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Within LTS Haskell 24.28 (ghc-9.10.3)

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  1. mapMonotonic :: (Interval k2 e, Ord k2) => (k1 -> k2) -> IntervalSet k1 -> IntervalSet k2

    IntervalMap Data.IntervalSet

    O(n). mapMonotonic f s == map f s, but works only when f is strictly monotonic. That is, for any values x and y, if x < y then f x < f y. The precondition is not checked.

  2. mappedText :: [(Text, a)] -> String a

    aeson-value-parser AesonValueParser

    No documentation available.

  3. mapConcurrentlyBatched :: (NFData b, Foldable t) => Int -> ([[b]] -> IO r) -> (a -> IO b) -> t a -> IO r

    async-extra Control.Concurrent.Async.Extra

    Span green threads to perform N (batch size) tasks in one thread and merge results using provided merge function

  4. mapConcurrentlyBatched_ :: Foldable t => Int -> (a -> IO ()) -> t a -> IO ()

    async-extra Control.Concurrent.Async.Extra

    Span green threads to perform N (batch size) tasks in one thread and ignore results

  5. mapConcurrentlyBounded :: Traversable t => Int -> (a -> IO b) -> t a -> IO (t b)

    async-extra Control.Concurrent.Async.Extra

    Span a green thread for each task, but only execute N tasks concurrently.

  6. mapConcurrentlyBounded_ :: Traversable t => Int -> (a -> IO ()) -> t a -> IO ()

    async-extra Control.Concurrent.Async.Extra

    Span a green thread for each task, but only execute N tasks concurrently. Ignore the result

  7. mapConcurrentlyChunks :: (NFData b, Foldable t) => Int -> ([[b]] -> IO r) -> (a -> IO b) -> t a -> IO r

    async-extra Control.Concurrent.Async.Extra

    Split input into N chunks with equal length and work on each chunk in a dedicated green thread. Then merge results using provided merge function

  8. mapConcurrentlyChunks_ :: Foldable t => Int -> (a -> IO ()) -> t a -> IO ()

    async-extra Control.Concurrent.Async.Extra

    Split input into N chunks with equal length and work on each chunk in a dedicated green thread. Ignore results

  9. mapConcurrently :: Traversable t => TaskGroup -> (a -> IO b) -> t a -> IO (t b)

    async-pool Control.Concurrent.Async.Pool

    maps an IO-performing function over any Traversable data type, performing all the IO actions concurrently, and returning the original data structure with the arguments replaced by the results. For example, mapConcurrently works with lists:

    pages <- mapConcurrently getURL ["url1", "url2", "url3"]
    

  10. mapRace :: Foldable t => TaskGroup -> t (IO a) -> IO (Async a, Either SomeException a)

    async-pool Control.Concurrent.Async.Pool

    Execute a group of tasks, but return the first result or failure and cancel the remaining tasks.

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