Becoming an Enterprise Django Developer. Discover best practices, tooling, and solutions for writing and organizing Django applications in production

Michael Dinder

Django is a powerful framework but choosing the right add-ons that match the scale and scope of your enterprise projects can be tricky. This book will help you explore the multifarious options available for enterprise Django development. Countless organizations are already using Django and more migrating to it, unleashing the power of Python with many different packages and dependencies, including AI technologies.This practical guide will help you understand practices, blueprints, and design decisions to put Django to work the way you want it to. You’ll learn various ways in which data can be rendered onto a page and discover the power of Django for large-scale production applications. Starting with the basics of getting an enterprise project up and running, you'll get to grips with maintaining the project throughout its lifecycle while learning what the Django application lifecycle is.By the end of this book, you'll have learned how to build and deploy a Django project to the web and implement various components into the site.

Beginning Data Science with Python and Jupyter. Use powerful industry-standard tools within Jupyter and the Python ecosystem to unlock new, actionable insights from your data

Alex Galea

Get to grips with the skills you need for entry-level data science in this hands-on Python and Jupyter course. You'll learn about some of the most commonly used libraries that are part of the Anaconda distribution, and then explore machine learning models with real datasets to give you the skills and exposure you need for the real world. We'll finish up by showing you how easy it can be to scrape and gather your own data from the open web, so that you can apply your new skills in an actionable context.

Bezpieczeństwo sieci w Pythonie. Rozwiązywanie problemów za pomocą skryptów i bibliotek. Wydanie II

José Manuel Ortega

Popularność Pythona wynika z jego wszechstronności, prostoty, a także ze zwięzłości i z łatwości pisania kodu. Rozbudowywana z każdą aktualizacją kolekcja narzędzi i bibliotek pozwala na używanie Pythona do coraz bardziej specjalistycznych zadań, takich jak zabezpieczanie sieci. O tym, że skuteczna ochrona sieci ma krytyczne znaczenie dla organizacji, świadczą powtarzające się przypadki cyberataków i utraty cennych danych. Warto więc wykorzystać możliwości Pythona do wykrywania zagrożeń i rozwiązywania różnych problemów związanych z siecią. Tę książkę docenią specjaliści do spraw bezpieczeństwa i inżynierowie sieci. Dzięki niej zapoznasz się z najnowszymi pakietami i bibliotekami Pythona i nauczysz się pisać skrypty, które pozwolą Ci zabezpieczyć sieć na wielu poziomach. Dowiesz się, w jaki sposób przesyłać dane i korzystać z sieci Tor. Nauczysz się też identyfikować podatności systemu na ataki, aby tym skuteczniej zapewnić mu bezpieczeństwo. W naturalny sposób przyswoisz wiedzę, która pozwoli Ci tworzyć w Pythonie bezpieczne aplikacje, zaczniesz również stosować techniki kryptograficzne i steganograficzne. Znajdziesz tu także wskazówki, jak rozwiązywać różne problemy sieciowe, pisać skrypty do wykrywania zagrożeń sieci i stron internetowych, zabezpieczać urządzenia końcowe, pozyskiwać metadane i pisać skrypty kryptograficzne. Najważniejsze zagadnienia: skrypty automatyzujące procedury bezpieczeństwa i testy penetracyjne narzędzia programistyczne służące do zabezpieczania sieci automatyczna analiza serwerów wykrywanie podatności na ataki i analiza bezpieczeństwa praca z siecią Tor stosowanie narzędzi do analizy śledczej Python w sieci: najlepsza ochrona!

Big Data Analysis with Python. Combine Spark and Python to unlock the powers of parallel computing and machine learning

Ivan Marin, Ankit Shukla, Sarang VK

Processing big data in real time is challenging due to scalability, information inconsistency, and fault tolerance. Big Data Analysis with Python teaches you how to use tools that can control this data avalanche for you. With this book, you'll learn practical techniques to aggregate data into useful dimensions for posterior analysis, extract statistical measurements, and transform datasets into features for other systems.The book begins with an introduction to data manipulation in Python using pandas. You'll then get familiar with statistical analysis and plotting techniques. With multiple hands-on activities in store, you'll be able to analyze data that is distributed on several computers by using Dask. As you progress, you'll study how to aggregate data for plots when the entire data cannot be accommodated in memory. You'll also explore Hadoop (HDFS and YARN), which will help you tackle larger datasets. The book also covers Spark and explains how it interacts with other tools.By the end of this book, you'll be able to bootstrap your own Python environment, process large files, and manipulate data to generate statistics, metrics, and graphs.

Bioinformatics with Python Cookbook. Learn how to use modern Python bioinformatics libraries and applications to do cutting-edge research in computational biology - Second Edition

Tiago Antao

Bioinformatics is an active research field that uses a range of simple-to-advanced computations to extract valuable information from biological data.This book covers next-generation sequencing, genomics, metagenomics, population genetics, phylogenetics, and proteomics. You'll learn modern programming techniques to analyze large amounts of biological data. With the help of real-world examples, you'll convert, analyze, and visualize datasets using various Python tools and libraries.This book will help you get a better understanding of working with a Galaxy server, which is the most widely used bioinformatics web-based pipeline system. This updated edition also includes advanced next-generation sequencing filtering techniques. You'll also explore topics such as SNP discovery using statistical approaches under high-performance computing frameworks such as Dask and Spark.By the end of this book, you'll be able to use and implement modern programming techniques and frameworks to deal with the ever-increasing deluge of bioinformatics data.

Bioinformatics with Python Cookbook. Use modern Python libraries and applications to solve real-world computational biology problems - Third Edition

Tiago Antao

Bioinformatics is an active research field that uses a range of simple-to-advanced computations to extract valuable information from biological data, and this book will show you how to manage these tasks using Python.This updated third edition of the Bioinformatics with Python Cookbook begins with a quick overview of the various tools and libraries in the Python ecosystem that will help you convert, analyze, and visualize biological datasets. Next, you'll cover key techniques for next-generation sequencing, single-cell analysis, genomics, metagenomics, population genetics, phylogenetics, and proteomics with the help of real-world examples. You'll learn how to work with important pipeline systems, such as Galaxy servers and Snakemake, and understand the various modules in Python for functional and asynchronous programming. This book will also help you explore topics such as SNP discovery using statistical approaches under high-performance computing frameworks, including Dask and Spark. In addition to this, you’ll explore the application of machine learning algorithms in bioinformatics.By the end of this bioinformatics Python book, you'll be equipped with the knowledge you need to implement the latest programming techniques and frameworks, empowering you to deal with bioinformatics data on every scale.

Blender 3D By Example. A project-based guide to learning the latest Blender 3D, EEVEE rendering engine, and Grease Pencil - Second Edition

Oscar Baechler, Xury Greer

Blender is a powerful 3D creation package that supports every aspect of the 3D pipeline. With this book, you'll learn about modeling, rigging, animation, rendering, and much more with the help of some interesting projects.This practical guide, based on the Blender 2.83 LTS version, starts by helping you brush up on your basic Blender skills and getting you acquainted with the software toolset. You’ll use basic modeling tools to understand the simplest 3D workflow by customizing a Viking themed scene. You'll get a chance to see the 3D modeling process from start to finish by building a time machine based on provided concept art. You will design your first 2D character while exploring the capabilities of the new Grease Pencil tools. The book then guides you in creating a sleek modern kitchen scene using EEVEE, Blender’s new state-of-the-art rendering engine. As you advance, you'll explore a variety of 3D design techniques, such as sculpting, retopologizing, unwrapping, baking, painting, rigging, and animating to bring a baby dragon to life.By the end of this book, you'll have learned how to work with Blender to create impressive computer graphics, art, design, and architecture, and you'll be able to use robust Blender tools for your design projects and video games.

Building Big Data Pipelines with Apache Beam. Use a single programming model for both batch and stream data processing

Jan Lukavský

Apache Beam is an open source unified programming model for implementing and executing data processing pipelines, including Extract, Transform, and Load (ETL), batch, and stream processing.This book will help you to confidently build data processing pipelines with Apache Beam. You’ll start with an overview of Apache Beam and understand how to use it to implement basic pipelines. You’ll also learn how to test and run the pipelines efficiently. As you progress, you’ll explore how to structure your code for reusability and also use various Domain Specific Languages (DSLs). Later chapters will show you how to use schemas and query your data using (streaming) SQL. Finally, you’ll understand advanced Apache Beam concepts, such as implementing your own I/O connectors.By the end of this book, you’ll have gained a deep understanding of the Apache Beam model and be able to apply it to solve problems.

Building Data Science Applications with FastAPI. Develop, manage, and deploy efficient machine learning applications with Python

FastAPI is a web framework for building APIs with Python 3.6 and its later versions based on standard Python-type hints. With this book, you’ll be able to create fast and reliable data science API backends using practical examples.This book starts with the basics of the FastAPI framework and associated modern Python programming language concepts. You'll be taken through all the aspects of the framework, including its powerful dependency injection system and how you can use it to communicate with databases, implement authentication and integrate machine learning models. Later, you’ll cover best practices relating to testing and deployment to run a high-quality and robust application. You’ll also be introduced to the extensive ecosystem of Python data science packages. As you progress, you’ll learn how to build data science applications in Python using FastAPI. The book also demonstrates how to develop fast and efficient machine learning prediction backends and test them to achieve the best performance. Finally, you’ll see how to implement a real-time face detection system using WebSockets and a web browser as a client.By the end of this FastAPI book, you’ll have not only learned how to implement Python in data science projects but also how to maintain and design them to meet high programming standards with the help of FastAPI.

Building Python Web APIs with FastAPI. A fast-paced guide to building high-performance, robust web APIs with very little boilerplate code

Abdulazeez Abdulazeez Adeshina

RESTful web services are commonly used to create APIs for web-based applications owing to their light weight and high scalability. This book will show you how FastAPI, a high-performance web framework for building RESTful APIs in Python, allows you to build robust web APIs that are simple and intuitive and makes it easy to build quickly with very little boilerplate code.This book will help you set up a FastAPI application in no time and show you how to use FastAPI to build a REST API that receives and responds to user requests. You’ll go on to learn how to handle routing and authentication while working with databases in a FastAPI application. The book walks you through the four key areas: building and using routes for create, read, update, and delete (CRUD) operations; connecting the application to SQL and NoSQL databases; securing the application built; and deploying your application locally or to a cloud environment.By the end of this book, you’ll have developed a solid understanding of the FastAPI framework and be able to build and deploy robust REST APIs.

Building Serverless Applications with Python. Develop fast, scalable, and cost-effective web applications that are always available

Jalem Raj Rohit

Serverless architectures allow you to build and run applications and services without having to manage the infrastructure. Many companies have adopted this architecture to save cost and improve scalability. This book will help you design serverless architectures for your applications with AWS and Python.The book is divided into three modules. The first module explains the fundamentals of serverless architecture and how AWS lambda functions work. In the next module, you will learn to build, release, and deploy your application to production. You will also learn to log and test your application. In the third module, we will take you through advanced topics such as building a serverless API for your application. You will also learn to troubleshoot and monitor your app and master AWS lambda programming concepts with API references. Moving on, you will also learn how to scale up serverless applications and handle distributed serverless systems in production.By the end of the book, you will be equipped with the knowledge required to build scalable and cost-efficient Python applications with a serverless framework.

Building Serverless Microservices in Python. A complete guide to building, testing, and deploying microservices using serverless computing on AWS

Richard Takashi Freeman

Over the last few years, there has been a massive shift from monolithic architecture to microservices, thanks to their small and independent deployments that allow increased flexibility and agile delivery. Traditionally, virtual machines and containers were the principal mediums for deploying microservices, but they involved a lot of operational effort, configuration, and maintenance. More recently, serverless computing has gained popularity due to its built-in autoscaling abilities, reduced operational costs, and increased productivity.Building Serverless Microservices in Python begins by introducing you to serverless microservice structures. You will then learn how to create your first serverless data API and test your microservice. Moving on, you'll delve into data management and work with serverless patterns. Finally, the book introduces you to the importance of securing microservices.By the end of the book, you will have gained the skills you need to combine microservices with serverless computing, making their deployment much easier thanks to the cloud provider managing the servers and capacity planning.

Building Serverless Python Web Services with Zappa. Build and deploy serverless applications on AWS using Zappa

Abdulwahid Abdulhaque Barguzar

Serverless applications are becoming very popular these days, not just because they save developers the trouble of managing the servers, but also because they provide several other benefits such as cutting heavy costs and improving the overall performance of the application.This book will help you build serverless applications in a quick and efficient way. We begin with an introduction to AWS and the API gateway, the environment for serverless development, and Zappa. We then look at building, testing, and deploying apps in AWS with three different frameworks--Flask, Django, and Pyramid. Setting up a custom domain along with SSL certificates and configuring them with Zappa is also covered. A few advanced Zappa settings are also covered along with securing Zappa with AWS VPC.By the end of the book you will have mastered using three frameworks to build robust and cost-efficient serverless apps in Python.

Clean Code in Python. Develop maintainable and efficient code - Second Edition

Mariano Anaya

Experienced professionals in every field face several instances of disorganization, poor readability, and testability due to unstructured code.With updated code and revised content aligned to the new features of Python 3.9, this second edition of Clean Code in Python will provide you with all the tools you need to overcome these obstacles and manage your projects successfully.The book begins by describing the basic elements of writing clean code and how it plays a key role in Python programming. You will learn about writing efficient and readable code using the Python standard library and best practices for software design.The book discusses object-oriented programming in Python and shows you how to use objects with descriptors and generators. It will also show you the design principles of software testing and how to resolve problems by implementing software design patterns in your code. In the concluding chapter, we break down a monolithic application into a microservices-based one starting from the code as the basis for a solid platform.By the end of this clean code book, you will be proficient in applying industry-approved coding practices to design clean, sustainable, and readable real-world Python code.

Clean Code in Python. Refactor your legacy code base

Mariano Anaya

Python is currently used in many different areas such as software construction, systems administration, and data processing. In all of these areas, experienced professionals can find examples of inefficiency, problems, and other perils, as a result of bad code. After reading this book, readers will understand these problems, and more importantly, how to correct them. The book begins by describing the basic elements of writing clean code and how it plays an important role in Python programming. You will learn about writing efficient and readable code using the Python standard library and best practices for software design. You will learn to implement the SOLID principles in Python and use decorators to improve your code. The book delves more deeply into object oriented programming in Python and shows you how to use objects with descriptors and generators. It will also show you the design principles of software testing and how to resolve software problems by implementing design patterns in your code. In the final chapter we break down a monolithic application to a microservice one, starting from the code as the basis for a solid platform. By the end of the book, you will be proficient in applying industry approved coding practices to design clean, sustainable and readable Python code.

Cloud Native Python. Build and deploy resilent applications on the cloud using microservices, AWS, Azure and more

Manish Sethi

Businesses today are evolving so rapidly that having their own infrastructure to support their expansion is not feasible. As a result, they have been resorting to the elasticity of the cloud to provide a platform to build and deploy their highly scalable applications. This book will be the one stop for you to learn all about building cloud-native architectures in Python. It will begin by introducing you to cloud-native architecture and will help break it down for you. Then you’ll learn how to build microservices in Python using REST APIs in an event driven approach and you will build the web layer. Next, you’ll learn about Interacting data services and building Web views with React, after which we will take a detailed look at application security and performance. Then, you’ll also learn how to Dockerize your services. And finally, you’ll learn how to deploy the application on the AWS and Azure platforms. We will end the book by discussing some concepts and techniques around troubleshooting problems that might occur with your applications after you’ve deployed them. This book will teach you how to craft applications that are built as small standard units, using all the proven best practices and avoiding the usual traps. It's a practical book: we're going to build everything using Python 3 and its amazing tooling ecosystem. The book will take you on a journey, the destination of which, is the creation of a complete Python application based on microservices over the cloud platform