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Data-Oriented Programming [Pehme köide]

3.67/5 (166 hinnangut Goodreads-ist)
  • Formaat: Paperback / softback, 325 pages, kõrgus x laius x paksus: 234x186x28 mm, kaal: 740 g
  • Ilmumisaeg: 15-Sep-2022
  • Kirjastus: Manning Publications
  • ISBN-10: 1617298573
  • ISBN-13: 9781617298578
Teised raamatud teemal:
Data-Oriented ProgrammingSuurem pilt
  • Formaat: Paperback / softback, 325 pages, kõrgus x laius x paksus: 234x186x28 mm, kaal: 740 g
  • Ilmumisaeg: 15-Sep-2022
  • Kirjastus: Manning Publications
  • ISBN-10: 1617298573
  • ISBN-13: 9781617298578
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781617298578.html
Märksõnad:
Data-Oriented Programming teaches you to design and implement software using the data-oriented programming paradigm. In it, you'll learn author Yehonathan Sharvit's unique approach to DOP that he has developed over a decade of experience. Every chapter contains a new light bulb moment that will change the way you think about programming. As you read, you'll build a library management system using the DOP paradigm. You'll design data models for business entities, manipulate immutable data collections, and write unit tests for data-oriented systems.

About the Technology Data-oriented programming is an exciting new paradigm that eliminates the usual complexity caused by combining data and code into objects and classes. In DOP, you maintain application data in persistent generic data structures separated from the program's code. You use general-purpose functions to manipulate the data without mutating it. This approach rids your applications of state-related bugs and makes your code much easier to understand and maintain.

Arvustused

"Insightful. Nicely illustrates the limits of OOP in managing the complexity of developing software. Explains how focusing on the data can simplify solving certain problems." Gregor Rayman

"This is a great guide to using Data-Oriented Programming to improve any new or existing OOP codebase." William E. Wheeler

"An interesting reada different approach that's worth examining and considering. It'll open your mind." Anne Epstein

"Read this through if you want to learn a different point of view and want to experience many 'aha!' moments." Christian Kreutzer-Beck

"Follows a very novel approach to introduce DOP concepts. Must read it if you want to rescue yourself from OOP." Kelum Prabath Senanayake

Forewords xiii
Preface xvii
Acknowledgments xviii
About This Book xx
About The Author xxiv
About The Cover Illustration xxv
Dramatis Personae xxvi
Part 1 Flexibility 1(136)
1 Complexity of object-oriented programming
3(23)
1.1 OOP design: Classic or classical?
4(9)
The design phase
4(2)
UML 101
6(3)
Explaining each piece of the class diagram
9(3)
The implementation phase
12(1)
1.2 Sources of complexity
13(13)
Many relations between classes
14(2)
Unpredictable code behavior
16(2)
Not trivial data serialization
18(2)
Complex class hierarchies
20(6)
2 Separation between code and data
26(17)
2.1 The two parts of a DOP system
27(2)
2.2 Data entities
29(2)
2.3 Code modules
31(5)
2.4 DOP systems are easy to understand
36(2)
2.5 DOP systems are flexible
38(5)
3 Basic data manipulation
43(28)
3.1 Designing a data model
44(4)
3.2 Representing records as maps
48(6)
3.3 Manipulating data with generic functions
54(4)
3.4 Calculating search results
58(7)
3.5 Handling records of different types
65(6)
4 State management
71(20)
4.1 Multiple versions of the system data
72(2)
4.2 Structural sharing
74(6)
4.3 Implementing structural sharing
80(2)
4.4 Data safety
82(1)
4.5 The commit phase of a mutation
83(2)
4.6 Ensuring system state integrity
85(1)
4.7 Restoring previous states
86(5)
5 Basic concurrency control
91(19)
5.1 Optimistic concurrency control
92(2)
5.2 Reconciliation between concurrent mutations
94(3)
5.3 Reducing collections
97(2)
5.4 Structural difference
99(7)
5.5 Implementing the reconciliation algorithm
106(4)
6 Unit tests
110(27)
6.1 The simplicity of data-oriented test cases
110(2)
6.2 Unit tests for data manipulation code
112(9)
The tree of function calls
113(2)
Unit tests for functions down the tree
115(4)
Unit tests for nodes in the tree
119(2)
6.3 Unit tests for queries
121(5)
6.4 Unit tests for mutations
126(11)
Part 2 Scalability 137(108)
7 Basic data validation
141(22)
7.1 Data validation in DOP
142(1)
7.2 JSON Schema in a nutshell
143(6)
7.3 Schema flexibility and strictness
149(5)
7.4 Schema composition
154(4)
7.5 Details about data validation failures
158(5)
8 Advanced concurrency control
163(12)
8.1 The complexity of locks
164(1)
8.2 Thread-safe counter with atoms
165(5)
8.3 Thread-safe cache with atoms
170(2)
8.4 State management with atoms
172(3)
9 Persistent data structures
175(13)
9.1 The need for persistent data structures
175(3)
9.2 The efficiency of persistent data structures
178(6)
9.3 Persistent data structures libraries
184(4)
Persistent data structures in Java
184(2)
Persistent data structures in JavaScript
186(2)
9.4 Persistent data structures in action
188(1)
10 Writing queries with persistent data structures
188(32)
Writing mutations with persistent data structures
191(1)
Serialization and deserialization
192(1)
Structural cliff
193(4)
Database operations
197(1)
10.1 Fetching data from the database
198(6)
10.2 Storing data in the database
204(3)
10.3 Simple data manipulation
207(4)
10.4 Advanced data manipulation
211(9)
11 Web services
220(25)
11.1 Another feature request
221(1)
11.2 Building the insides like the outsides
222(3)
11.3 Representing a client request as a map
225(2)
11.4 Representing a server response as a map
227(4)
11.5 Passing information forward
231(3)
11.6 Search result enrichment in action
234(11)
Part 3 Maintainability 245(88)
12 Advanced data validation
247(25)
12.1 Function arguments validation
248(7)
12.2 Return value validation
255(2)
12.3 Advanced data validation
257(3)
12.4 Automatic generation of data model diagrams
260(2)
12.5 Automatic generation of schema-based unit tests
262(7)
12.6 A new gift
269(3)
13 Polymorphism
272(23)
13.1 The essence of polymorphism
273(4)
13.2 Multimethods with single dispatch
277(4)
13.3 Multimethods with multiple dispatch
281(5)
13.4 Multimethods with dynamic dispatch
286(3)
13.5 Integrating multimethods in a production system
289(6)
14 Advanced data manipulation
295(16)
14.1 Updating a value in a map with eloquence
296(3)
14.2 Manipulating nested data
299(2)
14.3 Using the best tool for the job
301(4)
14.4 Unwinding at ease
305(6)
15 Debugging
311(22)
15.1 Determinism in programming
312(2)
15.2 Reproducibility with numbers and strings
314(4)
15.3 Reproducibility with any data
318(3)
15.4 Unit tests
321(8)
15.5 Dealing with external data sources
329(4)
Appendix A Principles of data-oriented programming 333(31)
Appendix B Generic data access in statically-typed languages 364(17)
Appendix C Data-oriented programming: A link in the chain of programming paradigms 381(6)
Appendix D Lodash reference 387(4)
Index 391
Yehonathan Sharvit has over twenty years experience as a software engineer, programming with C++, Java, Ruby, JavaScript, Clojure and ClojureScript. He currently works as a software architect at Cycognito building software infrastructures for high scale data pipelines. He writes about software engineering at his blog, speaks at conferences, and leads Clojure workshops around the world.