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Python is a dynamic programming language that's used in a wide range of domains thanks to its simple yet powerful nature. Although writing Python code is easy, making it readable, reusable, and easy to maintain is challenging. Complete with best practices, useful tools, and standards implemented by professional Python developers, the third edition of Expert Python Programming will help you overcome this challenge.The book will start by taking you through the new features in Python 3.7. You'll then learn the advanced components of Python syntax, in addition to understanding how to apply concepts of various programming paradigms, including object-oriented programming, functional programming, and event-driven programming. This book will also guide you through learning the naming best practices, writing your own distributable Python packages, and getting up to speed with automated ways to deploy your software on remote servers. You’ll discover how to create useful Python extensions with C, C++, Cython, and CFFI. Furthermore, studying about code management tools, writing clear documentation, and exploring test-driven development will help you write clean code.By the end of the book, you will have become an expert in writing efficient and maintainable Python code.
Big Data Analytics with R. Leverage R Programming to uncover hidden patterns in your Big Data
Big Data analytics is the process of examining large and complex data sets that often exceed the computational capabilities. R is a leading programming language of data science, consisting of powerful functions to tackle all problems related to Big Data processing.The book will begin with a brief introduction to the Big Data world and its current industry standards. With introduction to the R language and presenting its development, structure, applications in real world, and its shortcomings. Book will progress towards revision of major R functions for data management and transformations. Readers will be introduce to Cloud based Big Data solutions (e.g. Amazon EC2 instances and Amazon RDS, Microsoft Azure and its HDInsight clusters) and also provide guidance on R connectivity with relational and non-relational databases such as MongoDB and HBase etc. It will further expand to include Big Data tools such as Apache Hadoop ecosystem, HDFS and MapReduce frameworks. Also other R compatible tools such as Apache Spark, its machine learning library Spark MLlib, as well as H2O.
Virgilio Vasconcelos, Virgilio Carlo de Menezes Vasconcelos, Ton Roosendaal
Blender is an open source 3D graphics application that can be used for modeling, rigging, animating, rendering and thousands of other things. While modeling characters isn't the biggest of your worries, animating them to make them feel as-good-as alive is what differentiates a professional from an amateur. This book offers clear, illustrative, and easy-to-follow recipes to create character rigs and animations for common situations. Bring your characters to life by understanding the principles, techniques and approaches involved in creating rigs and animations, you'll be able to adapt them to your own characters and films. The book offers clear step-by-step tutorials, with detailed explanations, screenshots and support files to help you understand the principles behind each topic. Each recipe covers a logical step of the complete creation of a character rig and animation, so you're not overwhelmed with too much information at once.You'll see numerous examples and screenshots that guide to achieve various rigging and animation tasks, logically separated so you can understand each in detail. The rigging topics are divided by each region of the body (torso, limbs, face, eyes), and further separated by the specific topic (neck, fingers, mouth, eyelids, etc) for clarity. All rigging tasks are accomplished with the built-in tools in Blender, without the complexity of coding custom Python behaviors or user interface elements.The animation topics deal with common situations found in real world productions, showing good practices to understand and overcome the challenges.
In this new era of data platform system design, data lakes and data warehouses are giving way to the lakehouse – a new type of data platform system that aims to unify all data analytics into a single platform. Databricks, with its Databricks SQL product suite, is the hottest lakehouse platform out there, harnessing the power of Apache Spark™, Delta Lake, and other innovations to enable data warehousing capabilities on the lakehouse with data lake economics.This book is a comprehensive hands-on guide that helps you explore all the advanced features, use cases, and technology components of Databricks SQL. You’ll start with the lakehouse architecture fundamentals and understand how Databricks SQL fits into it. The book then shows you how to use the platform, from exploring data, executing queries, building reports, and using dashboards through to learning the administrative aspects of the lakehouse – data security, governance, and management of the computational power of the lakehouse. You’ll also delve into the core technology enablers of Databricks SQL – Delta Lake and Photon. Finally, you’ll get hands-on with advanced SQL commands for ingesting data and maintaining the lakehouse.By the end of this book, you’ll have mastered Databricks SQL and be able to deploy and deliver fast, scalable business intelligence on the lakehouse.
As an application’s code base increases, it becomes harder for developers to maintain existing features and introduce new ones. In this clean architecture book, you'll learn to identify when and how this problem emerges and how to structure your code to overcome it.The book starts by explaining clean architecture principles and Android architecture components and then explores the tools, frameworks, and libraries involved. You’ll learn how to structure your application in the data and domain layers, the technologies that go in each layer, and the role that each layer plays in keeping your application clean. You’ll understand how to arrange the code into these two layers and the components involved in assembling them. Finally, you'll cover the presentation layer and the patterns that can be applied to have a decoupled and testable code base.By the end of this architecture book, you'll be able to build an application following clean architecture principles and have the knowledge you need to maintain and test the application easily.