An introduction to F# (part 2) Bogdan Brinzarea-Iamandi Banca Romaneasca 25 February 2010

TopicCovered Today History22 february 2010 From imperative to functional22 february 2010 Fundamentals22 february 2010 Data structures22 february 2010 Pattern Matching22 february 2010 Immutability vs. Mutability22 february 2010 Object Oriented Programming22 february 2010 Async and Parallel Programming Unit testing

ProblemSolution I/O bound applicationAsynchronous processing CPU bound applicationParallel and distributed processing Freezing UIAsynchronous processing Sharing stateImmutability

 Working with threads is difficult  Synchronizing and sharing state are difficult  Introducing bugs is easy  The code is complicated

 Multiple active evaluations (threads computing results)  Multiple pending reactions (callbacks and agents waiting for events and messages)

 Not useful for asynchronous operations  Imperative programming  Sharing mutable data between threads  Cancellations  Raising events in the right thread

 Optimization opportunities  Easily transferable between threads  Reliability

 Ease of change  Cancellation checking  Simple resource management  Exception propagation

 Creates async objects  These tasks can be run  In the current thread  In a background thread  In parallel using fork/join mechanism  As continuations

 Takes async objects and creates async tasks  Uses QueueUserWorkItem  Fork/join pattern  Does not report progress seq > -> Async

 Runs synchronous computation  Waits for the result  Batch processing jobs  Matrix multiplication

 Starts and ends in the same thread  Useful for UI updating  Continuations for:  Complete  Exception  Cancellation

 let! for async method calls  The thread is suspended until the result in available  The rest of the code runs as a continuation  use! resource disposing equivalent of let!

 Leverage parallel hardware capabilities  Data parallel programming with PLinq  Easy to implement  Abstracts away complexity  Transparent partition and merge operations  Works on seq and IEnumerable  Task parallel programming using the new Task Parallel Library in.NET 4.0

 Erlang message passing style  “An actor is a computational entity that, in response to a message it receives, can concurrently: ▪ send a finite number of messages to other actors; ▪ create a finite number of new actors; ▪ designate the behavior to be used for the next message it receives.”

 Asynchronous message passing  Can have even 1000 agents  Agents are lightweight  Based on async programming  State isolation between agents  No concurrency and data races

 NUnit  xUnit.net

 FsUnit based on NUnit  FsCheck inspired from Haskell’s QuickCheck  FsTest based on xUnit.net  NaturalSpec based on NUnit  FsSpec readable DSL

 Expert F# by Don Syme  Programming F# by Chris Smith  CTO Corner -  HubFS  Matthew Podwysocki  Don Syme  Chris Smith