Python Essentials For Aws Cloud Developers

A comprehensive guide to implementing Python applications in AWS while learning about key AWS services Purchase of the print or Kindle book includes a free PDF eBook Key Features Gain hands-on experience in AWS services to effectively implement Python programming Utilize Python with open source libraries to develop data pipelines, APIs, and database applications Leverage the power of AWS to create a cloud-based server and use monitoring and logging features Book Description AWS provides a vast variety of services for implementing Python applications, which can pose a challenge for those without an AWS background. This book addresses one of the more predominant problems of choosing the right service and stepping into the implementation of exciting Python apps using AWS. The book begins by showing you how to install Python and create an AWS account, before helping you explore AWS Lambda, EC2, Elastic Beanstalk, and S3 for Python programming. You'll then gain hands-on experience in using these services to build the Python application. As you advance, you'll discover how to debug Python apps using PyCharm, and then start deploying the Python applications on Elastic Beanstalk. You'll also learn how to monitor Python applications using the CloudWatch service, along with creating and publishing APIs on AWS to access the Python application. The concluding chapters will help you get to grips with storing unstructured and semi-structured data using NoSQL and DynamoDB, as well as advance your knowledge using the Glue serverless data integration service in AWS. By the end of this Python book, you'll be able to take your application development skills up a notch with AWS services and advance in your career. What you will learn Understand the fundamentals of AWS services for Python programming Find out how to configure AWS services to build Python applications Run and deploy Python applications using Lambda, EC2, and Elastic Beanstalk Provision EC2 servers on AWS and run Python applications Debug and monitor Python applications using PyCharm and CloudWatch Understand database operations on AWS by learning about DynamoDB and RDS Explore the API gateway service on AWS using Python to grasp API programming Who this book is for This book is for cloud developers, software developers, and IT specialists who want to develop Python applications on AWS as well as learn the concepts underlying AWS services for implementing the applications. Experience in Python programming is needed to be able to implement the applications on AWS.

A comprehensive guide to implementing Python applications in AWS while learning about key AWS services Purchase of the print or Kindle book includes a free PDF eBook Key Features Gain hands-on experience in AWS services to effectively implement Python programming Utilize Python with open source libraries to develop data pipelines, APIs, and database applications Leverage the power of AWS to create a cloud-based server and use monitoring and logging features Book Description AWS provides a vast variety of services for implementing Python applications, which can pose a challenge for those without an AWS background. This book addresses one of the more predominant problems of choosing the right service and stepping into the implementation of exciting Python apps using AWS. The book begins by showing you how to install Python and create an AWS account, before helping you explore AWS Lambda, EC2, Elastic Beanstalk, and S3 for Python programming. You'll then gain hands-on experience in using these services to build the Python application. As you advance, you'll discover how to debug Python apps using PyCharm, and then start deploying the Python applications on Elastic Beanstalk. You'll also learn how to monitor Python applications using the CloudWatch service, along with creating and publishing APIs on AWS to access the Python application. The concluding chapters will help you get to grips with storing unstructured and semi-structured data using NoSQL and DynamoDB, as well as advance your knowledge using the Glue serverless data integration service in AWS. By the end of this Python book, you'll be able to take your application development skills up a notch with AWS services and advance in your career. What you will learn Understand the fundamentals of AWS services for Python programming Find out how to configure AWS services to build Python applications Run and deploy Python applications using Lambda, EC2, and Elastic Beanstalk Provision EC2 servers on AWS and run Python applications Debug and monitor Python applications using PyCharm and CloudWatch Understand database operations on AWS by learning about DynamoDB and RDS Explore the API gateway service on AWS using Python to grasp API programming Who this book is for This book is for cloud developers, software developers, and IT specialists who want to develop Python applications on AWS as well as learn the concepts underlying AWS services for implementing the applications. Experience in Python programming is needed to be able to implement the applications on AWS.

Transform into a cloud-savvy professional by mastering cloud technologies through hands-on projects and expert guidance, paving the way for a thriving cloud computing career Key Features Learn all about cloud computing at your own pace with this easy-to-follow guide Develop a well-rounded skill set, encompassing fundamentals, data, machine learning, and security Work on real-world industrial projects and business use cases, and chart a path for your personal cloud career advancement Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe Self-Taught Cloud Computing Engineer is a comprehensive guide to mastering cloud computing concepts by building a broad and deep cloud knowledge base, developing hands-on cloud skills, and achieving professional cloud certifications. Even if you’re a beginner with a basic understanding of computer hardware and software, this book serves as the means to transition into a cloud computing career. Starting with the Amazon cloud, you’ll explore the fundamental AWS cloud services, then progress to advanced AWS cloud services in the domains of data, machine learning, and security. Next, you’ll build proficiency in Microsoft Azure Cloud and Google Cloud Platform (GCP) by examining the common attributes of the three clouds while distinguishing their unique features. You’ll further enhance your skills through practical experience on these platforms with real-life cloud project implementations. Finally, you’ll find expert guidance on cloud certifications and career development. By the end of this cloud computing book, you’ll have become a cloud-savvy professional well-versed in AWS, Azure, and GCP, ready to pursue cloud certifications to validate your skills.What you will learn Develop the core skills needed to work with cloud computing platforms such as AWS, Azure, and GCP Gain proficiency in compute, storage, and networking services across multi-cloud and hybrid-cloud environments Integrate cloud databases, big data, and machine learning services in multi-cloud environments Design and develop data pipelines, encompassing data ingestion, storage, processing, and visualization in the clouds Implement machine learning pipelines in a multi-cloud environment Secure cloud infrastructure ecosystems with advanced cloud security services Who this book is for Whether you're new to cloud computing or a seasoned professional looking to expand your expertise, this book is for anyone in the information technology domain who aspires to thrive in the realm of cloud computing. With this comprehensive roadmap, you’ll have the tools to build a successful cloud computing career.

Unleash DevOps excellence with Python and its ecosystem of tools for seamless orchestration on both local and cloud platforms, such as GCP, AWS, and Azure Key Features Integrate Python into DevOps for streamlined workflows, task automation, and improved collaboration Combine the principles of Python and DevOps into a unified approach for problem solving Learn about Python’s role in Infrastructure as Code (IaC), MLOps, networking, and other domains Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionPython stands out as a powerhouse in DevOps, boasting unparalleled libraries and support, which makes it the preferred programming language for problem solvers worldwide. This book will help you understand the true flexibility of Python, demonstrating how it can be integrated into incredibly useful DevOps workflows and workloads, through practical examples. You'll start by understanding the symbiotic relation between Python and DevOps philosophies and then explore the applications of Python for provisioning and manipulating VMs and other cloud resources to facilitate DevOps activities. With illustrated examples, you’ll become familiar with automating DevOps tasks and learn where and how Python can be used to enhance CI/CD pipelines. Further, the book highlights Python’s role in the Infrastructure as Code (IaC) process development, including its connections with tools like Ansible, SaltStack, and Terraform. The concluding chapters cover advanced concepts such as MLOps, DataOps, and Python’s integration with generative AI, offering a glimpse into the areas of monitoring, logging, Kubernetes, and more. By the end of this book, you’ll know how to leverage Python in your DevOps-based workloads to make your life easier and save time.What you will learn Implement DevOps practices and principles using Python Enhance your DevOps workloads with Python Create Python-based DevOps solutions to improve your workload efficiency Understand DevOps objectives and the mindset needed to achieve them Use Python to automate DevOps tasks and increase productivity Explore the concepts of DevSecOps, MLOps, DataOps, and more Use Python for containerized workloads in Docker and Kubernetes Who this book is for This book is for IT professionals venturing into DevOps, particularly programmers seeking to apply their existing programming knowledge to excel in this field. For DevOps professionals without a coding background, this book serves as a resource to enhance their understanding of development practices and communicate more effectively with developers. Solutions architects, programmers, and anyone regularly working with DevOps solutions and Python will also benefit from this hands-on guide.

Everything you need to get running with IaaS for Amazon Web Services Modern businesses rely on Infrastructure-as-a-Service (IaaS)—a setup in which someone else foots the bill to create application environments—and developers are expected to know how to write both platform-specific and IaaS-supported applications. If you're a developer who writes desktop and web applications but have little-to-no experience with cloud development, this book is an essential tool in getting started in the IaaS environment with Amazon Web Services. In Amazon Web Services For Developers For Dummies, you'll quickly and easily get up to speed on which language or platform will work best to meet a specific need, how to work with management consoles, ways you'll interact with services at the command line, how to create applications with the AWS API, and so much more. Assess development options to produce the kind of result that's actually needed Use the simplest approach to accomplish any given task Automate tasks using something as simple as the batch processing features offered by most platforms Create example applications using JavaScript, Python, and R Discover how to use the XML files that appear in the management console to fine tune your configuration Making sense of Amazon Web Services doesn't have to be as difficult as it seems—and this book shows you how.

Much has changed in technology over the past decade. Data is hot, the cloud is ubiquitous, and many organizations need some form of automation. Throughout these transformations, Python has become one of the most popular languages in the world. This practical resource shows you how to use Python for everyday Linux systems administration tasks with today’s most useful DevOps tools, including Docker, Kubernetes, and Terraform. Learning how to interact and automate with Linux is essential for millions of professionals. Python makes it much easier. With this book, you’ll learn how to develop software and solve problems using containers, as well as how to monitor, instrument, load-test, and operationalize your software. Looking for effective ways to "get stuff done" in Python? This is your guide. Python foundations, including a brief introduction to the language How to automate text, write command-line tools, and automate the filesystem Linux utilities, package management, build systems, monitoring and instrumentation, and automated testing Cloud computing, infrastructure as code, Kubernetes, and serverless Machine learning operations and data engineering from a DevOps perspective Building, deploying, and operationalizing a machine learning project

Gain comprehensive insights into programming practices, and code portability and reuse to build flexible and maintainable apps using object-oriented principles Key FeaturesExtend core OOP techniques to increase integration of classes created with PythonExplore various Python libraries for handling persistence and object serializationLearn alternative approaches for solving programming problems, with different attributes to address your problem domainBook Description Object-oriented programming (OOP) is a relatively complex discipline to master, and it can be difficult to see how general principles apply to each language's unique features. With the help of the latest edition of Mastering Objected-Oriented Python, you'll be shown how to effectively implement OOP in Python, and even explore Python 3.x. Complete with practical examples, the book guides you through the advanced concepts of OOP in Python, and demonstrates how you can apply them to solve complex problems in OOP. You will learn how to create high-quality Python programs by exploring design alternatives and determining which design offers the best performance. Next, you'll work through special methods for handling simple object conversions and also learn about hashing and comparison of objects. As you cover later chapters, you'll discover how essential it is to locate the best algorithms and optimal data structures for developing robust solutions to programming problems with minimal computer processing. Finally, the book will assist you in leveraging various Python features by implementing object-oriented designs in your programs. By the end of this book, you will have learned a number of alternate approaches with different attributes to confidently solve programming problems in Python. What you will learnExplore a variety of different design patterns for the __init__() methodLearn to use Flask to build a RESTful web serviceDiscover SOLID design patterns and principlesUse the features of Python 3's abstract baseCreate classes for your own applicationsDesign testable code using pytest and fixturesUnderstand how to design context managers that leverage the 'with' statementCreate a new type of collection using standard library and design techniquesDevelop new number types above and beyond the built-in classes of numbersWho this book is for This book is for developers who want to use Python to create efficient programs. A good understanding of Python programming is required to make the most out of this book. Knowledge of concepts related to object-oriented design patterns will also be useful.

Use the computational thinking philosophy to solve complex problems by designing appropriate algorithms to produce optimal results across various domains Key Features Develop logical reasoning and problem-solving skills that will help you tackle complex problems Explore core computer science concepts and important computational thinking elements using practical examples Find out how to identify the best-suited algorithmic solution for your problem Book DescriptionComputational thinking helps you to develop logical processing and algorithmic thinking while solving real-world problems across a wide range of domains. It's an essential skill that you should possess to keep ahead of the curve in this modern era of information technology. Developers can apply their knowledge of computational thinking to solve problems in multiple areas, including economics, mathematics, and artificial intelligence. This book begins by helping you get to grips with decomposition, pattern recognition, pattern generalization and abstraction, and algorithm design, along with teaching you how to apply these elements practically while designing solutions for challenging problems. You’ll then learn about various techniques involved in problem analysis, logical reasoning, algorithm design, clusters and classification, data analysis, and modeling, and understand how computational thinking elements can be used together with these aspects to design solutions. Toward the end, you will discover how to identify pitfalls in the solution design process and how to choose the right functionalities to create the best possible algorithmic solutions. By the end of this algorithm book, you will have gained the confidence to successfully apply computational thinking techniques to software development.What you will learn Find out how to use decomposition to solve problems through visual representation Employ pattern generalization and abstraction to design solutions Build analytical skills to assess algorithmic solutions Use computational thinking with Python for statistical analysis Understand the input and output needs for designing algorithmic solutions Use computational thinking to solve data processing problems Identify errors in logical processing to refine your solution design Apply computational thinking in domains, such as cryptography, and machine learning Who this book is for This book is for students, developers, and professionals looking to develop problem-solving skills and tactics involved in writing or debugging software programs and applications. Familiarity with Python programming is required.