Writing DSL's in Scala
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Scala is well-suited for building internal domain-specific languages (DSLs) due to its functional programming capabilities and static typing. Some key advantages of using Scala for DSLs include its elegant and succinct syntax, type inference, implicit conversions, higher-order functions, pattern matching, and for-comprehensions. These features allow building DSLs that are concise yet expressive for the domain and prevent invalid operations. The document provides examples of using Scala to build DSLs for tasks like defining cloud computing resources and processing machine specifications.
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Writing DSL's in Scala
- 1. Using Scala for building DSL’s Abhijit Sharma Innovation Lab, BMC Software 1
- 2. What is a DSL? • Domain Specific Language • Appropriate abstraction level for domain - uses precise concepts and semantics of domain • Concise and expressive for a specific domain – not general purpose • Domain experts can communicate, critique better with programmers and amongst themselves • Math – Mathematica, UI – HTML, CSS, Database - SQL 2
- 3. DSL’s at large - Ant • Build tool Ant is an XML based DSL • Task to build a jar with a dependency on task compile 3
- 4. DSL’s at large – RoR ActiveRecord • Web App framework Ruby on Rails • ActiveRecord to model domain objects and persist them – • Domain constraint implementations do not clutter API – uniqueness, cardinality, null check 4
- 5. Cloud Computing DSL • Audience – Non tech savvy cloud end users • DSL - English language sentence for requesting a machine with technical and price specifications 5
- 6. Cloud Computing DSL - Model • Domain Concept – Machine • Technical specifications - cpu, os • Pricing specifications - spot price, pricing strategy – default or define inline Machine •cpu:Cpu •os:String •spotPrice:Int Cpu •arch: String •cpus: Int 6
- 7. Cloud Computing Java DSL • Builder pattern - Method Chaining Fluent Interface 7
- 8. Cloud Computing Java DSL - Pattern • Builder Pattern - Method Chaining 8
- 9. Cloud Computing Java DSL - Issues • Syntax restrictions, verbosity – parenthesis, dot, semi- colons • Non Domain complexity – Builder • No Inline strategy – no higher order functions 9
- 10. DSL Classification • Internal DSL • Embedded in a host language like Ruby, Scala, Groovy – use their features • Bound by host language syntax and semantics • External DSL – standalone developed ground up • Define syntax and semantics as a grammar • Use tools like lexical analyzers, parsers, interpretation, code generators 10
- 11. Internal DSL Classification • Internal DSL • Generative - Ruby, Groovy Techniques like runtime metaprogramming • Meta Objects – inject new behaviour at runtime • Embedded in host language • Smart API – Method chaining – Java etc. • Syntax tree manipulation – Groovy, Ruby libraries • Type Embedding – Scala – statically typed, type constraints, no invalid operations on types 11
- 12. Scala Language • Scala is a “scalable” language • JVM based – leverage libs, JVM perf, tools, install base etc • Mixed Paradigm – Object Oriented + Functional Programming • Object Oriented Programming - Improves on Java OOP (Traits, no statics, advanced types) 12
- 13. Scala Language • Functional Programming - Functions • No side effects and immutable variables • “First-class” citizens - Can be assigned, passed around, returned • Higher order functions promote composition using other more primitive functions • Lots of powerful features – discussed later • Statically Typed – Type Safe DSL 13
- 14. Scala – Readable style - Syntax • Elegant, succinct syntax unlike verbose Java • Optional dots, Operators are methods • Syntactic sugar method takes one/zero argument, drop period and parentheses 14
- 15. Scala – Readable style - Inference • Type inference minimizes the need for explicit type information – still Type safe 15
- 16. Scala - Implicits • Implicit Conversions – wrap original type e.g. Integer • Generative expression - Implicit conversion converts the 1, an Int, to a RichInt which defines a ‘to’ method • Lexically scoped – Unlike other languages like Groovy where such modifications are global in scope • Implicit argument to function – don’t need to pass – Concise syntax 16
- 17. Scala - Higher order functions • Functions as parameters or return values • Flexible mechanism for composition • Anonymous Functions 17
- 18. Scala - Higher order functions • Currying – set some parameters – concise & powerful 18
- 19. Scala – Functional Combinators • Calculate the total price of all Linux machines – uses several combinators – filter, map, foldLeft – all take other functions as predicates 19
- 20. Scala – Cloud Computing DSL - Relook 20
- 21. Scala – Cloud Computing DSL - Implicits • Consider excerpt - 8 cpus “64bit” – Using Implicit conversion we get the object representing the CPU - Cpu(8, 64bit) 21
- 22. Scala – Cloud Computing DSL – E2E DSL - new Machine having (8 cpus "64bit") with_os “Linux“ • Implicit Conversion • Method Chaining – Builder pattern – without the cruft • Syntactic sugar no parenthesis, dot, brackets 22
- 23. Scala – Cloud Computing DSL – Functions • Using Higher Order Functions – Flexible pricing • Spot Price Threshold - Inline strategy - Anonymous Functions 23
- 24. Scala - Pattern Matching • Pattern Matching – Switch Case on Steroids • Cases can include value, types, wild-cards, sequences, tuples, deep inspection of objects 24
- 25. Scala - Pattern Matching &Case Classes • Case Classes – simplified construction and can be used in pattern matching • Pattern matching on Case Classes • Deep pattern matching on object contents • Make good succinct powerful DSL 25
- 26. Scala - Pattern Matching – Visitor Pattern • Pattern match and case classes – extensible visitor • Different operations on tree • Expression Evaluation • Prefix Notation • Very expressive, flexible and concise code 26
- 27. Scala – For Comprehensions • Loop through Iterable sequences and comprehend/compute something • E.g. Filter 32, 64 bit architectures 27
- 28. Scala – For Comprehensions + Option • Wrap vars & function returns as Option – Null Checks, resilient programming • Option sub classes : None and Some • Options with for comprehensions, automatic removal of None elements from comprehensions 28
- 29. Scala – For Comprehensions + Option • Validate and audit machines • Using Options with for comprehensions eliminate the need for most “null/empty” checks. • Succinct, safe DSL with uncluttered API 29
- 30. External DSL in Scala DSL - having (8 cpus "64bit") with_os "Linux" at_spot_price 30 • Parser Combinator library – available as a library on host language – Scala • External Parser Generators like JavaCC – use tools to generate code for tokenizing, parsing • Parser Combinator Specification is like a BNF grammar 30
- 31. External DSL in Scala • Each function is a parser - works on a portion of the input, parses it and may optionally pass on the remaining part to the next parser in the chain via the combinator • Several combinators provided by the library like ‘~’ the sequencing combinator composes two parsers sequentially. • Optional function application combinator (^^) can work, applying the function on the result of the sequencing combinator. 31
- 32. Thanks abhijit.sharma@gmail.com Twitter : sharmaabhijit Blog : abhijitsharma.blogspot.com 32
- 33. Scala - Traits • Traits are collections of fields and behaviors that you can extend or mixin to your classes. • Modularize these concerns, yet enable the fine-grained “mixing” of their behaviors with other concerns at build or run time – Callbacks & Ordered • Traits can be mixed-in at class level or at instance creation • AOP Pervasive concerns - Logging, Ordering, Callback Handling 33