Polymorphism and testing

David Wagner

Recently I contributed a retry functionality to the cache-s3 Haskell project. After I had shared a draft PR with Alexey Kuleshevich, the project’s maintainer, he suggested some improvements. In this post I describe a simplified version of the resulting upstream pull-request and explain how it works.

Retrying in case of failure

Retrying is a simple error recovery algorithm. Communicating software components regularly experience network failures. If the network outage is intermittent, retransmitting the data shortly after a failing transfer may succeed. Thus, reducing the apparent error rate of the subsystem.

cache-s3 is used by continuous integration (CI) systems for storing a compilation cache database in an S3 bucket. Typically, a successful build is followed by the upload of the cache database, so that it can be reused by the next build. If the database upload fails the CI system fails the whole build task. This is annoying when you waited a long time for your build, but now you have no build and nor a saved cache database. You have to start everything again…

Instead, if the upload to the bucket is retried a couple of times the intermittent network problem is completely hidden from the user.

Give me an integer

In cache-s3 a complex HTTP request is retried, in this post I’m using a simpler example. The action we will retry is a question: we ask the user for an integer:

question :: IO (Maybe Int)
question = do
  putStr "Give me an integer: "
  readMaybe <$> getLine

This function returns Nothing if the user enters anything but an integer.

GHCI> question
Give me an integer: 5
Just 5

GHCI> question
Give me an integer: FOO

If this question is a part of a longer quiz we let the user guess again before we fail the whole program. We would like to write a function retry with the following type signature:

retry :: Int -> IO (Maybe a) -> IO (Maybe a)

This function takes two arguments: the number of times to retry and the action to run. It returns a more perseverant action with the retry logic “baked-in”. In other words the retry alters the action’s runtime behavior, but it doesn’t change its type.

retry will operate like this:

GHCI> retry 3 question
Give me an integer: text
Retrying 1/3
Give me an integer: 5.5
Retrying 2/3
Give me an integer: 5
Just 5

In this example, after the second additional attempt the integer’s was finally received.

Implementing retry

Here’s an implementation of retry:

  :: Int -- ^ number of times to retry
  -> IO (Maybe a) -- ^ action to retry
  -> IO (Maybe a)
retry n action = action >>= go 1                             -- ①
    go i (Just res) = return (Just res)                      -- ②
    go i Nothing                                             -- ③
      if i > n
        then return Nothing                                  -- ④
        else do
          putStrLn $ "Retrying " <> show i <> "/" <> show n  -- ⑤
          res' <- action                                     -- ⑥
          go (i + 1) res'                                    -- ⑦

This function uses a recursive inner function, called go by convention.

  1. The provided action is executed and its result is passed to go
  2. The action succeeded, just return its result
  3. The action failed, try again
  4. If limit is reached we return Nothing
  5. Otherwise inform the user about the retry in progress
  6. Re-execute the action
  7. Pass the result to the next iteration of go

In real code we’d wait a bit before step ⑥ , but now I’m skipping this. You can load this function into an interactive session and try how it works. You should see an output similar to that in the previous section.

Notice that retry is polymorphic in the action’s return type a. In the function’s body we don’t manipulate this value at all, therefore a can stand for any type.

Let’s develop an automatic test for this function and convince ourselves and our colleagues that this function really does what it’s supposed to do. The bad news is that in its current shape this function is hard to test because it’s doing too much IO operations.

Next, we are going to make retry more polymorphic and more testable.

Make it more polymorphic

The problem with the first implementation is the appearance of IO. We need to get rid of that. Notice that in the function’s body we don’t do abitrary IO operation but really just calling putStrLn as a logging function. The appearance of the bind (>>=) operator tells us that we exploit that IO is a monad.

Inspired by these two observations we replace IO with a generic m type constructor with two constraints:

retry :: (Monad m, HasLogFunc m) => Int -> m (Maybe a) -> m (Maybe a)

The Monad typeclass is part of the Prelude (“built-in”). We define the HasLogFunc class ourselves:

class HasLogFunc m where
  logInfo :: String -> m ()

instance HasLogFunc IO where
  logInfo = putStrLn

The first two lines defines the HasLogFunc as an interface where logInfo must be implemented. The last two lines provide IO with an instance of this interface: the implementation of logInfo is just putStrLn.

With the following modifications we obtain to a more generic form of retry:

retry ::
     (Monad m, HasLogFunc m)                                -- ①
  => Int         -- ^ number of times to retry
  -> m (Maybe a) -- ^ action to retry                       -- ②
  -> m (Maybe a)

-- same code as before

          logInfo $ "Retrying " <> show i <> "/" <> show n  -- ③

-- same code as before
  1. Two constraints restrict what m can be: it must be a monad and must have a log function
  2. Instead of IO-only, the function operates on generic actions of m
  3. We replace putStrLn with logInfo which is available in HasLogFunc environment

This version works exactly the same as the first attempt because IO is a monad and we took care of its HasLogFunc instance.

More polymorphic, more testable

This new version of retry is more testable because in our test code we are free to use any m (given it satisfies the constraints we imposed) to express our assertions. To demonstrate this let’s test if the right sequence of error messages are displayed to the user. For example, if we had an action which always fails:

alwaysFails :: FakeAction (Maybe String)
alwaysFails = return Nothing

We’d expect retries until the specified number of attempts is exhausted.

We want our tests to be pure therefore, instead of using IO, we implement a FakeAction type using the Writer monad:

type FakeAction = Writer [String]

This is a monad which aggregates the log messages of type String. We specify what logInfo means in this context:

instance HasLogFunc FakeAction where
  logInfo msg = tell [msg]

Now we can express the always failing scenario:

describe "retry" $ do
  it "gives up after the specified time" $
    runWriter (retry 3 alwaysFails) `shouldBe`
    ( Nothing
    , [ "Retrying 1/3"
      , "Retrying 2/3"
      , "Retrying 3/3"

runWriter returns the result of the provided action, in this case Nothing, paired up with the log messages which were produced during the evaluation. FakeAction is pure, it doesn’t do any IO, but it helps us to test retrys behavior.

This testing strategy can be further extended to cover other types of effects. In the complete code samples on GitHub you’ll see how I implemented exponential back-off: in production retry waits some seconds before it re-executes the action, however the test code is pure, running fast without any side-effects.


In this post I presented a simplified version of this pull-request which adds a simple retry mechanism to cache-s3.

I showed that we can make a function more testable by making it a more generic. Polymorphism allows us to inject test points into our function. This is often achieved by mocks and fakes in traditional programming languages. In Haskell exploiting polymorphism is particularly elegant because we can code against powerful, abstract interfaces such as the monad.

The code is available on GitHub.