Isbn: 9798182316569 - the python engineer's guide to data-intensive applications: designing scalable, reliable, and distributed systems for big data: 2 (modern python development series) (5 resultados)

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New. Print on Demand.

Paperback. Condición: new. Paperback. The Python Engineer's Guide to Data-Intensive ApplicationsModern applications generate more data than ever before. Building systems that can process, store, and scale that data efficiently is one of the greatest challenges facing software engineers today. The Python Engineer's Guide to Data-Intensive Applications provides a practical roadmap for designing robust, high-performance systems capable of handling real-world workloads.Whether you're developing analytics platforms, cloud-native services, streaming pipelines, or distributed applications, this book bridges the gap between Python programming and large-scale system architecture. Complex concepts are explained in clear, approachable language, making advanced topics accessible without sacrificing technical depth.What Makes This Book Different?Unlike theory-heavy references, this guide focuses on practical engineering principles and Python-based solutions used in modern production environments. It combines software architecture, distributed systems, databases, messaging systems, scalability patterns, and reliability techniques into one comprehensive resource designed specifically for developers.Inside This BookFoundations of data-intensive systems and scalability principlesData models, storage engines, and database architecturesReplication, partitioning, and fault tolerance strategiesDistributed systems concepts explained with practical examplesEvent-driven architectures and messaging systemsStream processing and batch processing frameworksDesigning reliable, maintainable, and observable applicationsPerformance optimization and scalability techniquesBuilding resilient cloud-native applications with PythonReal-world architectural patterns and best practicesWho Is This Book For?Python developers seeking to build large-scale applicationsBackend engineers and software architectsData engineers and analytics professionalsDevOps and cloud practitionersComputer science students and technology enthusiastsAnyone looking to understand how modern distributed systems workBuild Systems That Scale. Solve Problems That Matter.From databases and distributed computing to reliability and performance, The Python Engineer's Guide to Data-Intensive Applications equips you with the knowledge and practical insights needed to design systems that remain fast, scalable, and dependable as data grows.If you're ready to move beyond writing code and start engineering systems that power modern applications, this book belongs on your shelf. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condición: new. Paperback. The Python Engineer's Guide to Data-Intensive ApplicationsModern applications generate more data than ever before. Building systems that can process, store, and scale that data efficiently is one of the greatest challenges facing software engineers today. The Python Engineer's Guide to Data-Intensive Applications provides a practical roadmap for designing robust, high-performance systems capable of handling real-world workloads.Whether you're developing analytics platforms, cloud-native services, streaming pipelines, or distributed applications, this book bridges the gap between Python programming and large-scale system architecture. Complex concepts are explained in clear, approachable language, making advanced topics accessible without sacrificing technical depth.What Makes This Book Different?Unlike theory-heavy references, this guide focuses on practical engineering principles and Python-based solutions used in modern production environments. It combines software architecture, distributed systems, databases, messaging systems, scalability patterns, and reliability techniques into one comprehensive resource designed specifically for developers.Inside This BookFoundations of data-intensive systems and scalability principlesData models, storage engines, and database architecturesReplication, partitioning, and fault tolerance strategiesDistributed systems concepts explained with practical examplesEvent-driven architectures and messaging systemsStream processing and batch processing frameworksDesigning reliable, maintainable, and observable applicationsPerformance optimization and scalability techniquesBuilding resilient cloud-native applications with PythonReal-world architectural patterns and best practicesWho Is This Book For?Python developers seeking to build large-scale applicationsBackend engineers and software architectsData engineers and analytics professionalsDevOps and cloud practitionersComputer science students and technology enthusiastsAnyone looking to understand how modern distributed systems workBuild Systems That Scale. Solve Problems That Matter.From databases and distributed computing to reliability and performance, The Python Engineer's Guide to Data-Intensive Applications equips you with the knowledge and practical insights needed to design systems that remain fast, scalable, and dependable as data grows.If you're ready to move beyond writing code and start engineering systems that power modern applications, this book belongs on your shelf. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…