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Synopsis
Python Architecture Patterns: Designing Scalable Applications is a practical guide for developers, software engineers, architects, and technical leaders who want to move beyond writing code and start designing robust software systems. Through real-world examples, proven architectural patterns, and production-focused techniques, you'll learn how successful Python applications are structured—from startup MVPs to enterprise-scale platforms.
Whether you're building web applications, APIs, microservices, data platforms, automation systems, or cloud-native solutions, this book provides the architectural foundations needed to create software that is easier to test, extend, deploy, and maintain.
Inside, you'll discover how to:
- Apply layered, hexagonal, clean, and domain-driven architectures in Python
- Design loosely coupled systems using dependency injection and inversion of control
- Implement Repository, Unit of Work, Service Layer, and Factory patterns effectively
- Build scalable APIs and backend services with maintainability in mind
- Structure large codebases for long-term growth and team collaboration
- Separate business logic from infrastructure and framework dependencies
- Design event-driven architectures and asynchronous processing workflows
- Create resilient microservices and distributed systems architectures
- Improve testability through architectural boundaries and abstractions
- Integrate databases, messaging systems, caching layers, and external services cleanly
- Apply CQRS, Event Sourcing, and modern enterprise design principles
- Optimize performance, reliability, observability, and operational scalability
- Refactor legacy applications into maintainable, modular architectures
- Deploy cloud-ready Python systems using modern DevOps practices
Packed with practical examples, architectural diagrams, implementation strategies, and industry best practices, this book bridges the gap between theory and real-world software engineering. Each chapter demonstrates how architectural decisions impact scalability, maintainability, security, and developer productivity.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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Python Architecture Patterns: Designing Scalable Applications
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Python Architecture Patterns (Paperback)
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Paperback. Etat : new. Paperback. Python Architecture Patterns: Designing Scalable Applications is a practical guide for developers, software engineers, architects, and technical leaders who want to move beyond writing code and start designing robust software systems. Through real-world examples, proven architectural patterns, and production-focused techniques, you'll learn how successful Python applications are structured-from startup MVPs to enterprise-scale platforms.Whether you're building web applications, APIs, microservices, data platforms, automation systems, or cloud-native solutions, this book provides the architectural foundations needed to create software that is easier to test, extend, deploy, and maintain.Inside, you'll discover how to: Apply layered, hexagonal, clean, and domain-driven architectures in PythonDesign loosely coupled systems using dependency injection and inversion of controlImplement Repository, Unit of Work, Service Layer, and Factory patterns effectivelyBuild scalable APIs and backend services with maintainability in mindStructure large codebases for long-term growth and team collaborationSeparate business logic from infrastructure and framework dependenciesDesign event-driven architectures and asynchronous processing workflowsCreate resilient microservices and distributed systems architecturesImprove testability through architectural boundaries and abstractionsIntegrate databases, messaging systems, caching layers, and external services cleanlyApply CQRS, Event Sourcing, and modern enterprise design principlesOptimize performance, reliability, observability, and operational scalabilityRefactor legacy applications into maintainable, modular architecturesDeploy cloud-ready Python systems using modern DevOps practicesPacked with practical examples, architectural diagrams, implementation strategies, and industry best practices, this book bridges the gap between theory and real-world software engineering. Each chapter demonstrates how architectural decisions impact scalability, maintainability, security, and developer productivity. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798198474819
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Python Architecture Patterns : Designing Scalable Applications
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Taschenbuch. Etat : Neu. Neuware - Python Architecture Patterns: Designing Scalable Applications is a practical guide for developers, software engineers, architects, and technical leaders who want to move beyond writing code and start designing robust software systems. Through real-world examples, proven architectural patterns, and production-focused techniques, you'll learn how successful Python applications are structured-from startup MVPs to enterprise-scale platforms.Whether you're building web applications, APIs, microservices, data platforms, automation systems, or cloud-native solutions, this book provides the architectural foundations needed to create software that is easier to test, extend, deploy, and maintain.Inside, you'll discover how to: - Apply layered, hexagonal, clean, and domain-driven architectures in Python- Design loosely coupled systems using dependency injection and inversion of control- Implement Repository, Unit of Work, Service Layer, and Factory patterns effectively- Build scalable APIs and backend services with maintainability in mind- Structure large codebases for long-term growth and team collaboration- Separate business logic from infrastructure and framework dependencies- Design event-driven architectures and asynchronous processing workflows- Create resilient microservices and distributed systems architectures- Improve testability through architectural boundaries and abstractions- Integrate databases, messaging systems, caching layers, and external services cleanly- Apply CQRS, Event Sourcing, and modern enterprise design principles- Optimize performance, reliability, observability, and operational scalability- Refactor legacy applications into maintainable, modular architectures- Deploy cloud-ready Python systems using modern DevOps practicesPacked with practical examples, architectural diagrams, implementation strategies, and industry best practices, this book bridges the gap between theory and real-world software engineering. Each chapter demonstrates how architectural decisions impact scalability, maintainability, security, and developer productivity. N° de réf. du vendeur 9798198474819
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