Download or read book Concurrent File I O in Python written by Jason Brownlee and published by SuperFastPython.com. This book was released on with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: File I/O can be faster in Python when using concurrency. * Discover how to write files 3x faster with processes * Discover how to read files 3x faster with processes and threads * Discover how to unzip files 4x faster with processes and threads File I/O stands for File Input/Output, referring to the process of reading data from and writing data to files on a storage device like a hard drive. Studying how to bring concurrency to file I/O is critical for Python developers. Adding concurrency into your file I/O tasks, you can unlock the full potential of modern computer hardware, making your applications more efficient and capable of handling large workloads. The problem is, there is no silver bullet. Each program and each task is different and unique. We cannot know which approach to Python concurrency will give good or even the best performance. Therefore in addition to learning how to perform file I/O operations concurrently, Python developers must learn how to benchmark a suite of different approaches to implementing file I/O operations concurrently. Introducing: "Concurrent File I/O in Python". A new book designed to teach you how to bring concurrency to your file I/O tasks in Python, super fast! You will get rapid-paced tutorials showing you how to bring concurrency to the most common file I/O tasks. Including: * How to perform file I/O operation in the background. * How to concurrently read files from disk and write files to disk. * How to concurrently delete files from disk. * How to concurrently copy, move, and rename files on disk. * How to efficiently append files on disk. * How to concurrently zip files and unzip files on disk. Don't worry if you are new to file I/O or concurrency, you will also get primers on the background required to get the most out of this book, including: * The importance of concurrency for high-performance file I/O. * How to perform common file I/O operations in Python. * How to use Python concurrency APIs including threading, multiprocessing, and asyncio. * How to perform file I/O with coroutines in asyncio using the aiofiles library. * How to use programming patterns for concurrent file I/O. Each tutorial is carefully designed to teach one critical aspect of how to bring concurrency to file I/O tasks. Stop copy-pasting code from StackOverflow answers. Learn Python concurrency correctly, step-by-step.

Download or read book Learning Concurrency in Python written by Elliot Forbes and published by Packt Publishing Ltd. This book was released on 2017-08-16 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practically and deeply understand concurrency in Python to write efficient programs About This Book Build highly efficient, robust, and concurrent applications Work through practical examples that will help you address the challenges of writing concurrent code Improve the overall speed of execution in multiprocessor and multicore systems and keep them highly available Who This Book Is For This book is for Python developers who would like to get started with concurrent programming. Readers are expected to have a working knowledge of the Python language, as this book will build on these fundamentals concepts. What You Will Learn Explore the concept of threading and multiprocessing in Python Understand concurrency with threads Manage exceptions in child threads Handle the hardest part in a concurrent system — shared resources Build concurrent systems with Communicating Sequential Processes (CSP) Maintain all concurrent systems and master them Apply reactive programming to build concurrent systems Use GPU to solve specific problems In Detail Python is a very high level, general purpose language that is utilized heavily in fields such as data science and research, as well as being one of the top choices for general purpose programming for programmers around the world. It features a wide number of powerful, high and low-level libraries and frameworks that complement its delightful syntax and enable Python programmers to create. This book introduces some of the most popular libraries and frameworks and goes in-depth into how you can leverage these libraries for your own high-concurrent, highly-performant Python programs. We'll cover the fundamental concepts of concurrency needed to be able to write your own concurrent and parallel software systems in Python. The book will guide you down the path to mastering Python concurrency, giving you all the necessary hardware and theoretical knowledge. We'll cover concepts such as debugging and exception handling as well as some of the most popular libraries and frameworks that allow you to create event-driven and reactive systems. By the end of the book, you'll have learned the techniques to write incredibly efficient concurrent systems that follow best practices. Style and approach This easy-to-follow guide teaches you new practices and techniques to optimize your code, and then moves toward more advanced ways to effectively write efficient Python code. Small and simple practical examples will help you test the concepts yourself, and you will be able to easily adapt them for any application.

Download or read book Python Concurrency with asyncio written by Matthew Fowler and published by Simon and Schuster. This book was released on 2022-03-15 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to speed up slow Python code with concurrent programming and the cutting-edge asyncio library. Use coroutines and tasks alongside async/await syntax to run code concurrently Build web APIs and make concurrency web requests with aiohttp Run thousands of SQL queries concurrently Create a map-reduce job that can process gigabytes of data concurrently Use threading with asyncio to mix blocking code with asyncio code Python is flexible, versatile, and easy to learn. It can also be very slow compared to lower-level languages. Python Concurrency with asyncio teaches you how to boost Python's performance by applying a variety of concurrency techniques. You'll learn how the complex-but-powerful asyncio library can achieve concurrency with just a single thread and use asyncio's APIs to run multiple web requests and database queries simultaneously. The book covers using asyncio with the entire Python concurrency landscape, including multiprocessing and multithreading. About the technology It’s easy to overload standard Python and watch your programs slow to a crawl. Th e asyncio library was built to solve these problems by making it easy to divide and schedule tasks. It seamlessly handles multiple operations concurrently, leading to apps that are lightning fast and scalable. About the book Python Concurrency with asyncio introduces asynchronous, parallel, and concurrent programming through hands-on Python examples. Hard-to-grok concurrency topics are broken down into simple flowcharts that make it easy to see how your tasks are running. You’ll learn how to overcome the limitations of Python using asyncio to speed up slow web servers and microservices. You’ll even combine asyncio with traditional multiprocessing techniques for huge improvements to performance. What's inside Build web APIs and make concurrency web requests with aiohttp Run thousands of SQL queries concurrently Create a map-reduce job that can process gigabytes of data concurrently Use threading with asyncio to mix blocking code with asyncio code About the reader For intermediate Python programmers. No previous experience of concurrency required. About the author Matthew Fowler has over 15 years of software engineering experience in roles from architect to engineering director. Table of Contents 1 Getting to know asyncio 2 asyncio basics 3 A first asyncio application 4 Concurrent web requests 5 Non-blocking database drivers 6 Handling CPU-bound work 7 Handling blocking work with threads 8 Streams 9 Web applications 10 Microservices 11 Synchronization 12 Asynchronous queues 13 Managing subprocesses 14 Advanced asyncio

Download or read book Mastering Concurrency in Python written by Quan Nguyen and published by Packt Publishing Ltd. This book was released on 2018-11-27 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: Immerse yourself in the world of Python concurrency and tackle the most complex concurrent programming problems Key FeaturesExplore the core syntaxes, language features and modern patterns of concurrency in PythonUnderstand how to use concurrency to keep data consistent and applications responsiveUtilize application scaffolding to design highly-scalable programs Book Description Python is one of the most popular programming languages, with numerous libraries and frameworks that facilitate high-performance computing. Concurrency and parallelism in Python are essential when it comes to multiprocessing and multithreading; they behave differently, but their common aim is to reduce the execution time. This book serves as a comprehensive introduction to various advanced concepts in concurrent engineering and programming. Mastering Concurrency in Python starts by introducing the concepts and principles in concurrency, right from Amdahl's Law to multithreading programming, followed by elucidating multiprocessing programming, web scraping, and asynchronous I/O, together with common problems that engineers and programmers face in concurrent programming. Next, the book covers a number of advanced concepts in Python concurrency and how they interact with the Python ecosystem, including the Global Interpreter Lock (GIL). Finally, you'll learn how to solve real-world concurrency problems through examples. By the end of the book, you will have gained extensive theoretical knowledge of concurrency and the ways in which concurrency is supported by the Python language What you will learnExplore the concepts of concurrency in programmingExplore the core syntax and features that enable concurrency in PythonUnderstand the correct way to implement concurrencyAbstract methods to keep the data consistent in your programAnalyze problems commonly faced in concurrent programmingUse application scaffolding to design highly-scalable programsWho this book is for This book is for developers who wish to build high-performance applications and learn about signle-core, multicore programming or distributed concurrency. Some experience with Python programming language is assumed.

Download or read book Python Threading Jump Start written by Jason Brownlee and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Python in Practice written by Mark Summerfield and published by Addison-Wesley. This book was released on 2013-08-20 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Winner of the 2014 Jolt Award for "Best Book" “Whether you are an experienced programmer or are starting your career, Python in Practice is full of valuable advice and example to help you improve your craft by thinking about problems from different perspectives, introducing tools, and detailing techniques to create more effective solutions.” —Doug Hellmann, Senior Developer, DreamHost If you’re an experienced Python programmer, Python in Practice will help you improve the quality, reliability, speed, maintainability, and usability of all your Python programs. Mark Summerfield focuses on four key themes: design patterns for coding elegance, faster processing through concurrency and compiled Python (Cython), high-level networking, and graphics. He identifies well-proven design patterns that are useful in Python, illuminates them with expert-quality code, and explains why some object-oriented design patterns are irrelevant to Python. He also explodes several counterproductive myths about Python programming—showing, for example, how Python can take full advantage of multicore hardware. All examples, including three complete case studies, have been tested with Python 3.3 (and, where possible, Python 3.2 and 3.1) and crafted to maintain compatibility with future Python 3.x versions. All code has been tested on Linux, and most code has also been tested on OS X and Windows. All code may be downloaded at www.qtrac.eu/pipbook.html. Coverage includes Leveraging Python’s most effective creational, structural, and behavioral design patterns Supporting concurrency with Python’s multiprocessing, threading, and concurrent.futures modules Avoiding concurrency problems using thread-safe queues and futures rather than fragile locks Simplifying networking with high-level modules, including xmlrpclib and RPyC Accelerating Python code with Cython, C-based Python modules, profiling, and other techniques Creating modern-looking GUI applications with Tkinter Leveraging today’s powerful graphics hardware via the OpenGL API using pyglet and PyOpenGL

Download or read book Python ThreadPool Jump Start written by Jason Brownlee and published by SuperFastPython.com. This book was released on 2022-08-09 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: How much faster could your Python code run (if you used 100s of threads)? The ThreadPool class provides easy-to-use thread-based concurrency for IO-bound tasks. This is not some random third-party library, this is a class provided in the Python standard library (already installed on your system). This is the class you need to make your code run faster. There's just one problem. No one knows about it (or how to use it well). Introducing: "Python ThreadPool Jump-Start". A new book designed to teach you thread pools in Python, super fast! You will get a rapid-paced, 7-part course to get you started and make you awesome at using the ThreadPool. Including: * How to create thread pools and when to use them. * How to configure thread pools including the number of threads. * How to execute tasks with worker threads and wait for results. * How to execute tasks in the thread pool asynchronously. * How to execute tasks lazily and respond to results as tasks complete. * How to handle results with callbacks and check the status of tasks. * How to develop a port scanner that is 70x faster than the sequential version. Each of the 7 lessons was carefully designed to teach one critical aspect of the ThreadPool, with explanations, code snippets and worked examples. Each lesson ends with an exercise for you to complete to confirm you understood the topic, a summary of what was learned, and links for further reading if you want to go deeper. Stop copy-pasting code from StackOverflow answers. Learn Python concurrency correctly, step-by-step.

Download or read book Parallel Programming in MPI and OpenMP written by Victor Eijkhout and published by Lulu.com. This book was released on 2017-11-27 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a textbook about parallel programming of scientific application on large computers, using MPI and OpenMP.

Download or read book Python for the Lab written by Aquiles Carattino and published by . This book was released on 2020-10-11 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python for the Lab is the first book covering how to develop instrumentation software. It is ideal for researchers willing to automatize their setups and bring their experiments to the next level. The book is the product of countless workshops at different universities, and a carefully design pedagogical strategy. With an easy to follow and task-oriented design, the book uncovers all the best practices in the field. It also shows how to design code for long-term maintainability, opening the doors of fruitful collaboration among researchers from different labs.

Download or read book Python in a Nutshell written by Alex Martelli and published by "O'Reilly Media, Inc.". This book was released on 2006-07-14 with total page 734 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume offers Python programmers a straightforward guide to the important tools and modules of this open source language. It deals with the most frequently used parts of the standard library as well as the most popular and important third party extensions.

Download or read book Python Concurrent Futures Interview Questions written by Jason Brownlee and published by SuperFastPython.com. This book was released on with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: How well do you know the ThreadPoolExecutor and ProcessPoolExecutor in Python? The concurrent.futures module provides the ability to launch parallel and concurrent tasks in Python using thread and process-based concurrency. Importantly, the ThreadPoolExecutor and ProcessPoolExecutor offer the same modern interface with asynchronous tasks, Future objects, and the ability to wait on groups of tasks. The concurrent.futures module with the ThreadPoolExecutor and ProcessPoolExecutor classes offers the best way to execute ad hoc tasks concurrently in Python, and few developers know about it, let alone how to use it well. * Do you know how to handle task results in the order tasks finish? * Do you know how to wait for the first task to fail? * Do you know how many workers are created by default? Discover 130+ interview questions and their answers on the concurrent.futures module. * Study the questions and answers and improve your skill. * Test yourself to see what you really know, and what you don't. * Select questions to interview developers on a new role. Prepare for an interview or test your ThreadPoolExecutor and ProcessPoolExecutor skills in Python today.

Download or read book Parallel and High Performance Programming with Python written by Fabio Nelli and published by Orange Education Pvt Ltd. This book was released on 2023-04-13 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unleash the capabilities of Python and its libraries for solving high performance computational problems. KEY FEATURES ● Explores parallel programming concepts and techniques for high-performance computing. ● Covers parallel algorithms, multiprocessing, distributed computing, and GPU programming. ● Provides practical use of popular Python libraries/tools like NumPy, Pandas, Dask, and TensorFlow. DESCRIPTION This book will teach you everything about the powerful techniques and applications of parallel computing, from the basics of parallel programming to the cutting-edge innovations shaping the future of computing. The book starts with an introduction to parallel programming and the different types of parallelism, including parallel programming with threads and processes. The book then delves into asynchronous programming, distributed Python, and GPU programming with Python, providing you with the tools you need to optimize your programs for distributed and high-performance computing. The book also covers a wide range of applications for parallel computing, including data science, artificial intelligence, and other complex scientific simulations. You will learn about the challenges and opportunities presented by parallel computing for these applications and how to overcome them. By the end of the book, you will have insights into the future of parallel computing, the latest research and developments in the field, and explore the exciting possibilities that lie ahead. WHAT WILL YOU LEARN ● Build faster, smarter, and more efficient applications for data analysis, machine learning, and scientific computing ● Implement parallel algorithms in Python ● Best practices for designing, implementing, and scaling parallel programs in Python WHO IS THIS BOOK FOR? This book is aimed at software developers who wish to take their careers to the next level by improving their skills and learning about concurrent and parallel programming. It is also intended for Python developers who aspire to write fast and efficient programs, and for students who wish to learn the fundamentals of parallel computing and its practical uses. TABLE OF CONTENTS 1. Introduction to Parallel Programming 2. Building Multithreaded Programs 3. Working with Multiprocessing and mpi4py Library 4. Asynchronous Programming with AsyncIO 5. Realizing Parallelism with Distributed Systems 6. Maximizing Performance with GPU Programming using CUDA 7. Embracing the Parallel Computing Revolution 8. Scaling Your Data Science Applications with Dask 9. Exploring the Potential of AI with Parallel Computing 10. Hands-on Applications of Parallel Computing

Download or read book Mastering Python for Networking and Security written by José Ortega and published by Packt Publishing Ltd. This book was released on 2021-01-04 with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tackle security and networking issues using Python libraries such as Nmap, requests, asyncio, and scapy Key Features Enhance your Python programming skills in securing systems and executing networking tasks Explore Python scripts to debug and secure complex networks Learn to avoid common cyber events with modern Python scripting Book DescriptionIt’s now more apparent than ever that security is a critical aspect of IT infrastructure, and that devastating data breaches can occur from simple network line hacks. As shown in this book, combining the latest version of Python with an increased focus on network security can help you to level up your defenses against cyber attacks and cyber threats. Python is being used for increasingly advanced tasks, with the latest update introducing new libraries and packages featured in the Python 3.7.4 recommended version. Moreover, most scripts are compatible with the latest versions of Python and can also be executed in a virtual environment. This book will guide you through using these updated packages to build a secure network with the help of Python scripting. You’ll cover a range of topics, from building a network to the procedures you need to follow to secure it. Starting by exploring different packages and libraries, you’ll learn about various ways to build a network and connect with the Tor network through Python scripting. You will also learn how to assess a network's vulnerabilities using Python security scripting. Later, you’ll learn how to achieve endpoint protection by leveraging Python packages, along with writing forensic scripts. By the end of this Python book, you’ll be able to use Python to build secure apps using cryptography and steganography techniques.What you will learn Create scripts in Python to automate security and pentesting tasks Explore Python programming tools that are used in network security processes Automate tasks such as analyzing and extracting information from servers Understand how to detect server vulnerabilities and analyze security modules Discover ways to connect to and get information from the Tor network Focus on how to extract information with Python forensics tools Who this book is for This Python network security book is for network engineers, system administrators, or any security professional looking to overcome networking and security challenges. You will also find this book useful if you’re a programmer with prior experience in Python. A basic understanding of general programming structures and the Python programming language is required before getting started.

Download or read book A Primer for Computational Biology written by Shawn T. O'Neil and published by . This book was released on 2017-12-21 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Primer for Computational Biology aims to provide life scientists and students the skills necessary for research in a data-rich world. The text covers accessing and using remote servers via the command-line, writing programs and pipelines for data analysis, and provides useful vocabulary for interdisciplinary work. The book is broken into three parts: Introduction to Unix/Linux: The command-line is the "natural environment" of scientific computing, and this part covers a wide range of topics, including logging in, working with files and directories, installing programs and writing scripts, and the powerful "pipe" operator for file and data manipulation. Programming in Python: Python is both a premier language for learning and a common choice in scientific software development. This part covers the basic concepts in programming (data types, if-statements and loops, functions) via examples of DNA-sequence analysis. This part also covers more complex subjects in software development such as objects and classes, modules, and APIs. Programming in R: The R language specializes in statistical data analysis, and is also quite useful for visualizing large datasets. This third part covers the basics of R as a programming language (data types, if-statements, functions, loops and when to use them) as well as techniques for large-scale, multi-test analyses. Other topics include S3 classes and data visualization with ggplot2.

Download or read book PYTHON PROGRAMMING written by Dr.M Sirish Kumar and published by RAJA SURESH. This book was released on 2023-02-22 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to provide a broad PYTHON PROGRAMMING for the importance of PYTHON PROGRAMMING is well known in various engineering fields. The book uses to explain the fundamentals of this subject. It provides a logical method of explaining various complicated concepts and stepwise methods to explain important topics. Each chapter is well supported with necessary illustrations. All the chapters in the book are arranged in a proper sequence that permits each topic to build upon earlier studies. PYTHON PROGRAMMING an important research area. The techniques developed in this area so far require to be summarized appropriately. In this book, the fundamental theories of these techniques are introduced. Particularly, the functions required in image processing techniques are introduced.

Download or read book Python Networking 101 written by Odette Windsor and published by GitforGits. This book was released on 2023-05-06 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python Networking 101 is the ultimate guide for aspiring network administrators looking to build their network management and automation skills using Python. With a comprehensive and hands-on approach, this book covers the most important aspects of networking, including network fundamentals, network automation, monitoring, security, topology, and testing. The book begins with an overview of the Python language and its libraries used for networking tasks. Each chapter then focuses on a specific networking task, providing readers with a deep understanding of the topic and practical demonstrations using Python libraries. By the end of each chapter, readers will be well-versed in the execution and implementation of these tasks. Throughout the book, readers will learn about the best Python libraries network administrators prefer, including Netmiko, Paramiko, SNMP, Flask, AsyncIO, and more. Practical examples and exercises will help them gain hands-on experience working with these libraries to achieve various networking objectives. The book also discusses advanced network automation techniques, providing insights into network automation frameworks, such as Ansible, and how to build custom network automation solutions using Python. By the end of the book, readers will be equipped with the knowledge to integrate Python with network management tools, making them efficient and effective network administrators. Key Learnings Master Python language and its networking libraries for network administration tasks. Monitor and analyze network performance and troubleshoot issues effectively. Enhance network security using Python libraries and best practices. Get well-versed with Netmiko, Paramiko, Socket, PySNMP, AsyncIO, and SimPy. Develop custom network services and interact with RESTful APIs using Python. Improve performance with asynchronous programming using AsyncIO in network applications. Get hands-on with Ansible to create playbooks and perform every possible network automation. Perform network testing and simulation, and analyze results for optimized performance. Manage and automate network configuration changes and ensure compliance. Leverage advanced network automation techniques and frameworks for efficient administration. Table of Content Introduction to Python and Networking Libraries TCP, UDP and Socket Programming Working with Application Layer Exploring Network Automation Network Monitoring and Analysis Network Security and Python Working with APIs and Network Services Network Programming with AsyncIO Network Testing and Simulation Network Configuration Management Ansible and Python Audience "Python Networking 101" is designed to provide readers with the skills required to excel as a network administrators. The practical approach, coupled with real-world examples, ensures readers can implement the techniques learned in their professional careers. Knowing Python and the basics of computer networks is sufficient, to begin with this book.

Download or read book Concurrent Programming in Python written by BignumWorks LLP and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Harness the power of modern code structures with Python to improve performance and flexibility About This Video A Practical course that focuses on concurrent programming in Python Covers the latest concurrent applications to take advantage of modern-day programming in Python Shows how to use different synchronization primitives to write multi-threaded code In Detail In this course, you will skill-up with techniques related to various aspects of concurrent programming in Python, including common thread programming techniques and approaches to parallel processing. Filled with examples, this course will show you all you need to know to start using concurrency in Python. You will learn about the principal approaches to concurrency that Python has to offer, including libraries and tools needed to exploit the performance of your processor. Learn the basic theory and history of parallelism and choose the best approach when it comes to parallel processing. After taking this course you will have gained an in-depth knowledge of using threads and processes with the help of real-world examples.