Bøker av Mihalis Tsoukalos

Learning the new system''s programming language for all Unix-type systemsKey FeaturesLearn how to write system''s level code in Golang, similar to Unix/Linux systems codeRamp up in Go quicklyDeep dive into Goroutines and Go concurrency to be able to take advantage of Go server-level constructsBook DescriptionGo is the new systems programming language for Linux and Unix systems. It is also the language in which some of the most prominent cloud-level systems have been written, such as Docker. Where C programmers used to rule, Go programmers are in demand to write highly optimized systems programming code.Created by some of the original designers of C and Unix, Go expands the systems programmers toolkit and adds a mature, clear programming language. Traditional system applications become easier to write since pointers are not relevant and garbage collection has taken away the most problematic area for low-level systems code: memory management.This book opens up the world of high-performance Unix system applications to the beginning Go programmer. It does not get stuck on single systems or even system types, but tries to expand the original teachings from Unix system level programming to all types of servers, the cloud, and the web. What you will learnExplore the Go language from the standpoint of a developer conversant with Unix, Linux, and so onUnderstand Goroutines, the lightweight threads used for systems and concurrent applicationsLearn how to translate Unix and Linux systems code in C to Golang codeHow to write fast and lightweight server codeDive into concurrency with GoWrite low-level networking codeWho this book is for:Intermediate Linux and general Unix programmers. Network programmers from beginners to advanced practitioners. C and C++ programmers interested in different approaches to concurrency and Linux systems programming.

Build and use the most popular time series index available today with Python to search and join time series at the subsequence levelPurchase of the print or Kindle book includes a free PDF eBookKey Features:Learn how to implement algorithms and techniques from research papersGet to grips with building time series indexes using iSAXLeverage iSAX to solve real-world time series problemsBook Description:Time series are everywhere, ranging from financial data and system metrics to weather stations and medical records. Being able to access, search, and compare time series data quickly is essential, and this comprehensive guide enables you to do just that by helping you explore SAX representation and the most effective time series index, iSAX.The book begins by teaching you about the implementation of SAX representation in Python as well as the iSAX index, along with the required theory sourced from academic research papers. The chapters are filled with figures and plots to help you follow the presented topics and understand key concepts easily. But what makes this book really great is that it contains the right amount of knowledge about time series indexing using the right amount of theory and practice so that you can work with time series and develop time series indexes successfully. Additionally, the presented code can be easily ported to any other modern programming language, such as Swift, Java, C, C++, Ruby, Kotlin, Go, Rust, and JavaScript.By the end of this book, you'll have learned how to harness the power of iSAX and SAX representation to efficiently index and analyze time series data and will be equipped to develop your own time series indexes and effectively work with time series data.What You Will Learn:Find out how to develop your own Python packages and write simple Python testsUnderstand what a time series index is and why it is usefulGain a theoretical and practical understanding of operating and creating time series indexesDiscover how to use SAX representation and the iSAX indexFind out how to search and compare time seriesUtilize iSAX visualizations to aid in the interpretation of complex or large time seriesWho this book is for:This book is for practitioners, university students working with time series, researchers, and anyone looking to learn more about time series. Basic knowledge of UNIX, Linux, and Python and an understanding of basic programming concepts are needed to grasp the topics in this book. This book will also be handy for people who want to learn how to read research papers, learn from them, and implement their algorithms.