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Learning Python
Learn to code like a professional with Python - an open source, versatile, and powerful programming languageKey FeaturesLearn the fundamentals of programming with Python - one of the best languages ever createdDevelop a strong set of programming skills that you will be able to express in any situation, on every platform, thanks to Python's portabilityCreate outstanding applications of all kind, from websites to scripting, and from GUIs to data scienceBook DescriptionLearning Python has a dynamic and varied nature. It reads easily and lays a good foundation for those who are interested in digging deeper. It has a practical and example-oriented approach through which both the introductory and the advanced topics are explained. Starting with the fundamentals of programming and Python, it ends by exploring very different topics, like GUIs, web apps and data science. The book takes you all the way to creating a fully fledged application.The book begins by exploring the essentials of programming, data structures and teaches you how to manipulate them. It then moves on to controlling the flow of a program and writing reusable and error proof code. You will then explore different programming paradigms that will allow you to find the best approach to any situation, and also learn how to perform performance optimization as well as effective debugging. Throughout, the book steers you through the various types of applications, and it concludes with a complete mini website built upon all the concepts that you learned.What you will learnGet Python up and running on Windows, Mac, and Linux in no timeGrasp the fundamental concepts of coding, along with the basics of data structures and control flow.Write elegant, reusable, and efficient code in any situationUnderstand when to use the functional or the object oriented programming approachCreate bulletproof, reliable software by writing tests to support your codeExplore examples of GUIs, scripting, data science and web applicationsLearn to be independent, capable of fetching any resource you need, as well as dig deeperWho this book is forPython is the most popular introductory teaching language in U.S. top computer science universities, so if you are new to software development, or maybe you have little experience, and would like to start off on the right foot, then this language and this book are what you need. Its amazing design and portability will help you become productive regardless of the environment you choose to work with.
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Advanced Python Programming
Write fast, robust, and highly reusable applications using Python's internal optimization, state-of-the-art performance-benchmarking tools, and cutting-edge librariesKey FeaturesBenchmark, profile, and accelerate Python programs using optimization toolsScale applications to multiple processors with concurrent programmingMake applications robust and reusable using effective design patternsBook DescriptionPython's powerful capabilities for implementing robust and efficient programs make it one of the most sought-after programming languages.In this book, you'll explore the tools that allow you to improve performance and take your Python programs to the next level.This book starts by examining the built-in as well as external libraries that streamline tasks in the development cycle, such as benchmarking, profiling, and optimizing. You'll then get to grips with using specialized tools such as dedicated libraries and compilers to increase your performance at number-crunching tasks, including training machine learning models.The book covers concurrency, a major solution to making programs more efficient and scalable, and various concurrent programming techniques such as multithreading, multiprocessing, and asynchronous programming.You'll also understand the common problems that cause undesirable behavior in concurrent programs.Finally, you'll work with a wide range of design patterns, including creational, structural, and behavioral patterns that enable you to tackle complex design and architecture challenges, making your programs more robust and maintainable.By the end of the book, you'll be exposed to a wide range of advanced functionalities in Python and be equipped with the practical knowledge needed to apply them to your use cases.What you will learnWrite efficient numerical code with NumPy, pandas, and XarrayUse Cython and Numba to achieve native performanceFind bottlenecks in your Python code using profilersOptimize your machine learning models with JAXImplement multithreaded, multiprocessing, and asynchronous programsSolve common problems in concurrent programming, such as deadlocksTackle architecture challenges with design patternsWho this book is forThis book is for intermediate to experienced Python programmers who are looking to scale up their applications in a systematic and robust manner. Programmers from a range of backgrounds will find this book useful, including software engineers, scientific programmers, and software architects.
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Introduction to Python for Science and Engineering
Introduction to Python for Science and Engineering offers a quick and incisive introduction to the Python programming language for use in any science or engineering discipline. The approach is pedagogical and “bottom up,” which means starting with examples and extracting more general principles from that experience. No prior programming experience is assumed.Readers will learn the basics of Python syntax, data structures, input and output, conditionals and loops, user-defined functions, plotting, animation, and visualization. They will also learn how to use Python for numerical analysis, including curve fitting, random numbers, linear algebra, solutions to nonlinear equations, numerical integration, solutions to differential equations, and fast Fourier transforms.Readers learn how to interact and program with Python using JupyterLab and Spyder, two simple and widely used integrated development environments.All the major Python libraries for science and engineering are covered, including NumPy, SciPy, Matplotlib, and Pandas. Other packages are also introduced, including Numba, which can render Python numerical calculations as fast as compiled computer languages such as C but without their complex overhead.
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Mastering Python Design Patterns
Exploit various design patterns to master the art of solving problems using PythonKey FeaturesMaster the application design using the core design patterns and latest features of Python 3.7Learn tricks to solve common design and architectural challengesChoose the right plan to improve your programs and increase their productivityBook DescriptionPython is an object-oriented scripting language that is used in a wide range of categories. In software engineering, a design pattern is an elected solution for solving software design problems. Although they have been around for a while, design patterns remain one of the top topics in software engineering, and are a ready source for software developers to solve the problems they face on a regular basis. This book takes you through a variety of design patterns and explains them with real-world examples. You will get to grips with low-level details and concepts that show you how to write Python code, without focusing on common solutions as enabled in Java and C++. You'll also fnd sections on corrections, best practices, system architecture, and its designing aspects. This book will help you learn the core concepts of design patterns and the way they can be used to resolve software design problems. You'll focus on most of the Gang of Four (GoF) design patterns, which are used to solve everyday problems, and take your skills to the next level with reactive and functional patterns that help you build resilient, scalable, and robust applications. By the end of the book, you'll be able to effciently address commonly faced problems and develop applications, and also be comfortable working on scalable and maintainable projects of any size.What you will learnExplore Factory Method and Abstract Factory for object creationClone objects using the Prototype patternMake incompatible interfaces compatible using the Adapter patternSecure an interface using the Proxy patternChoose an algorithm dynamically using the Strategy patternKeep the logic decoupled from the UI using the MVC patternLeverage the Observer pattern to understand reactive programmingExplore patterns for cloud-native, microservices, and serverless architecturesWho this book is forThis book is for intermediate Python developers. Prior knowledge of design patterns is not required to enjoy this book.
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Learning OpenCV 5 Computer Vision with Python
Master computer vision with OpenCV 5 and Python 3 by building practical applications for image processing, object detection, tracking, face recognition, machine learning, 3D vision, and cloud computing.Free with your book: DRM-free PDF version + access to Packt's next-gen Reader*Key FeaturesBuild powerful computer vision applications in concise code with OpenCV 5 and Python 3Learn the fundamental concepts of image processing, object classification, and 2D and 3D trackingTrain, use, and understand machine learning models, and deploy them in the CloudBook DescriptionComputer vision is a fast-moving field of artificial intelligence, powering applications that need to understand images, video, objects, faces, motion, depth, and 3D environments. Learning OpenCV 5 Computer Vision with Python gives you a practical path to building these systems with OpenCV 5 and Python 3.You will begin by setting up OpenCV, understanding what is new in OpenCV 5, and working with images, video, camera feeds, files, and graphical interfaces. From there, you will learn essential image-processing techniques, depth estimation and segmentation, face detection and recognition, and image retrieval using visual descriptors. As your skills develop, you will build custom object detectors, classify and track moving objects, and explore camera models, augmented reality, 3D reconstruction, and navigation. You will also work with machine learning and neural networks, applying them to practical vision tasks before learning how computer vision solutions can be deployed to the cloud and scaled beyond local experimentation.Throughout the book, hands-on Python examples help you connect core concepts with working implementations. By the end, you will have the practical skills to design, build, and extend real-world computer vision applications with OpenCV 5 across desktop and cloud-based workflows.*Email sign-up and proof of purchase requiredWhat you will learnInstall and familiarize yourself with OpenCV 5's Python 3 bindingsUnderstand image processing and video analysisUse a depth camera to distinguish foreground and background regionsDetect and identify objects, and track their motion in videosTrain and use your own models to match images and classify objectsDetect and recognize faces, and classify their ageBuild augmented reality applications, and navigate the real 3D worldTrain neural networks and deploy them as Cloud-based solutionsWho this book is forThis book is for Python programmers who want to learn computer vision and machine learning with OpenCV 5. It is also suitable for computer vision developers, AI/ML engineers, and practitioners who want to strengthen or refresh their OpenCV skills. No prior computer vision or machine learning experience is required, but readers should be comfortable with basic Python programming.
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Intuitive Python
Developers power their projects with Python because it emphasizes readability, ease of use, and access to a meticulously maintained set of packages and tools. The language itself continues to improve with every release: writing in Python is full of possibility. But to maintain a successful Python project, you need to know more than just the language. You need tooling and instincts to help you make the most out of what's available to you. Use this book as your guide to help you hone your skills and sculpt a Python project that can stand the test of time.No matter your experience level or background, Python's batteries-included standard library and rich third-party ecosystem provide a solid foundation to build your projects on. With the right intuition and background knowledge, you can take advantage of all the power Python offers. Take a guided tour of some of Python's high points to craft a project that you can sustain and build on for a long time.Run static analysis tools to detect and eliminate classes of bugs before you run code. Experiment with Python's concurrency model and develop patterns for using Python's thread and process abstractions to their full potential. Introduce yourself to Python's type hinting system: mypy. Download and run third-party Python packages and do so safely without compromising on security. Debug code using Python's built in debugger, and try procedures out in the interactive console. Run your code under new versions of the Python interpreter to unlock performance and usability improvements. All along the way, sharpen your Python instincts so you can keep your code clean and reduce the chance of bugs.Mine Python for all you can by playing to its strengths and embracing patterns that harness its potential.What You Need:The books assumes you have some experience programming in any language (not necessarily Python). To run the code presented in the book, you'll need a Python environment which you can download from https://www.python.org/downloads/.
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Mastering Python for Networking and Security
Master Python scripting to build a network and perform security operationsKey FeaturesLearn to handle cyber attacks with modern Python scriptingDiscover various Python libraries for building and securing your networkUnderstand Python packages and libraries to secure your network infrastructureBook DescriptionIt’s becoming more and more apparent that security is a critical aspect of IT infrastructure. A data breach is a major security incident, usually carried out by just hacking a simple network line. Increasing your network’s security helps step up your defenses against cyber attacks. Meanwhile, Python is being used for increasingly advanced tasks, with the latest update introducing many new packages. This book focuses on leveraging these updated packages to build a secure network with the help of Python scripting. This book covers topics from building a network to the different procedures you need to follow to secure it. You’ll first be introduced to different packages and libraries, before moving on to different ways to build a network with the help of Python scripting. Later, you will learn how to check a network’s vulnerability using Python security scripting, and understand how to check vulnerabilities in your network. As you progress through the chapters, you will also learn how to achieve endpoint protection by leveraging Python packages along with writing forensic scripts. By the end of this book, you will be able to get the most out of the Python language to build secure and robust networks that are resilient to attacks.What you will learnDevelop Python scripts for automating security and pentesting tasksDiscover the Python standard library's main modules used for performing security-related tasksAutomate analytical tasks and the extraction of information from serversExplore processes for detecting and exploiting vulnerabilities in serversUse network software for Python programmingPerform server scripting and port scanning with PythonIdentify vulnerabilities in web applications with PythonUse Python to extract metadata and forensicsWho this book is forThis book is ideal for network engineers, system administrators, or any security professional looking at tackling networking and security challenges. Programmers with some prior experience in Python will get the most out of this book. Some basic understanding of general programming structures and Python is required.
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Visual Studio Code for Python Programmers
Become proficient and efficient with Visual Studio Code and learn how to integrate all your external tools! Visual Studio Code for Python Programmers helps Python developers become not just familiar, but productive in Visual Studio Code. To start, you’ll find the steps for installing Visual Studio Code on Windows, Mac and Linux platforms, along with an introduction to the editing features of the workspace. Coverage of more advanced functionality includes managing source code, debugging, unit testing, and Jupyter Notebook support. The book finishes with a walk-through of real-world projects which utilize Visual Studio Code features introduced in the book. For developers, the choice of an editor is a very personal one. You have idiosyncratic needs and wants that are unique to you as a developer. This book will help you learn how to customize Visual Studio Code to meet your needs and Python development workflow. Introduces you to the features of the Visual Studio Code workspace and how those features can be customizedDemonstrates how Visual Studio Code allows you to choose your structure according to your needsCovers editing code in Python, including syntax highlighting, code completion, object definition, refactoring, and code navigationDescribes Git integration and how to perform common Git functions (commits, checkouts, branches, and merges) from within Visual Studio CodeHighlights debugging features for Python developers A final section on Real World Applications will step you through several examples (and features integration with Django, Flask, Jupyter Notebook, Docker, and Azure), so you can hit the ground running with Visual Studio Code.
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Python Essentials for AWS Cloud Developers
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.Key FeaturesGain hands-on experience in AWS services to effectively implement Python programmingUtilize Python with open source libraries to develop data pipelines, APIs, and database applicationsLeverage the power of AWS to create a cloud-based server and use monitoring and logging featuresWhat you will learnUnderstand the fundamentals of AWS services for Python programmingFind out how to configure AWS services to build Python applicationsRun and deploy Python applications using Lambda, EC2, and Elastic BeanstalkProvision EC2 servers on AWS and run Python applicationsDebug and monitor Python applications using PyCharm and CloudWatchUnderstand database operations on AWS by learning about DynamoDB and RDSExplore the API gateway service on AWS using Python to grasp API programmingWho this book is forThis 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.
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