Polyglot and functional (Devoxx Nov/2011)


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Part 2/3 of our Devoxx University session. A discussion of functional programming and polyglot programming on the JVM for the Java developer!

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  • \n
  • It’s always worth repeating a bad joke\n
  • Explain what polyglot means\n
  • Do yourself a favour and get a JRebel license if you web hack in Java\n
  • Learning non-Java languages will make you a better programmer\n
  • Java confuses matters as it’s.... both\nStatic types can be resolved at compile time for example\n\n
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  • Intro the web dev slides. “One major use case for poly is web dev.”\nHands up if you do Struts or JSF. Hands up if you like it.\n
  • Upcoming 20 bullet point slide\n
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  • Actually I can talk to the start-up story here - MV\n\n\n
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  • So, we have 2 sources of data, and we want to check whether the same elements appear in each. We need two loops to do this - as there are 3 cases - id is OK, id only appears in source, and only in DB\n
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  • If you’ve ever found yourself writing collections code and getting frustrated because there’s a method which almost provides a way to do\nwhat you need, but you just need to tweak it slightly, then that frustration is an itch is could be scratched by functional programming.\n
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  • So, we’ve come at this a different way - we started out by saying that we need to pass in function values to customize functions. This is what’s called “higher-order functions”. This is a different approach.\n
  • Of course, this method doesn’t really exist. That’s why Eclipse has red-underlined it.\n
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  • Let’s show a bit more context, and show how the reconcile() method gets called. DBInfo is the type which was actually returned from the DB lookup\nAlso, another slightly sneaky trick is in the call to reconcile() – we pass the returned List from extractPrimaryKeys() into the constructor for HashSet to convert it to a Set. This handily de-dups the List for us, making the contains() call more compact in the reconcile() method.\n
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  • Notice the “defensive copy”. We return a new List. \nWe don’t mutate the existing List (so once again the filter() form behaves like a mathematical function). \nWe build up a new List by testing each element against a function which returns boolean. \nIf the result of testing an element is true, we add it into the output List.\n
  • Predicate is the jargon for the returns-boolean testing function that we apply to each element in turn.\n\n
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  • Polyglot and functional (Devoxx Nov/2011)

    1. 1. The WGJD - Polyglot &Functional Programming Ben Evans and Martijn Verburg (@kittylyst @karianna) http://www.teamsparq.net Slide Design by http://www.kerrykenneally.com
    2. 2. This is still not an Oracle legal slide 2
    3. 3. Polyglot and Functional - Why is it important?• The WGJD wants to code rapidly• The WGJD wants to code concisely• The WGJD wants to take advantage of: – The JVM – Non Object-Orientated approaches – Dynamic language approaches• Polyglot and functional languages exist on the JVM – The JVM is no longer tied to Java the language 3
    4. 4. Why Java is not a Golden Hammer• Recompilation is laborious• Static typing can be inflexible – Can lead to long refactoring times• Deployment is a heavyweight process – JRebel can mitigate this for web apps• Javas syntax is not a natural fit for producing DSLs 4
    5. 5. Java is a conservative language• New language features take a while to arrive in Java• This is deliberate• Languages which try to move quickly can “repent at leisure” – There are some features in Scala which everyone now regrets• Non-Java languages are a test-bed for features – A good place to learn and experiment 5
    6. 6. Language Zoology• Interpreted vs. Compiled – Interpreted source code is executed as-is – Compiled code is converted to machine code before execution• Dynamic vs. static – Dynamic variables can have different types at different times – Dynamic types are only resolved at execution time – Static types can be resolved much earlier• Imperative vs. functional – OO and Procedural are both imperative styles – Imperative: Code operates on Data – Functional: Code & Data are one and the same 6
    7. 7. Languages on the JVM• There are now over 200, falling into several broad groupings• Language re-implementations – JRuby, Jython• Attempted Java killers – Fantom, Ceylon, Xtend, Scala• Dynamic languages – Groovy, Rhino, Clojure• Academic – Ioke, Seph 7
    8. 8. Polyglot Programming Pyramid• Courtesy of Ola Bini 8
    9. 9. Ola - JVM languages expert? Meh, do not talk to him 9
    10. 10. Polyglot Layers• Domain-specific – Tightly coupled to a specific part of the application domain. – e.g. Apache Camel DSL, Drools, Web templating• Dynamic – Rapid, productive, flexible development of functionality – e.g. Groovy, Jython, Clojure• Stable – Core functionality, stable, well-tested, performant. – e.g. Java, Scala 10
    11. 11. Questions to ask yourself before going Poly• Is the project area low risk?• How easily does the language interoperate with Java?• What tooling support is there for the language? – e.g. IDE support• How easy is it to build, test & deploy in this language?• How steep is the learning curve for this language?• How easy is it to hire developers for this language? 11
    12. 12. Experts: “use < 5 bullet points”We have a fr&%!en movie screen! 12
    13. 13. Case Study: Rapid Web Development• Matt Raible - 20 criteria for a web framework • Developer Productivity • Developer Perception • Learning Curve • Project Health • Developer Availability • Job Trends • Templating • Components • Ajax • Plugins or Add-Ons • Scalability • Testing Support • i18n and l10n • Validation • Multi-language Support • Quality of Documentation/Tutorials • Books Published • REST Support (client and server) • Mobile / iPhone Support • Degree of Risk 13
    14. 14. JVM language web framework shoot out• Grails Wins!• http://bit.ly/jvm-frameworks-matrix 14
    15. 15. Functional Programming• Show a Java-centric approach to Functional Programming (FP)• Focus on what’s missing & how we would want it to work in Java• Example-driven• Make the connection to other languages (especially Scala) 15
    16. 16. Example - Reconciliation Service• We have 2 sources of data• Source 1 - The upstream system “sourceData” – e.g Call a web service for transaction records• Source 2 - The downstream database• We need a reconciliation system – Check that data is actually reaching the DB. 16
    17. 17. Reconciliation - Java Take 1 17
    18. 18. Output of Reconciliation - Java Take 1• 7172329 OK• 7173341 OK• 1R6GT OK• 1R6GV OK• 1R6GW OK• main_ref: 1R6H2 not present in DB• main_ref: 1R6H3 not present in DB• 1R6H6 OK• 623SRC OK 18
    19. 19. Analysing the data• What’s gone wrong?• The answer is that upstream system is case-insensitive – Whereas the downstream one is case-sensitive• 1R6H2 is present in the DB – It’s just called 1r6h2 instead• Let’s go back to the code slide – Can anyone see a problem with the code now?• There’s no containsCaseInsensitive() method – This is an irritant 19
    20. 20. Reconciliation - Fixing Case SensitivityWith this: 20
    21. 21. Introducing Functional Concepts• This are two ideas related to FP in the previous example• First idea is: – Operating on collections / data structures as a whole – Rather than explicitly iterating over their contents• Second idea is: – A lack of capability to add additional logic to existing methods• Both ideas help with writing concise, safer OO code 21
    22. 22. What if we could...• Suppose we could tweak the functionality of a method by adding in some new code of our own.• We’d need to pass the code into the method as a parameter.• We need some way to treat a code blob as though it was a value – Want to be able to put it into a variable.• FP requires the ability to represent bits of logic as though they were values. 22
    23. 23. Reconciliation - With Match FunctionImaginary FP-in-Java syntax: 23
    24. 24. Library Support• There’s no actual 2-parameter contains() method.• But that’s what we would want, if we could start again• Other languages have this functionality• Called: Lambda expressions, closures, function literals• Need to have library support as well as the language primitive 24
    25. 25. “What if” is for namby pamby dreamers 25
    26. 26. FP Map Pattern• FP fans would call this a map() expression – extractPrimaryKeys() takes a List and returns a new List – Run an operation on each element in turn (and return the new list we built up). 26
    27. 27. FP - More on the Map Pattern• Note that the type contained in the returned List may be different from the incoming List. – Incoming type is DBInfo, outgoing is String – The original List hasn’t been affected in any way.• This is where the name “functional programming” comes from – The functions behave like mathematical functions• A function like f(x) = x * x doesn’t alter the value 2 when it’s passed in. Instead, it returns a different value, 4. 27
    28. 28. FP - The Filter Pattern• The use of map() is an absolutely classic FP idiom.• It’s usually paired with this well-known pattern, the filter() form. 28
    29. 29. Functions-as-values• Now we can see the construct that we need for function-as-value. – We need some way to represent that “predicate function” for filter()• Here’s one way we could write it (in almost-Scala): (msg) -> { !msg.get("status").equalsIgnoreCase("CANCELLED") };• This is a function which takes one argument – msg is a Map<String, String> – The function returns boolean• Actually, this is also how Java 8 is going to write it. – In fact this is a very Java-ish way of writing Scala • but that’s deliberate 29
    30. 30. There you go Scala folks!We finally gave you some props It’s the last time 30
    31. 31. What We Didn’t Have Time To Talk About• Why functional is good for modern concurrency – That’s in the next hour!• The myriad academic definitions of closures• Groovy in depth• Clojure• What Java 8 JVM changes mean for other languages – Jigsaw could be a major opportunity or a headache 31
    32. 32. What? You still here?Go take a break will you! 32