On my TODO list next is to hook up the various O(x)Caml memory profiling tools: we have statmemprof which does statistical sampling, and then the runtime events buffer, and (hopefully) stack activity in OxCaml's case from the compiler.
This provides a pretty good automation loop for a performance optimising coding agent: it can choose between heap vs local, or copy vs reference, or fixed layout (for SIMD) vs fragmentation (for multicore NUMA) depending on the tasks at hand.
Some references:
- Statmemprof in OCaml : https://tarides.com/blog/2025-03-06-feature-parity-series-st...
- "The saga of multicore OCaml" by Ron Minsky about how Jane Street viewed performance optimisation from the launch of OCaml 5.0 to where they are today with OxCaml https://www.youtube.com/watch?v=XGGSPpk1IB0
That's exactly what substructural logic/type systems allows you to do. Affine and linear types are one example of substructural type systems, but you can also go further in limiting moves, exchanges/swaps etc. which helps model scenarios where allocation and deallocation must be made explicit.
> I am also deeply sick and tired of maintaining large Python scripts recently, and crave the modularity and type safety of OCaml.
I can totally relate. Switching from Python to a purely functional language can feel like a rebirth.
Meanwhile, in Python, I just haven't figured out how to effectively do the same (even with uv ruff and other affordances) without writing a ton of tests. I'm sure it's possible, but OCaml's spoilt me enough that I don't want to have to learn it any more :-)
In my experience, "purely functional" always means "you can express pure functions on the type level" (thus guaranteeing that it is referentially transparent and has no side effects) -- see https://en.wikipedia.org/wiki/Pure_function
Without strict settings, it will let you pass this value as of any other type and introduce a bug.
But with strict settings, it will prevent you from recovering the actual type dynamically with type guards, because it flags the existence of the untyped expression itself, even if used in a sound way, which defeats the point of using a gradual checker.
Gradual type systems can and should keep the typed fragment sound, not just give up or (figuratively) panic.
In my experience "almost" is doing a lot of heavy lifting here. Typing in python certainly helps, but you can never quite trust it (or that the checker detects things correctly). And you can't trust that another developer didn't just write `dict` instead of `dict[int, string]` somewhere, which thus defaults to Any for both key and value. And that will type check (at least with mypy) and now you lost safety.
Using a statically typed language like C++ is way better, and moving to a language with an advanced type system like that of Rust is yet another massive improvement.
Although I've found that much of the pain of static type checks in Python is really that a lot of popular modules expose incorrect type hints that need to be worked around, which really isn't a pleasant way to spend one's finite time on Earth.
It's too difficult right now to directly jump to the functional version since I don't understand the flambda2 compiler well enough to predict whta optimisations will work! OxCaml is stabilising more this year so that should get easier in time.
When I learnt FP, the choice was between Lisp, Scheme, Miranda, Caml Light and Standard ML, depending on the assignment.
Nowadays some folks consider FP === Haskell.
let parse_int64 (local_ buf) (sp : span) : int64# =
let mutable acc : int64# = #0L in
let mutable i = 0 in
let mutable valid = true in
while valid && i < I16.to_int sp.#len do
let c = Bytes.get buf (I16.to_int sp.#off + i) in
match c with
| '0' .. '9' ->
acc <- I64.add (I64.mul acc #10L) (I64.of_int (Char.code c - 48));
i <- i + 1
| _ -> valid <- false
done;
acc