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: rivasss , 10:54 | : 0 |
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: rivasss , 08:19 | : 0 |
: Programming Crystal: Create High-Performance, Safe, Concurrent Apps
: Ivo Balbaert, Simon St. Laurent
: Pragmatic Bookshelf
: 2019
: 266
:
: pdf, djvu
: 10.18 MB

Crystal is for Ruby programmers who want more performance, or for developers who enjoy working in a high-level scripting environment. Crystal combines native execution speed and concurrency with Ruby-like syntax, so you will feel right at home. This book, the first available on Crystal, shows you how to write applications that have the beauty and elegance of a modern language, combined with the power of types and modern concurrency tooling. Now you can write beautiful code that runs faster, scales better, and is a breeze to deploy. Crystal is elegant to read and easy to program like Ruby, allowing full object-oriented development.
: Ingvar16 , 18:31 | : 0 |

: Programmer avec Arduino pour les Nuls
: Olivier Engler
: First Interactive
ISBN: 978-2-412-02387-7
: 2017
: PDF
: 467
: Mirknig.su
: 101.2 MB
: French

Arduino est un circuit compos? d'un microcontr?leur ultra performant qui se programme tr?s facilement et tr?s bon march?. Il permet de se connecter ? diff?rents composants comme des ?crans, des moteurs ?lectriques, tous types de capteurs, etc. C'est aujourd'hui un composant tr?s appr?ci? dans l'interfa?age avec de nombreux composants ?lectroniques. Son prix tr?s abordable attire de tr?s nombreux utilisateurs professionnels ou d?butants en ?lectronique.
: groov , 17:26 | : 0 |
: The Python Quick Syntax Reference
: Gregory Walters
: Apress
: 2013
: PDF
: 152
: 2 Mb
: English

The Python Quick Syntax Reference is the "go to" book that contains an easy to read and use guide to Python programming and development. This condensed code and syntax reference presents the Python language in a well-organized format designed to be used time and again.
You won't find jargon, bloated samples, case studies, or history of Hello World and computer theory in this handy reference. This Python syntax reference is packed with useful information and is a must-have for any Python developer.
: Ice Zero , 17:02 | : 0 |
: Getting Started with Storm: Continuous Streaming Computation with Twitter's Cluster Technology
: Jonathan Leibiusky, Gabriel Eisbruch, Dario Simonassi
: O'Reilly Media
: 2012
: PDF
: 106
: Mirknig.su
: 4.7 Mb
: English

Even as big data is turning the world upside down, the next phase of the revolution is already taking shape: real-time data analysis. This hands-on guide introduces you to Storm, a distributed, JVM-based system for processing streaming data. Through simple tutorials, sample Java code, and a complete real-world scenario, youll learn how to build fast, fault-tolerant solutions that process results as soon as the data arrives.
Discover how easy it is to set up Storm clusters for solving various problems, including continuous data computation, distributed remote procedure calls, and data stream processing.
: Ice Zero , 17:02 | : 0 |
: Getting Started with Roo: Rapid Application Development for Java and Spring
: Josh Long, Steve Mayzak
: O'Reilly Media
: 2011
: PDF
: 64
: 7.3 Mb
: English

Spring Roo goes a step beyond the Spring Framework by bringing true Rapid Application Development to Javajust as Grails has done with Groovy. This concise introduction shows you how to build applications with Roo, using the framework's shell as an intelligent and timesaving code-completion tool. It's an ideal RAD tool because Roo does much of the tedious code maintenance.
You'll get started by building a simple customer relationship management application, complete with step-by-step instructions and code examples. Learn how to control any part of the application with Roo's opt-in feature, while using this open source framework to automate the rest of the code.
: Ice Zero , 17:02 | : 0 |
: Getting Started with RStudio: An Integrated Development Environment for R
: John Verzani
: O'Reilly Media
: 2011
: PDF
: 98
: 6.1 Mb
: English

Dive into the RStudio Integrated Development Environment (IDE) for using and programming R, the popular open source software for statistical computing and graphics. This concise book provides new and experienced users with an overview of RStudio, as well as hands-on instructions for analyzing data, generating reports, and developing R software packages.
The open source RStudio IDE brings many powerful coding tools together into an intuitive, easy-to-learn interface. With this guide, youll learn how to use its main componentsincluding the console, source code editor, and data viewerthrough descriptions and case studies. Getting Started with RStudio serves as both a reference and introduction to this unique IDE.
: Ice Zero , 17:02 | : 0 |
: Cloud Native DevOps with Kubernetes: Building, Deploying, and Scaling Modern Applications in the Cloud (1st Edition)
: John Arundel, Justin Domingus
: O'Reilly Media
ISBN: 1492040762
: 2019
: 346
:
: epub, pdf (conv)
: 11.8 MB

Kubernetes is the operating system of the cloud-native world, providing a reliable and scalable platform for running containerized workloads. This book shows developers and operations staff how to apply industry-standard DevOps practices to Kubernetes in a cloud-native context. You'll learn all about the Kubernetes ecosystem and discover battle-tested solutions to everyday problems. In this friendly, pragmatic book, cloud experts John Arundel and Justin Domingus show you what Kubernetes can do - and what you can do with it. You'll build, step by step, an example cloud-native application and its supporting infrastructure, along with a development environment and continuous deployment pipeline that you can use for your own applications.
: Ingvar16 , 16:18 | : 0 |
: Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib, 2nd Edition
: Robert Johansson
: Apress
ISBN: 1484242459
: 2019
: 700
:
: pdf (true), epub
: 62.4 MB

Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute solutions and mathematically model applications in big data, cloud computing, financial engineering, business management and more. Numerical Python, Second Edition, presents many brand-new case study examples of applications in data science and statistics using Python, along with extensions to many previous examples.
: Ingvar16 , 16:07 | : 0 |

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