The Either monad: we can finally get rid of exceptions

Jessica Kerr recently wrote on the very interesting topic: what the best way to get rid of exceptions and of the mess they introduce into the program flow.
Simply put, she's gently introduced the Either monad in Scala language.
Although I find Scala to be a very advanced OO language with reasonably good FP support, I don't think the code Jessica used in her post can force anybody to change the habitual exception handling flow in favor of the Data Flow. This's why: Scala is too verbose.
But this is not the case in a more advanced functional language like OCaml, Haskell or F#. Let's take a look what the latter can offer:

The code is much more clear because of using the monadic function composition (>=>) and the amazing type inference.
Conclusion: if you do use monands, use their full power.

Comments

Post a Comment

Popular posts from this blog

Haskell: performance

It turned out that it's not Haskell who was slow in my previous Fibonacci test. It was my lack of Haskell knowledge. Haskell has two integral types - Int, which has bounds -2147483648..2147483647 and Integer, which is unbounded. Both types implement Integral type class, so out fib function can be defined in terms of this type class: OK, now we can test performance of the function parametrizing it with the two concrete types. Integer first: We get our previous result ~15 seconds which is rather slow. Now test it with Int type: Whoa! The Int type is ~6 times faster than Integer! And with result of 2.8 seconds Haskell's took the third position in our small rating :) Current list (in seconds): C# - 1.26 F# - 1.38 Nemerle - 1.45 Haskell - 2.8 Clojure - 9 Erlang - 17 Ruby - 60 Python - 120
Read more

Regular expressions: Rust vs F# vs Scala

Image
Let's implement the following task: read first 10M lines from a text file of the following format: then find all lines containing Microsoft namespace in them, and format the type names the usual way, like "Microsoft.Win32.IAssemblyEnum". First, F#: Now Rust: After several launches the file was cached by the OS and both implementations became non IO-bound. F# one took 29 seconds and 31MB of RAM at peak; Rust - 11 seconds and 18MB. The Rust code is as twice as long as F# one, but it's handling all possible errors explicitly - no surprises at runtime at all. The F# code may throw some exceptions (who knows what kind of them? Nobody). It's possible to wrap all calls to .NET framework with `Choice.attempt (fun _ -> ...)`, then define custom Error types for regex related code, for IO one and a top-level one, and the code'd be even longer then Rust's, hard to read and it would still give no guarantee that we catch all possible exceptions. Up
Read more

STM: F# vs Haskell

STM is a very nice parallel programming model used intensively in Haskell and Clojure. There's a F# implementation which can be found in FSharpx library. Today I'm going to test performance of both the Haskell and the F# STMs. The test is very simple - read a couple TVars, check their equality, then write them back incremented by 1, repeat a million times. First, the Haskell code: So, it took about 170 ms. OK, now F#: It took about 1,6 seconds which is an order of magnitude slower than the Haskell result. It's rather frustrating.
Read more