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fsharp-performance-types

Coding & development

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Updated 11-09 10:43

About this skill

F# performance types

Agents write F# collection code that makes several passes, allocates on each element, or uses a tree where a hash table fits. The compiler accepts this code. Human reviewers then ask for changes. Review evidence ranks collection efficiency among the strongest categories of human comments on agent F# code.

For readable shape (records, match, no let mutable accumulators), use fsharp-idiom-review. This skill does not repeat it. Use this skill only for code that a measurement shows to be hot, or that a reviewer or task names as hot. Outside a hot path, prefer the readable form.

Rules

Collections. references/COLLECTIONS.md has the choice table and examples.

  • Iterate an F# list with for, List.fold, or pattern matching. Do not index it, and do not copy it to an array only to loop over it.
  • Do not enumerate a seq more than once. Each enumeration runs the source again. Materialize it once, or compute all results in one pass.
  • Do not use @ or List.append in a loop. Cons onto the head and call List.rev once, or fill a ResizeArray.
  • In a hot loop that updates a table, use a local Dictionary or HashSet. Map.add allocates a new tree path on each update, and Map.tryFind allocates a Some on each hit. Return an immutable result at the end if the contract requires one. A Dictionary uses .NET equality: pass HashIdentity.Structural when the key needs F# structural equality, for example an array key.
  • Keep the order that the contract defines. List.sort, Array.sort, Map, and Set order strings by ordinal. Array.Sort, List<T>.Sort, and SortedDictionary use the current culture unless you pass StringComparer.Ordinal.
  • For a lookup table that is built once and read many times, use FrozenDictionary or FrozenSet.

Single pass.

  • Replace a filter |> map |> length chain over large input with one fold or one loop that computes every result.
  • Track the previous value in the loop instead of List.pairwise or Seq.windowed, which allocate a tuple or an array for each element.
  • Use Array.Parallel only when the work for each element is large compared with the cost of a task, and measure it.

Value types. references/VALUE-TYPES.md has the costs and the exceptions.

  • In a hot loop, return voption instead of option, and mark a partial active pattern [<return: Struct>].
  • Use struct (a, b) for a tuple that a non-inlined function returns in a hot loop, and for a Dictionary key. A reference tuple key allocates on each lookup.
  • Do not use a struct tuple as a sortBy key. F# generic comparison boxes it on each comparison. Use sortWith with String.CompareOrdinal or compare on each field.
  • Use [<Struct>] for a small record or union of a few primitive fields. Do not use a struct for a large value, for a value stored as obj or an interface, or for a value that you change through a copy.

Allocation.

  • Do not allocate on each element in a hot loop: no Some, tuple, closure, list cell, substring, or boxed value for each element.
  • Do not call sprintf in a hot loop. Use StringBuilder.Append or String.Concat with ToString(format, CultureInfo.InvariantCulture). sprintf and %.3f holes use the invariant culture. ToString("F3") and {x:F3} holes use the current culture, so the output changes on a machine with a comma decimal separator.
  • Do not build a string with + in a loop or a fold. Use one StringBuilder.
  • Use inline collection functions such as Array.sumBy instead of Array.filter |> Array.length. Mark your own small higher-order helper inline only when a measurement shows the closure cost.

Measurement. references/MEASURE.md has a harness and a BenchmarkDotNet setup.

  • Measure allocated bytes with GC.GetAllocatedBytesForCurrentThread() around one warm call in a Release build. Measure time as the median of several runs.
  • Compare before and after on the same input size as production. Report the numbers, not a claim.

Steps

  1. Find the hot functions. Build a production-size input and measure the allocated bytes and the median time of one call of each. Done when you have a number for each function.
  2. List each extra pass, each repeated seq enumeration, each @ or index in a loop, each Map or Set update in a loop, and each allocation for each element.
  3. Rewrite each item with the rules above. Keep the public types and signatures.
  4. Check that the output is the same as before on the same inputs, under a culture with a comma decimal separator such as de-DE, with strings that differ only in case, and with a single -0.0 value.
  5. Measure again with the same harness. Report the numbers before and after. If an item does not change the numbers, revert it to the readable form.

Verify

Run the proof script from the skill root:

pwsh ./scripts/run.ps1

The script runs in dotnet fsi --optimize+. It measures the allocation, order, and culture claims of this skill with GC.GetAllocatedBytesForCurrentThread(), a run count, or a time ratio. It fails when a measured result differs from the claim. The FrozenDictionary, ImmutableArray, and Array.Parallel advice comes from the .NET documentation, and the script does not measure it.