome to Practical Python Backend Programming. I'm Tim Peters, and in this book, I've simplified my years of software development experience to help you navigate the complex world of backend programming with Python. Whether you're a seasoned Python developer, a non-Python programmer venturing into Python's vast landscape, a full stack developer looking to improve your backend skills, or a new web developer starting out, this book is for you.

The challenges I faced as I transitioned from writing simple scripts to developing robust backend systems inspired me to write this book. I've learned over the years that the backend architecture is the foundation of any successful application. Data processing, security enforcement, and the business logic all take place here. As a result of Python's popularity as a top language for backend development, I saw a need for a resource that could walk developers through every step of the process.

This book begins with the fundamentals of creating a Python development environment optimized for backend development. You'll learn how to set up Python with the appropriate tools and libraries to improve your coding experience. From there, we'll delve deep into the heart of Python programming, where I'll help you master its syntax, data structures, and fundamental concepts, giving you a solid foundation to build on.

We then move on to more advanced topics like web development with popular frameworks like Flask and FastAPI. These chapters are intended to teach you not only how to build applications, but also about the structure and design patterns that result in scalable and maintainable code.

Since data is fundamental to backend programming, this book explores deeply into database management techniques. You'll work with relational databases like PostgreSQL and MySQL, as well as NoSQL options like MongoDB, to understand when and how to use them effectively. SQLAlchemy demonstrates how integrating an ORM can simplify database operations in your applications.

As applications grow, they need to handle more complex tasks like asynchronous operations and real-time data processing. Here, I'll show you how to do asynchronous programming in Python and real-time data handling with Kafka. You'll learn how to manage background tasks with Celery and build scalable applications that can handle large amounts of data without issue.

Security is critical, and this book provides a comprehensive look at how to secure your applications. From JWT and OAuth authentication to API endpoint security and SSL implementation, you'll learn how to effectively protect your application and data.

Finally, no modern backend book is complete without addressing deployment and scalability. You'll learn how to containerize your applications with Docker, manage them with Kubernetes, and deploy them to the cloud via AWS. I'll demonstrate how these technologies work to

gether to create a continuous pipeline from development to deployment.

Practical Python Backend Programming is more than just a programming guide; it is a path to becoming a skilled backend developer capable of designing and deploying powerful and efficient applications. Join me on this journey and let's create some incredible things with Python.

Copyright © 2024 by GitforGits

All rights reserved. This book is protected under copyright laws and no part of it may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without the prior written permission of the publisher. Any unauthorized reproduction, distribution, or transmission of this work may result in civil and criminal penalties and will be dealt with in the respective jurisdiction at anywhere in India, in accordance with the applicable copyright laws.

Published by: GitforGits

Publisher: Sonal Dhandre

www.gitforgits.com

[e-mail]

First Printing: January 2024

Cover Design by: Kitten Publishing

For permission to use material from this book, please contact GitforGits at [e-mail].

Content

Preface

GitforGits

Acknowledgement

Chapter 1: Fundamentals of Backend Development

Introduction

Overview of Backend Development

Essential Components of Backend Development

Server

Database

Application Programming Interfaces (API)

Web Framework

Middleware

Caching

Functioning of Backend Components

Role of Python in Backend Development

Versatility and Readability

Comprehensive Standard Library

Frameworks and Tools for Backend Development

Asynchronous Support

Integration Capabilities

Database Connectivity

Community and Resources

Use in AI and Machine Learning

Setting up Development Environment: Python, VS Code, and Linux

Installing Linux

Installing Python

Installing Visual Studio Code (VS Code)

Configuring VS Code for Python

Setting Up a Virtual Environment

Final Steps and Testing

Introduction to Virtual Environments

What is a Virtual Environment?

Why use Virtual Environments?

How to Setup and use Virtual Environments?

Installation

Creating Virtual Environment

Activating Virtual Environment

Installing Packages

Deactivating

Managing Dependencies

Best Practices

Basics of Command Line Interface (CLI)

Understanding the CLI

Basic CLI Commands

Tips for using CLI

Introduction to Version Control with Git

Introduction to Version Control and Git

Basic Git Operations for Backend Development

Installing Git

Configuring Git

Initializing Repository

Cloning Repository

Adding and Committing Files

Branching and Merging

Pushing Changes

Pulling Updates

Handling Merge Conflicts

Using the Git Log

Python Refresher: Syntax, Data Structures, and Functions

Python Syntax

Indentation

Variables

Comments

Data Structures

Lists

Tuples

Sets

Dictionaries

Functions

Defining a Function

Calling a Function

Parameters

Keyword Arguments

Arbitrary Arguments

Lambda Functions

Error Handling

Modules and Packages

Importing Modules

Importing with Aliases

From...Import Statement

Best Practices in Python Programming

Follow the Zen of Python

Adhere to PEP 8

Write Docstrings

Use Python’s Built-in Functions and Libraries

Utilize List Comprehensions and Generator Expressions

Error Handling with Exceptions

Use Context Managers for Resource Management

Keep Functions Small and Focused

Avoid Premature Optimization

Use Version Control

Test your Code

Summary

Chapter 2: Building Your First Web Application with Flask

Introduction

Flask Basics

What is Flask?

Core Features of Flask

Simplicity

Flexibility

Development Server and Debugger

Unicode Based

Documentation

Up and Running with Flask

Routing

Templates

Setting up Flask Environment

Organizing your Project

Setting up Flask

Install Flask

Create Flask Application

Create Simple View

Managing Dependencies with Pip

Configuring Flask App

Create Configuration File

Load Configuration

Running the Flask Application

Flask Command Line

Using a Script

Routing and Views

Defining Routes

Dynamic Routes

HTTP Methods

Constructing URLs

Error Handling

Combining Routes and Views Effectively

Templates and Static Files

Understanding Templates

Managing Static Files

Organizing Static Files

Serving Static Files

Form Handling and File Uploads

Handling Forms in Flask

Create HTML Form

Create Route to Display Form

Handling Form Data

File Uploads

Modifying HTML Form for File Uploads

Handling File Uploads in Flask

Database Integration Basics

Setting up SQLAlchemy with Flask

Install Flask-SQLAlchemy

Configure Application

Defining Models

Creating Database

Interacting with Database

Handling Relationships

Retrieving Related Data

Leveraging Query Options

Introduction to Flask Extensions

Understanding Flask Extensions

Flask-WTF

Flask-SQLAlchemy

Flask-Migrate

Flask-Login

Flask-Mail

Flask-RESTful

Using Flask Extensions

Install the Extension

Import and Initialize

Configure

Deploying Flask Application

Preparing Flask Application for Deployment

Switch to Production Database

Use Environment Variables for Configuration

Remove Debug Mode

Choosing Hosting Service

Setting up Web Server and WSGI Application Server

Using Heroku

Prepare Application

Set up Git Repository

Create Heroku App

Verify Deployment

Summary

Chapter 3: Advanced Flask Development

Introduction

Structuring Larger Applications with Flask Blueprints

What are Flask Blueprints?

Creating and Registering Blueprints

Define Blueprint

Register Blueprint

Structuring Views in Blueprints

Using Blueprints

Flask Application Factory Pattern

Understanding Flask Application Factory Pattern

Implementing Application Factory Pattern

Create Factory Function

Organize Configuration Settings

Register Blueprints and Extensions

Implementing RESTful Services with Flask-RESTful

Introduction to Flask-RESTful

Functioning of Flask-RESTful

Creation of REST API using Flask-RESTful

Testing the API

User Authentication and Authorization

Importance of Authentication, Authorization and Session Management

Authentication

Authorization

Session Management

Implementing Authentication in Flask

Configuring Flask-Login

User Loader Function

Defining User Model

Creating Authentication Routes

Implementing Authorization

Role-Based Access Control (RBAC)

Checking Permissions

Error Handling and Logging

Error Handling in Flask

Handling Application Errors

Handling Exceptions

Logging in Flask

Using Logging for Request Data

Custom Loggers

Performance Optimization Techniques

Database Optimization

Query Optimization

Batch Inserts and Updates

Request Handling Optimization

Efficient Data Serialization

Asynchronous Handlers

Caching Responses

Application and Web Server Configuration

Monitoring and Profiling

Integrating Flask Applications with Docker

Installing Docker

Create a Dockerfile

Create .dockerignore file

Build Docker Image

Run the Docker Container

Testing the Docker Container

Summary

Chapter 4: Introduction to FastAPI

Introduction

Transitioning to FastAPI

Key Differences Between FastAPI and Flask

Performance

Type Hints and Automatic Data Validation

Dependency Injection

Built-in Interactive API Documentation

Modern Python Features

Building RESTful APIs with FastAPI

Defining RESTful Endpoints

Path Parameters and Query Strings

Path Parameters

Query Parameters

Using Request Body

Response Handling

Custom Status Codes

Response Headers

Handling Errors

Dependency Injection

Understanding Dependency Injection in FastAPI

How Dependency Injection Works in FastAPI?

Defining Dependencies

Using Dependencies in Route Handlers

Handling Dependencies in Larger Applications

Advanced Database Integration with SQLAlchemy

Setting up SQLAlchemy with FastAPI

Install Necessary Packages

Configure Database URL

Create Database and Tables

Integrating SQLAlchemy with FastAPI

Database Session Dependency

Performing Database Operations

Asynchronous Handling

Setup Asynchronous Database Connection

Using Asynchronous Queries

Implementing Background Tasks

Basics of Background Tasks in FastAPI

How to Define Background Tasks?

Implementing More Complex Background Operations

Setting up Celery

Define Celery Tasks

Trigger Celery Tasks from FastAPI

FastAPI and Docker Integration

Installing Docker

Creating a Dockerfile for FastAPI

Building the Docker Image

Running FastAPI App in Docker Container

Verify Application

Summary

Chapter 5: Working with Databases

Introduction

MySQL and PostgreSQL

MySQL

PostgreSQL

Choosing Between MySQL and PostgreSQL

Application Requirements

Scalability

Support and Compatibility

MongoDB

Understanding MongoDB and Its Document Model

Documents

Collections

Why Choose MongoDB?

MongoDB's Key Features

Integrating MongoDB

Installation

Connecting to MongoDB

Operations

Database Design Principles

Core Principles of Database Design

Normalization

Entity-Relationship Model

Practical Database Schema Design

SQL Code for Creating Tables

CRUD Operations

Creating Records (CREATE)

Reading Records (READ)

Updating Records (UPDATE)

Deleting Records (DELETE)

Considerations for CRUD Operations

Advanced Querying Techniques

Subqueries

Joins

SQL Aggregate Functions

Advanced Filtering with HAVING

Window Functions

Database Migrations and Version Control

Understanding Database Migrations

Setting up Alembic

Initialize Alembic

Configure Alembic

Creating and Applying Migrations

Create Migration

Edit Migration Script

Apply Migrations

Managing Schema Changes

Versioning

Collaboration

Deployment

Integrating Databases with Python ORMs

Overview of Python ORMs

SQLAlchemy Overview

SQLAlchemy Core

SQLAlchemy ORM

Integrating SQLAlchemy ORM with Python

Installation

Defining Models

Creating Session

Performing Database Operations

Caching Strategies for Database Optimization

Types of Caching

Result Caching

Object Caching

Query Plan Caching

Implementing Caching in Web Applications

Considerations for Effective Caching

Summary

Chapter 6: Asynchronous Programming in Python

Introduction

Asynchronous Programming Overview

What is Asynchronous Programming?

Asynchronous Programming for Backend Development

Asynchronous Programming Use Cases

Web Servers

Data Processing

Real-time Applications

Microservices Architecture

How Asynchronous Programming Works?

Event Loop

Coroutines

Futures and Tasks

Sample Program: Asynchronous Execution

Asyncio Basics

‘async’ Syntax

‘await’ Syntax

Structure of Asyncio Program

Sample Program: Integrate Asyncio in University Application

Developing Asynchronous Web Applications

Sample Program: Asynchronous University Application

Setup and Installation

Defining Asynchronous Endpoints

Asynchronous Database Access

Understanding Asynchronous Database Access

Setup and Installation

Integrating Asynchronous Database Operations in FastAPI

Configuration

Asynchronous Database Functions

Using Asynchronous Functions in Routes

Implementing Websockets

Understanding WebSockets

Implementing WebSockets in FastAPI

Setup and Basic WebSocket Endpoint

Install FastAPI