cargo: update dependencies

Last of the functions that need to be ported over to strided-ndarray.

Cargo.lock

@@ -126,9 +126,9 @@ checksum = "1fd0f2584146f6f2ef48085050886acf353beff7305ebd1ae69500e27c67f64b"
 
 [[package]]
 name = "cc"
-version = "1.2.3"
+version = "1.2.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "27f657647bcff5394bf56c7317665bbf790a137a50eaaa5c6bfbb9e27a518f2d"
+checksum = "9157bbaa6b165880c27a4293a474c91cdcf265cc68cc829bf10be0964a391caf"
 dependencies = [
  "shlex",
 ]
@@ -559,9 +559,9 @@ checksum = "bbd2bcb4c963f2ddae06a2efc7e9f3591312473c50c6685e1f298068316e66fe"
 
 [[package]]
 name = "libc"
-version = "0.2.167"
+version = "0.2.168"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "09d6582e104315a817dff97f75133544b2e094ee22447d2acf4a74e189ba06fc"
+checksum = "5aaeb2981e0606ca11d79718f8bb01164f1d6ed75080182d3abf017e6d244b6d"
 
 [[package]]
 name = "libloading"
@@ -1004,9 +1004,9 @@ dependencies = [
 
 [[package]]
 name = "redox_syscall"
-version = "0.5.7"
+version = "0.5.8"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9b6dfecf2c74bce2466cabf93f6664d6998a69eb21e39f4207930065b27b771f"
+checksum = "03a862b389f93e68874fbf580b9de08dd02facb9a788ebadaf4a3fd33cf58834"
 dependencies = [
  "bitflags",
 ]
@@ -1089,24 +1089,24 @@ checksum = "94143f37725109f92c262ed2cf5e59bce7498c01bcc1502d7b9afe439a4e9f49"
 
 [[package]]
 name = "semver"
-version = "1.0.23"
+version = "1.0.24"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "61697e0a1c7e512e84a621326239844a24d8207b4669b41bc18b32ea5cbf988b"
+checksum = "3cb6eb87a131f756572d7fb904f6e7b68633f09cca868c5df1c4b8d1a694bbba"
 
 [[package]]
 name = "serde"
-version = "1.0.215"
+version = "1.0.216"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "6513c1ad0b11a9376da888e3e0baa0077f1aed55c17f50e7b2397136129fb88f"
+checksum = "0b9781016e935a97e8beecf0c933758c97a5520d32930e460142b4cd80c6338e"
 dependencies = [
  "serde_derive",
 ]
 
 [[package]]
 name = "serde_derive"
-version = "1.0.215"
+version = "1.0.216"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ad1e866f866923f252f05c889987993144fb74e722403468a4ebd70c3cd756c0"
+checksum = "46f859dbbf73865c6627ed570e78961cd3ac92407a2d117204c49232485da55e"
 dependencies = [
  "proc-macro2",
  "quote",

flake.lock

@@ -2,11 +2,11 @@
   "nodes": {
     "nixpkgs": {
       "locked": {
-        "lastModified": 1731319897,
-        "narHash": "sha256-PbABj4tnbWFMfBp6OcUK5iGy1QY+/Z96ZcLpooIbuEI=",
+        "lastModified": 1733940404,
+        "narHash": "sha256-Pj39hSoUA86ZePPF/UXiYHHM7hMIkios8TYG29kQT4g=",
         "owner": "NixOS",
         "repo": "nixpkgs",
-        "rev": "dc460ec76cbff0e66e269457d7b728432263166c",
+        "rev": "5d67ea6b4b63378b9c13be21e2ec9d1afc921713",
         "type": "github"
       },
       "original": {

nac3artiq/src/codegen.rs

@@ -12,16 +12,17 @@ use pyo3::{
     PyObject, PyResult, Python,
 };
 
+use super::{symbol_resolver::InnerResolver, timeline::TimeFns};
 use nac3core::{
     codegen::{
         expr::{destructure_range, gen_call},
-        irrt::call_ndarray_calc_size,
-        llvm_intrinsics::{call_int_smax, call_memcpy_generic, call_stackrestore, call_stacksave},
+        llvm_intrinsics::{call_int_smax, call_memcpy, call_stackrestore, call_stacksave},
         stmt::{gen_block, gen_for_callback_incrementing, gen_if_callback, gen_with},
-        types::NDArrayType,
+        type_aligned_alloca,
+        types::ndarray::NDArrayType,
         values::{
-            ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayValue, ProxyValue,
-            RangeValue, UntypedArrayLikeAccessor,
+            ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, ProxyValue, RangeValue,
+            UntypedArrayLikeAccessor,
         },
         CodeGenContext, CodeGenerator,
     },
@@ -34,12 +35,14 @@ use nac3core::{
     },
     nac3parser::ast::{Expr, ExprKind, Located, Stmt, StmtKind, StrRef},
     symbol_resolver::ValueEnum,
-    toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, DefinitionId, GenCall},
+    toplevel::{
+        helper::{extract_ndims, PrimDef},
+        numpy::unpack_ndarray_var_tys,
+        DefinitionId, GenCall,
+    },
     typecheck::typedef::{iter_type_vars, FunSignature, FuncArg, Type, TypeEnum, VarMap},
 };
 
-use super::{symbol_resolver::InnerResolver, timeline::TimeFns};
-
 /// The parallelism mode within a block.
 #[derive(Copy, Clone, Eq, PartialEq)]
 enum ParallelMode {
@@ -458,60 +461,49 @@ fn format_rpc_arg<'ctx>(
             let llvm_i1 = ctx.ctx.bool_type();
             let llvm_usize = generator.get_size_type(ctx.ctx);
 
-            let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, arg_ty);
-            let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-            let llvm_arg = NDArrayValue::from_pointer_value(
-                arg.into_pointer_value(),
-                llvm_elem_ty,
-                llvm_usize,
-                None,
-            );
+            let (elem_ty, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, arg_ty);
+            let ndims = extract_ndims(&ctx.unifier, ndims);
+            let dtype = ctx.get_llvm_type(generator, elem_ty);
+            let ndarray = NDArrayType::new(generator, ctx.ctx, dtype, Some(ndims))
+                .map_value(arg.into_pointer_value(), None);
 
-            let llvm_usize_sizeof = ctx
-                .builder
-                .build_int_truncate_or_bit_cast(
-                    llvm_arg.get_type().size_type().size_of(),
-                    llvm_usize,
-                    "",
-                )
-                .unwrap();
-            let llvm_pdata_sizeof = ctx
-                .builder
-                .build_int_truncate_or_bit_cast(
-                    llvm_elem_ty.ptr_type(AddressSpace::default()).size_of(),
-                    llvm_usize,
-                    "",
-                )
-                .unwrap();
+            let ndims = llvm_usize.const_int(ndims, false);
 
-            let dims_buf_sz =
-                ctx.builder.build_int_mul(llvm_arg.load_ndims(ctx), llvm_usize_sizeof, "").unwrap();
+            // `ndarray.data` is possibly not contiguous, and we need it to be contiguous for
+            // the reader.
+            // Turning it into a ContiguousNDArray to get a `data` that is contiguous.
+            let carray = ndarray.make_contiguous_ndarray(generator, ctx);
 
-            let buffer_size =
-                ctx.builder.build_int_add(dims_buf_sz, llvm_pdata_sizeof, "").unwrap();
+            let sizeof_usize = llvm_usize.size_of();
+            let sizeof_usize =
+                ctx.builder.build_int_z_extend_or_bit_cast(sizeof_usize, llvm_usize, "").unwrap();
 
-            let buffer = ctx.builder.build_array_alloca(llvm_i8, buffer_size, "rpc.arg").unwrap();
-            let buffer = ArraySliceValue::from_ptr_val(buffer, buffer_size, Some("rpc.arg"));
+            let sizeof_pdata = dtype.ptr_type(AddressSpace::default()).size_of();
+            let sizeof_pdata =
+                ctx.builder.build_int_z_extend_or_bit_cast(sizeof_pdata, llvm_usize, "").unwrap();
 
-            call_memcpy_generic(
-                ctx,
-                buffer.base_ptr(ctx, generator),
-                llvm_arg.ptr_to_data(ctx),
-                llvm_pdata_sizeof,
-                llvm_i1.const_zero(),
-            );
+            let sizeof_buf_shape = ctx.builder.build_int_mul(sizeof_usize, ndims, "").unwrap();
+            let sizeof_buf = ctx.builder.build_int_add(sizeof_buf_shape, sizeof_pdata, "").unwrap();
 
-            let pbuffer_dims_begin =
-                unsafe { buffer.ptr_offset_unchecked(ctx, generator, &llvm_pdata_sizeof, None) };
-            call_memcpy_generic(
-                ctx,
-                pbuffer_dims_begin,
-                llvm_arg.shape().base_ptr(ctx, generator),
-                dims_buf_sz,
-                llvm_i1.const_zero(),
-            );
+            // buf = { data: void*, shape: [size_t; ndims]; }
+            let buf = ctx.builder.build_array_alloca(llvm_i8, sizeof_buf, "rpc.arg").unwrap();
+            let buf = ArraySliceValue::from_ptr_val(buf, sizeof_buf, Some("rpc.arg"));
+            let buf_data = buf.base_ptr(ctx, generator);
+            let buf_shape =
+                unsafe { buf.ptr_offset_unchecked(ctx, generator, &sizeof_pdata, None) };
 
-            buffer.base_ptr(ctx, generator)
+            // Write to `buf->data`
+            let carray_data = carray.load_data(ctx);
+            let carray_data = ctx.builder.build_pointer_cast(carray_data, llvm_pi8, "").unwrap();
+            call_memcpy(ctx, buf_data, carray_data, sizeof_pdata, llvm_i1.const_zero());
+
+            // Write to `buf->shape`
+            let carray_shape = ndarray.shape().base_ptr(ctx, generator);
+            let carray_shape_i8 =
+                ctx.builder.build_pointer_cast(carray_shape, llvm_pi8, "").unwrap();
+            call_memcpy(ctx, buf_shape, carray_shape_i8, sizeof_buf_shape, llvm_i1.const_zero());
+
+            buf.base_ptr(ctx, generator)
         }
 
         _ => {
@@ -552,6 +544,8 @@ fn format_rpc_ret<'ctx>(
     let llvm_i32 = ctx.ctx.i32_type();
     let llvm_i8_8 = ctx.ctx.struct_type(&[llvm_i8.array_type(8).into()], false);
     let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
 
     let rpc_recv = ctx.module.get_function("rpc_recv").unwrap_or_else(|| {
         ctx.module.add_function("rpc_recv", llvm_i32.fn_type(&[llvm_pi8.into()], false), None)
@@ -572,8 +566,7 @@ fn format_rpc_ret<'ctx>(
 
     let result = match &*ctx.unifier.get_ty_immutable(ret_ty) {
         TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
-            let llvm_i1 = ctx.ctx.bool_type();
-            let llvm_usize = generator.get_size_type(ctx.ctx);
+            let num_0 = llvm_usize.const_zero();
 
             // Round `val` up to its modulo `power_of_two`
             let round_up = |ctx: &mut CodeGenContext<'ctx, '_>,
@@ -599,79 +592,49 @@ fn format_rpc_ret<'ctx>(
                     .unwrap()
             };
 
-            // Setup types
-            let (elem_ty, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, ret_ty);
-            let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-            let llvm_ret_ty = NDArrayType::new(generator, ctx.ctx, llvm_elem_ty);
-
             // Allocate the resulting ndarray
             // A condition after format_rpc_ret ensures this will not be popped this off.
-            let ndarray = llvm_ret_ty.alloca(generator, ctx, Some("rpc.result"));
+            let (dtype, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, ret_ty);
+            let dtype_llvm = ctx.get_llvm_type(generator, dtype);
+            let ndims = extract_ndims(&ctx.unifier, ndims);
+            let ndarray = NDArrayType::new(generator, ctx.ctx, dtype_llvm, Some(ndims))
+                .construct_uninitialized(generator, ctx, None);
 
-            // Setup ndims
-            let ndims =
-                if let TypeEnum::TLiteral { values, .. } = &*ctx.unifier.get_ty_immutable(ndims) {
-                    assert_eq!(values.len(), 1);
+            // NOTE: Current content of `ndarray`:
+            //   - * `data` - **NOT YET** allocated.
+            //   - * `itemsize` - initialized to be size_of(dtype).
+            //   - * `ndims` - initialized.
+            //   - * `shape` - allocated; has uninitialized values.
+            //   - * `strides` - allocated; has uninitialized values.
 
-                    u64::try_from(values[0].clone()).unwrap()
-                } else {
-                    unreachable!();
-                };
-            // Set `ndarray.ndims`
-            ndarray.store_ndims(ctx, generator, llvm_usize.const_int(ndims, false));
-            // Allocate `ndarray.shape` [size_t; ndims]
-            ndarray.create_shape(ctx, llvm_usize, ndarray.load_ndims(ctx));
-
-            /*
-                ndarray now:
-                  - .ndims: initialized
-                  - .shape: allocated but uninitialized .shape
-                  - .data: uninitialized
-            */
-
-            let llvm_usize_sizeof = ctx
-                .builder
-                .build_int_truncate_or_bit_cast(llvm_usize.size_of(), llvm_usize, "")
-                .unwrap();
-            let llvm_pdata_sizeof = ctx
-                .builder
-                .build_int_truncate_or_bit_cast(
-                    llvm_elem_ty.ptr_type(AddressSpace::default()).size_of(),
-                    llvm_usize,
-                    "",
-                )
-                .unwrap();
-            let llvm_elem_sizeof = ctx
-                .builder
-                .build_int_truncate_or_bit_cast(llvm_elem_ty.size_of().unwrap(), llvm_usize, "")
-                .unwrap();
+            let itemsize = ndarray.load_itemsize(ctx); // Same as doing a `ctx.get_llvm_type` on `dtype` and get its `size_of()`.
 
             // Allocates a buffer for the initial RPC'ed object, which is guaranteed to be
             // (4 + 4 * ndims) bytes with 8-byte alignment
-            let sizeof_dims =
-                ctx.builder.build_int_mul(ndarray.load_ndims(ctx), llvm_usize_sizeof, "").unwrap();
+            let sizeof_usize = llvm_usize.size_of();
+            let sizeof_usize =
+                ctx.builder.build_int_truncate_or_bit_cast(sizeof_usize, llvm_usize, "").unwrap();
+
+            let sizeof_ptr = llvm_i8.ptr_type(AddressSpace::default()).size_of();
+            let sizeof_ptr =
+                ctx.builder.build_int_z_extend_or_bit_cast(sizeof_ptr, llvm_usize, "").unwrap();
+
+            let sizeof_shape =
+                ctx.builder.build_int_mul(ndarray.load_ndims(ctx), sizeof_usize, "").unwrap();
+
+            // Size of the buffer for the initial `rpc_recv()`.
             let unaligned_buffer_size =
-                ctx.builder.build_int_add(sizeof_dims, llvm_pdata_sizeof, "").unwrap();
-            let buffer_size = round_up(ctx, unaligned_buffer_size, llvm_usize.const_int(8, false));
+                ctx.builder.build_int_add(sizeof_ptr, sizeof_shape, "").unwrap();
 
             let stackptr = call_stacksave(ctx, None);
-            // Just to be absolutely sure, alloca in [i8 x 8] slices to force 8-byte alignment
-            let buffer = ctx
-                .builder
-                .build_array_alloca(
-                    llvm_i8_8,
-                    ctx.builder
-                        .build_int_unsigned_div(buffer_size, llvm_usize.const_int(8, false), "")
-                        .unwrap(),
-                    "rpc.buffer",
-                )
-                .unwrap();
-            let buffer = ctx
-                .builder
-                .build_bit_cast(buffer, llvm_pi8, "")
-                .map(BasicValueEnum::into_pointer_value)
-                .unwrap();
-            let buffer = ArraySliceValue::from_ptr_val(buffer, buffer_size, None);
+            let buffer = type_aligned_alloca(
+                generator,
+                ctx,
+                llvm_i8_8,
+                unaligned_buffer_size,
+                Some("rpc.buffer"),
+            );
+            let buffer = ArraySliceValue::from_ptr_val(buffer, unaligned_buffer_size, None);
 
             // The first call to `rpc_recv` reads the top-level ndarray object: [pdata, shape]
             //
@@ -679,7 +642,7 @@ fn format_rpc_ret<'ctx>(
             let ndarray_nbytes = ctx
                 .build_call_or_invoke(
                     rpc_recv,
-                    &[buffer.base_ptr(ctx, generator).into()], // Reads [usize; ndims]. NOTE: We are allocated [size_t; ndims].
+                    &[buffer.base_ptr(ctx, generator).into()], // Reads [usize; ndims]
                     "rpc.size.next",
                 )
                 .map(BasicValueEnum::into_int_value)
@@ -687,16 +650,14 @@ fn format_rpc_ret<'ctx>(
 
             // debug_assert(ndarray_nbytes > 0)
             if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
+                let cmp = ctx
+                    .builder
+                    .build_int_compare(IntPredicate::UGT, ndarray_nbytes, num_0, "")
+                    .unwrap();
+
                 ctx.make_assert(
                     generator,
-                    ctx.builder
-                        .build_int_compare(
-                            IntPredicate::UGT,
-                            ndarray_nbytes,
-                            ndarray_nbytes.get_type().const_zero(),
-                            "",
-                        )
-                        .unwrap(),
+                    cmp,
                     "0:AssertionError",
                     "Unexpected RPC termination for ndarray - Expected data buffer next",
                     [None, None, None],
@@ -705,49 +666,50 @@ fn format_rpc_ret<'ctx>(
             }
 
             // Copy shape from the buffer to `ndarray.shape`.
-            let pbuffer_dims =
-                unsafe { buffer.ptr_offset_unchecked(ctx, generator, &llvm_pdata_sizeof, None) };
+            // We need to skip the first `sizeof(uint8_t*)` bytes to skip the `pdata` in `[pdata, shape]`.
+            let pbuffer_shape =
+                unsafe { buffer.ptr_offset_unchecked(ctx, generator, &sizeof_ptr, None) };
+            let pbuffer_shape =
+                ctx.builder.build_pointer_cast(pbuffer_shape, llvm_pusize, "").unwrap();
+
+            // Copy shape from buffer to `ndarray.shape`
+            ndarray.copy_shape_from_array(generator, ctx, pbuffer_shape);
 
-            call_memcpy_generic(
-                ctx,
-                ndarray.shape().base_ptr(ctx, generator),
-                pbuffer_dims,
-                sizeof_dims,
-                llvm_i1.const_zero(),
-            );
             // Restore stack from before allocation of buffer
             call_stackrestore(ctx, stackptr);
 
             // Allocate `ndarray.data`.
             // `ndarray.shape` must be initialized beforehand in this implementation
             //   (for ndarray.create_data() to know how many elements to allocate)
-            let num_elements =
-                call_ndarray_calc_size(generator, ctx, &ndarray.shape(), (None, None));
+            unsafe { ndarray.create_data(generator, ctx) }; // NOTE: the strides of `ndarray` has also been set to contiguous in `create_data`.
 
             // debug_assert(nelems * sizeof(T) >= ndarray_nbytes)
             if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
-                let sizeof_data =
-                    ctx.builder.build_int_mul(num_elements, llvm_elem_sizeof, "").unwrap();
+                let num_elements = ndarray.size(generator, ctx);
+
+                let expected_ndarray_nbytes =
+                    ctx.builder.build_int_mul(num_elements, itemsize, "").unwrap();
+                let cmp = ctx
+                    .builder
+                    .build_int_compare(
+                        IntPredicate::UGE,
+                        expected_ndarray_nbytes,
+                        ndarray_nbytes,
+                        "",
+                    )
+                    .unwrap();
 
                 ctx.make_assert(
                     generator,
-                    ctx.builder.build_int_compare(IntPredicate::UGE,
-                        sizeof_data,
-                        ndarray_nbytes,
-                        "",
-                    ).unwrap(),
+                    cmp,
                     "0:AssertionError",
                     "Unexpected allocation size request for ndarray data - Expected up to {0} bytes, got {1} bytes",
-                    [Some(sizeof_data), Some(ndarray_nbytes), None],
+                    [Some(expected_ndarray_nbytes), Some(ndarray_nbytes), None],
                     ctx.current_loc,
                 );
             }
 
-            ndarray.create_data(ctx, llvm_elem_ty, num_elements);
-
             let ndarray_data = ndarray.data().base_ptr(ctx, generator);
-            let ndarray_data_i8 =
-                ctx.builder.build_pointer_cast(ndarray_data, llvm_pi8, "").unwrap();
 
             // NOTE: Currently on `prehead_bb`
             ctx.builder.build_unconditional_branch(head_bb).unwrap();
@@ -756,7 +718,7 @@ fn format_rpc_ret<'ctx>(
             ctx.builder.position_at_end(head_bb);
 
             let phi = ctx.builder.build_phi(llvm_pi8, "rpc.ptr").unwrap();
-            phi.add_incoming(&[(&ndarray_data_i8, prehead_bb)]);
+            phi.add_incoming(&[(&ndarray_data, prehead_bb)]);
 
             let alloc_size = ctx
                 .build_call_or_invoke(rpc_recv, &[phi.as_basic_value()], "rpc.size.next")
@@ -771,12 +733,13 @@ fn format_rpc_ret<'ctx>(
 
             ctx.builder.position_at_end(alloc_bb);
             // Align the allocation to sizeof(T)
-            let alloc_size = round_up(ctx, alloc_size, llvm_elem_sizeof);
+            let alloc_size = round_up(ctx, alloc_size, itemsize);
+            // TODO(Derppening): Candidate for refactor into type_aligned_alloca
             let alloc_ptr = ctx
                 .builder
                 .build_array_alloca(
-                    llvm_elem_ty,
-                    ctx.builder.build_int_unsigned_div(alloc_size, llvm_elem_sizeof, "").unwrap(),
+                    dtype_llvm,
+                    ctx.builder.build_int_unsigned_div(alloc_size, itemsize, "").unwrap(),
                     "rpc.alloc",
                 )
                 .unwrap();
@@ -1375,62 +1338,50 @@ fn polymorphic_print<'ctx>(
             }
 
             TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
-                let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ty);
-                let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-
                 fmt.push_str("array([");
                 flush(ctx, generator, &mut fmt, &mut args);
 
-                let val = NDArrayValue::from_pointer_value(
-                    value.into_pointer_value(),
-                    llvm_elem_ty,
-                    llvm_usize,
-                    None,
-                );
-                let len = call_ndarray_calc_size(generator, ctx, &val.shape(), (None, None));
-                let last =
-                    ctx.builder.build_int_sub(len, llvm_usize.const_int(1, false), "").unwrap();
+                let (dtype, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ty);
+                let ndarray = NDArrayType::from_unifier_type(generator, ctx, ty)
+                    .map_value(value.into_pointer_value(), None);
 
-                gen_for_callback_incrementing(
-                    generator,
-                    ctx,
-                    None,
-                    llvm_usize.const_zero(),
-                    (len, false),
-                    |generator, ctx, _, i| {
-                        let elem = unsafe { val.data().get_unchecked(ctx, generator, &i, None) };
+                let num_0 = llvm_usize.const_zero();
 
-                        polymorphic_print(
-                            ctx,
-                            generator,
-                            &[(elem_ty, elem.into())],
-                            "",
-                            None,
-                            true,
-                            as_rtio,
-                        )?;
+                // Print `ndarray` as a flat list delimited by interspersed with ", \0"
+                ndarray.foreach(generator, ctx, |generator, ctx, _, hdl| {
+                    let i = hdl.get_index(ctx);
+                    let scalar = hdl.get_scalar(ctx);
 
-                        gen_if_callback(
-                            generator,
-                            ctx,
-                            |_, ctx| {
-                                Ok(ctx
-                                    .builder
-                                    .build_int_compare(IntPredicate::ULT, i, last, "")
-                                    .unwrap())
-                            },
-                            |generator, ctx| {
-                                printf(ctx, generator, ", \0".into(), Vec::default());
+                    // if (i != 0) puts(", ");
+                    gen_if_callback(
+                        generator,
+                        ctx,
+                        |_, ctx| {
+                            let not_first = ctx
+                                .builder
+                                .build_int_compare(IntPredicate::NE, i, num_0, "")
+                                .unwrap();
+                            Ok(not_first)
+                        },
+                        |generator, ctx| {
+                            printf(ctx, generator, ", \0".into(), Vec::default());
+                            Ok(())
+                        },
+                        |_, _| Ok(()),
+                    )?;
 
-                                Ok(())
-                            },
-                            |_, _| Ok(()),
-                        )?;
-
-                        Ok(())
-                    },
-                    llvm_usize.const_int(1, false),
-                )?;
+                    // Print element
+                    polymorphic_print(
+                        ctx,
+                        generator,
+                        &[(dtype, scalar.into())],
+                        "",
+                        None,
+                        true,
+                        as_rtio,
+                    )?;
+                    Ok(())
+                })?;
 
                 fmt.push_str(")]");
                 flush(ctx, generator, &mut fmt, &mut args);

nac3artiq/src/symbol_resolver.rs

@@ -10,12 +10,14 @@ use itertools::Itertools;
 use parking_lot::RwLock;
 use pyo3::{
     types::{PyDict, PyTuple},
-    PyAny, PyObject, PyResult, Python,
+    PyAny, PyErr, PyObject, PyResult, Python,
 };
 
+use super::PrimitivePythonId;
 use nac3core::{
     codegen::{
-        types::{NDArrayType, ProxyType},
+        types::{ndarray::NDArrayType, ProxyType},
+        values::ndarray::make_contiguous_strides,
         CodeGenContext, CodeGenerator,
     },
     inkwell::{
@@ -37,8 +39,6 @@ use nac3core::{
     },
 };
 
-use super::PrimitivePythonId;
-
 pub enum PrimitiveValue {
     I32(i32),
     I64(i64),
@@ -1085,18 +1085,19 @@ impl InnerResolver {
             } else {
                 unreachable!("must be ndarray")
             };
-            let (ndarray_dtype, ndarray_ndims) =
-                unpack_ndarray_var_tys(&mut ctx.unifier, ndarray_ty);
+            let (ndarray_dtype, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ndarray_ty);
 
+            let llvm_i8 = ctx.ctx.i8_type();
+            let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
             let llvm_usize = generator.get_size_type(ctx.ctx);
-            let ndarray_dtype_llvm_ty = ctx.get_llvm_type(generator, ndarray_dtype);
-            let ndarray_llvm_ty = NDArrayType::new(generator, ctx.ctx, ndarray_dtype_llvm_ty);
+            let llvm_ndarray = NDArrayType::from_unifier_type(generator, ctx, ndarray_ty);
+            let dtype = llvm_ndarray.element_type();
 
             {
                 if self.global_value_ids.read().contains_key(&id) {
                     let global = ctx.module.get_global(&id_str).unwrap_or_else(|| {
                         ctx.module.add_global(
-                            ndarray_llvm_ty.as_base_type().get_element_type().into_struct_type(),
+                            llvm_ndarray.as_base_type().get_element_type().into_struct_type(),
                             Some(AddressSpace::default()),
                             &id_str,
                         )
@@ -1106,40 +1107,41 @@ impl InnerResolver {
                 self.global_value_ids.write().insert(id, obj.into());
             }
 
-            let TypeEnum::TLiteral { values, .. } = &*ctx.unifier.get_ty_immutable(ndarray_ndims)
-            else {
-                unreachable!("Expected Literal for ndarray_ndims")
-            };
-
-            let ndarray_ndims = if values.len() == 1 {
-                values[0].clone()
-            } else {
-                todo!("Unpacking literal of more than one element unimplemented")
-            };
-            let Ok(ndarray_ndims) = u64::try_from(ndarray_ndims) else {
-                unreachable!("Expected u64 value for ndarray_ndims")
-            };
+            let ndims = llvm_ndarray.ndims().unwrap();
 
             // Obtain the shape of the ndarray
             let shape_tuple: &PyTuple = obj.getattr("shape")?.downcast()?;
-            assert_eq!(shape_tuple.len(), ndarray_ndims as usize);
-            let shape_values: Result<Option<Vec<_>>, _> = shape_tuple
+            assert_eq!(shape_tuple.len(), ndims as usize);
+
+            // The Rust type inferencer cannot figure this out
+            let shape_values = shape_tuple
                 .iter()
                 .enumerate()
                 .map(|(i, elem)| {
-                    self.get_obj_value(py, elem, ctx, generator, ctx.primitives.usize()).map_err(
-                        |e| super::CompileError::new_err(format!("Error getting element {i}: {e}")),
-                    )
+                    let value = self
+                        .get_obj_value(py, elem, ctx, generator, ctx.primitives.usize())
+                        .map_err(|e| {
+                            super::CompileError::new_err(format!("Error getting element {i}: {e}"))
+                        })?
+                        .unwrap();
+                    let value = value.into_int_value();
+                    Ok(value)
                 })
-                .collect();
-            let shape_values = shape_values?.unwrap();
-            let shape_values = llvm_usize.const_array(
-                &shape_values.into_iter().map(BasicValueEnum::into_int_value).collect_vec(),
-            );
+                .collect::<Result<Vec<_>, PyErr>>()?;
+
+            // Also use this opportunity to get the constant values of `shape_values` for calculating strides.
+            let shape_u64s = shape_values
+                .iter()
+                .map(|dim| {
+                    assert!(dim.is_const());
+                    dim.get_zero_extended_constant().unwrap()
+                })
+                .collect_vec();
+            let shape_values = llvm_usize.const_array(&shape_values);
 
             // create a global for ndarray.shape and initialize it using the shape
             let shape_global = ctx.module.add_global(
-                llvm_usize.array_type(ndarray_ndims as u32),
+                llvm_usize.array_type(ndims as u32),
                 Some(AddressSpace::default()),
                 &(id_str.clone() + ".shape"),
             );
@@ -1147,17 +1149,25 @@ impl InnerResolver {
 
             // Obtain the (flattened) elements of the ndarray
             let sz: usize = obj.getattr("size")?.extract()?;
-            let data: Result<Option<Vec<_>>, _> = (0..sz)
+            let data: Vec<_> = (0..sz)
                 .map(|i| {
                     obj.getattr("flat")?.get_item(i).and_then(|elem| {
-                        self.get_obj_value(py, elem, ctx, generator, ndarray_dtype).map_err(|e| {
-                            super::CompileError::new_err(format!("Error getting element {i}: {e}"))
-                        })
+                        let value = self
+                            .get_obj_value(py, elem, ctx, generator, ndarray_dtype)
+                            .map_err(|e| {
+                                super::CompileError::new_err(format!(
+                                    "Error getting element {i}: {e}"
+                                ))
+                            })?
+                            .unwrap();
+
+                        assert_eq!(value.get_type(), dtype);
+                        Ok(value)
                     })
                 })
-                .collect();
-            let data = data?.unwrap().into_iter();
-            let data = match ndarray_dtype_llvm_ty {
+                .try_collect()?;
+            let data = data.into_iter();
+            let data = match dtype {
                 BasicTypeEnum::ArrayType(ty) => {
                     ty.const_array(&data.map(BasicValueEnum::into_array_value).collect_vec())
                 }
@@ -1182,38 +1192,68 @@ impl InnerResolver {
             };
 
             // create a global for ndarray.data and initialize it using the elements
+            //
+            // NOTE: NDArray's `data` is `u8*`. Here, `data_global` is an array of `dtype`.
+            // We will have to cast it to an `u8*` later.
             let data_global = ctx.module.add_global(
-                ndarray_dtype_llvm_ty.array_type(sz as u32),
+                dtype.array_type(sz as u32),
                 Some(AddressSpace::default()),
                 &(id_str.clone() + ".data"),
             );
             data_global.set_initializer(&data);
 
+            // Get the constant itemsize.
+            let itemsize = dtype.size_of().unwrap();
+            let itemsize = itemsize.get_zero_extended_constant().unwrap();
+
+            // Create the strides needed for ndarray.strides
+            let strides = make_contiguous_strides(itemsize, ndims, &shape_u64s);
+            let strides =
+                strides.into_iter().map(|stride| llvm_usize.const_int(stride, false)).collect_vec();
+            let strides = llvm_usize.const_array(&strides);
+
+            // create a global for ndarray.strides and initialize it
+            let strides_global = ctx.module.add_global(
+                llvm_i8.array_type(ndims as u32),
+                Some(AddressSpace::default()),
+                &format!("${id_str}.strides"),
+            );
+            strides_global.set_initializer(&strides);
+
             // create a global for the ndarray object and initialize it
-            let value = ndarray_llvm_ty
+
+            // NOTE: data_global is an array of dtype, we want a `u8*`.
+            let ndarray_data = data_global.as_pointer_value();
+            let ndarray_data = ctx.builder.build_pointer_cast(ndarray_data, llvm_pi8, "").unwrap();
+
+            let ndarray_itemsize = llvm_usize.const_int(itemsize, false);
+
+            let ndarray_ndims = llvm_usize.const_int(ndims, false);
+
+            let ndarray_shape = shape_global.as_pointer_value();
+
+            let ndarray_strides = strides_global.as_pointer_value();
+
+            let ndarray = llvm_ndarray
                 .as_base_type()
                 .get_element_type()
                 .into_struct_type()
                 .const_named_struct(&[
-                    llvm_usize.const_int(ndarray_ndims, false).into(),
-                    shape_global
-                        .as_pointer_value()
-                        .const_cast(llvm_usize.ptr_type(AddressSpace::default()))
-                        .into(),
-                    data_global
-                        .as_pointer_value()
-                        .const_cast(ndarray_dtype_llvm_ty.ptr_type(AddressSpace::default()))
-                        .into(),
+                    ndarray_itemsize.into(),
+                    ndarray_ndims.into(),
+                    ndarray_shape.into(),
+                    ndarray_strides.into(),
+                    ndarray_data.into(),
                 ]);
 
-            let ndarray = ctx.module.add_global(
-                ndarray_llvm_ty.as_base_type().get_element_type().into_struct_type(),
+            let ndarray_global = ctx.module.add_global(
+                llvm_ndarray.as_base_type().get_element_type().into_struct_type(),
                 Some(AddressSpace::default()),
                 &id_str,
             );
-            ndarray.set_initializer(&value);
+            ndarray_global.set_initializer(&ndarray);
 
-            Ok(Some(ndarray.as_pointer_value().into()))
+            Ok(Some(ndarray_global.as_pointer_value().into()))
         } else if ty_id == self.primitive_ids.tuple {
             let expected_ty_enum = ctx.unifier.get_ty_immutable(expected_ty);
             let TypeEnum::TTuple { ty, is_vararg_ctx: false } = expected_ty_enum.as_ref() else {

nac3core/irrt/irrt.cpp

@@ -2,4 +2,9 @@
 #include "irrt/list.hpp"
 #include "irrt/math.hpp"
 #include "irrt/ndarray.hpp"
+#include "irrt/range.hpp"
 #include "irrt/slice.hpp"
+#include "irrt/ndarray/basic.hpp"
+#include "irrt/ndarray/def.hpp"
+#include "irrt/ndarray/iter.hpp"
+#include "irrt/ndarray/indexing.hpp"

nac3core/irrt/irrt/int_types.hpp

@@ -22,6 +22,6 @@ using uint64_t = unsigned _ExtInt(64);
 #endif
 
 // NDArray indices are always `uint32_t`.
-using NDIndex = uint32_t;
+using NDIndexInt = uint32_t;
 // The type of an index or a value describing the length of a range/slice is always `int32_t`.
 using SliceIndex = int32_t;

nac3core/irrt/irrt/ndarray.hpp

@@ -2,6 +2,8 @@
 
 #include "irrt/int_types.hpp"
 
+// TODO: To be deleted since NDArray with strides is done.
+
 namespace {
 template<typename SizeT>
 SizeT __nac3_ndarray_calc_size_impl(const SizeT* list_data, SizeT list_len, SizeT begin_idx, SizeT end_idx) {
@@ -17,7 +19,7 @@ SizeT __nac3_ndarray_calc_size_impl(const SizeT* list_data, SizeT list_len, Size
 }
 
 template<typename SizeT>
-void __nac3_ndarray_calc_nd_indices_impl(SizeT index, const SizeT* dims, SizeT num_dims, NDIndex* idxs) {
+void __nac3_ndarray_calc_nd_indices_impl(SizeT index, const SizeT* dims, SizeT num_dims, NDIndexInt* idxs) {
     SizeT stride = 1;
     for (SizeT dim = 0; dim < num_dims; dim++) {
         SizeT i = num_dims - dim - 1;
@@ -28,7 +30,10 @@ void __nac3_ndarray_calc_nd_indices_impl(SizeT index, const SizeT* dims, SizeT n
 }
 
 template<typename SizeT>
-SizeT __nac3_ndarray_flatten_index_impl(const SizeT* dims, SizeT num_dims, const NDIndex* indices, SizeT num_indices) {
+SizeT __nac3_ndarray_flatten_index_impl(const SizeT* dims,
+                                        SizeT num_dims,
+                                        const NDIndexInt* indices,
+                                        SizeT num_indices) {
     SizeT idx = 0;
     SizeT stride = 1;
     for (SizeT i = 0; i < num_dims; ++i) {
@@ -75,8 +80,8 @@ void __nac3_ndarray_calc_broadcast_impl(const SizeT* lhs_dims,
 template<typename SizeT>
 void __nac3_ndarray_calc_broadcast_idx_impl(const SizeT* src_dims,
                                             SizeT src_ndims,
-                                            const NDIndex* in_idx,
-                                            NDIndex* out_idx) {
+                                            const NDIndexInt* in_idx,
+                                            NDIndexInt* out_idx) {
     for (SizeT i = 0; i < src_ndims; ++i) {
         SizeT src_i = src_ndims - i - 1;
         out_idx[src_i] = src_dims[src_i] == 1 ? 0 : in_idx[src_i];
@@ -94,21 +99,23 @@ __nac3_ndarray_calc_size64(const uint64_t* list_data, uint64_t list_len, uint64_
     return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
 }
 
-void __nac3_ndarray_calc_nd_indices(uint32_t index, const uint32_t* dims, uint32_t num_dims, NDIndex* idxs) {
+void __nac3_ndarray_calc_nd_indices(uint32_t index, const uint32_t* dims, uint32_t num_dims, NDIndexInt* idxs) {
     __nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
 }
 
-void __nac3_ndarray_calc_nd_indices64(uint64_t index, const uint64_t* dims, uint64_t num_dims, NDIndex* idxs) {
+void __nac3_ndarray_calc_nd_indices64(uint64_t index, const uint64_t* dims, uint64_t num_dims, NDIndexInt* idxs) {
     __nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
 }
 
 uint32_t
-__nac3_ndarray_flatten_index(const uint32_t* dims, uint32_t num_dims, const NDIndex* indices, uint32_t num_indices) {
+__nac3_ndarray_flatten_index(const uint32_t* dims, uint32_t num_dims, const NDIndexInt* indices, uint32_t num_indices) {
     return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
 }
 
-uint64_t
-__nac3_ndarray_flatten_index64(const uint64_t* dims, uint64_t num_dims, const NDIndex* indices, uint64_t num_indices) {
+uint64_t __nac3_ndarray_flatten_index64(const uint64_t* dims,
+                                        uint64_t num_dims,
+                                        const NDIndexInt* indices,
+                                        uint64_t num_indices) {
     return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
 }
 
@@ -130,15 +137,15 @@ void __nac3_ndarray_calc_broadcast64(const uint64_t* lhs_dims,
 
 void __nac3_ndarray_calc_broadcast_idx(const uint32_t* src_dims,
                                        uint32_t src_ndims,
-                                       const NDIndex* in_idx,
-                                       NDIndex* out_idx) {
+                                       const NDIndexInt* in_idx,
+                                       NDIndexInt* out_idx) {
     __nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
 }
 
 void __nac3_ndarray_calc_broadcast_idx64(const uint64_t* src_dims,
                                          uint64_t src_ndims,
-                                         const NDIndex* in_idx,
-                                         NDIndex* out_idx) {
+                                         const NDIndexInt* in_idx,
+                                         NDIndexInt* out_idx) {
     __nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
 }
 }  // namespace

nac3core/irrt/irrt/ndarray/basic.hpp

@@ -0,0 +1,342 @@
+#pragma once
+
+#include "irrt/debug.hpp"
+#include "irrt/exception.hpp"
+#include "irrt/int_types.hpp"
+#include "irrt/ndarray/def.hpp"
+
+namespace {
+namespace ndarray {
+namespace basic {
+/**
+ * @brief Assert that `shape` does not contain negative dimensions.
+ *
+ * @param ndims Number of dimensions in `shape`
+ * @param shape The shape to check on
+ */
+template<typename SizeT>
+void assert_shape_no_negative(SizeT ndims, const SizeT* shape) {
+    for (SizeT axis = 0; axis < ndims; axis++) {
+        if (shape[axis] < 0) {
+            raise_exception(SizeT, EXN_VALUE_ERROR,
+                            "negative dimensions are not allowed; axis {0} "
+                            "has dimension {1}",
+                            axis, shape[axis], NO_PARAM);
+        }
+    }
+}
+
+/**
+ * @brief Assert that two shapes are the same in the context of writing output to an ndarray.
+ */
+template<typename SizeT>
+void assert_output_shape_same(SizeT ndarray_ndims,
+                              const SizeT* ndarray_shape,
+                              SizeT output_ndims,
+                              const SizeT* output_shape) {
+    if (ndarray_ndims != output_ndims) {
+        // There is no corresponding NumPy error message like this.
+        raise_exception(SizeT, EXN_VALUE_ERROR, "Cannot write output of ndims {0} to an ndarray with ndims {1}",
+                        output_ndims, ndarray_ndims, NO_PARAM);
+    }
+
+    for (SizeT axis = 0; axis < ndarray_ndims; axis++) {
+        if (ndarray_shape[axis] != output_shape[axis]) {
+            // There is no corresponding NumPy error message like this.
+            raise_exception(SizeT, EXN_VALUE_ERROR,
+                            "Mismatched dimensions on axis {0}, output has "
+                            "dimension {1}, but destination ndarray has dimension {2}.",
+                            axis, output_shape[axis], ndarray_shape[axis]);
+        }
+    }
+}
+
+/**
+ * @brief Return the number of elements of an ndarray given its shape.
+ *
+ * @param ndims Number of dimensions in `shape`
+ * @param shape The shape of the ndarray
+ */
+template<typename SizeT>
+SizeT calc_size_from_shape(SizeT ndims, const SizeT* shape) {
+    SizeT size = 1;
+    for (SizeT axis = 0; axis < ndims; axis++)
+        size *= shape[axis];
+    return size;
+}
+
+/**
+ * @brief Compute the array indices of the `nth` (0-based) element of an ndarray given only its shape.
+ *
+ * @param ndims Number of elements in `shape` and `indices`
+ * @param shape The shape of the ndarray
+ * @param indices The returned indices indexing the ndarray with shape `shape`.
+ * @param nth The index of the element of interest.
+ */
+template<typename SizeT>
+void set_indices_by_nth(SizeT ndims, const SizeT* shape, SizeT* indices, SizeT nth) {
+    for (SizeT i = 0; i < ndims; i++) {
+        SizeT axis = ndims - i - 1;
+        SizeT dim = shape[axis];
+
+        indices[axis] = nth % dim;
+        nth /= dim;
+    }
+}
+
+/**
+ * @brief Return the number of elements of an `ndarray`
+ *
+ * This function corresponds to `<an_ndarray>.size`
+ */
+template<typename SizeT>
+SizeT size(const NDArray<SizeT>* ndarray) {
+    return calc_size_from_shape(ndarray->ndims, ndarray->shape);
+}
+
+/**
+ * @brief Return of the number of its content of an `ndarray`.
+ *
+ * This function corresponds to `<an_ndarray>.nbytes`.
+ */
+template<typename SizeT>
+SizeT nbytes(const NDArray<SizeT>* ndarray) {
+    return size(ndarray) * ndarray->itemsize;
+}
+
+/**
+ * @brief Get the `len()` of an ndarray, and asserts that `ndarray` is a sized object.
+ *
+ * This function corresponds to `<an_ndarray>.__len__`.
+ *
+ * @param dst_length The length.
+ */
+template<typename SizeT>
+SizeT len(const NDArray<SizeT>* ndarray) {
+    if (ndarray->ndims != 0) {
+        return ndarray->shape[0];
+    }
+
+    // numpy prohibits `__len__` on unsized objects
+    raise_exception(SizeT, EXN_TYPE_ERROR, "len() of unsized object", NO_PARAM, NO_PARAM, NO_PARAM);
+    __builtin_unreachable();
+}
+
+/**
+ * @brief Return a boolean indicating if `ndarray` is (C-)contiguous.
+ *
+ * You may want to see ndarray's rules for C-contiguity:
+ * https://github.com/numpy/numpy/blob/df256d0d2f3bc6833699529824781c58f9c6e697/numpy/core/src/multiarray/flagsobject.c#L95C1-L99C45
+ */
+template<typename SizeT>
+bool is_c_contiguous(const NDArray<SizeT>* ndarray) {
+    // References:
+    // - tinynumpy's implementation:
+    // https://github.com/wadetb/tinynumpy/blob/0d23d22e07062ffab2afa287374c7b366eebdda1/tinynumpy/tinynumpy.py#L102
+    // - ndarray's flags["C_CONTIGUOUS"]:
+    // https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flags.html#numpy.ndarray.flags
+    // - ndarray's rules for C-contiguity:
+    // https://github.com/numpy/numpy/blob/df256d0d2f3bc6833699529824781c58f9c6e697/numpy/core/src/multiarray/flagsobject.c#L95C1-L99C45
+
+    // From
+    // https://github.com/numpy/numpy/blob/df256d0d2f3bc6833699529824781c58f9c6e697/numpy/core/src/multiarray/flagsobject.c#L95C1-L99C45:
+    //
+    // The traditional rule is that for an array to be flagged as C contiguous,
+    // the following must hold:
+    //
+    // strides[-1] == itemsize
+    // strides[i] == shape[i+1] * strides[i + 1]
+    // [...]
+    // According to these rules, a 0- or 1-dimensional array is either both
+    // C- and F-contiguous, or neither; and an array with 2+ dimensions
+    // can be C- or F- contiguous, or neither, but not both. Though there
+    // there are exceptions for arrays with zero or one item, in the first
+    // case the check is relaxed up to and including the first dimension
+    // with shape[i] == 0. In the second case `strides == itemsize` will
+    // can be true for all dimensions and both flags are set.
+
+    if (ndarray->ndims == 0) {
+        return true;
+    }
+
+    if (ndarray->strides[ndarray->ndims - 1] != ndarray->itemsize) {
+        return false;
+    }
+
+    for (SizeT i = 1; i < ndarray->ndims; i++) {
+        SizeT axis_i = ndarray->ndims - i - 1;
+        if (ndarray->strides[axis_i] != ndarray->shape[axis_i + 1] * ndarray->strides[axis_i + 1]) {
+            return false;
+        }
+    }
+
+    return true;
+}
+
+/**
+ * @brief Return the pointer to the element indexed by `indices` along the ndarray's axes.
+ *
+ * This function does no bound check.
+ */
+template<typename SizeT>
+void* get_pelement_by_indices(const NDArray<SizeT>* ndarray, const SizeT* indices) {
+    void* element = ndarray->data;
+    for (SizeT dim_i = 0; dim_i < ndarray->ndims; dim_i++)
+        element = static_cast<uint8_t*>(element) + indices[dim_i] * ndarray->strides[dim_i];
+    return element;
+}
+
+/**
+ * @brief Return the pointer to the nth (0-based) element of `ndarray` in flattened view.
+ *
+ * This function does no bound check.
+ */
+template<typename SizeT>
+void* get_nth_pelement(const NDArray<SizeT>* ndarray, SizeT nth) {
+    void* element = ndarray->data;
+    for (SizeT i = 0; i < ndarray->ndims; i++) {
+        SizeT axis = ndarray->ndims - i - 1;
+        SizeT dim = ndarray->shape[axis];
+        element = static_cast<uint8_t*>(element) + ndarray->strides[axis] * (nth % dim);
+        nth /= dim;
+    }
+    return element;
+}
+
+/**
+ * @brief Update the strides of an ndarray given an ndarray `shape` to be contiguous.
+ *
+ * You might want to read https://ajcr.net/stride-guide-part-1/.
+ */
+template<typename SizeT>
+void set_strides_by_shape(NDArray<SizeT>* ndarray) {
+    SizeT stride_product = 1;
+    for (SizeT i = 0; i < ndarray->ndims; i++) {
+        SizeT axis = ndarray->ndims - i - 1;
+        ndarray->strides[axis] = stride_product * ndarray->itemsize;
+        stride_product *= ndarray->shape[axis];
+    }
+}
+
+/**
+ * @brief Set an element in `ndarray`.
+ *
+ * @param pelement Pointer to the element in `ndarray` to be set.
+ * @param pvalue Pointer to the value `pelement` will be set to.
+ */
+template<typename SizeT>
+void set_pelement_value(NDArray<SizeT>* ndarray, void* pelement, const void* pvalue) {
+    __builtin_memcpy(pelement, pvalue, ndarray->itemsize);
+}
+
+/**
+ * @brief Copy data from one ndarray to another of the exact same size and itemsize.
+ *
+ * Both ndarrays will be viewed in their flatten views when copying the elements.
+ */
+template<typename SizeT>
+void copy_data(const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
+    // TODO: Make this faster with memcpy when we see a contiguous segment.
+    // TODO: Handle overlapping.
+
+    debug_assert_eq(SizeT, src_ndarray->itemsize, dst_ndarray->itemsize);
+
+    for (SizeT i = 0; i < size(src_ndarray); i++) {
+        auto src_element = ndarray::basic::get_nth_pelement(src_ndarray, i);
+        auto dst_element = ndarray::basic::get_nth_pelement(dst_ndarray, i);
+        ndarray::basic::set_pelement_value(dst_ndarray, dst_element, src_element);
+    }
+}
+}  // namespace basic
+}  // namespace ndarray
+}  // namespace
+
+extern "C" {
+using namespace ndarray::basic;
+
+void __nac3_ndarray_util_assert_shape_no_negative(int32_t ndims, int32_t* shape) {
+    assert_shape_no_negative(ndims, shape);
+}
+
+void __nac3_ndarray_util_assert_shape_no_negative64(int64_t ndims, int64_t* shape) {
+    assert_shape_no_negative(ndims, shape);
+}
+
+void __nac3_ndarray_util_assert_output_shape_same(int32_t ndarray_ndims,
+                                                  const int32_t* ndarray_shape,
+                                                  int32_t output_ndims,
+                                                  const int32_t* output_shape) {
+    assert_output_shape_same(ndarray_ndims, ndarray_shape, output_ndims, output_shape);
+}
+
+void __nac3_ndarray_util_assert_output_shape_same64(int64_t ndarray_ndims,
+                                                    const int64_t* ndarray_shape,
+                                                    int64_t output_ndims,
+                                                    const int64_t* output_shape) {
+    assert_output_shape_same(ndarray_ndims, ndarray_shape, output_ndims, output_shape);
+}
+
+uint32_t __nac3_ndarray_size(NDArray<int32_t>* ndarray) {
+    return size(ndarray);
+}
+
+uint64_t __nac3_ndarray_size64(NDArray<int64_t>* ndarray) {
+    return size(ndarray);
+}
+
+uint32_t __nac3_ndarray_nbytes(NDArray<int32_t>* ndarray) {
+    return nbytes(ndarray);
+}
+
+uint64_t __nac3_ndarray_nbytes64(NDArray<int64_t>* ndarray) {
+    return nbytes(ndarray);
+}
+
+int32_t __nac3_ndarray_len(NDArray<int32_t>* ndarray) {
+    return len(ndarray);
+}
+
+int64_t __nac3_ndarray_len64(NDArray<int64_t>* ndarray) {
+    return len(ndarray);
+}
+
+bool __nac3_ndarray_is_c_contiguous(NDArray<int32_t>* ndarray) {
+    return is_c_contiguous(ndarray);
+}
+
+bool __nac3_ndarray_is_c_contiguous64(NDArray<int64_t>* ndarray) {
+    return is_c_contiguous(ndarray);
+}
+
+void* __nac3_ndarray_get_nth_pelement(const NDArray<int32_t>* ndarray, int32_t nth) {
+    return get_nth_pelement(ndarray, nth);
+}
+
+void* __nac3_ndarray_get_nth_pelement64(const NDArray<int64_t>* ndarray, int64_t nth) {
+    return get_nth_pelement(ndarray, nth);
+}
+
+void* __nac3_ndarray_get_pelement_by_indices(const NDArray<int32_t>* ndarray, int32_t* indices) {
+    return get_pelement_by_indices(ndarray, indices);
+}
+
+void* __nac3_ndarray_get_pelement_by_indices64(const NDArray<int64_t>* ndarray, int64_t* indices) {
+    return get_pelement_by_indices(ndarray, indices);
+}
+
+void __nac3_ndarray_set_strides_by_shape(NDArray<int32_t>* ndarray) {
+    set_strides_by_shape(ndarray);
+}
+
+void __nac3_ndarray_set_strides_by_shape64(NDArray<int64_t>* ndarray) {
+    set_strides_by_shape(ndarray);
+}
+
+void __nac3_ndarray_copy_data(NDArray<int32_t>* src_ndarray, NDArray<int32_t>* dst_ndarray) {
+    copy_data(src_ndarray, dst_ndarray);
+}
+
+void __nac3_ndarray_copy_data64(NDArray<int64_t>* src_ndarray, NDArray<int64_t>* dst_ndarray) {
+    copy_data(src_ndarray, dst_ndarray);
+}
+}

nac3core/irrt/irrt/ndarray/def.hpp

@@ -0,0 +1,51 @@
+#pragma once
+
+#include "irrt/int_types.hpp"
+
+namespace {
+/**
+ * @brief The NDArray object
+ *
+ * Official numpy implementation:
+ * https://github.com/numpy/numpy/blob/735a477f0bc2b5b84d0e72d92f224bde78d4e069/doc/source/reference/c-api/types-and-structures.rst#pyarrayinterface
+ *
+ * Note that this implementation is based on `PyArrayInterface` rather of `PyArrayObject`. The
+ * difference between `PyArrayInterface` and `PyArrayObject` (relevant to our implementation) is
+ * that `PyArrayInterface` *has* `itemsize` and uses `void*` for its `data`, whereas `PyArrayObject`
+ * does not require `itemsize` (probably using `strides[-1]` instead) and uses `char*` for its
+ * `data`. There are also minor differences in the struct layout.
+ */
+template<typename SizeT>
+struct NDArray {
+    /**
+     * @brief The number of bytes of a single element in `data`.
+     */
+    SizeT itemsize;
+
+    /**
+     * @brief The number of dimensions of this shape.
+     */
+    SizeT ndims;
+
+    /**
+     * @brief The NDArray shape, with length equal to `ndims`.
+     *
+     * Note that it may contain 0.
+     */
+    SizeT* shape;
+
+    /**
+     * @brief Array strides, with length equal to `ndims`
+     *
+     * The stride values are in units of bytes, not number of elements.
+     *
+     * Note that `strides` can have negative values or contain 0.
+     */
+    SizeT* strides;
+
+    /**
+     * @brief The underlying data this `ndarray` is pointing to.
+     */
+    void* data;
+};
+}  // namespace

nac3core/irrt/irrt/ndarray/indexing.hpp

@@ -0,0 +1,220 @@
+#pragma once
+
+#include "irrt/exception.hpp"
+#include "irrt/int_types.hpp"
+#include "irrt/ndarray/basic.hpp"
+#include "irrt/ndarray/def.hpp"
+#include "irrt/range.hpp"
+#include "irrt/slice.hpp"
+
+namespace {
+typedef uint8_t NDIndexType;
+
+/**
+ * @brief A single element index
+ *
+ * `data` points to a `int32_t`.
+ */
+const NDIndexType ND_INDEX_TYPE_SINGLE_ELEMENT = 0;
+
+/**
+ * @brief A slice index
+ *
+ * `data` points to a `Slice<int32_t>`.
+ */
+const NDIndexType ND_INDEX_TYPE_SLICE = 1;
+
+/**
+ * @brief `np.newaxis` / `None`
+ *
+ * `data` is unused.
+ */
+const NDIndexType ND_INDEX_TYPE_NEWAXIS = 2;
+
+/**
+ * @brief `Ellipsis` / `...`
+ *
+ * `data` is unused.
+ */
+const NDIndexType ND_INDEX_TYPE_ELLIPSIS = 3;
+
+/**
+ * @brief An index used in ndarray indexing
+ *
+ * That is:
+ * ```
+ * my_ndarray[::-1, 3, ..., np.newaxis]
+ *            ^^^^  ^  ^^^  ^^^^^^^^^^ each of these is represented by an NDIndex.
+ * ```
+ */
+struct NDIndex {
+    /**
+     * @brief Enum tag to specify the type of index.
+     *
+     * Please see the comment of each enum constant.
+     */
+    NDIndexType type;
+
+    /**
+     * @brief The accompanying data associated with `type`.
+     *
+     * Please see the comment of each enum constant.
+     */
+    uint8_t* data;
+};
+}  // namespace
+
+namespace {
+namespace ndarray {
+namespace indexing {
+/**
+ * @brief Perform ndarray "basic indexing" (https://numpy.org/doc/stable/user/basics.indexing.html#basic-indexing)
+ *
+ * This function is very similar to performing `dst_ndarray = src_ndarray[indices]` in Python.
+ *
+ * This function also does proper assertions on `indices` to check for out of bounds access and more.
+ *
+ * # Notes on `dst_ndarray`
+ * The caller is responsible for allocating space for the resulting ndarray.
+ * Here is what this function expects from `dst_ndarray` when called:
+ *   - `dst_ndarray->data` does not have to be initialized.
+ *   - `dst_ndarray->itemsize` does not have to be initialized.
+ *   - `dst_ndarray->ndims` must be initialized, and it must be equal to the expected `ndims` of the `dst_ndarray` after
+ *       indexing `src_ndarray` with `indices`.
+ *   - `dst_ndarray->shape` must be allocated, through it can contain uninitialized values.
+ *   - `dst_ndarray->strides` must be allocated, through it can contain uninitialized values.
+ * When this function call ends:
+ *   - `dst_ndarray->data` is set to `src_ndarray->data`.
+ *   - `dst_ndarray->itemsize` is set to `src_ndarray->itemsize`.
+ *   - `dst_ndarray->ndims` is unchanged.
+ *   - `dst_ndarray->shape` is updated according to how `src_ndarray` is indexed.
+ *   - `dst_ndarray->strides` is updated accordingly by how ndarray indexing works.
+ *
+ * @param indices indices to index `src_ndarray`, ordered in the same way you would write them in Python.
+ * @param src_ndarray The NDArray to be indexed.
+ * @param dst_ndarray The resulting NDArray after indexing. Further details in the comments above,
+ */
+template<typename SizeT>
+void index(SizeT num_indices, const NDIndex* indices, const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
+    // Validate `indices`.
+
+    // Expected value of `dst_ndarray->ndims`.
+    SizeT expected_dst_ndims = src_ndarray->ndims;
+    // To check for "too many indices for array: array is ?-dimensional, but ? were indexed"
+    SizeT num_indexed = 0;
+    // There may be ellipsis `...` in `indices`. There can only be 0 or 1 ellipsis.
+    SizeT num_ellipsis = 0;
+
+    for (SizeT i = 0; i < num_indices; i++) {
+        if (indices[i].type == ND_INDEX_TYPE_SINGLE_ELEMENT) {
+            expected_dst_ndims--;
+            num_indexed++;
+        } else if (indices[i].type == ND_INDEX_TYPE_SLICE) {
+            num_indexed++;
+        } else if (indices[i].type == ND_INDEX_TYPE_NEWAXIS) {
+            expected_dst_ndims++;
+        } else if (indices[i].type == ND_INDEX_TYPE_ELLIPSIS) {
+            num_ellipsis++;
+            if (num_ellipsis > 1) {
+                raise_exception(SizeT, EXN_INDEX_ERROR, "an index can only have a single ellipsis ('...')", NO_PARAM,
+                                NO_PARAM, NO_PARAM);
+            }
+        } else {
+            __builtin_unreachable();
+        }
+    }
+
+    debug_assert_eq(SizeT, expected_dst_ndims, dst_ndarray->ndims);
+
+    if (src_ndarray->ndims - num_indexed < 0) {
+        raise_exception(SizeT, EXN_INDEX_ERROR,
+                        "too many indices for array: array is {0}-dimensional, "
+                        "but {1} were indexed",
+                        src_ndarray->ndims, num_indices, NO_PARAM);
+    }
+
+    dst_ndarray->data = src_ndarray->data;
+    dst_ndarray->itemsize = src_ndarray->itemsize;
+
+    // Reference code:
+    // https://github.com/wadetb/tinynumpy/blob/0d23d22e07062ffab2afa287374c7b366eebdda1/tinynumpy/tinynumpy.py#L652
+    SizeT src_axis = 0;
+    SizeT dst_axis = 0;
+
+    for (int32_t i = 0; i < num_indices; i++) {
+        const NDIndex* index = &indices[i];
+        if (index->type == ND_INDEX_TYPE_SINGLE_ELEMENT) {
+            SizeT input = (SizeT) * ((int32_t*)index->data);
+
+            SizeT k = slice::resolve_index_in_length(src_ndarray->shape[src_axis], input);
+            if (k == -1) {
+                raise_exception(SizeT, EXN_INDEX_ERROR,
+                                "index {0} is out of bounds for axis {1} "
+                                "with size {2}",
+                                input, src_axis, src_ndarray->shape[src_axis]);
+            }
+
+            dst_ndarray->data = static_cast<uint8_t*>(dst_ndarray->data) + k * src_ndarray->strides[src_axis];
+
+            src_axis++;
+        } else if (index->type == ND_INDEX_TYPE_SLICE) {
+            Slice<int32_t>* slice = (Slice<int32_t>*)index->data;
+
+            Range<int32_t> range = slice->indices_checked<SizeT>(src_ndarray->shape[src_axis]);
+
+            dst_ndarray->data = static_cast<uint8_t*>(dst_ndarray->data) + (SizeT)range.start * src_ndarray->strides[src_axis];
+            dst_ndarray->strides[dst_axis] = ((SizeT)range.step) * src_ndarray->strides[src_axis];
+            dst_ndarray->shape[dst_axis] = (SizeT)range.len<SizeT>();
+
+            dst_axis++;
+            src_axis++;
+        } else if (index->type == ND_INDEX_TYPE_NEWAXIS) {
+            dst_ndarray->strides[dst_axis] = 0;
+            dst_ndarray->shape[dst_axis] = 1;
+
+            dst_axis++;
+        } else if (index->type == ND_INDEX_TYPE_ELLIPSIS) {
+            // The number of ':' entries this '...' implies.
+            SizeT ellipsis_size = src_ndarray->ndims - num_indexed;
+
+            for (SizeT j = 0; j < ellipsis_size; j++) {
+                dst_ndarray->strides[dst_axis] = src_ndarray->strides[src_axis];
+                dst_ndarray->shape[dst_axis] = src_ndarray->shape[src_axis];
+
+                dst_axis++;
+                src_axis++;
+            }
+        } else {
+            __builtin_unreachable();
+        }
+    }
+
+    for (; dst_axis < dst_ndarray->ndims; dst_axis++, src_axis++) {
+        dst_ndarray->shape[dst_axis] = src_ndarray->shape[src_axis];
+        dst_ndarray->strides[dst_axis] = src_ndarray->strides[src_axis];
+    }
+
+    debug_assert_eq(SizeT, src_ndarray->ndims, src_axis);
+    debug_assert_eq(SizeT, dst_ndarray->ndims, dst_axis);
+}
+}  // namespace indexing
+}  // namespace ndarray
+}  // namespace
+
+extern "C" {
+using namespace ndarray::indexing;
+
+void __nac3_ndarray_index(int32_t num_indices,
+                          NDIndex* indices,
+                          NDArray<int32_t>* src_ndarray,
+                          NDArray<int32_t>* dst_ndarray) {
+    index(num_indices, indices, src_ndarray, dst_ndarray);
+}
+
+void __nac3_ndarray_index64(int64_t num_indices,
+                            NDIndex* indices,
+                            NDArray<int64_t>* src_ndarray,
+                            NDArray<int64_t>* dst_ndarray) {
+    index(num_indices, indices, src_ndarray, dst_ndarray);
+}
+}

nac3core/irrt/irrt/ndarray/iter.hpp

@@ -0,0 +1,146 @@
+#pragma once
+
+#include "irrt/int_types.hpp"
+#include "irrt/ndarray/def.hpp"
+
+namespace {
+/**
+ * @brief Helper struct to enumerate through an ndarray *efficiently*.
+ *
+ * Example usage (in pseudo-code):
+ * ```
+ * // Suppose my_ndarray has been initialized, with shape [2, 3] and dtype `double`
+ * NDIter nditer;
+ * nditer.initialize(my_ndarray);
+ * while (nditer.has_element()) {
+ *    // This body is run 6 (= my_ndarray.size) times.
+ *
+ *    // [0, 0] -> [0, 1] -> [0, 2] -> [1, 0] -> [1, 1] -> [1, 2] -> end
+ *    print(nditer.indices);
+ *
+ *    // 0 -> 1 -> 2 -> 3 -> 4 -> 5
+ *    print(nditer.nth);
+ *
+ *    // <1st element> -> <2nd element> -> ... -> <6th element> -> end
+ *    print(*((double *) nditer.element))
+ *
+ *    nditer.next(); // Go to next element.
+ * }
+ * ```
+ *
+ * Interesting cases:
+ * - If `my_ndarray.ndims` == 0, there is one iteration.
+ * - If `my_ndarray.shape` contains zeroes, there are no iterations.
+ */
+template<typename SizeT>
+struct NDIter {
+    // Information about the ndarray being iterated over.
+    SizeT ndims;
+    SizeT* shape;
+    SizeT* strides;
+
+    /**
+     * @brief The current indices.
+     *
+     * Must be allocated by the caller.
+     */
+    SizeT* indices;
+
+    /**
+     * @brief The nth (0-based) index of the current indices.
+     *
+     * Initially this is 0.
+     */
+    SizeT nth;
+
+    /**
+     * @brief Pointer to the current element.
+     *
+     * Initially this points to first element of the ndarray.
+     */
+    void* element;
+
+    /**
+     * @brief Cache for the product of shape.
+     *
+     * Could be 0 if `shape` has 0s in it.
+     */
+    SizeT size;
+
+    void initialize(SizeT ndims, SizeT* shape, SizeT* strides, void* element, SizeT* indices) {
+        this->ndims = ndims;
+        this->shape = shape;
+        this->strides = strides;
+
+        this->indices = indices;
+        this->element = element;
+
+        // Compute size
+        this->size = 1;
+        for (SizeT i = 0; i < ndims; i++) {
+            this->size *= shape[i];
+        }
+
+        // `indices` starts on all 0s.
+        for (SizeT axis = 0; axis < ndims; axis++)
+            indices[axis] = 0;
+        nth = 0;
+    }
+
+    void initialize_by_ndarray(NDArray<SizeT>* ndarray, SizeT* indices) {
+        // NOTE: ndarray->data is pointing to the first element, and `NDIter`'s `element` should also point to the first
+        // element as well.
+        this->initialize(ndarray->ndims, ndarray->shape, ndarray->strides, ndarray->data, indices);
+    }
+
+    // Is the current iteration valid?
+    // If true, then `element`, `indices` and `nth` contain details about the current element.
+    bool has_element() { return nth < size; }
+
+    // Go to the next element.
+    void next() {
+        for (SizeT i = 0; i < ndims; i++) {
+            SizeT axis = ndims - i - 1;
+            indices[axis]++;
+            if (indices[axis] >= shape[axis]) {
+                indices[axis] = 0;
+
+                // TODO: There is something called backstrides to speedup iteration.
+                // See https://ajcr.net/stride-guide-part-1/, and
+                // https://docs.scipy.org/doc/numpy-1.13.0/reference/c-api.types-and-structures.html#c.PyArrayIterObject.PyArrayIterObject.backstrides.
+                element = static_cast<void*>(reinterpret_cast<uint8_t*>(element) - strides[axis] * (shape[axis] - 1));
+            } else {
+                element = static_cast<void*>(reinterpret_cast<uint8_t*>(element) + strides[axis]);
+                break;
+            }
+        }
+        nth++;
+    }
+};
+}  // namespace
+
+extern "C" {
+void __nac3_nditer_initialize(NDIter<int32_t>* iter, NDArray<int32_t>* ndarray, int32_t* indices) {
+    iter->initialize_by_ndarray(ndarray, indices);
+}
+
+void __nac3_nditer_initialize64(NDIter<int64_t>* iter, NDArray<int64_t>* ndarray, int64_t* indices) {
+    iter->initialize_by_ndarray(ndarray, indices);
+}
+
+bool __nac3_nditer_has_element(NDIter<int32_t>* iter) {
+    return iter->has_element();
+}
+
+bool __nac3_nditer_has_element64(NDIter<int64_t>* iter) {
+    return iter->has_element();
+}
+
+void __nac3_nditer_next(NDIter<int32_t>* iter) {
+    iter->next();
+}
+
+void __nac3_nditer_next64(NDIter<int64_t>* iter) {
+    iter->next();
+}
+}

nac3core/irrt/irrt/range.hpp

@@ -0,0 +1,47 @@
+#pragma once
+
+#include "irrt/debug.hpp"
+#include "irrt/int_types.hpp"
+
+namespace {
+namespace range {
+template<typename T>
+T len(T start, T stop, T step) {
+    // Reference:
+    // https://github.com/python/cpython/blob/9dbd12375561a393eaec4b21ee4ac568a407cdb0/Objects/rangeobject.c#L933
+    if (step > 0 && start < stop)
+        return 1 + (stop - 1 - start) / step;
+    else if (step < 0 && start > stop)
+        return 1 + (start - 1 - stop) / (-step);
+    else
+        return 0;
+}
+}  // namespace range
+
+/**
+ * @brief A Python range.
+ */
+template<typename T>
+struct Range {
+    T start;
+    T stop;
+    T step;
+
+    /**
+     * @brief Calculate the `len()` of this range.
+     */
+    template<typename SizeT>
+    T len() {
+        debug_assert(SizeT, step != 0);
+        return range::len(start, stop, step);
+    }
+};
+}  // namespace
+
+extern "C" {
+using namespace range;
+
+SliceIndex __nac3_range_slice_len(const SliceIndex start, const SliceIndex end, const SliceIndex step) {
+    return len(start, end, step);
+}
+}

nac3core/irrt/irrt/slice.hpp

@@ -1,6 +1,145 @@
 #pragma once
 
+#include "irrt/debug.hpp"
+#include "irrt/exception.hpp"
 #include "irrt/int_types.hpp"
+#include "irrt/math_util.hpp"
+#include "irrt/range.hpp"
+
+namespace {
+namespace slice {
+/**
+ * @brief Resolve a possibly negative index in a list of a known length.
+ *
+ * Returns -1 if the resolved index is out of the list's bounds.
+ */
+template<typename T>
+T resolve_index_in_length(T length, T index) {
+    T resolved = index < 0 ? length + index : index;
+    if (0 <= resolved && resolved < length) {
+        return resolved;
+    } else {
+        return -1;
+    }
+}
+
+/**
+ * @brief Resolve a slice as a range.
+ *
+ * This is equivalent to `range(*slice(start, stop, step).indices(length))` in Python.
+ */
+template<typename T>
+void indices(bool start_defined,
+             T start,
+             bool stop_defined,
+             T stop,
+             bool step_defined,
+             T step,
+             T length,
+             T* range_start,
+             T* range_stop,
+             T* range_step) {
+    // Reference: https://github.com/python/cpython/blob/main/Objects/sliceobject.c#L388
+    *range_step = step_defined ? step : 1;
+    bool step_is_negative = *range_step < 0;
+
+    T lower, upper;
+    if (step_is_negative) {
+        lower = -1;
+        upper = length - 1;
+    } else {
+        lower = 0;
+        upper = length;
+    }
+
+    if (start_defined) {
+        *range_start = start < 0 ? max(lower, start + length) : min(upper, start);
+    } else {
+        *range_start = step_is_negative ? upper : lower;
+    }
+
+    if (stop_defined) {
+        *range_stop = stop < 0 ? max(lower, stop + length) : min(upper, stop);
+    } else {
+        *range_stop = step_is_negative ? lower : upper;
+    }
+}
+}  // namespace slice
+
+/**
+ * @brief A Python-like slice with **unresolved** indices.
+ */
+template<typename T>
+struct Slice {
+    bool start_defined;
+    T start;
+
+    bool stop_defined;
+    T stop;
+
+    bool step_defined;
+    T step;
+
+    Slice() { this->reset(); }
+
+    void reset() {
+        this->start_defined = false;
+        this->stop_defined = false;
+        this->step_defined = false;
+    }
+
+    void set_start(T start) {
+        this->start_defined = true;
+        this->start = start;
+    }
+
+    void set_stop(T stop) {
+        this->stop_defined = true;
+        this->stop = stop;
+    }
+
+    void set_step(T step) {
+        this->step_defined = true;
+        this->step = step;
+    }
+
+    /**
+     * @brief Resolve this slice as a range.
+     *
+     * In Python, this would be `range(*slice(start, stop, step).indices(length))`.
+     */
+    template<typename SizeT>
+    Range<T> indices(T length) {
+        // Reference:
+        // https://github.com/python/cpython/blob/main/Objects/sliceobject.c#L388
+        debug_assert(SizeT, length >= 0);
+
+        Range<T> result;
+        slice::indices(start_defined, start, stop_defined, stop, step_defined, step, length, &result.start,
+                       &result.stop, &result.step);
+        return result;
+    }
+
+    /**
+     * @brief Like `.indices()` but with assertions.
+     */
+    template<typename SizeT>
+    Range<T> indices_checked(T length) {
+        // TODO: Switch to `SizeT length`
+
+        if (length < 0) {
+            raise_exception(SizeT, EXN_VALUE_ERROR, "length should not be negative, got {0}", length, NO_PARAM,
+                            NO_PARAM);
+        }
+
+        if (this->step_defined && this->step == 0) {
+            raise_exception(SizeT, EXN_VALUE_ERROR, "slice step cannot be zero", NO_PARAM, NO_PARAM, NO_PARAM);
+        }
+
+        return this->indices<SizeT>(length);
+    }
+};
+}  // namespace
 
 extern "C" {
 SliceIndex __nac3_slice_index_bound(SliceIndex i, const SliceIndex len) {
@@ -14,15 +153,4 @@ SliceIndex __nac3_slice_index_bound(SliceIndex i, const SliceIndex len) {
     }
     return i;
 }
-
-SliceIndex __nac3_range_slice_len(const SliceIndex start, const SliceIndex end, const SliceIndex step) {
-    SliceIndex diff = end - start;
-    if (diff > 0 && step > 0) {
-        return ((diff - 1) / step) + 1;
-    } else if (diff < 0 && step < 0) {
-        return ((diff + 1) / step) + 1;
-    } else {
-        return 0;
-    }
 }
-}  // namespace

nac3core/src/codegen/expr.rs

@@ -32,9 +32,10 @@ use super::{
         gen_for_callback_incrementing, gen_if_callback, gen_if_else_expr_callback, gen_raise,
         gen_var,
     },
-    types::ListType,
+    types::{ndarray::NDArrayType, ListType},
     values::{
-        ArrayLikeIndexer, ArrayLikeValue, ListValue, NDArrayValue, ProxyValue, RangeValue,
+        ndarray::{NDArrayValue, RustNDIndex},
+        ArrayLikeIndexer, ArrayLikeValue, ListValue, ProxyValue, RangeValue,
         TypedArrayLikeAccessor, UntypedArrayLikeAccessor,
     },
     CodeGenContext, CodeGenTask, CodeGenerator,
@@ -42,8 +43,8 @@ use super::{
 use crate::{
     symbol_resolver::{SymbolValue, ValueEnum},
     toplevel::{
-        helper::PrimDef,
-        numpy::{make_ndarray_ty, unpack_ndarray_var_tys},
+        helper::{extract_ndims, PrimDef},
+        numpy::unpack_ndarray_var_tys,
         DefinitionId, TopLevelDef,
     },
     typecheck::{
@@ -1553,8 +1554,6 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
     } else if ty1.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id())
         || ty2.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id())
     {
-        let llvm_usize = generator.get_size_type(ctx.ctx);
-
         let is_ndarray1 = ty1.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id());
         let is_ndarray2 = ty2.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id());
 
@@ -1564,21 +1563,10 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
 
             assert!(ctx.unifier.unioned(ndarray_dtype1, ndarray_dtype2));
 
-            let llvm_ndarray_dtype1 = ctx.get_llvm_type(generator, ndarray_dtype1);
-            let llvm_ndarray_dtype2 = ctx.get_llvm_type(generator, ndarray_dtype2);
-
-            let left_val = NDArrayValue::from_pointer_value(
-                left_val.into_pointer_value(),
-                llvm_ndarray_dtype1,
-                llvm_usize,
-                None,
-            );
-            let right_val = NDArrayValue::from_pointer_value(
-                right_val.into_pointer_value(),
-                llvm_ndarray_dtype2,
-                llvm_usize,
-                None,
-            );
+            let left_val = NDArrayType::from_unifier_type(generator, ctx, ty1)
+                .map_value(left_val.into_pointer_value(), None);
+            let right_val = NDArrayType::from_unifier_type(generator, ctx, ty2)
+                .map_value(right_val.into_pointer_value(), None);
 
             let res = if op.base == Operator::MatMult {
                 // MatMult is the only binop which is not an elementwise op
@@ -1627,13 +1615,12 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
         } else {
             let (ndarray_dtype, _) =
                 unpack_ndarray_var_tys(&mut ctx.unifier, if is_ndarray1 { ty1 } else { ty2 });
-            let llvm_ndarray_dtype = ctx.get_llvm_type(generator, ndarray_dtype);
-            let ndarray_val = NDArrayValue::from_pointer_value(
-                if is_ndarray1 { left_val } else { right_val }.into_pointer_value(),
-                llvm_ndarray_dtype,
-                llvm_usize,
-                None,
-            );
+            let ndarray_val =
+                NDArrayType::from_unifier_type(generator, ctx, if is_ndarray1 { ty1 } else { ty2 })
+                    .map_value(
+                        if is_ndarray1 { left_val } else { right_val }.into_pointer_value(),
+                        None,
+                    );
             let res = numpy::ndarray_elementwise_binop_impl(
                 generator,
                 ctx,
@@ -1821,16 +1808,10 @@ pub fn gen_unaryop_expr_with_values<'ctx, G: CodeGenerator>(
             _ => val.into(),
         }
     } else if ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) {
-        let llvm_usize = generator.get_size_type(ctx.ctx);
+        let llvm_ndarray_ty = NDArrayType::from_unifier_type(generator, ctx, ty);
         let (ndarray_dtype, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ty);
-        let llvm_ndarray_dtype = ctx.get_llvm_type(generator, ndarray_dtype);
 
-        let val = NDArrayValue::from_pointer_value(
-            val.into_pointer_value(),
-            llvm_ndarray_dtype,
-            llvm_usize,
-            None,
-        );
+        let val = llvm_ndarray_ty.map_value(val.into_pointer_value(), None);
 
         // ndarray uses `~` rather than `not` to perform elementwise inversion, convert it before
         // passing it to the elementwise codegen function
@@ -1904,8 +1885,6 @@ pub fn gen_cmpop_expr_with_values<'ctx, G: CodeGenerator>(
         if left_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id())
             || right_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id())
         {
-            let llvm_usize = generator.get_size_type(ctx.ctx);
-
             let (Some(left_ty), lhs) = left else { codegen_unreachable!(ctx) };
             let (Some(right_ty), rhs) = comparators[0] else { codegen_unreachable!(ctx) };
             let op = ops[0];
@@ -1921,14 +1900,8 @@ pub fn gen_cmpop_expr_with_values<'ctx, G: CodeGenerator>(
 
                 assert!(ctx.unifier.unioned(ndarray_dtype1, ndarray_dtype2));
 
-                let llvm_ndarray_dtype1 = ctx.get_llvm_type(generator, ndarray_dtype1);
-
-                let left_val = NDArrayValue::from_pointer_value(
-                    lhs.into_pointer_value(),
-                    llvm_ndarray_dtype1,
-                    llvm_usize,
-                    None,
-                );
+                let left_val = NDArrayType::from_unifier_type(generator, ctx, left_ty)
+                    .map_value(lhs.into_pointer_value(), None);
                 let res = numpy::ndarray_elementwise_binop_impl(
                     generator,
                     ctx,
@@ -2549,7 +2522,7 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
     generator: &mut G,
     ctx: &mut CodeGenContext<'ctx, '_>,
     ty: Type,
-    ndims: Type,
+    ndims_ty: Type,
     v: NDArrayValue<'ctx>,
     slice: &Expr<Option<Type>>,
 ) -> Result<Option<ValueEnum<'ctx>>, String> {
@@ -2557,7 +2530,7 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
     let llvm_i32 = ctx.ctx.i32_type();
     let llvm_usize = generator.get_size_type(ctx.ctx);
 
-    let TypeEnum::TLiteral { values, .. } = &*ctx.unifier.get_ty_immutable(ndims) else {
+    let TypeEnum::TLiteral { values, .. } = &*ctx.unifier.get_ty_immutable(ndims_ty) else {
         codegen_unreachable!(ctx)
     };
 
@@ -2590,14 +2563,6 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
         _ => 1,
     };
 
-    let ndarray_ndims_ty = ctx.unifier.get_fresh_literal(
-        ndims.iter().map(|v| SymbolValue::U64(v - subscripted_dims)).collect(),
-        None,
-    );
-    let ndarray_ty =
-        make_ndarray_ty(&mut ctx.unifier, &ctx.primitives, Some(ty), Some(ndarray_ndims_ty));
-    let llvm_pndarray_t = ctx.get_llvm_type(generator, ndarray_ty).into_pointer_type();
-    let llvm_ndarray_t = llvm_pndarray_t.get_element_type().into_struct_type();
     let llvm_ndarray_data_t = ctx.get_llvm_type(generator, ty).as_basic_type_enum();
     let sizeof_elem = llvm_ndarray_data_t.size_of().unwrap();
 
@@ -2789,31 +2754,15 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
 
             _ => {
                 // Accessing an element from a multi-dimensional `ndarray`
-
                 let Some(index_addr) = make_indices_arr(generator, ctx)? else { return Ok(None) };
 
+                let num_dims = extract_ndims(&ctx.unifier, ndims_ty) - 1;
+
                 // Create a new array, remove the top dimension from the dimension-size-list, and copy the
                 // elements over
-                let subscripted_ndarray =
-                    generator.gen_var_alloc(ctx, llvm_ndarray_t.into(), None)?;
-                let ndarray = NDArrayValue::from_pointer_value(
-                    subscripted_ndarray,
-                    llvm_ndarray_data_t,
-                    llvm_usize,
-                    None,
-                );
-
-                let num_dims = v.load_ndims(ctx);
-                ndarray.store_ndims(
-                    ctx,
-                    generator,
-                    ctx.builder
-                        .build_int_sub(num_dims, llvm_usize.const_int(1, false), "")
-                        .unwrap(),
-                );
-
-                let ndarray_num_dims = ndarray.load_ndims(ctx);
-                ndarray.create_shape(ctx, llvm_usize, ndarray_num_dims);
+                let ndarray =
+                    NDArrayType::new(generator, ctx.ctx, llvm_ndarray_data_t, Some(num_dims))
+                        .construct_uninitialized(generator, ctx, None);
 
                 let ndarray_num_dims = ctx
                     .builder
@@ -2842,7 +2791,7 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
                     llvm_i1.const_zero(),
                 );
 
-                let ndarray_num_elems = call_ndarray_calc_size(
+                let ndarray_num_elems = ndarray::call_ndarray_calc_size(
                     generator,
                     ctx,
                     &ndarray.shape().as_slice_value(ctx, generator),
@@ -2852,7 +2801,7 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
                     .builder
                     .build_int_z_extend_or_bit_cast(ndarray_num_elems, sizeof_elem.get_type(), "")
                     .unwrap();
-                ndarray.create_data(ctx, llvm_ndarray_data_t, ndarray_num_elems);
+                unsafe { ndarray.create_data(generator, ctx) };
 
                 let v_data_src_ptr = v.data().ptr_offset(ctx, generator, &index_addr, None);
                 call_memcpy_generic(
@@ -3537,19 +3486,22 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
                         v.data().get(ctx, generator, &index, None).into()
                     }
                 }
-                TypeEnum::TObj { obj_id, params, .. } if *obj_id == PrimDef::NDArray.id() => {
-                    let (ty, ndims) = params.iter().map(|(_, ty)| ty).collect_tuple().unwrap();
-                    let llvm_ty = ctx.get_llvm_type(generator, *ty);
-
-                    let v = if let Some(v) = generator.gen_expr(ctx, value)? {
-                        v.to_basic_value_enum(ctx, generator, value.custom.unwrap())?
-                            .into_pointer_value()
-                    } else {
+                TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
+                    let Some(ndarray) = generator.gen_expr(ctx, value)? else {
                         return Ok(None);
                     };
-                    let v = NDArrayValue::from_pointer_value(v, llvm_ty, usize, None);
 
-                    return gen_ndarray_subscript_expr(generator, ctx, *ty, *ndims, v, slice);
+                    let ndarray_ty = value.custom.unwrap();
+                    let ndarray = ndarray.to_basic_value_enum(ctx, generator, ndarray_ty)?;
+                    let ndarray = NDArrayType::from_unifier_type(generator, ctx, ndarray_ty)
+                        .map_value(ndarray.into_pointer_value(), None);
+
+                    let indices = RustNDIndex::from_subscript_expr(generator, ctx, slice)?;
+                    let result = ndarray
+                        .index(generator, ctx, &indices)
+                        .split_unsized(generator, ctx)
+                        .to_basic_value_enum();
+                    return Ok(Some(ValueEnum::Dynamic(result)));
                 }
                 TypeEnum::TTuple { .. } => {
                     let index: u32 =
@@ -3598,3 +3550,97 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
         _ => unimplemented!(),
     }))
 }
+
+/// Creates a function in the current module and inserts a `call` instruction into the LLVM IR.
+#[allow(clippy::too_many_arguments)]
+pub fn create_fn_and_call<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+    fn_name: &str,
+    ret_type: Option<BasicTypeEnum<'ctx>>,
+    params: &[BasicTypeEnum<'ctx>],
+    args: &[BasicValueEnum<'ctx>],
+    is_var_args: bool,
+    call_value_name: Option<&str>,
+    configure: Option<&dyn Fn(&FunctionValue<'ctx>)>,
+) -> Option<BasicValueEnum<'ctx>> {
+    let intrinsic_fn = ctx.module.get_function(fn_name).unwrap_or_else(|| {
+        let params = params.iter().copied().map(BasicTypeEnum::into).collect_vec();
+        let fn_type = if let Some(ret_type) = ret_type {
+            ret_type.fn_type(params.as_slice(), is_var_args)
+        } else {
+            ctx.ctx.void_type().fn_type(params.as_slice(), is_var_args)
+        };
+
+        ctx.module.add_function(fn_name, fn_type, None)
+    });
+
+    if let Some(configure) = configure {
+        configure(&intrinsic_fn);
+    }
+
+    let args = args.iter().copied().map(BasicValueEnum::into).collect_vec();
+    ctx.builder
+        .build_call(intrinsic_fn, args.as_slice(), call_value_name.unwrap_or_default())
+        .map(CallSiteValue::try_as_basic_value)
+        .map(Either::left)
+        .unwrap()
+}
+
+/// Creates a function in the current module and inserts a `call` instruction into the LLVM IR.
+///
+/// This is a wrapper around [`create_fn_and_call`] for non-vararg function. This function allows
+/// parameters and arguments to be specified as tuples to better indicate the expected type and
+/// actual value of each parameter-argument pair of the call.
+pub fn create_and_call_function<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+    fn_name: &str,
+    ret_type: Option<BasicTypeEnum<'ctx>>,
+    params: &[(BasicTypeEnum<'ctx>, BasicValueEnum<'ctx>)],
+    value_name: Option<&str>,
+    configure: Option<&dyn Fn(&FunctionValue<'ctx>)>,
+) -> Option<BasicValueEnum<'ctx>> {
+    let param_tys = params.iter().map(|(ty, _)| ty).copied().map(BasicTypeEnum::into).collect_vec();
+    let arg_values =
+        params.iter().map(|(_, value)| value).copied().map(BasicValueEnum::into).collect_vec();
+
+    create_fn_and_call(
+        ctx,
+        fn_name,
+        ret_type,
+        param_tys.as_slice(),
+        arg_values.as_slice(),
+        false,
+        value_name,
+        configure,
+    )
+}
+
+/// Creates a function in the current module and inserts a `call` instruction into the LLVM IR.
+///
+/// This is a wrapper around [`create_fn_and_call`] for non-vararg function. This function allows
+/// only arguments to be specified and performs inference for the parameter types of the function
+/// using [`BasicValueEnum::get_type`] on the arguments.
+///
+/// This function is recommended if it is known that all function arguments match the parameter
+/// types of the invoked function.
+pub fn infer_and_call_function<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+    fn_name: &str,
+    ret_type: Option<BasicTypeEnum<'ctx>>,
+    args: &[BasicValueEnum<'ctx>],
+    value_name: Option<&str>,
+    configure: Option<&dyn Fn(&FunctionValue<'ctx>)>,
+) -> Option<BasicValueEnum<'ctx>> {
+    let param_tys = args.iter().map(BasicValueEnum::get_type).collect_vec();
+
+    create_fn_and_call(
+        ctx,
+        fn_name,
+        ret_type,
+        param_tys.as_slice(),
+        args,
+        false,
+        value_name,
+        configure,
+    )
+}

nac3core/src/codegen/irrt/mod.rs

@@ -13,12 +13,13 @@ use super::{CodeGenContext, CodeGenerator};
 use crate::{symbol_resolver::SymbolResolver, typecheck::typedef::Type};
 pub use list::*;
 pub use math::*;
-pub use ndarray::*;
+pub use range::*;
 pub use slice::*;
 
 mod list;
 mod math;
-mod ndarray;
+pub mod ndarray;
+mod range;
 mod slice;
 
 #[must_use]
@@ -60,6 +61,27 @@ pub fn load_irrt<'ctx>(ctx: &'ctx Context, symbol_resolver: &dyn SymbolResolver)
     irrt_mod
 }
 
+/// Returns the name of a function which contains variants for 32-bit and 64-bit `size_t`.
+///
+/// - When [`TypeContext::size_type`] is 32-bits, the function name is `fn_name}`.
+/// - When [`TypeContext::size_type`] is 64-bits, the function name is `{fn_name}64`.
+#[must_use]
+pub fn get_usize_dependent_function_name<G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'_, '_>,
+    name: &str,
+) -> String {
+    let mut name = name.to_owned();
+    match generator.get_size_type(ctx.ctx).get_bit_width() {
+        32 => {}
+        64 => name.push_str("64"),
+        bit_width => {
+            panic!("Unsupported int type bit width {bit_width}, must be either 32-bits or 64-bits")
+        }
+    }
+    name
+}
+
 /// NOTE: the output value of the end index of this function should be compared ***inclusively***,
 /// because python allows `a[2::-1]`, whose semantic is `[a[2], a[1], a[0]]`, which is equivalent to
 /// NO numeric slice in python.

nac3core/src/codegen/irrt/ndarray/basic.rs

@@ -0,0 +1,250 @@
+use inkwell::{
+    values::{BasicValueEnum, IntValue, PointerValue},
+    AddressSpace,
+};
+
+use crate::codegen::{
+    expr::{create_and_call_function, infer_and_call_function},
+    irrt::get_usize_dependent_function_name,
+    types::ProxyType,
+    values::{ndarray::NDArrayValue, ProxyValue},
+    CodeGenContext, CodeGenerator,
+};
+
+pub fn call_nac3_ndarray_util_assert_shape_no_negative<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    ndims: IntValue<'ctx>,
+    shape: PointerValue<'ctx>,
+) {
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
+
+    let name = get_usize_dependent_function_name(
+        generator,
+        ctx,
+        "__nac3_ndarray_util_assert_shape_no_negative",
+    );
+
+    create_and_call_function(
+        ctx,
+        &name,
+        Some(llvm_usize.into()),
+        &[(llvm_usize.into(), ndims.into()), (llvm_pusize.into(), shape.into())],
+        None,
+        None,
+    );
+}
+
+pub fn call_nac3_ndarray_util_assert_output_shape_same<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    ndarray_ndims: IntValue<'ctx>,
+    ndarray_shape: PointerValue<'ctx>,
+    output_ndims: IntValue<'ctx>,
+    output_shape: IntValue<'ctx>,
+) {
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
+
+    let name = get_usize_dependent_function_name(
+        generator,
+        ctx,
+        "__nac3_ndarray_util_assert_output_shape_same",
+    );
+
+    create_and_call_function(
+        ctx,
+        &name,
+        Some(llvm_usize.into()),
+        &[
+            (llvm_usize.into(), ndarray_ndims.into()),
+            (llvm_pusize.into(), ndarray_shape.into()),
+            (llvm_usize.into(), output_ndims.into()),
+            (llvm_pusize.into(), output_shape.into()),
+        ],
+        None,
+        None,
+    );
+}
+
+pub fn call_nac3_ndarray_size<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    ndarray: NDArrayValue<'ctx>,
+) -> IntValue<'ctx> {
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_ndarray = ndarray.get_type().as_base_type();
+
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_size");
+
+    create_and_call_function(
+        ctx,
+        &name,
+        Some(llvm_usize.into()),
+        &[(llvm_ndarray.into(), ndarray.as_base_value().into())],
+        Some("size"),
+        None,
+    )
+    .map(BasicValueEnum::into_int_value)
+    .unwrap()
+}
+
+pub fn call_nac3_ndarray_nbytes<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    ndarray: NDArrayValue<'ctx>,
+) -> IntValue<'ctx> {
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_ndarray = ndarray.get_type().as_base_type();
+
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_nbytes");
+
+    create_and_call_function(
+        ctx,
+        &name,
+        Some(llvm_usize.into()),
+        &[(llvm_ndarray.into(), ndarray.as_base_value().into())],
+        Some("nbytes"),
+        None,
+    )
+    .map(BasicValueEnum::into_int_value)
+    .unwrap()
+}
+
+pub fn call_nac3_ndarray_len<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    ndarray: NDArrayValue<'ctx>,
+) -> IntValue<'ctx> {
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_ndarray = ndarray.get_type().as_base_type();
+
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_len");
+
+    create_and_call_function(
+        ctx,
+        &name,
+        Some(llvm_usize.into()),
+        &[(llvm_ndarray.into(), ndarray.as_base_value().into())],
+        Some("len"),
+        None,
+    )
+    .map(BasicValueEnum::into_int_value)
+    .unwrap()
+}
+
+pub fn call_nac3_ndarray_is_c_contiguous<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    ndarray: NDArrayValue<'ctx>,
+) -> IntValue<'ctx> {
+    let llvm_i1 = ctx.ctx.bool_type();
+    let llvm_ndarray = ndarray.get_type().as_base_type();
+
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_is_c_contiguous");
+
+    create_and_call_function(
+        ctx,
+        &name,
+        Some(llvm_i1.into()),
+        &[(llvm_ndarray.into(), ndarray.as_base_value().into())],
+        Some("is_c_contiguous"),
+        None,
+    )
+    .map(BasicValueEnum::into_int_value)
+    .unwrap()
+}
+
+pub fn call_nac3_ndarray_get_nth_pelement<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    ndarray: NDArrayValue<'ctx>,
+    index: IntValue<'ctx>,
+) -> PointerValue<'ctx> {
+    let llvm_i8 = ctx.ctx.i8_type();
+    let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_ndarray = ndarray.get_type().as_base_type();
+
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_get_nth_pelement");
+
+    create_and_call_function(
+        ctx,
+        &name,
+        Some(llvm_pi8.into()),
+        &[(llvm_ndarray.into(), ndarray.as_base_value().into()), (llvm_usize.into(), index.into())],
+        Some("pelement"),
+        None,
+    )
+    .map(BasicValueEnum::into_pointer_value)
+    .unwrap()
+}
+
+pub fn call_nac3_ndarray_get_pelement_by_indices<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    ndarray: NDArrayValue<'ctx>,
+    indices: PointerValue<'ctx>,
+) -> PointerValue<'ctx> {
+    let llvm_i8 = ctx.ctx.i8_type();
+    let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
+    let llvm_ndarray = ndarray.get_type().as_base_type();
+
+    let name =
+        get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_get_pelement_by_indices");
+
+    create_and_call_function(
+        ctx,
+        &name,
+        Some(llvm_pi8.into()),
+        &[
+            (llvm_ndarray.into(), ndarray.as_base_value().into()),
+            (llvm_pusize.into(), indices.into()),
+        ],
+        Some("pelement"),
+        None,
+    )
+    .map(BasicValueEnum::into_pointer_value)
+    .unwrap()
+}
+
+pub fn call_nac3_ndarray_set_strides_by_shape<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    ndarray: NDArrayValue<'ctx>,
+) {
+    let llvm_ndarray = ndarray.get_type().as_base_type();
+
+    let name =
+        get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_set_strides_by_shape");
+
+    create_and_call_function(
+        ctx,
+        &name,
+        None,
+        &[(llvm_ndarray.into(), ndarray.as_base_value().into())],
+        None,
+        None,
+    );
+}
+
+pub fn call_nac3_ndarray_copy_data<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    src_ndarray: NDArrayValue<'ctx>,
+    dst_ndarray: NDArrayValue<'ctx>,
+) {
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_copy_data");
+
+    infer_and_call_function(
+        ctx,
+        &name,
+        None,
+        &[src_ndarray.as_base_value().into(), dst_ndarray.as_base_value().into()],
+        None,
+        None,
+    );
+}

nac3core/src/codegen/irrt/ndarray/indexing.rs

@@ -0,0 +1,29 @@
+use crate::codegen::{
+    expr::infer_and_call_function,
+    irrt::get_usize_dependent_function_name,
+    values::{ndarray::NDArrayValue, ArrayLikeValue, ArraySliceValue, ProxyValue},
+    CodeGenContext, CodeGenerator,
+};
+
+pub fn call_nac3_ndarray_index<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    indices: ArraySliceValue<'ctx>,
+    src_ndarray: NDArrayValue<'ctx>,
+    dst_ndarray: NDArrayValue<'ctx>,
+) {
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_index");
+    infer_and_call_function(
+        ctx,
+        &name,
+        None,
+        &[
+            indices.size(ctx, generator).into(),
+            indices.base_ptr(ctx, generator).into(),
+            src_ndarray.as_base_value().into(),
+            dst_ndarray.as_base_value().into(),
+        ],
+        None,
+        None,
+    );
+}

nac3core/src/codegen/irrt/ndarray/iter.rs

@@ -0,0 +1,70 @@
+use inkwell::{
+    values::{BasicValueEnum, IntValue},
+    AddressSpace,
+};
+
+use crate::codegen::{
+    expr::{create_and_call_function, infer_and_call_function},
+    irrt::get_usize_dependent_function_name,
+    types::ProxyType,
+    values::{
+        ndarray::{NDArrayValue, NDIterValue},
+        ArrayLikeValue, ArraySliceValue, ProxyValue,
+    },
+    CodeGenContext, CodeGenerator,
+};
+
+pub fn call_nac3_nditer_initialize<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    iter: NDIterValue<'ctx>,
+    ndarray: NDArrayValue<'ctx>,
+    indices: ArraySliceValue<'ctx>,
+) {
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
+
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_nditer_initialize");
+
+    create_and_call_function(
+        ctx,
+        &name,
+        None,
+        &[
+            (iter.get_type().as_base_type().into(), iter.as_base_value().into()),
+            (ndarray.get_type().as_base_type().into(), ndarray.as_base_value().into()),
+            (llvm_pusize.into(), indices.base_ptr(ctx, generator).into()),
+        ],
+        None,
+        None,
+    );
+}
+
+pub fn call_nac3_nditer_has_element<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    iter: NDIterValue<'ctx>,
+) -> IntValue<'ctx> {
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_nditer_has_element");
+
+    infer_and_call_function(
+        ctx,
+        &name,
+        Some(ctx.ctx.bool_type().into()),
+        &[iter.as_base_value().into()],
+        None,
+        None,
+    )
+    .map(BasicValueEnum::into_int_value)
+    .unwrap()
+}
+
+pub fn call_nac3_nditer_next<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    iter: NDIterValue<'ctx>,
+) {
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_nditer_next");
+
+    infer_and_call_function(ctx, &name, None, &[iter.as_base_value().into()], None, None);
+}

nac3core/src/codegen/irrt/ndarray/mod.rs

@@ -10,11 +10,18 @@ use crate::codegen::{
     macros::codegen_unreachable,
     stmt::gen_for_callback_incrementing,
     values::{
-        ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, NDArrayValue, TypedArrayLikeAccessor,
-        TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
+        ndarray::NDArrayValue, ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue,
+        TypedArrayLikeAccessor, TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
     },
     CodeGenContext, CodeGenerator,
 };
+pub use basic::*;
+pub use indexing::*;
+pub use iter::*;
+
+mod basic;
+mod indexing;
+mod iter;
 
 /// Generates a call to `__nac3_ndarray_calc_size`. Returns an [`IntValue`] representing the
 /// calculated total size.
@@ -77,7 +84,7 @@ where
 ///   `NDArray`.
 pub fn call_ndarray_calc_nd_indices<'ctx, G: CodeGenerator + ?Sized>(
     generator: &G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
+    ctx: &CodeGenContext<'ctx, '_>,
     index: IntValue<'ctx>,
     ndarray: NDArrayValue<'ctx>,
 ) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
@@ -201,8 +208,8 @@ where
 ///   `NDArray`.
 /// * `indices` - The multidimensional index to compute the flattened index for.
 pub fn call_ndarray_flatten_index<'ctx, G, Index>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
     ndarray: NDArrayValue<'ctx>,
     indices: &Index,
 ) -> IntValue<'ctx>

nac3core/src/codegen/irrt/range.rs

@@ -0,0 +1,42 @@
+use inkwell::{
+    values::{BasicValueEnum, CallSiteValue, IntValue},
+    IntPredicate,
+};
+use itertools::Either;
+
+use crate::codegen::{CodeGenContext, CodeGenerator};
+
+pub fn calculate_len_for_slice_range<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    start: IntValue<'ctx>,
+    end: IntValue<'ctx>,
+    step: IntValue<'ctx>,
+) -> IntValue<'ctx> {
+    const SYMBOL: &str = "__nac3_range_slice_len";
+    let len_func = ctx.module.get_function(SYMBOL).unwrap_or_else(|| {
+        let i32_t = ctx.ctx.i32_type();
+        let fn_t = i32_t.fn_type(&[i32_t.into(), i32_t.into(), i32_t.into()], false);
+        ctx.module.add_function(SYMBOL, fn_t, None)
+    });
+
+    // assert step != 0, throw exception if not
+    let not_zero = ctx
+        .builder
+        .build_int_compare(IntPredicate::NE, step, step.get_type().const_zero(), "range_step_ne")
+        .unwrap();
+    ctx.make_assert(
+        generator,
+        not_zero,
+        "0:ValueError",
+        "step must not be zero",
+        [None, None, None],
+        ctx.current_loc,
+    );
+    ctx.builder
+        .build_call(len_func, &[start.into(), end.into(), step.into()], "calc_len")
+        .map(CallSiteValue::try_as_basic_value)
+        .map(|v| v.map_left(BasicValueEnum::into_int_value))
+        .map(Either::unwrap_left)
+        .unwrap()
+}

nac3core/src/codegen/irrt/slice.rs

@@ -1,8 +1,6 @@
-use inkwell::{
-    values::{BasicValueEnum, CallSiteValue, IntValue},
-    IntPredicate,
-};
+use inkwell::values::{BasicValueEnum, CallSiteValue, IntValue};
 use itertools::Either;
+
 use nac3parser::ast::Expr;
 
 use crate::{
@@ -39,38 +37,3 @@ pub fn handle_slice_index_bound<'ctx, G: CodeGenerator>(
             .unwrap(),
     ))
 }
-
-pub fn calculate_len_for_slice_range<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    start: IntValue<'ctx>,
-    end: IntValue<'ctx>,
-    step: IntValue<'ctx>,
-) -> IntValue<'ctx> {
-    const SYMBOL: &str = "__nac3_range_slice_len";
-    let len_func = ctx.module.get_function(SYMBOL).unwrap_or_else(|| {
-        let i32_t = ctx.ctx.i32_type();
-        let fn_t = i32_t.fn_type(&[i32_t.into(), i32_t.into(), i32_t.into()], false);
-        ctx.module.add_function(SYMBOL, fn_t, None)
-    });
-
-    // assert step != 0, throw exception if not
-    let not_zero = ctx
-        .builder
-        .build_int_compare(IntPredicate::NE, step, step.get_type().const_zero(), "range_step_ne")
-        .unwrap();
-    ctx.make_assert(
-        generator,
-        not_zero,
-        "0:ValueError",
-        "step must not be zero",
-        [None, None, None],
-        ctx.current_loc,
-    );
-    ctx.builder
-        .build_call(len_func, &[start.into(), end.into(), step.into()], "calc_len")
-        .map(CallSiteValue::try_as_basic_value)
-        .map(|v| v.map_left(BasicValueEnum::into_int_value))
-        .map(Either::unwrap_left)
-        .unwrap()
-}

nac3core/src/codegen/llvm_intrinsics.rs

@@ -201,6 +201,49 @@ pub fn call_memcpy_generic<'ctx>(
     call_memcpy(ctx, dest, src, len, is_volatile);
 }
 
+/// Invokes the `llvm.memcpy` intrinsic.
+///
+/// Unlike [`call_memcpy`], this function accepts any type of pointer value. If `dest` or `src` is
+/// not a pointer to an integer, the pointer(s) will be cast to `i8*` before invoking `memcpy`.
+/// Moreover, `len` now refers to the number of elements to copy (rather than number of bytes to
+/// copy).
+pub fn call_memcpy_generic_array<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+    dest: PointerValue<'ctx>,
+    src: PointerValue<'ctx>,
+    len: IntValue<'ctx>,
+    is_volatile: IntValue<'ctx>,
+) {
+    let llvm_i8 = ctx.ctx.i8_type();
+    let llvm_p0i8 = llvm_i8.ptr_type(AddressSpace::default());
+    let llvm_sizeof_expr_t = llvm_i8.size_of().get_type();
+
+    let dest_elem_t = dest.get_type().get_element_type();
+    let src_elem_t = src.get_type().get_element_type();
+
+    let dest = if matches!(dest_elem_t, IntType(t) if t.get_bit_width() == 8) {
+        dest
+    } else {
+        ctx.builder
+            .build_bit_cast(dest, llvm_p0i8, "")
+            .map(BasicValueEnum::into_pointer_value)
+            .unwrap()
+    };
+    let src = if matches!(src_elem_t, IntType(t) if t.get_bit_width() == 8) {
+        src
+    } else {
+        ctx.builder
+            .build_bit_cast(src, llvm_p0i8, "")
+            .map(BasicValueEnum::into_pointer_value)
+            .unwrap()
+    };
+
+    let len = ctx.builder.build_int_z_extend_or_bit_cast(len, llvm_sizeof_expr_t, "").unwrap();
+    let len = ctx.builder.build_int_mul(len, src_elem_t.size_of().unwrap(), "").unwrap();
+
+    call_memcpy(ctx, dest, src, len, is_volatile);
+}
+
 /// Macro to find and generate build call for llvm intrinsic (body of llvm intrinsic function)
 ///
 /// Arguments:
@@ -343,3 +386,25 @@ pub fn call_float_powi<'ctx>(
         .map(Either::unwrap_left)
         .unwrap()
 }
+
+/// Invokes the [`llvm.ctpop`](https://llvm.org/docs/LangRef.html#llvm-ctpop-intrinsic) intrinsic.
+pub fn call_int_ctpop<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+    src: IntValue<'ctx>,
+    name: Option<&str>,
+) -> IntValue<'ctx> {
+    const FN_NAME: &str = "llvm.ctpop";
+
+    let llvm_src_t = src.get_type();
+
+    let intrinsic_fn = Intrinsic::find(FN_NAME)
+        .and_then(|intrinsic| intrinsic.get_declaration(&ctx.module, &[llvm_src_t.into()]))
+        .unwrap();
+
+    ctx.builder
+        .build_call(intrinsic_fn, &[src.into()], name.unwrap_or_default())
+        .map(CallSiteValue::try_as_basic_value)
+        .map(|v| v.map_left(BasicValueEnum::into_int_value))
+        .map(Either::unwrap_left)
+        .unwrap()
+}

nac3core/src/codegen/mod.rs

@@ -30,7 +30,11 @@ use nac3parser::ast::{Location, Stmt, StrRef};
 
 use crate::{
     symbol_resolver::{StaticValue, SymbolResolver},
-    toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, TopLevelContext, TopLevelDef},
+    toplevel::{
+        helper::{extract_ndims, PrimDef},
+        numpy::unpack_ndarray_var_tys,
+        TopLevelContext, TopLevelDef,
+    },
     typecheck::{
         type_inferencer::{CodeLocation, PrimitiveStore},
         typedef::{CallId, FuncArg, Type, TypeEnum, Unifier},
@@ -38,7 +42,7 @@ use crate::{
 };
 use concrete_type::{ConcreteType, ConcreteTypeEnum, ConcreteTypeStore};
 pub use generator::{CodeGenerator, DefaultCodeGenerator};
-use types::{ListType, NDArrayType, ProxyType, RangeType};
+use types::{ndarray::NDArrayType, ListType, ProxyType, RangeType};
 
 pub mod builtin_fns;
 pub mod concrete_type;
@@ -510,12 +514,13 @@ fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
                         }
 
                         TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
-                            let (dtype, _) = unpack_ndarray_var_tys(unifier, ty);
+                            let (dtype, ndims) = unpack_ndarray_var_tys(unifier, ty);
+                            let ndims = extract_ndims(unifier, ndims);
                             let element_type = get_llvm_type(
                                 ctx, module, generator, unifier, top_level, type_cache, dtype,
                             );
 
-                            NDArrayType::new(generator, ctx, element_type).as_base_type().into()
+                            NDArrayType::new(generator, ctx, element_type, Some(ndims)).as_base_type().into()
                         }
 
                         _ => unreachable!(
@@ -1119,3 +1124,106 @@ fn gen_in_range_check<'ctx>(
 fn get_va_count_arg_name(arg_name: StrRef) -> StrRef {
     format!("__{}_va_count", &arg_name).into()
 }
+
+/// Returns the alignment of the type.
+///
+/// This is necessary as `get_alignment` is not implemented as part of [`BasicType`].
+pub fn get_type_alignment<'ctx>(ty: impl Into<BasicTypeEnum<'ctx>>) -> IntValue<'ctx> {
+    match ty.into() {
+        BasicTypeEnum::ArrayType(ty) => ty.get_alignment(),
+        BasicTypeEnum::FloatType(ty) => ty.get_alignment(),
+        BasicTypeEnum::IntType(ty) => ty.get_alignment(),
+        BasicTypeEnum::PointerType(ty) => ty.get_alignment(),
+        BasicTypeEnum::StructType(ty) => ty.get_alignment(),
+        BasicTypeEnum::VectorType(ty) => ty.get_alignment(),
+    }
+}
+
+/// Inserts an `alloca` instruction with allocation `size` given in bytes and the alignment of the
+/// given type.
+///
+/// The returned [`PointerValue`] will have a type of `i8*`, a size of at least `size`, and will be
+/// aligned with the alignment of `align_ty`.
+pub fn type_aligned_alloca<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    align_ty: impl Into<BasicTypeEnum<'ctx>>,
+    size: IntValue<'ctx>,
+    name: Option<&str>,
+) -> PointerValue<'ctx> {
+    /// Round `val` up to its modulo `power_of_two`.
+    fn round_up<'ctx>(
+        ctx: &CodeGenContext<'ctx, '_>,
+        val: IntValue<'ctx>,
+        power_of_two: IntValue<'ctx>,
+    ) -> IntValue<'ctx> {
+        debug_assert_eq!(
+            val.get_type().get_bit_width(),
+            power_of_two.get_type().get_bit_width(),
+            "`val` ({}) and `power_of_two` ({}) must be the same type",
+            val.get_type(),
+            power_of_two.get_type(),
+        );
+
+        let llvm_val_t = val.get_type();
+
+        let max_rem =
+            ctx.builder.build_int_sub(power_of_two, llvm_val_t.const_int(1, false), "").unwrap();
+        ctx.builder
+            .build_and(
+                ctx.builder.build_int_add(val, max_rem, "").unwrap(),
+                ctx.builder.build_not(max_rem, "").unwrap(),
+                "",
+            )
+            .unwrap()
+    }
+
+    let llvm_i8 = ctx.ctx.i8_type();
+    let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let align_ty = align_ty.into();
+
+    let size = ctx.builder.build_int_truncate_or_bit_cast(size, llvm_usize, "").unwrap();
+
+    debug_assert_eq!(
+        size.get_type().get_bit_width(),
+        llvm_usize.get_bit_width(),
+        "Expected size_t ({}) for parameter `size` of `aligned_alloca`, got {}",
+        llvm_usize,
+        size.get_type(),
+    );
+
+    let alignment = get_type_alignment(align_ty);
+    let alignment = ctx.builder.build_int_truncate_or_bit_cast(alignment, llvm_usize, "").unwrap();
+
+    if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
+        let alignment_bitcount = llvm_intrinsics::call_int_ctpop(ctx, alignment, None);
+
+        ctx.make_assert(
+            generator,
+            ctx.builder
+                .build_int_compare(
+                    IntPredicate::EQ,
+                    alignment_bitcount,
+                    alignment_bitcount.get_type().const_int(1, false),
+                    "",
+                )
+                .unwrap(),
+            "0:AssertionError",
+            "Expected power-of-two alignment for aligned_alloca, got {0}",
+            [Some(alignment), None, None],
+            ctx.current_loc,
+        );
+    }
+
+    let buffer_size = round_up(ctx, size, alignment);
+    let aligned_slices = ctx.builder.build_int_unsigned_div(buffer_size, alignment, "").unwrap();
+
+    // Just to be absolutely sure, alloca in [i8 x alignment] slices
+    let buffer = ctx.builder.build_array_alloca(align_ty, aligned_slices, "").unwrap();
+
+    ctx.builder
+        .build_bit_cast(buffer, llvm_pi8, name.unwrap_or_default())
+        .map(BasicValueEnum::into_pointer_value)
+        .unwrap()
+}

nac3core/src/codegen/numpy.rs

@@ -3,21 +3,25 @@ use inkwell::{
     values::{BasicValue, BasicValueEnum, IntValue, PointerValue},
     AddressSpace, IntPredicate, OptimizationLevel,
 };
+use itertools::Itertools;
 
 use nac3parser::ast::{Operator, StrRef};
 
 use super::{
     expr::gen_binop_expr_with_values,
     irrt::{
-        calculate_len_for_slice_range, call_ndarray_calc_broadcast,
-        call_ndarray_calc_broadcast_index, call_ndarray_calc_nd_indices, call_ndarray_calc_size,
+        calculate_len_for_slice_range,
+        ndarray::{
+            call_ndarray_calc_broadcast, call_ndarray_calc_broadcast_index,
+            call_ndarray_calc_nd_indices, call_ndarray_calc_size,
+        },
     },
     llvm_intrinsics::{self, call_memcpy_generic},
     macros::codegen_unreachable,
     stmt::{gen_for_callback_incrementing, gen_for_range_callback, gen_if_else_expr_callback},
-    types::{ListType, NDArrayType, ProxyType},
+    types::{ndarray::NDArrayType, ListType, ProxyType},
     values::{
-        ArrayLikeIndexer, ArrayLikeValue, ListValue, NDArrayValue, ProxyValue,
+        ndarray::NDArrayValue, ArrayLikeIndexer, ArrayLikeValue, ListValue, ProxyValue,
         TypedArrayLikeAccessor, TypedArrayLikeAdapter, TypedArrayLikeMutator,
         UntypedArrayLikeAccessor, UntypedArrayLikeMutator,
     },
@@ -25,39 +29,13 @@ use super::{
 };
 use crate::{
     symbol_resolver::ValueEnum,
-    toplevel::{
-        helper::{arraylike_flatten_element_type, PrimDef},
-        numpy::{make_ndarray_ty, unpack_ndarray_var_tys},
-        DefinitionId,
-    },
+    toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, DefinitionId},
     typecheck::{
         magic_methods::Binop,
         typedef::{FunSignature, Type, TypeEnum},
     },
 };
 
-/// Creates an uninitialized `NDArray` instance.
-fn create_ndarray_uninitialized<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    elem_ty: Type,
-) -> Result<NDArrayValue<'ctx>, String> {
-    let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-    let ndarray_ty = make_ndarray_ty(&mut ctx.unifier, &ctx.primitives, Some(elem_ty), None);
-
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-
-    let llvm_ndarray_t = ctx
-        .get_llvm_type(generator, ndarray_ty)
-        .into_pointer_type()
-        .get_element_type()
-        .into_struct_type();
-
-    let ndarray = generator.gen_var_alloc(ctx, llvm_ndarray_t.into(), None)?;
-
-    Ok(NDArrayValue::from_pointer_value(ndarray, llvm_elem_ty, llvm_usize, None))
-}
-
 /// Creates an `NDArray` instance from a dynamic shape.
 ///
 /// * `elem_ty` - The element type of the `NDArray`.
@@ -83,6 +61,7 @@ where
     ) -> Result<IntValue<'ctx>, String>,
 {
     let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
 
     // Assert that all dimensions are non-negative
     let shape_len = shape_len_fn(generator, ctx, shape)?;
@@ -115,20 +94,17 @@ where
                 ctx.current_loc,
             );
 
-            // TODO: Disallow dim_sz > u32_MAX
+            // TODO: Disallow shape > u32_MAX
 
             Ok(())
         },
         llvm_usize.const_int(1, false),
     )?;
 
-    let ndarray = create_ndarray_uninitialized(generator, ctx, elem_ty)?;
-
     let num_dims = shape_len_fn(generator, ctx, shape)?;
-    ndarray.store_ndims(ctx, generator, num_dims);
 
-    let ndarray_num_dims = ndarray.load_ndims(ctx);
-    ndarray.create_shape(ctx, llvm_usize, ndarray_num_dims);
+    let ndarray = NDArrayType::new(generator, ctx.ctx, llvm_elem_ty, None)
+        .construct_dyn_ndims(generator, ctx, num_dims, None);
 
     // Copy the dimension sizes from shape to ndarray.dims
     let shape_len = shape_len_fn(generator, ctx, shape)?;
@@ -153,7 +129,7 @@ where
         llvm_usize.const_int(1, false),
     )?;
 
-    let ndarray = ndarray_init_data(generator, ctx, elem_ty, ndarray);
+    unsafe { ndarray.create_data(generator, ctx) };
 
     Ok(ndarray)
 }
@@ -186,57 +162,18 @@ pub fn create_ndarray_const_shape<'ctx, G: CodeGenerator + ?Sized>(
             ctx.current_loc,
         );
 
-        // TODO: Disallow dim_sz > u32_MAX
+        // TODO: Disallow shape > u32_MAX
     }
 
-    let ndarray = create_ndarray_uninitialized(generator, ctx, elem_ty)?;
+    let llvm_dtype = ctx.get_llvm_type(generator, elem_ty);
 
-    let num_dims = llvm_usize.const_int(shape.len() as u64, false);
-    ndarray.store_ndims(ctx, generator, num_dims);
-
-    let ndarray_num_dims = ndarray.load_ndims(ctx);
-    ndarray.create_shape(ctx, llvm_usize, ndarray_num_dims);
-
-    for (i, &shape_dim) in shape.iter().enumerate() {
-        let shape_dim = ctx.builder.build_int_z_extend(shape_dim, llvm_usize, "").unwrap();
-        let ndarray_dim = unsafe {
-            ndarray.shape().ptr_offset_unchecked(
-                ctx,
-                generator,
-                &llvm_usize.const_int(i as u64, true),
-                None,
-            )
-        };
-
-        ctx.builder.build_store(ndarray_dim, shape_dim).unwrap();
-    }
-
-    let ndarray = ndarray_init_data(generator, ctx, elem_ty, ndarray);
+    let ndarray = NDArrayType::new(generator, ctx.ctx, llvm_dtype, Some(shape.len() as u64))
+        .construct_dyn_shape(generator, ctx, shape, None);
+    unsafe { ndarray.create_data(generator, ctx) };
 
     Ok(ndarray)
 }
 
-/// Initializes the `data` field of [`NDArrayValue`] based on the `ndims` and `dim_sz` fields.
-fn ndarray_init_data<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    elem_ty: Type,
-    ndarray: NDArrayValue<'ctx>,
-) -> NDArrayValue<'ctx> {
-    let llvm_ndarray_data_t = ctx.get_llvm_type(generator, elem_ty).as_basic_type_enum();
-    assert!(llvm_ndarray_data_t.is_sized());
-
-    let ndarray_num_elems = call_ndarray_calc_size(
-        generator,
-        ctx,
-        &ndarray.shape().as_slice_value(ctx, generator),
-        (None, None),
-    );
-    ndarray.create_data(ctx, llvm_ndarray_data_t, ndarray_num_elems);
-
-    ndarray
-}
-
 fn ndarray_zero_value<'ctx, G: CodeGenerator + ?Sized>(
     generator: &mut G,
     ctx: &mut CodeGenContext<'ctx, '_>,
@@ -338,20 +275,24 @@ fn call_ndarray_empty_impl<'ctx, G: CodeGenerator + ?Sized>(
             // Get the length/size of the tuple, which also happens to be the value of `ndims`.
             let ndims = shape_tuple.get_type().count_fields();
 
-            let mut shape = Vec::with_capacity(ndims as usize);
-            for dim_i in 0..ndims {
-                let dim = ctx
-                    .builder
-                    .build_extract_value(shape_tuple, dim_i, format!("dim{dim_i}").as_str())
-                    .unwrap()
-                    .into_int_value();
+            let shape = (0..ndims)
+                .map(|dim_i| {
+                    ctx.builder
+                        .build_extract_value(shape_tuple, dim_i, format!("dim{dim_i}").as_str())
+                        .map(BasicValueEnum::into_int_value)
+                        .map(|v| {
+                            ctx.builder.build_int_z_extend_or_bit_cast(v, llvm_usize, "").unwrap()
+                        })
+                        .unwrap()
+                })
+                .collect_vec();
 
-                shape.push(dim);
-            }
             create_ndarray_const_shape(generator, ctx, elem_ty, shape.as_slice())
         }
         BasicValueEnum::IntValue(shape_int) => {
             // 3. A scalar int; e.g., `np.empty(3)`, this is functionally equivalent to `np.empty([3])`
+            let shape_int =
+                ctx.builder.build_int_z_extend_or_bit_cast(shape_int, llvm_usize, "").unwrap();
 
             create_ndarray_const_shape(generator, ctx, elem_ty, &[shape_int])
         }
@@ -474,8 +415,8 @@ fn ndarray_broadcast_fill<'ctx, 'a, G, ValueFn>(
     generator: &mut G,
     ctx: &mut CodeGenContext<'ctx, 'a>,
     res: NDArrayValue<'ctx>,
-    lhs: (Type, BasicValueEnum<'ctx>, bool),
-    rhs: (Type, BasicValueEnum<'ctx>, bool),
+    (lhs_ty, lhs_val, lhs_scalar): (Type, BasicValueEnum<'ctx>, bool),
+    (rhs_ty, rhs_val, rhs_scalar): (Type, BasicValueEnum<'ctx>, bool),
     value_fn: ValueFn,
 ) -> Result<NDArrayValue<'ctx>, String>
 where
@@ -486,11 +427,6 @@ where
         (BasicValueEnum<'ctx>, BasicValueEnum<'ctx>),
     ) -> Result<BasicValueEnum<'ctx>, String>,
 {
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-
-    let (lhs_ty, lhs_val, lhs_scalar) = lhs;
-    let (rhs_ty, rhs_val, rhs_scalar) = rhs;
-
     assert!(
         !(lhs_scalar && rhs_scalar),
         "One of the operands must be a ndarray instance: `{}`, `{}`",
@@ -500,26 +436,14 @@ where
 
     // Assert that all ndarray operands are broadcastable to the target size
     if !lhs_scalar {
-        let lhs_dtype = arraylike_flatten_element_type(&mut ctx.unifier, lhs_ty);
-        let llvm_lhs_elem_ty = ctx.get_llvm_type(generator, lhs_dtype);
-        let lhs_val = NDArrayValue::from_pointer_value(
-            lhs_val.into_pointer_value(),
-            llvm_lhs_elem_ty,
-            llvm_usize,
-            None,
-        );
+        let lhs_val = NDArrayType::from_unifier_type(generator, ctx, lhs_ty)
+            .map_value(lhs_val.into_pointer_value(), None);
         ndarray_assert_is_broadcastable(generator, ctx, res, lhs_val);
     }
 
     if !rhs_scalar {
-        let rhs_dtype = arraylike_flatten_element_type(&mut ctx.unifier, rhs_ty);
-        let llvm_rhs_elem_ty = ctx.get_llvm_type(generator, rhs_dtype);
-        let rhs_val = NDArrayValue::from_pointer_value(
-            rhs_val.into_pointer_value(),
-            llvm_rhs_elem_ty,
-            llvm_usize,
-            None,
-        );
+        let rhs_val = NDArrayType::from_unifier_type(generator, ctx, rhs_ty)
+            .map_value(rhs_val.into_pointer_value(), None);
         ndarray_assert_is_broadcastable(generator, ctx, res, rhs_val);
     }
 
@@ -527,14 +451,8 @@ where
         let lhs_elem = if lhs_scalar {
             lhs_val
         } else {
-            let lhs_dtype = arraylike_flatten_element_type(&mut ctx.unifier, lhs_ty);
-            let llvm_lhs_elem_ty = ctx.get_llvm_type(generator, lhs_dtype);
-            let lhs = NDArrayValue::from_pointer_value(
-                lhs_val.into_pointer_value(),
-                llvm_lhs_elem_ty,
-                llvm_usize,
-                None,
-            );
+            let lhs = NDArrayType::from_unifier_type(generator, ctx, lhs_ty)
+                .map_value(lhs_val.into_pointer_value(), None);
             let lhs_idx = call_ndarray_calc_broadcast_index(generator, ctx, lhs, idx);
 
             unsafe { lhs.data().get_unchecked(ctx, generator, &lhs_idx, None) }
@@ -543,14 +461,8 @@ where
         let rhs_elem = if rhs_scalar {
             rhs_val
         } else {
-            let rhs_dtype = arraylike_flatten_element_type(&mut ctx.unifier, rhs_ty);
-            let llvm_rhs_elem_ty = ctx.get_llvm_type(generator, rhs_dtype);
-            let rhs = NDArrayValue::from_pointer_value(
-                rhs_val.into_pointer_value(),
-                llvm_rhs_elem_ty,
-                llvm_usize,
-                None,
-            );
+            let rhs = NDArrayType::from_unifier_type(generator, ctx, rhs_ty)
+                .map_value(rhs_val.into_pointer_value(), None);
             let rhs_idx = call_ndarray_calc_broadcast_index(generator, ctx, rhs, idx);
 
             unsafe { rhs.data().get_unchecked(ctx, generator, &rhs_idx, None) }
@@ -704,9 +616,7 @@ fn llvm_arraylike_get_ndims<'ctx, G: CodeGenerator + ?Sized>(
         BasicValueEnum::PointerValue(v)
             if NDArrayValue::is_representable(v, llvm_usize).is_ok() =>
         {
-            let dtype = arraylike_flatten_element_type(&mut ctx.unifier, ty);
-            let llvm_elem_ty = ctx.get_llvm_type(generator, dtype);
-            NDArrayValue::from_pointer_value(v, llvm_elem_ty, llvm_usize, None).load_ndims(ctx)
+            NDArrayType::from_unifier_type(generator, ctx, ty).map_value(v, None).load_ndims(ctx)
         }
 
         BasicValueEnum::PointerValue(v) if ListValue::is_representable(v, llvm_usize).is_ok() => {
@@ -857,7 +767,7 @@ fn call_ndarray_array_impl<'ctx, G: CodeGenerator + ?Sized>(
     // object is an NDArray instance - copy object unless copy=0 && ndmin < object.ndims
     if NDArrayValue::is_representable(object, llvm_usize).is_ok() {
         let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-        let object = NDArrayValue::from_pointer_value(object, llvm_elem_ty, llvm_usize, None);
+        let object = NDArrayValue::from_pointer_value(object, llvm_elem_ty, None, llvm_usize, None);
 
         let ndarray = gen_if_else_expr_callback(
             generator,
@@ -933,6 +843,7 @@ fn call_ndarray_array_impl<'ctx, G: CodeGenerator + ?Sized>(
         return Ok(NDArrayValue::from_pointer_value(
             ndarray.map(BasicValueEnum::into_pointer_value).unwrap(),
             llvm_elem_ty,
+            None,
             llvm_usize,
             None,
         ));
@@ -1126,7 +1037,7 @@ fn call_ndarray_eye_impl<'ctx, G: CodeGenerator + ?Sized>(
 
 /// Copies a slice of an [`NDArrayValue`] to another.
 ///
-/// - `dst_arr`: The [`NDArrayValue`] instance of the destination array. The `ndims` and `dim_sz`
+/// - `dst_arr`: The [`NDArrayValue`] instance of the destination array. The `ndims` and `shape`
 ///   fields should be populated before calling this function.
 /// - `dst_slice_ptr`: The [`PointerValue`] to the first element of the currently processing
 ///   dimensional slice in the destination array.
@@ -1270,85 +1181,86 @@ pub fn ndarray_sliced_copy<'ctx, G: CodeGenerator + ?Sized>(
 ) -> Result<NDArrayValue<'ctx>, String> {
     let llvm_i32 = ctx.ctx.i32_type();
     let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
 
-    let ndarray = if slices.is_empty() {
-        create_ndarray_dyn_shape(
-            generator,
-            ctx,
-            elem_ty,
-            &this,
-            |_, ctx, shape| Ok(shape.load_ndims(ctx)),
-            |generator, ctx, shape, idx| unsafe {
-                Ok(shape.shape().get_typed_unchecked(ctx, generator, &idx, None))
-            },
-        )?
-    } else {
-        let ndarray = create_ndarray_uninitialized(generator, ctx, elem_ty)?;
-        ndarray.store_ndims(ctx, generator, this.load_ndims(ctx));
+    let ndarray =
+        if slices.is_empty() {
+            create_ndarray_dyn_shape(
+                generator,
+                ctx,
+                elem_ty,
+                &this,
+                |_, ctx, shape| Ok(shape.load_ndims(ctx)),
+                |generator, ctx, shape, idx| unsafe {
+                    Ok(shape.shape().get_typed_unchecked(ctx, generator, &idx, None))
+                },
+            )?
+        } else {
+            let ndarray = NDArrayType::new(generator, ctx.ctx, llvm_elem_ty, None)
+                .construct_dyn_ndims(generator, ctx, this.load_ndims(ctx), None);
 
-        let ndims = this.load_ndims(ctx);
-        ndarray.create_shape(ctx, llvm_usize, ndims);
+            // Populate the first slices.len() dimensions by computing the size of each dim slice
+            for (i, (start, stop, step)) in slices.iter().enumerate() {
+                // HACK: workaround calculate_len_for_slice_range requiring exclusive stop
+                let stop = ctx
+                    .builder
+                    .build_select(
+                        ctx.builder
+                            .build_int_compare(
+                                IntPredicate::SLT,
+                                *step,
+                                llvm_i32.const_zero(),
+                                "is_neg",
+                            )
+                            .unwrap(),
+                        ctx.builder
+                            .build_int_sub(*stop, llvm_i32.const_int(1, true), "e_min_one")
+                            .unwrap(),
+                        ctx.builder
+                            .build_int_add(*stop, llvm_i32.const_int(1, true), "e_add_one")
+                            .unwrap(),
+                        "final_e",
+                    )
+                    .map(BasicValueEnum::into_int_value)
+                    .unwrap();
 
-        // Populate the first slices.len() dimensions by computing the size of each dim slice
-        for (i, (start, stop, step)) in slices.iter().enumerate() {
-            // HACK: workaround calculate_len_for_slice_range requiring exclusive stop
-            let stop = ctx
-                .builder
-                .build_select(
-                    ctx.builder
-                        .build_int_compare(
-                            IntPredicate::SLT,
-                            *step,
-                            llvm_i32.const_zero(),
-                            "is_neg",
-                        )
-                        .unwrap(),
-                    ctx.builder
-                        .build_int_sub(*stop, llvm_i32.const_int(1, true), "e_min_one")
-                        .unwrap(),
-                    ctx.builder
-                        .build_int_add(*stop, llvm_i32.const_int(1, true), "e_add_one")
-                        .unwrap(),
-                    "final_e",
-                )
-                .map(BasicValueEnum::into_int_value)
-                .unwrap();
+                let slice_len = calculate_len_for_slice_range(generator, ctx, *start, stop, *step);
+                let slice_len =
+                    ctx.builder.build_int_z_extend_or_bit_cast(slice_len, llvm_usize, "").unwrap();
 
-            let slice_len = calculate_len_for_slice_range(generator, ctx, *start, stop, *step);
-            let slice_len =
-                ctx.builder.build_int_z_extend_or_bit_cast(slice_len, llvm_usize, "").unwrap();
-
-            unsafe {
-                ndarray.shape().set_typed_unchecked(
-                    ctx,
-                    generator,
-                    &llvm_usize.const_int(i as u64, false),
-                    slice_len,
-                );
-            }
-        }
-
-        // Populate the rest by directly copying the dim size from the source array
-        gen_for_callback_incrementing(
-            generator,
-            ctx,
-            None,
-            llvm_usize.const_int(slices.len() as u64, false),
-            (this.load_ndims(ctx), false),
-            |generator, ctx, _, idx| {
                 unsafe {
-                    let dim_sz = this.shape().get_typed_unchecked(ctx, generator, &idx, None);
-                    ndarray.shape().set_typed_unchecked(ctx, generator, &idx, dim_sz);
+                    ndarray.shape().set_typed_unchecked(
+                        ctx,
+                        generator,
+                        &llvm_usize.const_int(i as u64, false),
+                        slice_len,
+                    );
                 }
+            }
 
-                Ok(())
-            },
-            llvm_usize.const_int(1, false),
-        )
-        .unwrap();
+            // Populate the rest by directly copying the dim size from the source array
+            gen_for_callback_incrementing(
+                generator,
+                ctx,
+                None,
+                llvm_usize.const_int(slices.len() as u64, false),
+                (this.load_ndims(ctx), false),
+                |generator, ctx, _, idx| {
+                    unsafe {
+                        let shape = this.shape().get_typed_unchecked(ctx, generator, &idx, None);
+                        ndarray.shape().set_typed_unchecked(ctx, generator, &idx, shape);
+                    }
 
-        ndarray_init_data(generator, ctx, elem_ty, ndarray)
-    };
+                    Ok(())
+                },
+                llvm_usize.const_int(1, false),
+            )
+            .unwrap();
+
+            unsafe { ndarray.create_data(generator, ctx) };
+
+            ndarray
+        };
 
     ndarray_sliced_copyto_impl(
         generator,
@@ -1447,8 +1359,6 @@ where
         (BasicValueEnum<'ctx>, BasicValueEnum<'ctx>),
     ) -> Result<BasicValueEnum<'ctx>, String>,
 {
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-
     let (lhs_ty, lhs_val, lhs_scalar) = lhs;
     let (rhs_ty, rhs_val, rhs_scalar) = rhs;
 
@@ -1461,22 +1371,10 @@ where
 
     let ndarray = res.unwrap_or_else(|| {
         if lhs_scalar && rhs_scalar {
-            let lhs_dtype = arraylike_flatten_element_type(&mut ctx.unifier, lhs_ty);
-            let llvm_lhs_elem_ty = ctx.get_llvm_type(generator, lhs_dtype);
-            let lhs_val = NDArrayValue::from_pointer_value(
-                lhs_val.into_pointer_value(),
-                llvm_lhs_elem_ty,
-                llvm_usize,
-                None,
-            );
-            let rhs_dtype = arraylike_flatten_element_type(&mut ctx.unifier, rhs_ty);
-            let llvm_rhs_elem_ty = ctx.get_llvm_type(generator, rhs_dtype);
-            let rhs_val = NDArrayValue::from_pointer_value(
-                rhs_val.into_pointer_value(),
-                llvm_rhs_elem_ty,
-                llvm_usize,
-                None,
-            );
+            let lhs_val = NDArrayType::from_unifier_type(generator, ctx, lhs_ty)
+                .map_value(lhs_val.into_pointer_value(), None);
+            let rhs_val = NDArrayType::from_unifier_type(generator, ctx, rhs_ty)
+                .map_value(rhs_val.into_pointer_value(), None);
 
             let ndarray_dims = call_ndarray_calc_broadcast(generator, ctx, lhs_val, rhs_val);
 
@@ -1492,17 +1390,12 @@ where
             )
             .unwrap()
         } else {
-            let dtype = arraylike_flatten_element_type(
-                &mut ctx.unifier,
+            let ndarray = NDArrayType::from_unifier_type(
+                generator,
+                ctx,
                 if lhs_scalar { rhs_ty } else { lhs_ty },
-            );
-            let llvm_elem_ty = ctx.get_llvm_type(generator, dtype);
-            let ndarray = NDArrayValue::from_pointer_value(
-                if lhs_scalar { rhs_val } else { lhs_val }.into_pointer_value(),
-                llvm_elem_ty,
-                llvm_usize,
-                None,
-            );
+            )
+            .map_value(if lhs_scalar { rhs_val } else { lhs_val }.into_pointer_value(), None);
 
             create_ndarray_dyn_shape(
                 generator,
@@ -2046,25 +1939,18 @@ pub fn gen_ndarray_copy<'ctx>(
     assert!(obj.is_some());
     assert!(args.is_empty());
 
-    let llvm_usize = generator.get_size_type(context.ctx);
-
     let this_ty = obj.as_ref().unwrap().0;
     let (this_elem_ty, _) = unpack_ndarray_var_tys(&mut context.unifier, this_ty);
     let this_arg =
         obj.as_ref().unwrap().1.clone().to_basic_value_enum(context, generator, this_ty)?;
 
-    let llvm_elem_ty = context.get_llvm_type(generator, this_elem_ty);
+    let llvm_this_ty = NDArrayType::from_unifier_type(generator, context, this_ty);
 
     ndarray_copy_impl(
         generator,
         context,
         this_elem_ty,
-        NDArrayValue::from_pointer_value(
-            this_arg.into_pointer_value(),
-            llvm_elem_ty,
-            llvm_usize,
-            None,
-        ),
+        llvm_this_ty.map_value(this_arg.into_pointer_value(), None),
     )
     .map(NDArrayValue::into)
 }
@@ -2080,10 +1966,7 @@ pub fn gen_ndarray_fill<'ctx>(
     assert!(obj.is_some());
     assert_eq!(args.len(), 1);
 
-    let llvm_usize = generator.get_size_type(context.ctx);
-
     let this_ty = obj.as_ref().unwrap().0;
-    let this_elem_ty = arraylike_flatten_element_type(&mut context.unifier, this_ty);
     let this_arg = obj
         .as_ref()
         .unwrap()
@@ -2094,12 +1977,12 @@ pub fn gen_ndarray_fill<'ctx>(
     let value_ty = fun.0.args[0].ty;
     let value_arg = args[0].1.clone().to_basic_value_enum(context, generator, value_ty)?;
 
-    let llvm_elem_ty = context.get_llvm_type(generator, this_elem_ty);
+    let llvm_this_ty = NDArrayType::from_unifier_type(generator, context, this_ty);
 
     ndarray_fill_flattened(
         generator,
         context,
-        NDArrayValue::from_pointer_value(this_arg, llvm_elem_ty, llvm_usize, None),
+        llvm_this_ty.map_value(this_arg, None),
         |generator, ctx, _| {
             let value = if value_arg.is_pointer_value() {
                 let llvm_i1 = ctx.ctx.bool_type();
@@ -2132,16 +2015,16 @@ pub fn gen_ndarray_fill<'ctx>(
 pub fn ndarray_transpose<'ctx, G: CodeGenerator + ?Sized>(
     generator: &mut G,
     ctx: &mut CodeGenContext<'ctx, '_>,
-    x1: (Type, BasicValueEnum<'ctx>),
+    (x1_ty, x1): (Type, BasicValueEnum<'ctx>),
 ) -> Result<BasicValueEnum<'ctx>, String> {
     const FN_NAME: &str = "ndarray_transpose";
-    let (x1_ty, x1) = x1;
+
     let llvm_usize = generator.get_size_type(ctx.ctx);
 
     if let BasicValueEnum::PointerValue(n1) = x1 {
+        let llvm_ndarray_ty = NDArrayType::from_unifier_type(generator, ctx, x1_ty);
         let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
-        let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-        let n1 = NDArrayValue::from_pointer_value(n1, llvm_elem_ty, llvm_usize, None);
+        let n1 = llvm_ndarray_ty.map_value(n1, None);
         let n_sz = call_ndarray_calc_size(generator, ctx, &n1.shape(), (None, None));
 
         // Dimensions are reversed in the transposed array
@@ -2260,8 +2143,8 @@ pub fn ndarray_reshape<'ctx, G: CodeGenerator + ?Sized>(
 
     if let BasicValueEnum::PointerValue(n1) = x1 {
         let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
-        let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-        let n1 = NDArrayValue::from_pointer_value(n1, llvm_elem_ty, llvm_usize, None);
+        let llvm_ndarray_ty = NDArrayType::from_unifier_type(generator, ctx, x1_ty);
+        let n1 = llvm_ndarray_ty.map_value(n1, None);
         let n_sz = call_ndarray_calc_size(generator, ctx, &n1.shape(), (None, None));
 
         let acc = generator.gen_var_alloc(ctx, llvm_usize.into(), None)?;
@@ -2544,13 +2427,8 @@ pub fn ndarray_dot<'ctx, G: CodeGenerator + ?Sized>(
 
     match (x1, x2) {
         (BasicValueEnum::PointerValue(n1), BasicValueEnum::PointerValue(n2)) => {
-            let n1_dtype = arraylike_flatten_element_type(&mut ctx.unifier, x1_ty);
-            let n2_dtype = arraylike_flatten_element_type(&mut ctx.unifier, x2_ty);
-            let llvm_n1_data_ty = ctx.get_llvm_type(generator, n1_dtype);
-            let llvm_n2_data_ty = ctx.get_llvm_type(generator, n2_dtype);
-
-            let n1 = NDArrayValue::from_pointer_value(n1, llvm_n1_data_ty, llvm_usize, None);
-            let n2 = NDArrayValue::from_pointer_value(n2, llvm_n2_data_ty, llvm_usize, None);
+            let n1 = NDArrayType::from_unifier_type(generator, ctx, x1_ty).map_value(n1, None);
+            let n2 = NDArrayType::from_unifier_type(generator, ctx, x2_ty).map_value(n2, None);
 
             let n1_sz = call_ndarray_calc_size(generator, ctx, &n1.shape(), (None, None));
             let n2_sz = call_ndarray_calc_size(generator, ctx, &n1.shape(), (None, None));

nac3core/src/codegen/test.rs

@@ -17,7 +17,7 @@ use parking_lot::RwLock;
 
 use super::{
     concrete_type::ConcreteTypeStore,
-    types::{ListType, NDArrayType, ProxyType, RangeType},
+    types::{ndarray::NDArrayType, ListType, ProxyType, RangeType},
     CodeGenContext, CodeGenLLVMOptions, CodeGenTargetMachineOptions, CodeGenTask, CodeGenerator,
     DefaultCodeGenerator, WithCall, WorkerRegistry,
 };
@@ -471,6 +471,6 @@ fn test_classes_ndarray_type_new() {
     let llvm_i32 = ctx.i32_type();
     let llvm_usize = generator.get_size_type(&ctx);
 
-    let llvm_ndarray = NDArrayType::new(&generator, &ctx, llvm_i32.into());
+    let llvm_ndarray = NDArrayType::new(&generator, &ctx, llvm_i32.into(), None);
     assert!(NDArrayType::is_representable(llvm_ndarray.as_base_type(), llvm_usize).is_ok());
 }

nac3core/src/codegen/types/mod.rs

@@ -23,13 +23,13 @@ use super::{
     {CodeGenContext, CodeGenerator},
 };
 pub use list::*;
-pub use ndarray::*;
 pub use range::*;
 
 mod list;
-mod ndarray;
+pub mod ndarray;
 mod range;
 pub mod structure;
+pub mod utils;
 
 /// A LLVM type that is used to represent a corresponding type in NAC3.
 pub trait ProxyType<'ctx>: Into<Self::Base> {

nac3core/src/codegen/types/ndarray/contiguous.rs

@@ -0,0 +1,257 @@
+use inkwell::{
+    context::Context,
+    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
+    values::{IntValue, PointerValue},
+    AddressSpace,
+};
+use itertools::Itertools;
+
+use nac3core_derive::StructFields;
+
+use crate::{
+    codegen::{
+        types::{
+            structure::{
+                check_struct_type_matches_fields, FieldIndexCounter, StructField, StructFields,
+            },
+            ProxyType,
+        },
+        values::{ndarray::ContiguousNDArrayValue, ArraySliceValue, ProxyValue},
+        CodeGenContext, CodeGenerator,
+    },
+    toplevel::numpy::unpack_ndarray_var_tys,
+    typecheck::typedef::Type,
+};
+
+#[derive(Debug, PartialEq, Eq, Clone, Copy)]
+pub struct ContiguousNDArrayType<'ctx> {
+    ty: PointerType<'ctx>,
+    item: BasicTypeEnum<'ctx>,
+    llvm_usize: IntType<'ctx>,
+}
+
+#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
+pub struct ContiguousNDArrayFields<'ctx> {
+    #[value_type(usize)]
+    pub ndims: StructField<'ctx, IntValue<'ctx>>,
+    #[value_type(usize.ptr_type(AddressSpace::default()))]
+    pub shape: StructField<'ctx, PointerValue<'ctx>>,
+    #[value_type(i8_type().ptr_type(AddressSpace::default()))]
+    pub data: StructField<'ctx, PointerValue<'ctx>>,
+}
+
+impl<'ctx> ContiguousNDArrayFields<'ctx> {
+    #[must_use]
+    pub fn new_typed(item: BasicTypeEnum<'ctx>, llvm_usize: IntType<'ctx>) -> Self {
+        let mut counter = FieldIndexCounter::default();
+
+        ContiguousNDArrayFields {
+            ndims: StructField::create(&mut counter, "ndims", llvm_usize),
+            shape: StructField::create(
+                &mut counter,
+                "shape",
+                llvm_usize.ptr_type(AddressSpace::default()),
+            ),
+            data: StructField::create(&mut counter, "data", item.ptr_type(AddressSpace::default())),
+        }
+    }
+}
+
+impl<'ctx> ContiguousNDArrayType<'ctx> {
+    /// Checks whether `llvm_ty` represents a `ndarray` type, returning [Err] if it does not.
+    pub fn is_representable(
+        llvm_ty: PointerType<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> Result<(), String> {
+        let ctx = llvm_ty.get_context();
+
+        let llvm_ty = llvm_ty.get_element_type();
+        let AnyTypeEnum::StructType(llvm_ty) = llvm_ty else {
+            return Err(format!(
+                "Expected struct type for `ContiguousNDArray` type, got {llvm_ty}"
+            ));
+        };
+
+        let fields = ContiguousNDArrayFields::new(ctx, llvm_usize);
+
+        check_struct_type_matches_fields(
+            fields,
+            llvm_ty,
+            "ContiguousNDArray",
+            &[(fields.data.name(), &|ty| {
+                if ty.is_pointer_type() {
+                    Ok(())
+                } else {
+                    Err(format!("Expected T* for `ContiguousNDArray.data`, got {ty}"))
+                }
+            })],
+        )
+    }
+
+    /// Returns an instance of [`StructFields`] containing all field accessors for this type.
+    #[must_use]
+    fn fields(
+        item: BasicTypeEnum<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> ContiguousNDArrayFields<'ctx> {
+        ContiguousNDArrayFields::new_typed(item, llvm_usize)
+    }
+
+    /// See [`NDArrayType::fields`].
+    // TODO: Move this into e.g. StructProxyType
+    #[must_use]
+    pub fn get_fields(&self) -> ContiguousNDArrayFields<'ctx> {
+        Self::fields(self.item, self.llvm_usize)
+    }
+
+    /// Creates an LLVM type corresponding to the expected structure of an `NDArray`.
+    #[must_use]
+    fn llvm_type(
+        ctx: &'ctx Context,
+        item: BasicTypeEnum<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> PointerType<'ctx> {
+        let field_tys =
+            Self::fields(item, llvm_usize).into_iter().map(|field| field.1).collect_vec();
+
+        ctx.struct_type(&field_tys, false).ptr_type(AddressSpace::default())
+    }
+
+    /// Creates an instance of [`ContiguousNDArrayType`].
+    #[must_use]
+    pub fn new<G: CodeGenerator + ?Sized>(
+        generator: &G,
+        ctx: &'ctx Context,
+        item: BasicTypeEnum<'ctx>,
+    ) -> Self {
+        let llvm_usize = generator.get_size_type(ctx);
+        let llvm_cndarray = Self::llvm_type(ctx, item, llvm_usize);
+
+        Self { ty: llvm_cndarray, item, llvm_usize }
+    }
+
+    /// Creates an [`ContiguousNDArrayType`] from a [unifier type][Type].
+    #[must_use]
+    pub fn from_unifier_type<G: CodeGenerator + ?Sized>(
+        generator: &G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ty: Type,
+    ) -> Self {
+        let (dtype, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ty);
+
+        let llvm_dtype = ctx.get_llvm_type(generator, dtype);
+        let llvm_usize = generator.get_size_type(ctx.ctx);
+
+        Self { ty: Self::llvm_type(ctx.ctx, llvm_dtype, llvm_usize), item: llvm_dtype, llvm_usize }
+    }
+
+    /// Creates an [`ContiguousNDArrayType`] from a [`PointerType`] representing an `NDArray`.
+    #[must_use]
+    pub fn from_type(
+        ptr_ty: PointerType<'ctx>,
+        item: BasicTypeEnum<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> Self {
+        debug_assert!(Self::is_representable(ptr_ty, llvm_usize).is_ok());
+
+        Self { ty: ptr_ty, item, llvm_usize }
+    }
+
+    /// Allocates an instance of [`ContiguousNDArrayValue`] as if by calling `alloca` on the base type.
+    #[must_use]
+    pub fn alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            self.raw_alloca(generator, ctx, name),
+            self.item,
+            self.llvm_usize,
+            name,
+        )
+    }
+
+    /// Converts an existing value into a [`ContiguousNDArrayValue`].
+    #[must_use]
+    pub fn map_value(
+        &self,
+        value: <<Self as ProxyType<'ctx>>::Value as ProxyValue<'ctx>>::Base,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            value,
+            self.item,
+            self.llvm_usize,
+            name,
+        )
+    }
+}
+
+impl<'ctx> ProxyType<'ctx> for ContiguousNDArrayType<'ctx> {
+    type Base = PointerType<'ctx>;
+    type Value = ContiguousNDArrayValue<'ctx>;
+
+    fn is_type<G: CodeGenerator + ?Sized>(
+        generator: &G,
+        ctx: &'ctx Context,
+        llvm_ty: impl BasicType<'ctx>,
+    ) -> Result<(), String> {
+        if let BasicTypeEnum::PointerType(ty) = llvm_ty.as_basic_type_enum() {
+            <Self as ProxyType<'ctx>>::is_representable(generator, ctx, ty)
+        } else {
+            Err(format!("Expected pointer type, got {llvm_ty:?}"))
+        }
+    }
+
+    fn is_representable<G: CodeGenerator + ?Sized>(
+        generator: &G,
+        ctx: &'ctx Context,
+        llvm_ty: Self::Base,
+    ) -> Result<(), String> {
+        Self::is_representable(llvm_ty, generator.get_size_type(ctx))
+    }
+
+    fn raw_alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self::Value as ProxyValue<'ctx>>::Base {
+        generator
+            .gen_var_alloc(
+                ctx,
+                self.as_base_type().get_element_type().into_struct_type().into(),
+                name,
+            )
+            .unwrap()
+    }
+
+    fn array_alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        size: IntValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> ArraySliceValue<'ctx> {
+        generator
+            .gen_array_var_alloc(
+                ctx,
+                self.as_base_type().get_element_type().into_struct_type().into(),
+                size,
+                name,
+            )
+            .unwrap()
+    }
+
+    fn as_base_type(&self) -> Self::Base {
+        self.ty
+    }
+}
+
+impl<'ctx> From<ContiguousNDArrayType<'ctx>> for PointerType<'ctx> {
+    fn from(value: ContiguousNDArrayType<'ctx>) -> Self {
+        value.as_base_type()
+    }
+}

nac3core/src/codegen/types/ndarray/indexing.rs

@@ -0,0 +1,215 @@
+use inkwell::{
+    context::{AsContextRef, Context},
+    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
+    values::{IntValue, PointerValue},
+    AddressSpace,
+};
+use itertools::Itertools;
+
+use nac3core_derive::StructFields;
+
+use crate::codegen::{
+    types::{
+        structure::{check_struct_type_matches_fields, StructField, StructFields},
+        ProxyType,
+    },
+    values::{
+        ndarray::{NDIndexValue, RustNDIndex},
+        ArrayLikeIndexer, ArraySliceValue, ProxyValue,
+    },
+    CodeGenContext, CodeGenerator,
+};
+
+#[derive(Debug, PartialEq, Eq, Clone, Copy)]
+pub struct NDIndexType<'ctx> {
+    ty: PointerType<'ctx>,
+    llvm_usize: IntType<'ctx>,
+}
+
+#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
+pub struct NDIndexStructFields<'ctx> {
+    #[value_type(i8_type())]
+    pub type_: StructField<'ctx, IntValue<'ctx>>,
+    #[value_type(i8_type().ptr_type(AddressSpace::default()))]
+    pub data: StructField<'ctx, PointerValue<'ctx>>,
+}
+
+impl<'ctx> NDIndexType<'ctx> {
+    /// Checks whether `llvm_ty` represents a `ndindex` type, returning [Err] if it does not.
+    pub fn is_representable(
+        llvm_ty: PointerType<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> Result<(), String> {
+        let ctx = llvm_ty.get_context();
+
+        let llvm_ty = llvm_ty.get_element_type();
+        let AnyTypeEnum::StructType(llvm_ty) = llvm_ty else {
+            return Err(format!(
+                "Expected struct type for `ContiguousNDArray` type, got {llvm_ty}"
+            ));
+        };
+
+        let fields = NDIndexStructFields::new(ctx, llvm_usize);
+
+        check_struct_type_matches_fields(fields, llvm_ty, "NDIndex", &[])
+    }
+
+    #[must_use]
+    fn fields(
+        ctx: impl AsContextRef<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> NDIndexStructFields<'ctx> {
+        NDIndexStructFields::new(ctx, llvm_usize)
+    }
+
+    #[must_use]
+    pub fn get_fields(&self) -> NDIndexStructFields<'ctx> {
+        Self::fields(self.ty.get_context(), self.llvm_usize)
+    }
+
+    #[must_use]
+    fn llvm_type(ctx: &'ctx Context, llvm_usize: IntType<'ctx>) -> PointerType<'ctx> {
+        let field_tys =
+            Self::fields(ctx, llvm_usize).into_iter().map(|field| field.1).collect_vec();
+
+        ctx.struct_type(&field_tys, false).ptr_type(AddressSpace::default())
+    }
+
+    #[must_use]
+    pub fn new<G: CodeGenerator + ?Sized>(generator: &G, ctx: &'ctx Context) -> Self {
+        let llvm_usize = generator.get_size_type(ctx);
+        let llvm_ndindex = Self::llvm_type(ctx, llvm_usize);
+
+        Self { ty: llvm_ndindex, llvm_usize }
+    }
+
+    #[must_use]
+    pub fn from_type(ptr_ty: PointerType<'ctx>, llvm_usize: IntType<'ctx>) -> Self {
+        debug_assert!(Self::is_representable(ptr_ty, llvm_usize).is_ok());
+
+        Self { ty: ptr_ty, llvm_usize }
+    }
+
+    #[must_use]
+    pub fn alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            self.raw_alloca(generator, ctx, name),
+            self.llvm_usize,
+            name,
+        )
+    }
+
+    /// Serialize a list of [`RustNDIndex`] as a newly allocated LLVM array of [`NDIndexValue`].
+    #[must_use]
+    pub fn construct_ndindices<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        in_ndindices: &[RustNDIndex<'ctx>],
+    ) -> ArraySliceValue<'ctx> {
+        // Allocate the LLVM ndindices.
+        let num_ndindices = self.llvm_usize.const_int(in_ndindices.len() as u64, false);
+        let ndindices = self.array_alloca(generator, ctx, num_ndindices, None);
+
+        // Initialize all of them.
+        for (i, in_ndindex) in in_ndindices.iter().enumerate() {
+            let pndindex = unsafe {
+                ndindices.ptr_offset_unchecked(
+                    ctx,
+                    generator,
+                    &ctx.ctx.i64_type().const_int(u64::try_from(i).unwrap(), false),
+                    None,
+                )
+            };
+
+            in_ndindex.write_to_ndindex(
+                generator,
+                ctx,
+                NDIndexValue::from_pointer_value(pndindex, self.llvm_usize, None),
+            );
+        }
+
+        ndindices
+    }
+
+    #[must_use]
+    pub fn map_value(
+        &self,
+        value: <<Self as ProxyType<'ctx>>::Value as ProxyValue<'ctx>>::Base,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(value, self.llvm_usize, name)
+    }
+}
+
+impl<'ctx> ProxyType<'ctx> for NDIndexType<'ctx> {
+    type Base = PointerType<'ctx>;
+    type Value = NDIndexValue<'ctx>;
+
+    fn is_type<G: CodeGenerator + ?Sized>(
+        generator: &G,
+        ctx: &'ctx Context,
+        llvm_ty: impl BasicType<'ctx>,
+    ) -> Result<(), String> {
+        if let BasicTypeEnum::PointerType(ty) = llvm_ty.as_basic_type_enum() {
+            <Self as ProxyType<'ctx>>::is_representable(generator, ctx, ty)
+        } else {
+            Err(format!("Expected pointer type, got {llvm_ty:?}"))
+        }
+    }
+
+    fn is_representable<G: CodeGenerator + ?Sized>(
+        generator: &G,
+        ctx: &'ctx Context,
+        llvm_ty: Self::Base,
+    ) -> Result<(), String> {
+        Self::is_representable(llvm_ty, generator.get_size_type(ctx))
+    }
+
+    fn raw_alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self::Value as ProxyValue<'ctx>>::Base {
+        generator
+            .gen_var_alloc(
+                ctx,
+                self.as_base_type().get_element_type().into_struct_type().into(),
+                name,
+            )
+            .unwrap()
+    }
+
+    fn array_alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        size: IntValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> ArraySliceValue<'ctx> {
+        generator
+            .gen_array_var_alloc(
+                ctx,
+                self.as_base_type().get_element_type().into_struct_type().into(),
+                size,
+                name,
+            )
+            .unwrap()
+    }
+
+    fn as_base_type(&self) -> Self::Base {
+        self.ty
+    }
+}
+
+impl<'ctx> From<NDIndexType<'ctx>> for PointerType<'ctx> {
+    fn from(value: NDIndexType<'ctx>) -> Self {
+        value.as_base_type()
+    }
+}

nac3core/src/codegen/types/ndarray/mod.rs

@@ -1,7 +1,7 @@
 use inkwell::{
-    context::Context,
+    context::{AsContextRef, Context},
     types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
-    values::{IntValue, PointerValue},
+    values::{BasicValue, IntValue, PointerValue},
     AddressSpace,
 };
 use itertools::Itertools;
@@ -9,28 +9,49 @@ use itertools::Itertools;
 use nac3core_derive::StructFields;
 
 use super::{
-    structure::{StructField, StructFields},
+    structure::{check_struct_type_matches_fields, StructField, StructFields},
     ProxyType,
 };
-use crate::codegen::{
-    values::{ArraySliceValue, NDArrayValue, ProxyValue},
-    {CodeGenContext, CodeGenerator},
+use crate::{
+    codegen::{
+        values::{ndarray::NDArrayValue, ArraySliceValue, ProxyValue, TypedArrayLikeMutator},
+        {CodeGenContext, CodeGenerator},
+    },
+    toplevel::{helper::extract_ndims, numpy::unpack_ndarray_var_tys},
+    typecheck::typedef::Type,
 };
+pub use contiguous::*;
+pub use indexing::*;
+pub use nditer::*;
+
+mod contiguous;
+mod indexing;
+mod nditer;
 
 /// Proxy type for a `ndarray` type in LLVM.
 #[derive(Debug, PartialEq, Eq, Clone, Copy)]
 pub struct NDArrayType<'ctx> {
     ty: PointerType<'ctx>,
     dtype: BasicTypeEnum<'ctx>,
+    ndims: Option<u64>,
     llvm_usize: IntType<'ctx>,
 }
 
 #[derive(PartialEq, Eq, Clone, Copy, StructFields)]
 pub struct NDArrayStructFields<'ctx> {
+    /// The size of each `NDArray` element in bytes.
+    #[value_type(usize)]
+    pub itemsize: StructField<'ctx, IntValue<'ctx>>,
+    /// Number of dimensions in the array.
     #[value_type(usize)]
     pub ndims: StructField<'ctx, IntValue<'ctx>>,
+    /// Pointer to an array containing the shape of the `NDArray`.
     #[value_type(usize.ptr_type(AddressSpace::default()))]
     pub shape: StructField<'ctx, PointerValue<'ctx>>,
+    /// Pointer to an array indicating the number of bytes between each element at a dimension
+    #[value_type(usize.ptr_type(AddressSpace::default()))]
+    pub strides: StructField<'ctx, PointerValue<'ctx>>,
+    /// Pointer to an array containing the array data
     #[value_type(i8_type().ptr_type(AddressSpace::default()))]
     pub data: StructField<'ctx, PointerValue<'ctx>>,
 }
@@ -41,90 +62,40 @@ impl<'ctx> NDArrayType<'ctx> {
         llvm_ty: PointerType<'ctx>,
         llvm_usize: IntType<'ctx>,
     ) -> Result<(), String> {
+        let ctx = llvm_ty.get_context();
+
         let llvm_ndarray_ty = llvm_ty.get_element_type();
         let AnyTypeEnum::StructType(llvm_ndarray_ty) = llvm_ndarray_ty else {
             return Err(format!("Expected struct type for `NDArray` type, got {llvm_ndarray_ty}"));
         };
-        if llvm_ndarray_ty.count_fields() != 3 {
-            return Err(format!(
-                "Expected 3 fields in `NDArray`, got {}",
-                llvm_ndarray_ty.count_fields()
-            ));
-        }
 
-        let ndarray_ndims_ty = llvm_ndarray_ty.get_field_type_at_index(0).unwrap();
-        let Ok(ndarray_ndims_ty) = IntType::try_from(ndarray_ndims_ty) else {
-            return Err(format!("Expected int type for `ndarray.0`, got {ndarray_ndims_ty}"));
-        };
-        if ndarray_ndims_ty.get_bit_width() != llvm_usize.get_bit_width() {
-            return Err(format!(
-                "Expected {}-bit int type for `ndarray.0`, got {}-bit int",
-                llvm_usize.get_bit_width(),
-                ndarray_ndims_ty.get_bit_width()
-            ));
-        }
-
-        let ndarray_dims_ty = llvm_ndarray_ty.get_field_type_at_index(1).unwrap();
-        let Ok(ndarray_pdims) = PointerType::try_from(ndarray_dims_ty) else {
-            return Err(format!("Expected pointer type for `ndarray.1`, got {ndarray_dims_ty}"));
-        };
-        let ndarray_dims = ndarray_pdims.get_element_type();
-        let Ok(ndarray_dims) = IntType::try_from(ndarray_dims) else {
-            return Err(format!(
-                "Expected pointer-to-int type for `ndarray.1`, got pointer-to-{ndarray_dims}"
-            ));
-        };
-        if ndarray_dims.get_bit_width() != llvm_usize.get_bit_width() {
-            return Err(format!(
-                "Expected pointer-to-{}-bit int type for `ndarray.1`, got pointer-to-{}-bit int",
-                llvm_usize.get_bit_width(),
-                ndarray_dims.get_bit_width()
-            ));
-        }
-
-        let ndarray_data_ty = llvm_ndarray_ty.get_field_type_at_index(2).unwrap();
-        let Ok(ndarray_pdata) = PointerType::try_from(ndarray_data_ty) else {
-            return Err(format!("Expected pointer type for `ndarray.2`, got {ndarray_data_ty}"));
-        };
-        let ndarray_data = ndarray_pdata.get_element_type();
-        let Ok(ndarray_data) = IntType::try_from(ndarray_data) else {
-            return Err(format!(
-                "Expected pointer-to-int type for `ndarray.2`, got pointer-to-{ndarray_data}"
-            ));
-        };
-        if ndarray_data.get_bit_width() != 8 {
-            return Err(format!(
-                "Expected pointer-to-8-bit int type for `ndarray.1`, got pointer-to-{}-bit int",
-                ndarray_data.get_bit_width()
-            ));
-        }
-
-        Ok(())
+        check_struct_type_matches_fields(
+            Self::fields(ctx, llvm_usize),
+            llvm_ndarray_ty,
+            "NDArray",
+            &[],
+        )
     }
 
     /// Returns an instance of [`StructFields`] containing all field accessors for this type.
     #[must_use]
-    fn fields(ctx: &'ctx Context, llvm_usize: IntType<'ctx>) -> NDArrayStructFields<'ctx> {
+    fn fields(
+        ctx: impl AsContextRef<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> NDArrayStructFields<'ctx> {
         NDArrayStructFields::new(ctx, llvm_usize)
     }
 
     /// See [`NDArrayType::fields`].
     // TODO: Move this into e.g. StructProxyType
     #[must_use]
-    pub fn get_fields(&self, ctx: &'ctx Context) -> NDArrayStructFields<'ctx> {
+    pub fn get_fields(&self, ctx: impl AsContextRef<'ctx>) -> NDArrayStructFields<'ctx> {
         Self::fields(ctx, self.llvm_usize)
     }
 
     /// Creates an LLVM type corresponding to the expected structure of an `NDArray`.
     #[must_use]
     fn llvm_type(ctx: &'ctx Context, llvm_usize: IntType<'ctx>) -> PointerType<'ctx> {
-        // struct NDArray { num_dims: size_t, dims: size_t*, data: i8* }
-        //
-        // * data    : Pointer to an array containing the array data
-        // * itemsize: The size of each NDArray elements in bytes
-        // * ndims   : Number of dimensions in the array
-        // * shape   : Pointer to an array containing the shape of the NDArray
-        // * strides : Pointer to an array indicating the number of bytes between each element at a dimension
         let field_tys =
             Self::fields(ctx, llvm_usize).into_iter().map(|field| field.1).collect_vec();
 
@@ -137,11 +108,46 @@ impl<'ctx> NDArrayType<'ctx> {
         generator: &G,
         ctx: &'ctx Context,
         dtype: BasicTypeEnum<'ctx>,
+        ndims: Option<u64>,
     ) -> Self {
         let llvm_usize = generator.get_size_type(ctx);
         let llvm_ndarray = Self::llvm_type(ctx, llvm_usize);
 
-        NDArrayType { ty: llvm_ndarray, dtype, llvm_usize }
+        NDArrayType { ty: llvm_ndarray, dtype, ndims, llvm_usize }
+    }
+
+    /// Creates an instance of [`NDArrayType`] with `ndims` of 0.
+    #[must_use]
+    pub fn new_unsized<G: CodeGenerator + ?Sized>(
+        generator: &G,
+        ctx: &'ctx Context,
+        dtype: BasicTypeEnum<'ctx>,
+    ) -> Self {
+        let llvm_usize = generator.get_size_type(ctx);
+        let llvm_ndarray = Self::llvm_type(ctx, llvm_usize);
+
+        NDArrayType { ty: llvm_ndarray, dtype, ndims: Some(0), llvm_usize }
+    }
+
+    /// Creates an [`NDArrayType`] from a [unifier type][Type].
+    #[must_use]
+    pub fn from_unifier_type<G: CodeGenerator + ?Sized>(
+        generator: &G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ty: Type,
+    ) -> Self {
+        let (dtype, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, ty);
+
+        let llvm_dtype = ctx.get_llvm_type(generator, dtype);
+        let llvm_usize = generator.get_size_type(ctx.ctx);
+        let ndims = extract_ndims(&ctx.unifier, ndims);
+
+        NDArrayType {
+            ty: Self::llvm_type(ctx.ctx, llvm_usize),
+            dtype: llvm_dtype,
+            ndims: Some(ndims),
+            llvm_usize,
+        }
     }
 
     /// Creates an [`NDArrayType`] from a [`PointerType`] representing an `NDArray`.
@@ -149,22 +155,18 @@ impl<'ctx> NDArrayType<'ctx> {
     pub fn from_type(
         ptr_ty: PointerType<'ctx>,
         dtype: BasicTypeEnum<'ctx>,
+        ndims: Option<u64>,
         llvm_usize: IntType<'ctx>,
     ) -> Self {
         debug_assert!(Self::is_representable(ptr_ty, llvm_usize).is_ok());
 
-        NDArrayType { ty: ptr_ty, dtype, llvm_usize }
+        NDArrayType { ty: ptr_ty, dtype, ndims, llvm_usize }
     }
 
     /// Returns the type of the `size` field of this `ndarray` type.
     #[must_use]
     pub fn size_type(&self) -> IntType<'ctx> {
-        self.as_base_type()
-            .get_element_type()
-            .into_struct_type()
-            .get_field_type_at_index(0)
-            .map(BasicTypeEnum::into_int_type)
-            .unwrap()
+        self.llvm_usize
     }
 
     /// Returns the element type of this `ndarray` type.
@@ -173,6 +175,12 @@ impl<'ctx> NDArrayType<'ctx> {
         self.dtype
     }
 
+    /// Returns the number of dimensions of this `ndarray` type.
+    #[must_use]
+    pub fn ndims(&self) -> Option<u64> {
+        self.ndims
+    }
+
     /// Allocates an instance of [`NDArrayValue`] as if by calling `alloca` on the base type.
     #[must_use]
     pub fn alloca<G: CodeGenerator + ?Sized>(
@@ -184,11 +192,198 @@ impl<'ctx> NDArrayType<'ctx> {
         <Self as ProxyType<'ctx>>::Value::from_pointer_value(
             self.raw_alloca(generator, ctx, name),
             self.dtype,
+            self.ndims,
             self.llvm_usize,
             name,
         )
     }
 
+    /// Allocates an [`NDArrayValue`] on the stack and initializes all fields as follows:
+    ///
+    /// - `data`: uninitialized.
+    /// - `itemsize`: set to the size of `self.dtype`.
+    /// - `ndims`: set to the value of  `ndims`.
+    /// - `shape`: allocated on the stack with an array of length `ndims` with uninitialized values.
+    /// - `strides`: allocated on the stack with an array of length `ndims` with uninitialized
+    ///   values.
+    #[must_use]
+    fn construct_impl<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ndims: IntValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        let ndarray = self.alloca(generator, ctx, name);
+
+        let itemsize = ctx
+            .builder
+            .build_int_truncate_or_bit_cast(self.dtype.size_of().unwrap(), self.llvm_usize, "")
+            .unwrap();
+        ndarray.store_itemsize(ctx, generator, itemsize);
+
+        ndarray.store_ndims(ctx, generator, ndims);
+
+        ndarray.create_shape(ctx, self.llvm_usize, ndims);
+        ndarray.create_strides(ctx, self.llvm_usize, ndims);
+
+        ndarray
+    }
+
+    /// Allocate an [`NDArrayValue`] on the stack using `dtype` and `ndims` of this [`NDArrayType`]
+    /// instance.
+    ///
+    /// The returned ndarray's content will be:
+    /// - `data`: uninitialized.
+    /// - `itemsize`: set to the size of `dtype`.
+    /// - `ndims`: set to the value of `self.ndims`.
+    /// - `shape`: allocated on the stack with an array of length `ndims` with uninitialized values.
+    /// - `strides`: allocated on the stack with an array of length `ndims` with uninitialized
+    ///   values.
+    #[must_use]
+    pub fn construct_uninitialized<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        assert!(self.ndims.is_some(), "NDArrayType::construct can only be called on an instance with compile-time known ndims (self.ndims = Some(ndims))");
+
+        let Some(ndims) = self.ndims.map(|ndims| self.llvm_usize.const_int(ndims, false)) else {
+            unreachable!()
+        };
+
+        self.construct_impl(generator, ctx, ndims, name)
+    }
+
+    /// Allocate an [`NDArrayValue`] on the stack given its `ndims` and `dtype`.
+    ///
+    /// `shape` and `strides` will be automatically allocated onto the stack.
+    ///
+    /// The returned ndarray's content will be:
+    /// - `data`: uninitialized.
+    /// - `itemsize`: set to the size of `dtype`.
+    /// - `ndims`: set to the value of `ndims`.
+    /// - `shape`: allocated with an array of length `ndims` with uninitialized values.
+    /// - `strides`: allocated with an array of length `ndims` with uninitialized values.
+    #[deprecated = "Prefer construct_uninitialized or construct_*_shape."]
+    #[must_use]
+    pub fn construct_dyn_ndims<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ndims: IntValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        assert!(self.ndims.is_none(), "NDArrayType::construct_dyn_ndims can only be called on an instance with compile-time unknown ndims (self.ndims = None)");
+
+        self.construct_impl(generator, ctx, ndims, name)
+    }
+
+    /// Convenience function. Allocate an [`NDArrayValue`] with a statically known shape.
+    ///
+    /// The returned [`NDArrayValue`]'s `data` and `strides` are uninitialized.
+    #[must_use]
+    pub fn construct_const_shape<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        shape: &[u64],
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        assert!(self.ndims.is_none_or(|ndims| shape.len() as u64 == ndims));
+
+        let ndarray = Self::new(generator, ctx.ctx, self.dtype, Some(shape.len() as u64))
+            .construct_uninitialized(generator, ctx, name);
+
+        let llvm_usize = generator.get_size_type(ctx.ctx);
+
+        // Write shape
+        let ndarray_shape = ndarray.shape();
+        for (i, dim) in shape.iter().enumerate() {
+            let dim = llvm_usize.const_int(*dim, false);
+            unsafe {
+                ndarray_shape.set_typed_unchecked(
+                    ctx,
+                    generator,
+                    &llvm_usize.const_int(i as u64, false),
+                    dim,
+                );
+            }
+        }
+
+        ndarray
+    }
+
+    /// Convenience function. Allocate an [`NDArrayValue`] with a dynamically known shape.
+    ///
+    /// The returned [`NDArrayValue`]'s `data` and `strides` are uninitialized.
+    #[must_use]
+    pub fn construct_dyn_shape<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        shape: &[IntValue<'ctx>],
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        assert!(self.ndims.is_none_or(|ndims| shape.len() as u64 == ndims));
+
+        let ndarray = Self::new(generator, ctx.ctx, self.dtype, Some(shape.len() as u64))
+            .construct_uninitialized(generator, ctx, name);
+
+        let llvm_usize = generator.get_size_type(ctx.ctx);
+
+        // Write shape
+        let ndarray_shape = ndarray.shape();
+        for (i, dim) in shape.iter().enumerate() {
+            assert_eq!(
+                dim.get_type(),
+                llvm_usize,
+                "Expected {} but got {}",
+                llvm_usize.print_to_string(),
+                dim.get_type().print_to_string()
+            );
+            unsafe {
+                ndarray_shape.set_typed_unchecked(
+                    ctx,
+                    generator,
+                    &llvm_usize.const_int(i as u64, false),
+                    *dim,
+                );
+            }
+        }
+
+        ndarray
+    }
+
+    /// Create an unsized ndarray to contain `value`.
+    #[must_use]
+    pub fn construct_unsized<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        value: &impl BasicValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> NDArrayValue<'ctx> {
+        let value = value.as_basic_value_enum();
+
+        assert_eq!(value.get_type(), self.dtype);
+        assert!(self.ndims.is_none_or(|ndims| ndims == 0));
+
+        // We have to put the value on the stack to get a data pointer.
+        let data = ctx.builder.build_alloca(value.get_type(), "construct_unsized").unwrap();
+        ctx.builder.build_store(data, value).unwrap();
+        let data = ctx
+            .builder
+            .build_pointer_cast(data, ctx.ctx.i8_type().ptr_type(AddressSpace::default()), "")
+            .unwrap();
+
+        let ndarray = Self::new_unsized(generator, ctx.ctx, value.get_type())
+            .construct_uninitialized(generator, ctx, name);
+        ctx.builder.build_store(ndarray.ptr_to_data(ctx), data).unwrap();
+        ndarray
+    }
+
     /// Converts an existing value into a [`NDArrayValue`].
     #[must_use]
     pub fn map_value(
@@ -199,6 +394,7 @@ impl<'ctx> NDArrayType<'ctx> {
         <Self as ProxyType<'ctx>>::Value::from_pointer_value(
             value,
             self.dtype,
+            self.ndims,
             self.llvm_usize,
             name,
         )

nac3core/src/codegen/types/ndarray/nditer.rs

@@ -0,0 +1,241 @@
+use inkwell::{
+    context::{AsContextRef, Context},
+    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
+    values::{IntValue, PointerValue},
+    AddressSpace,
+};
+use itertools::Itertools;
+
+use nac3core_derive::StructFields;
+
+use super::ProxyType;
+use crate::codegen::{
+    irrt,
+    types::structure::{check_struct_type_matches_fields, StructField, StructFields},
+    values::{
+        ndarray::{NDArrayValue, NDIterValue},
+        ArraySliceValue, ProxyValue,
+    },
+    CodeGenContext, CodeGenerator,
+};
+
+#[derive(Debug, PartialEq, Eq, Clone, Copy)]
+pub struct NDIterType<'ctx> {
+    ty: PointerType<'ctx>,
+    llvm_usize: IntType<'ctx>,
+}
+
+#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
+pub struct NDIterStructFields<'ctx> {
+    #[value_type(usize)]
+    pub ndims: StructField<'ctx, IntValue<'ctx>>,
+    #[value_type(usize.ptr_type(AddressSpace::default()))]
+    pub shape: StructField<'ctx, PointerValue<'ctx>>,
+    #[value_type(usize.ptr_type(AddressSpace::default()))]
+    pub strides: StructField<'ctx, PointerValue<'ctx>>,
+    #[value_type(usize.ptr_type(AddressSpace::default()))]
+    pub indices: StructField<'ctx, PointerValue<'ctx>>,
+    #[value_type(usize)]
+    pub nth: StructField<'ctx, IntValue<'ctx>>,
+    #[value_type(i8_type().ptr_type(AddressSpace::default()))]
+    pub element: StructField<'ctx, PointerValue<'ctx>>,
+    #[value_type(usize)]
+    pub size: StructField<'ctx, IntValue<'ctx>>,
+}
+
+impl<'ctx> NDIterType<'ctx> {
+    /// Checks whether `llvm_ty` represents a `nditer` type, returning [Err] if it does not.
+    pub fn is_representable(
+        llvm_ty: PointerType<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> Result<(), String> {
+        let ctx = llvm_ty.get_context();
+
+        let llvm_ty = llvm_ty.get_element_type();
+        let AnyTypeEnum::StructType(llvm_ndarray_ty) = llvm_ty else {
+            return Err(format!("Expected struct type for `NDIter` type, got {llvm_ty}"));
+        };
+
+        check_struct_type_matches_fields(
+            Self::fields(ctx, llvm_usize),
+            llvm_ndarray_ty,
+            "NDIter",
+            &[],
+        )
+    }
+
+    /// Returns an instance of [`StructFields`] containing all field accessors for this type.
+    #[must_use]
+    fn fields(ctx: impl AsContextRef<'ctx>, llvm_usize: IntType<'ctx>) -> NDIterStructFields<'ctx> {
+        NDIterStructFields::new(ctx, llvm_usize)
+    }
+
+    /// See [`NDIterType::fields`].
+    // TODO: Move this into e.g. StructProxyType
+    #[must_use]
+    pub fn get_fields(&self, ctx: impl AsContextRef<'ctx>) -> NDIterStructFields<'ctx> {
+        Self::fields(ctx, self.llvm_usize)
+    }
+
+    /// Creates an LLVM type corresponding to the expected structure of an `NDIter`.
+    #[must_use]
+    fn llvm_type(ctx: &'ctx Context, llvm_usize: IntType<'ctx>) -> PointerType<'ctx> {
+        let field_tys =
+            Self::fields(ctx, llvm_usize).into_iter().map(|field| field.1).collect_vec();
+
+        ctx.struct_type(&field_tys, false).ptr_type(AddressSpace::default())
+    }
+
+    /// Creates an instance of [`NDIter`].
+    #[must_use]
+    pub fn new<G: CodeGenerator + ?Sized>(generator: &G, ctx: &'ctx Context) -> Self {
+        let llvm_usize = generator.get_size_type(ctx);
+        let llvm_nditer = Self::llvm_type(ctx, llvm_usize);
+
+        Self { ty: llvm_nditer, llvm_usize }
+    }
+
+    /// Creates an [`NDIterType`] from a [`PointerType`] representing an `NDIter`.
+    #[must_use]
+    pub fn from_type(ptr_ty: PointerType<'ctx>, llvm_usize: IntType<'ctx>) -> Self {
+        debug_assert!(Self::is_representable(ptr_ty, llvm_usize).is_ok());
+
+        Self { ty: ptr_ty, llvm_usize }
+    }
+
+    /// Returns the type of the `size` field of this `nditer` type.
+    #[must_use]
+    pub fn size_type(&self) -> IntType<'ctx> {
+        self.llvm_usize
+    }
+
+    #[must_use]
+    pub fn alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        parent: NDArrayValue<'ctx>,
+        indices: ArraySliceValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            self.raw_alloca(generator, ctx, name),
+            parent,
+            indices,
+            self.llvm_usize,
+            name,
+        )
+    }
+
+    /// Allocate an [`NDIter`] that iterates through the given `ndarray`.
+    #[must_use]
+    pub fn construct<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ndarray: NDArrayValue<'ctx>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        let nditer = self.raw_alloca(generator, ctx, None);
+        let ndims = ndarray.load_ndims(ctx);
+
+        // The caller has the responsibility to allocate 'indices' for `NDIter`.
+        let indices =
+            generator.gen_array_var_alloc(ctx, self.llvm_usize.into(), ndims, None).unwrap();
+
+        let nditer = <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            nditer,
+            ndarray,
+            indices,
+            self.llvm_usize,
+            None,
+        );
+
+        irrt::ndarray::call_nac3_nditer_initialize(generator, ctx, nditer, ndarray, indices);
+
+        nditer
+    }
+
+    #[must_use]
+    pub fn map_value(
+        &self,
+        value: <<Self as ProxyType<'ctx>>::Value as ProxyValue<'ctx>>::Base,
+        parent: NDArrayValue<'ctx>,
+        indices: ArraySliceValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            value,
+            parent,
+            indices,
+            self.llvm_usize,
+            name,
+        )
+    }
+}
+
+impl<'ctx> ProxyType<'ctx> for NDIterType<'ctx> {
+    type Base = PointerType<'ctx>;
+    type Value = NDIterValue<'ctx>;
+
+    fn is_type<G: CodeGenerator + ?Sized>(
+        generator: &G,
+        ctx: &'ctx Context,
+        llvm_ty: impl BasicType<'ctx>,
+    ) -> Result<(), String> {
+        if let BasicTypeEnum::PointerType(ty) = llvm_ty.as_basic_type_enum() {
+            <Self as ProxyType<'ctx>>::is_representable(generator, ctx, ty)
+        } else {
+            Err(format!("Expected pointer type, got {llvm_ty:?}"))
+        }
+    }
+
+    fn is_representable<G: CodeGenerator + ?Sized>(
+        generator: &G,
+        ctx: &'ctx Context,
+        llvm_ty: Self::Base,
+    ) -> Result<(), String> {
+        Self::is_representable(llvm_ty, generator.get_size_type(ctx))
+    }
+
+    fn raw_alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self::Value as ProxyValue<'ctx>>::Base {
+        generator
+            .gen_var_alloc(
+                ctx,
+                self.as_base_type().get_element_type().into_struct_type().into(),
+                name,
+            )
+            .unwrap()
+    }
+
+    fn array_alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        size: IntValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> ArraySliceValue<'ctx> {
+        generator
+            .gen_array_var_alloc(
+                ctx,
+                self.as_base_type().get_element_type().into_struct_type().into(),
+                size,
+                name,
+            )
+            .unwrap()
+    }
+
+    fn as_base_type(&self) -> Self::Base {
+        self.ty
+    }
+}
+
+impl<'ctx> From<NDIterType<'ctx>> for PointerType<'ctx> {
+    fn from(value: NDIterType<'ctx>) -> Self {
+        value.as_base_type()
+    }
+}

nac3core/src/codegen/types/structure.rs

@@ -2,7 +2,7 @@ use std::marker::PhantomData;
 
 use inkwell::{
     context::AsContextRef,
-    types::{BasicTypeEnum, IntType},
+    types::{BasicTypeEnum, IntType, StructType},
     values::{BasicValue, BasicValueEnum, IntValue, PointerValue, StructValue},
 };
 
@@ -103,6 +103,12 @@ where
         StructField { index, name, ty: ty.into(), _value_ty: PhantomData }
     }
 
+    /// Returns the name of this field.
+    #[must_use]
+    pub fn name(&self) -> &'static str {
+        self.name
+    }
+
     /// Creates a pointer to this field in an arbitrary structure by performing a `getelementptr i32
     /// {idx...}, i32 {self.index}`.
     pub fn ptr_by_array_gep(
@@ -201,3 +207,49 @@ impl FieldIndexCounter {
         v
     }
 }
+
+type FieldTypeVerifier<'ctx> = dyn Fn(BasicTypeEnum<'ctx>) -> Result<(), String>;
+
+/// Checks whether [`llvm_ty`][StructType] contains the fields described by the given
+/// [`StructFields`] instance.
+///
+/// By default, this function will compare the type of each field in `expected_fields` against
+/// `llvm_ty`. To override this behavior for individual fields, pass in overrides to
+/// `custom_verifiers`, which will use the specified verifier when a field with the matching field
+/// name is being checked.
+pub(super) fn check_struct_type_matches_fields<'ctx>(
+    expected_fields: impl StructFields<'ctx>,
+    llvm_ty: StructType<'ctx>,
+    ty_name: &'static str,
+    custom_verifiers: &[(&str, &FieldTypeVerifier<'ctx>)],
+) -> Result<(), String> {
+    let expected_fields = expected_fields.to_vec();
+
+    if llvm_ty.count_fields() != u32::try_from(expected_fields.len()).unwrap() {
+        return Err(format!(
+            "Expected {} fields in `{ty_name}`, got {}",
+            expected_fields.len(),
+            llvm_ty.count_fields(),
+        ));
+    }
+
+    expected_fields
+        .into_iter()
+        .enumerate()
+        .map(|(i, (field_name, expected_ty))| {
+            (field_name, expected_ty, llvm_ty.get_field_type_at_index(i as u32).unwrap())
+        })
+        .try_for_each(|(field_name, expected_ty, actual_ty)| {
+            if let Some((_, verifier)) =
+                custom_verifiers.iter().find(|verifier| verifier.0 == field_name)
+            {
+                verifier(actual_ty)
+            } else if expected_ty == actual_ty {
+                Ok(())
+            } else {
+                Err(format!("Expected {expected_ty} for `{ty_name}.{field_name}`, got {actual_ty}"))
+            }
+        })?;
+
+    Ok(())
+}

nac3core/src/codegen/types/utils/mod.rs

@@ -0,0 +1,3 @@
+pub use slice::*;
+
+mod slice;

nac3core/src/codegen/types/utils/slice.rs

@@ -0,0 +1,254 @@
+use inkwell::{
+    context::{AsContextRef, Context, ContextRef},
+    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
+    values::IntValue,
+    AddressSpace,
+};
+use itertools::Itertools;
+
+use nac3core_derive::StructFields;
+
+use crate::codegen::{
+    types::{
+        structure::{
+            check_struct_type_matches_fields, FieldIndexCounter, StructField, StructFields,
+        },
+        ProxyType,
+    },
+    values::{utils::SliceValue, ArraySliceValue, ProxyValue},
+    CodeGenContext, CodeGenerator,
+};
+
+#[derive(Debug, PartialEq, Eq, Clone, Copy)]
+pub struct SliceType<'ctx> {
+    ty: PointerType<'ctx>,
+    int_ty: IntType<'ctx>,
+    llvm_usize: IntType<'ctx>,
+}
+
+#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
+pub struct SliceFields<'ctx> {
+    #[value_type(bool_type())]
+    pub start_defined: StructField<'ctx, IntValue<'ctx>>,
+    #[value_type(usize)]
+    pub start: StructField<'ctx, IntValue<'ctx>>,
+    #[value_type(bool_type())]
+    pub stop_defined: StructField<'ctx, IntValue<'ctx>>,
+    #[value_type(usize)]
+    pub stop: StructField<'ctx, IntValue<'ctx>>,
+    #[value_type(bool_type())]
+    pub step_defined: StructField<'ctx, IntValue<'ctx>>,
+    #[value_type(usize)]
+    pub step: StructField<'ctx, IntValue<'ctx>>,
+}
+
+impl<'ctx> SliceFields<'ctx> {
+    /// Creates a new instance of [`SliceFields`] with a custom integer type for its range values.
+    #[must_use]
+    pub fn new_sized(ctx: &impl AsContextRef<'ctx>, int_ty: IntType<'ctx>) -> Self {
+        let ctx = unsafe { ContextRef::new(ctx.as_ctx_ref()) };
+        let mut counter = FieldIndexCounter::default();
+
+        SliceFields {
+            start_defined: StructField::create(&mut counter, "start_defined", ctx.bool_type()),
+            start: StructField::create(&mut counter, "start", int_ty),
+            stop_defined: StructField::create(&mut counter, "stop_defined", ctx.bool_type()),
+            stop: StructField::create(&mut counter, "stop", int_ty),
+            step_defined: StructField::create(&mut counter, "step_defined", ctx.bool_type()),
+            step: StructField::create(&mut counter, "step", int_ty),
+        }
+    }
+}
+
+impl<'ctx> SliceType<'ctx> {
+    /// Checks whether `llvm_ty` represents a `slice` type, returning [Err] if it does not.
+    pub fn is_representable(
+        llvm_ty: PointerType<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> Result<(), String> {
+        let ctx = llvm_ty.get_context();
+
+        let fields = SliceFields::new(ctx, llvm_usize);
+
+        let llvm_ty = llvm_ty.get_element_type();
+        let AnyTypeEnum::StructType(llvm_ty) = llvm_ty else {
+            return Err(format!("Expected struct type for `Slice` type, got {llvm_ty}"));
+        };
+
+        check_struct_type_matches_fields(
+            fields,
+            llvm_ty,
+            "Slice",
+            &[
+                (fields.start.name(), &|ty| {
+                    if ty.is_int_type() {
+                        Ok(())
+                    } else {
+                        Err(format!("Expected int type for `Slice.start`, got {ty}"))
+                    }
+                }),
+                (fields.stop.name(), &|ty| {
+                    if ty.is_int_type() {
+                        Ok(())
+                    } else {
+                        Err(format!("Expected int type for `Slice.stop`, got {ty}"))
+                    }
+                }),
+                (fields.step.name(), &|ty| {
+                    if ty.is_int_type() {
+                        Ok(())
+                    } else {
+                        Err(format!("Expected int type for `Slice.step`, got {ty}"))
+                    }
+                }),
+            ],
+        )
+    }
+
+    // TODO: Move this into e.g. StructProxyType
+    #[must_use]
+    pub fn get_fields(&self) -> SliceFields<'ctx> {
+        SliceFields::new_sized(&self.int_ty.get_context(), self.int_ty)
+    }
+
+    /// Creates an LLVM type corresponding to the expected structure of a `Slice`.
+    #[must_use]
+    fn llvm_type(ctx: &'ctx Context, int_ty: IntType<'ctx>) -> PointerType<'ctx> {
+        let field_tys = SliceFields::new_sized(&int_ty.get_context(), int_ty)
+            .into_iter()
+            .map(|field| field.1)
+            .collect_vec();
+
+        ctx.struct_type(&field_tys, false).ptr_type(AddressSpace::default())
+    }
+
+    /// Creates an instance of [`SliceType`] with `int_ty` as its backing integer type.
+    #[must_use]
+    pub fn new(ctx: &'ctx Context, int_ty: IntType<'ctx>, llvm_usize: IntType<'ctx>) -> Self {
+        let llvm_ty = Self::llvm_type(ctx, int_ty);
+
+        Self { ty: llvm_ty, int_ty, llvm_usize }
+    }
+
+    /// Creates an instance of [`SliceType`] with `usize` as its backing integer type.
+    #[must_use]
+    pub fn new_usize<G: CodeGenerator + ?Sized>(generator: &G, ctx: &'ctx Context) -> Self {
+        let llvm_usize = generator.get_size_type(ctx);
+        Self::new(ctx, llvm_usize, llvm_usize)
+    }
+
+    /// Creates an [`SliceType`] from a [`PointerType`] representing a `slice`.
+    #[must_use]
+    pub fn from_type(
+        ptr_ty: PointerType<'ctx>,
+        int_ty: IntType<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> Self {
+        debug_assert!(Self::is_representable(ptr_ty, int_ty).is_ok());
+
+        Self { ty: ptr_ty, int_ty, llvm_usize }
+    }
+
+    #[must_use]
+    pub fn element_type(&self) -> IntType<'ctx> {
+        self.int_ty
+    }
+
+    /// Allocates an instance of [`ContiguousNDArrayValue`] as if by calling `alloca` on the base type.
+    #[must_use]
+    pub fn alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            self.raw_alloca(generator, ctx, name),
+            self.int_ty,
+            self.llvm_usize,
+            name,
+        )
+    }
+
+    /// Converts an existing value into a [`ContiguousNDArrayValue`].
+    #[must_use]
+    pub fn map_value(
+        &self,
+        value: <<Self as ProxyType<'ctx>>::Value as ProxyValue<'ctx>>::Base,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            value,
+            self.int_ty,
+            self.llvm_usize,
+            name,
+        )
+    }
+}
+
+impl<'ctx> ProxyType<'ctx> for SliceType<'ctx> {
+    type Base = PointerType<'ctx>;
+    type Value = SliceValue<'ctx>;
+
+    fn is_type<G: CodeGenerator + ?Sized>(
+        generator: &G,
+        ctx: &'ctx Context,
+        llvm_ty: impl BasicType<'ctx>,
+    ) -> Result<(), String> {
+        if let BasicTypeEnum::PointerType(ty) = llvm_ty.as_basic_type_enum() {
+            <Self as ProxyType<'ctx>>::is_representable(generator, ctx, ty)
+        } else {
+            Err(format!("Expected pointer type, got {llvm_ty:?}"))
+        }
+    }
+
+    fn is_representable<G: CodeGenerator + ?Sized>(
+        generator: &G,
+        ctx: &'ctx Context,
+        llvm_ty: Self::Base,
+    ) -> Result<(), String> {
+        Self::is_representable(llvm_ty, generator.get_size_type(ctx))
+    }
+
+    fn raw_alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self::Value as ProxyValue<'ctx>>::Base {
+        generator
+            .gen_var_alloc(
+                ctx,
+                self.as_base_type().get_element_type().into_struct_type().into(),
+                name,
+            )
+            .unwrap()
+    }
+
+    fn array_alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        size: IntValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> ArraySliceValue<'ctx> {
+        generator
+            .gen_array_var_alloc(
+                ctx,
+                self.as_base_type().get_element_type().into_struct_type().into(),
+                size,
+                name,
+            )
+            .unwrap()
+    }
+
+    fn as_base_type(&self) -> Self::Base {
+        self.ty
+    }
+}
+
+impl<'ctx> From<SliceType<'ctx>> for PointerType<'ctx> {
+    fn from(value: SliceType<'ctx>) -> Self {
+        value.as_base_type()
+    }
+}

nac3core/src/codegen/values/array.rs

@@ -207,7 +207,7 @@ pub trait TypedArrayLikeMutator<'ctx, T, Index = IntValue<'ctx>>:
 
 /// Type alias for a function that casts a [`BasicValueEnum`] into a `T`.
 type ValueDowncastFn<'ctx, T> =
-    Box<dyn Fn(&mut CodeGenContext<'ctx, '_>, BasicValueEnum<'ctx>) -> T>;
+    Box<dyn Fn(&mut CodeGenContext<'ctx, '_>, BasicValueEnum<'ctx>) -> T + 'ctx>;
 /// Type alias for a function that casts a `T` into a [`BasicValueEnum`].
 type ValueUpcastFn<'ctx, T> = Box<dyn Fn(&mut CodeGenContext<'ctx, '_>, T) -> BasicValueEnum<'ctx>>;
 

nac3core/src/codegen/values/mod.rs

@@ -4,13 +4,13 @@ use super::types::ProxyType;
 use crate::codegen::CodeGenerator;
 pub use array::*;
 pub use list::*;
-pub use ndarray::*;
 pub use range::*;
 
 mod array;
 mod list;
-mod ndarray;
+pub mod ndarray;
 mod range;
+pub mod utils;
 
 /// A LLVM type that is used to represent a non-primitive value in NAC3.
 pub trait ProxyValue<'ctx>: Into<Self::Base> {

nac3core/src/codegen/values/ndarray/contiguous.rs

@@ -0,0 +1,202 @@
+use inkwell::{
+    types::{BasicType, BasicTypeEnum, IntType},
+    values::{IntValue, PointerValue},
+    AddressSpace,
+};
+
+use super::{ArrayLikeValue, NDArrayValue, ProxyValue};
+use crate::codegen::{
+    stmt::gen_if_callback,
+    types::{
+        ndarray::{ContiguousNDArrayType, NDArrayType},
+        structure::StructField,
+    },
+    CodeGenContext, CodeGenerator,
+};
+
+#[derive(Copy, Clone)]
+pub struct ContiguousNDArrayValue<'ctx> {
+    value: PointerValue<'ctx>,
+    item: BasicTypeEnum<'ctx>,
+    llvm_usize: IntType<'ctx>,
+    name: Option<&'ctx str>,
+}
+
+impl<'ctx> ContiguousNDArrayValue<'ctx> {
+    /// Checks whether `value` is an instance of `ContiguousNDArray`, returning [Err] if `value` is
+    /// not an instance.
+    pub fn is_representable(
+        value: PointerValue<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> Result<(), String> {
+        <Self as ProxyValue<'ctx>>::Type::is_representable(value.get_type(), llvm_usize)
+    }
+
+    /// Creates an [`ContiguousNDArrayValue`] from a [`PointerValue`].
+    #[must_use]
+    pub fn from_pointer_value(
+        ptr: PointerValue<'ctx>,
+        dtype: BasicTypeEnum<'ctx>,
+        llvm_usize: IntType<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> Self {
+        debug_assert!(Self::is_representable(ptr, llvm_usize).is_ok());
+
+        Self { value: ptr, item: dtype, llvm_usize, name }
+    }
+
+    fn ndims_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields().ndims
+    }
+
+    pub fn store_ndims(&self, ctx: &CodeGenContext<'ctx, '_>, value: IntValue<'ctx>) {
+        self.ndims_field().set(ctx, self.as_base_value(), value, self.name);
+    }
+
+    fn shape_field(&self) -> StructField<'ctx, PointerValue<'ctx>> {
+        self.get_type().get_fields().shape
+    }
+
+    pub fn store_shape(&self, ctx: &CodeGenContext<'ctx, '_>, value: PointerValue<'ctx>) {
+        self.shape_field().set(ctx, self.as_base_value(), value, self.name);
+    }
+
+    pub fn load_shape(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
+        self.shape_field().get(ctx, self.value, self.name)
+    }
+
+    fn data_field(&self) -> StructField<'ctx, PointerValue<'ctx>> {
+        self.get_type().get_fields().data
+    }
+
+    pub fn store_data(&self, ctx: &CodeGenContext<'ctx, '_>, value: PointerValue<'ctx>) {
+        self.data_field().set(ctx, self.as_base_value(), value, self.name);
+    }
+
+    pub fn load_data(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
+        self.data_field().get(ctx, self.value, self.name)
+    }
+}
+
+impl<'ctx> ProxyValue<'ctx> for ContiguousNDArrayValue<'ctx> {
+    type Base = PointerValue<'ctx>;
+    type Type = ContiguousNDArrayType<'ctx>;
+
+    fn get_type(&self) -> Self::Type {
+        <Self as ProxyValue<'ctx>>::Type::from_type(
+            self.as_base_value().get_type(),
+            self.item,
+            self.llvm_usize,
+        )
+    }
+
+    fn as_base_value(&self) -> Self::Base {
+        self.value
+    }
+}
+
+impl<'ctx> From<ContiguousNDArrayValue<'ctx>> for PointerValue<'ctx> {
+    fn from(value: ContiguousNDArrayValue<'ctx>) -> Self {
+        value.as_base_value()
+    }
+}
+
+impl<'ctx> NDArrayValue<'ctx> {
+    /// Create a [`ContiguousNDArrayValue`] from the contents of this ndarray.
+    ///
+    /// This function may or may not be expensive depending on if this ndarray has contiguous data.
+    ///
+    /// If this ndarray is not C-contiguous, this function will allocate memory on the stack for the
+    /// `data` field of the returned [`ContiguousNDArrayValue`] and copy contents of this ndarray to
+    /// there.
+    ///
+    /// If this ndarray is C-contiguous, contents of this ndarray will not be copied. The created
+    /// [`ContiguousNDArrayValue`] will share memory with this ndarray.
+    pub fn make_contiguous_ndarray<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> ContiguousNDArrayValue<'ctx> {
+        let result = ContiguousNDArrayType::new(generator, ctx.ctx, self.dtype)
+            .alloca(generator, ctx, self.name);
+
+        // Set ndims and shape.
+        let ndims = self
+            .ndims
+            .map_or_else(|| self.load_ndims(ctx), |ndims| self.llvm_usize.const_int(ndims, false));
+        result.store_ndims(ctx, ndims);
+
+        let shape = self.shape();
+        result.store_shape(ctx, shape.base_ptr(ctx, generator));
+
+        gen_if_callback(
+            generator,
+            ctx,
+            |generator, ctx| Ok(self.is_c_contiguous(generator, ctx)),
+            |_, ctx| {
+                // This ndarray is contiguous.
+                let data = self.data_field(ctx).get(ctx, self.as_base_value(), self.name);
+                let data = ctx
+                    .builder
+                    .build_pointer_cast(data, result.item.ptr_type(AddressSpace::default()), "")
+                    .unwrap();
+                result.store_data(ctx, data);
+
+                Ok(())
+            },
+            |generator, ctx| {
+                // This ndarray is not contiguous. Do a full-copy on `data`. `make_copy` produces an
+                // ndarray with contiguous `data`.
+                let copied_ndarray = self.make_copy(generator, ctx);
+                let data = copied_ndarray.data().base_ptr(ctx, generator);
+                let data = ctx
+                    .builder
+                    .build_pointer_cast(data, result.item.ptr_type(AddressSpace::default()), "")
+                    .unwrap();
+                result.store_data(ctx, data);
+
+                Ok(())
+            },
+        )
+        .unwrap();
+
+        result
+    }
+
+    /// Create an [`NDArrayValue`] from a [`ContiguousNDArrayValue`].
+    ///
+    /// The operation is cheap. The newly created [`NDArrayValue`] will share the same memory as the
+    /// [`ContiguousNDArrayValue`].
+    ///
+    /// `ndims` has to be provided as [`NDArrayValue`] requires a statically known `ndims` value,
+    /// despite the fact that the information should be contained within the
+    /// [`ContiguousNDArrayValue`].
+    pub fn from_contiguous_ndarray<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        carray: ContiguousNDArrayValue<'ctx>,
+        ndims: u64,
+    ) -> Self {
+        // TODO: Debug assert `ndims == carray.ndims` to catch bugs.
+
+        // Allocate the resulting ndarray.
+        let ndarray = NDArrayType::new(generator, ctx.ctx, carray.item, Some(ndims))
+            .construct_uninitialized(generator, ctx, carray.name);
+
+        // Copy shape and update strides
+        let shape = carray.load_shape(ctx);
+        ndarray.copy_shape_from_array(generator, ctx, shape);
+        ndarray.set_strides_contiguous(generator, ctx);
+
+        // Share data
+        let data = carray.load_data(ctx);
+        ndarray.store_data(
+            ctx,
+            ctx.builder
+                .build_pointer_cast(data, ctx.ctx.i8_type().ptr_type(AddressSpace::default()), "")
+                .unwrap(),
+        );
+
+        ndarray
+    }
+}

nac3core/src/codegen/values/ndarray/indexing.rs

@@ -0,0 +1,262 @@
+use inkwell::{
+    types::IntType,
+    values::{IntValue, PointerValue},
+    AddressSpace,
+};
+use itertools::Itertools;
+
+use nac3parser::ast::{Expr, ExprKind};
+
+use crate::{
+    codegen::{
+        irrt,
+        types::{
+            ndarray::{NDArrayType, NDIndexType},
+            structure::StructField,
+            utils::SliceType,
+        },
+        values::{ndarray::NDArrayValue, utils::RustSlice, ProxyValue},
+        CodeGenContext, CodeGenerator,
+    },
+    typecheck::typedef::Type,
+};
+
+/// An IRRT representation of an ndarray subscript index.
+#[derive(Copy, Clone)]
+pub struct NDIndexValue<'ctx> {
+    value: PointerValue<'ctx>,
+    llvm_usize: IntType<'ctx>,
+    name: Option<&'ctx str>,
+}
+
+impl<'ctx> NDIndexValue<'ctx> {
+    /// Checks whether `value` is an instance of `ndindex`, returning [Err] if `value` is not an
+    /// instance.
+    pub fn is_representable(
+        value: PointerValue<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> Result<(), String> {
+        <Self as ProxyValue<'ctx>>::Type::is_representable(value.get_type(), llvm_usize)
+    }
+
+    /// Creates an [`NDIndexValue`] from a [`PointerValue`].
+    #[must_use]
+    pub fn from_pointer_value(
+        ptr: PointerValue<'ctx>,
+        llvm_usize: IntType<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> Self {
+        debug_assert!(Self::is_representable(ptr, llvm_usize).is_ok());
+
+        Self { value: ptr, llvm_usize, name }
+    }
+
+    fn type_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields().type_
+    }
+
+    pub fn load_type(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
+        self.type_field().get(ctx, self.value, self.name)
+    }
+
+    pub fn store_type(&self, ctx: &CodeGenContext<'ctx, '_>, value: IntValue<'ctx>) {
+        self.type_field().set(ctx, self.value, value, self.name);
+    }
+
+    fn data_field(&self) -> StructField<'ctx, PointerValue<'ctx>> {
+        self.get_type().get_fields().data
+    }
+
+    pub fn load_data(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
+        self.data_field().get(ctx, self.value, self.name)
+    }
+
+    pub fn store_data(&self, ctx: &CodeGenContext<'ctx, '_>, value: PointerValue<'ctx>) {
+        self.data_field().set(ctx, self.value, value, self.name);
+    }
+}
+
+impl<'ctx> ProxyValue<'ctx> for NDIndexValue<'ctx> {
+    type Base = PointerValue<'ctx>;
+    type Type = NDIndexType<'ctx>;
+
+    fn get_type(&self) -> Self::Type {
+        Self::Type::from_type(self.value.get_type(), self.llvm_usize)
+    }
+
+    fn as_base_value(&self) -> Self::Base {
+        self.value
+    }
+}
+
+impl<'ctx> From<NDIndexValue<'ctx>> for PointerValue<'ctx> {
+    fn from(value: NDIndexValue<'ctx>) -> Self {
+        value.as_base_value()
+    }
+}
+
+impl<'ctx> NDArrayValue<'ctx> {
+    /// Get the expected `ndims` after indexing with `indices`.
+    #[must_use]
+    fn deduce_ndims_after_indexing_with(&self, indices: &[RustNDIndex<'ctx>]) -> Option<u64> {
+        let mut ndims = self.ndims?;
+
+        for index in indices {
+            match index {
+                RustNDIndex::SingleElement(_) => {
+                    ndims -= 1; // Single elements decrements ndims
+                }
+                RustNDIndex::NewAxis => {
+                    ndims += 1; // `np.newaxis` / `none` adds a new axis
+                }
+                RustNDIndex::Ellipsis | RustNDIndex::Slice(_) => {}
+            }
+        }
+
+        Some(ndims)
+    }
+
+    /// Index into the ndarray, and return a newly-allocated view on this ndarray.
+    ///
+    /// This function behaves like NumPy's ndarray indexing, but if the indices index
+    /// into a single element, an unsized ndarray is returned.
+    #[must_use]
+    pub fn index<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        indices: &[RustNDIndex<'ctx>],
+    ) -> Self {
+        assert!(self.ndims.is_some(), "NDArrayValue::index is only supported for instances with compile-time known ndims (self.ndims = Some(...))");
+
+        let dst_ndims = self.deduce_ndims_after_indexing_with(indices);
+        let dst_ndarray = NDArrayType::new(generator, ctx.ctx, self.dtype, dst_ndims)
+            .construct_uninitialized(generator, ctx, None);
+
+        let indices =
+            NDIndexType::new(generator, ctx.ctx).construct_ndindices(generator, ctx, indices);
+        irrt::ndarray::call_nac3_ndarray_index(generator, ctx, indices, *self, dst_ndarray);
+
+        dst_ndarray
+    }
+}
+
+/// A convenience enum representing a [`NDIndexValue`].
+// TODO: Rename to CTConstNDIndex
+#[derive(Debug, Clone)]
+pub enum RustNDIndex<'ctx> {
+    SingleElement(IntValue<'ctx>),
+    Slice(RustSlice<'ctx>),
+    NewAxis,
+    Ellipsis,
+}
+
+impl<'ctx> RustNDIndex<'ctx> {
+    /// Generate LLVM code to transform an ndarray subscript expression to
+    /// its list of [`RustNDIndex`]
+    ///
+    /// i.e.,
+    /// ```python
+    /// my_ndarray[::3, 1, :2:]
+    ///            ^^^^^^^^^^^ Then these into a three `RustNDIndex`es
+    /// ```
+    pub fn from_subscript_expr<G: CodeGenerator>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        subscript: &Expr<Option<Type>>,
+    ) -> Result<Vec<RustNDIndex<'ctx>>, String> {
+        // Annoying notes about `slice`
+        //  - `my_array[5]`
+        //    - slice is a `Constant`
+        //  - `my_array[:5]`
+        //    - slice is a `Slice`
+        //  - `my_array[:]`
+        //    - slice is a `Slice`, but lower upper step would all be `Option::None`
+        //  - `my_array[:, :]`
+        //    - slice is now a `Tuple` of two `Slice`-s
+        //
+        // In summary:
+        //  - when there is a comma "," within [], `slice` will be a `Tuple` of the entries.
+        //  - when there is not comma "," within [] (i.e., just a single entry), `slice` will be that entry itself.
+        //
+        // So we first "flatten" out the slice expression
+        let index_exprs = match &subscript.node {
+            ExprKind::Tuple { elts, .. } => elts.iter().collect_vec(),
+            _ => vec![subscript],
+        };
+
+        // Process all index expressions
+        let mut rust_ndindices: Vec<RustNDIndex> = Vec::with_capacity(index_exprs.len()); // Not using iterators here because `?` is used here.
+        for index_expr in index_exprs {
+            // NOTE: Currently nac3core's slices do not have an object representation,
+            // so the code/implementation looks awkward - we have to do pattern matching on the expression
+            let ndindex = if let ExprKind::Slice { lower, upper, step } = &index_expr.node {
+                // Handle slices
+                let slice = RustSlice::from_slice_expr(generator, ctx, lower, upper, step)?;
+                RustNDIndex::Slice(slice)
+            } else {
+                // Treat and handle everything else as a single element index.
+                let index = generator.gen_expr(ctx, index_expr)?.unwrap().to_basic_value_enum(
+                    ctx,
+                    generator,
+                    ctx.primitives.int32, // Must be int32, this checks for illegal values
+                )?;
+                let index = index.into_int_value();
+
+                RustNDIndex::SingleElement(index)
+            };
+            rust_ndindices.push(ndindex);
+        }
+        Ok(rust_ndindices)
+    }
+
+    /// Get the value to set `NDIndex::type` for this variant.
+    #[must_use]
+    pub fn get_type_id(&self) -> u64 {
+        // Defined in IRRT, must be in sync
+        match self {
+            RustNDIndex::SingleElement(_) => 0,
+            RustNDIndex::Slice(_) => 1,
+            RustNDIndex::NewAxis => 2,
+            RustNDIndex::Ellipsis => 3,
+        }
+    }
+
+    /// Serialize this [`RustNDIndex`] by writing it into an LLVM [`NDIndexValue`].
+    pub fn write_to_ndindex<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dst_ndindex: NDIndexValue<'ctx>,
+    ) {
+        let llvm_pi8 = ctx.ctx.i8_type().ptr_type(AddressSpace::default());
+
+        // Set `dst_ndindex.type`
+        dst_ndindex.store_type(ctx, ctx.ctx.i8_type().const_int(self.get_type_id(), false));
+
+        // Set `dst_ndindex_ptr->data`
+        match self {
+            RustNDIndex::SingleElement(in_index) => {
+                let index_ptr = ctx.builder.build_alloca(ctx.ctx.i32_type(), "").unwrap();
+                ctx.builder.build_store(index_ptr, *in_index).unwrap();
+
+                dst_ndindex.store_data(
+                    ctx,
+                    ctx.builder.build_pointer_cast(index_ptr, llvm_pi8, "").unwrap(),
+                );
+            }
+            RustNDIndex::Slice(in_rust_slice) => {
+                let user_slice_ptr =
+                    SliceType::new(ctx.ctx, ctx.ctx.i32_type(), generator.get_size_type(ctx.ctx))
+                        .alloca(generator, ctx, None);
+                in_rust_slice.write_to_slice(ctx, user_slice_ptr);
+
+                dst_ndindex.store_data(
+                    ctx,
+                    ctx.builder.build_pointer_cast(user_slice_ptr.into(), llvm_pi8, "").unwrap(),
+                );
+            }
+            RustNDIndex::NewAxis | RustNDIndex::Ellipsis => {}
+        }
+    }
+}

nac3core/src/codegen/values/ndarray/mod.rs

@@ -9,18 +9,29 @@ use super::{
     UntypedArrayLikeAccessor, UntypedArrayLikeMutator,
 };
 use crate::codegen::{
-    irrt::{call_ndarray_calc_size, call_ndarray_flatten_index},
-    llvm_intrinsics::call_int_umin,
+    irrt,
+    llvm_intrinsics::{call_int_umin, call_memcpy_generic_array},
     stmt::gen_for_callback_incrementing,
-    types::{structure::StructField, NDArrayType},
+    type_aligned_alloca,
+    types::{ndarray::NDArrayType, structure::StructField},
     CodeGenContext, CodeGenerator,
 };
+pub use contiguous::*;
+pub use indexing::*;
+pub use nditer::*;
+pub use view::*;
+
+mod contiguous;
+mod indexing;
+mod nditer;
+mod view;
 
 /// Proxy type for accessing an `NDArray` value in LLVM.
 #[derive(Copy, Clone)]
 pub struct NDArrayValue<'ctx> {
     value: PointerValue<'ctx>,
     dtype: BasicTypeEnum<'ctx>,
+    ndims: Option<u64>,
     llvm_usize: IntType<'ctx>,
     name: Option<&'ctx str>,
 }
@@ -40,12 +51,13 @@ impl<'ctx> NDArrayValue<'ctx> {
     pub fn from_pointer_value(
         ptr: PointerValue<'ctx>,
         dtype: BasicTypeEnum<'ctx>,
+        ndims: Option<u64>,
         llvm_usize: IntType<'ctx>,
         name: Option<&'ctx str>,
     ) -> Self {
         debug_assert!(Self::is_representable(ptr, llvm_usize).is_ok());
 
-        NDArrayValue { value: ptr, dtype, llvm_usize, name }
+        NDArrayValue { value: ptr, dtype, ndims, llvm_usize, name }
     }
 
     fn ndims_field(&self, ctx: &CodeGenContext<'ctx, '_>) -> StructField<'ctx, IntValue<'ctx>> {
@@ -76,6 +88,27 @@ impl<'ctx> NDArrayValue<'ctx> {
         ctx.builder.build_load(pndims, "").map(BasicValueEnum::into_int_value).unwrap()
     }
 
+    fn itemsize_field(&self, ctx: &CodeGenContext<'ctx, '_>) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields(ctx.ctx).itemsize
+    }
+
+    /// Stores the size of each element `itemsize` into this instance.
+    pub fn store_itemsize<G: CodeGenerator + ?Sized>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        generator: &G,
+        itemsize: IntValue<'ctx>,
+    ) {
+        debug_assert_eq!(itemsize.get_type(), generator.get_size_type(ctx.ctx));
+
+        self.itemsize_field(ctx).set(ctx, self.value, itemsize, self.name);
+    }
+
+    /// Returns the size of each element of this `NDArray` as a value.
+    pub fn load_itemsize(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
+        self.itemsize_field(ctx).get(ctx, self.value, self.name)
+    }
+
     fn shape_field(&self, ctx: &CodeGenContext<'ctx, '_>) -> StructField<'ctx, PointerValue<'ctx>> {
         self.get_type().get_fields(ctx.ctx).shape
     }
@@ -107,6 +140,40 @@ impl<'ctx> NDArrayValue<'ctx> {
         NDArrayShapeProxy(self)
     }
 
+    fn strides_field(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+    ) -> StructField<'ctx, PointerValue<'ctx>> {
+        self.get_type().get_fields(ctx.ctx).strides
+    }
+
+    /// Returns the double-indirection pointer to the `strides` array, as if by calling
+    /// `getelementptr` on the field.
+    fn ptr_to_strides(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
+        self.strides_field(ctx).ptr_by_gep(ctx, self.value, self.name)
+    }
+
+    /// Stores the array of stride sizes `strides` into this instance.
+    fn store_strides(&self, ctx: &CodeGenContext<'ctx, '_>, strides: PointerValue<'ctx>) {
+        self.strides_field(ctx).set(ctx, self.as_base_value(), strides, self.name);
+    }
+
+    /// Convenience method for creating a new array storing the stride with the given `size`.
+    pub fn create_strides(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        llvm_usize: IntType<'ctx>,
+        size: IntValue<'ctx>,
+    ) {
+        self.store_strides(ctx, ctx.builder.build_array_alloca(llvm_usize, size, "").unwrap());
+    }
+
+    /// Returns a proxy object to the field storing the stride of each dimension of this `NDArray`.
+    #[must_use]
+    pub fn strides(&self) -> NDArrayStridesProxy<'ctx, '_> {
+        NDArrayStridesProxy(self)
+    }
+
     fn data_field(&self, ctx: &CodeGenContext<'ctx, '_>) -> StructField<'ctx, PointerValue<'ctx>> {
         self.get_type().get_fields(ctx.ctx).data
     }
@@ -128,23 +195,23 @@ impl<'ctx> NDArrayValue<'ctx> {
 
     /// Convenience method for creating a new array storing data elements with the given element
     /// type `elem_ty` and `size`.
-    pub fn create_data(
+    ///
+    /// The data buffer will be allocated on the stack, and is considered to be owned by this ndarray instance.
+    ///
+    /// # Safety
+    ///
+    /// The caller must ensure that `shape` and `itemsize` of this ndarray instance is initialized.
+    pub unsafe fn create_data<G: CodeGenerator + ?Sized>(
         &self,
-        ctx: &CodeGenContext<'ctx, '_>,
-        elem_ty: BasicTypeEnum<'ctx>,
-        size: IntValue<'ctx>,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
     ) {
-        let itemsize = ctx
-            .builder
-            .build_int_z_extend_or_bit_cast(elem_ty.size_of().unwrap(), size.get_type(), "")
-            .unwrap();
-        let nbytes = ctx.builder.build_int_mul(size, itemsize, "").unwrap();
+        let nbytes = self.nbytes(generator, ctx);
 
-        // TODO: What about alignment?
-        self.store_data(
-            ctx,
-            ctx.builder.build_array_alloca(ctx.ctx.i8_type(), nbytes, "").unwrap(),
-        );
+        let data = type_aligned_alloca(generator, ctx, self.dtype, nbytes, None);
+        self.store_data(ctx, data);
+
+        self.set_strides_contiguous(generator, ctx);
     }
 
     /// Returns a proxy object to the field storing the data of this `NDArray`.
@@ -152,6 +219,219 @@ impl<'ctx> NDArrayValue<'ctx> {
     pub fn data(&self) -> NDArrayDataProxy<'ctx, '_> {
         NDArrayDataProxy(self)
     }
+
+    /// Copy shape dimensions from an array.
+    pub fn copy_shape_from_array<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        shape: PointerValue<'ctx>,
+    ) {
+        let num_items = self.load_ndims(ctx);
+
+        call_memcpy_generic_array(
+            ctx,
+            self.shape().base_ptr(ctx, generator),
+            shape,
+            num_items,
+            ctx.ctx.bool_type().const_zero(),
+        );
+    }
+
+    /// Copy shape dimensions from an ndarray.
+    /// Panics if `ndims` mismatches.
+    pub fn copy_shape_from_ndarray<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        src_ndarray: NDArrayValue<'ctx>,
+    ) {
+        if self.ndims.is_some() && src_ndarray.ndims.is_some() {
+            assert_eq!(self.ndims, src_ndarray.ndims);
+        } else {
+            let self_ndims = self.load_ndims(ctx);
+            let src_ndims = src_ndarray.load_ndims(ctx);
+
+            ctx.make_assert(
+                generator,
+                ctx.builder.build_int_compare(
+                    IntPredicate::EQ,
+                    self_ndims,
+                    src_ndims,
+                    ""
+                ).unwrap(),
+                "0:AssertionError",
+                "NDArrayValue::copy_shape_from_ndarray: Expected self.ndims ({0}) == src_ndarray.ndims ({1})",
+                [Some(self_ndims), Some(src_ndims), None],
+                ctx.current_loc
+            );
+        }
+
+        let src_shape = src_ndarray.shape().base_ptr(ctx, generator);
+        self.copy_shape_from_array(generator, ctx, src_shape);
+    }
+
+    /// Copy strides dimensions from an array.
+    pub fn copy_strides_from_array<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        strides: PointerValue<'ctx>,
+    ) {
+        let num_items = self.load_ndims(ctx);
+
+        call_memcpy_generic_array(
+            ctx,
+            self.strides().base_ptr(ctx, generator),
+            strides,
+            num_items,
+            ctx.ctx.bool_type().const_zero(),
+        );
+    }
+
+    /// Copy strides dimensions from an ndarray.
+    /// Panics if `ndims` mismatches.
+    pub fn copy_strides_from_ndarray<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        src_ndarray: NDArrayValue<'ctx>,
+    ) {
+        if self.ndims.is_some() && src_ndarray.ndims.is_some() {
+            assert_eq!(self.ndims, src_ndarray.ndims);
+        } else {
+            let self_ndims = self.load_ndims(ctx);
+            let src_ndims = src_ndarray.load_ndims(ctx);
+
+            ctx.make_assert(
+                generator,
+                ctx.builder.build_int_compare(
+                    IntPredicate::EQ,
+                    self_ndims,
+                    src_ndims,
+                    ""
+                ).unwrap(),
+                "0:AssertionError",
+                "NDArrayValue::copy_shape_from_ndarray: Expected self.ndims ({0}) == src_ndarray.ndims ({1})",
+                [Some(self_ndims), Some(src_ndims), None],
+                ctx.current_loc
+            );
+        }
+
+        let src_strides = src_ndarray.strides().base_ptr(ctx, generator);
+        self.copy_strides_from_array(generator, ctx, src_strides);
+    }
+
+    /// Get the `np.size()` of this ndarray.
+    pub fn size<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &CodeGenContext<'ctx, '_>,
+    ) -> IntValue<'ctx> {
+        irrt::ndarray::call_nac3_ndarray_size(generator, ctx, *self)
+    }
+
+    /// Get the `ndarray.nbytes` of this ndarray.
+    pub fn nbytes<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &CodeGenContext<'ctx, '_>,
+    ) -> IntValue<'ctx> {
+        irrt::ndarray::call_nac3_ndarray_nbytes(generator, ctx, *self)
+    }
+
+    /// Get the `len()` of this ndarray.
+    pub fn len<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &CodeGenContext<'ctx, '_>,
+    ) -> IntValue<'ctx> {
+        irrt::ndarray::call_nac3_ndarray_len(generator, ctx, *self)
+    }
+
+    /// Check if this ndarray is C-contiguous.
+    ///
+    /// See NumPy's `flags["C_CONTIGUOUS"]`: <https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flags.html#numpy.ndarray.flags>
+    pub fn is_c_contiguous<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &CodeGenContext<'ctx, '_>,
+    ) -> IntValue<'ctx> {
+        irrt::ndarray::call_nac3_ndarray_is_c_contiguous(generator, ctx, *self)
+    }
+
+    /// Call [`call_nac3_ndarray_set_strides_by_shape`] on this ndarray to update `strides`.
+    ///
+    /// Update the ndarray's strides to make the ndarray contiguous.
+    pub fn set_strides_contiguous<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &CodeGenContext<'ctx, '_>,
+    ) {
+        irrt::ndarray::call_nac3_ndarray_set_strides_by_shape(generator, ctx, *self);
+    }
+
+    #[must_use]
+    pub fn make_copy<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Self {
+        let clone = if self.ndims.is_some() {
+            self.get_type().construct_uninitialized(generator, ctx, None)
+        } else {
+            self.get_type().construct_dyn_ndims(generator, ctx, self.load_ndims(ctx), None)
+        };
+
+        let shape = self.shape();
+        clone.copy_shape_from_array(generator, ctx, shape.base_ptr(ctx, generator));
+        unsafe { clone.create_data(generator, ctx) };
+        clone.copy_data_from(generator, ctx, *self);
+        clone
+    }
+
+    /// Copy data from another ndarray.
+    ///
+    /// This ndarray and `src` is that their `np.size()` should be the same. Their shapes
+    /// do not matter. The copying order is determined by how their flattened views look.
+    ///
+    /// Panics if the `dtype`s of ndarrays are different.
+    pub fn copy_data_from<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        src: NDArrayValue<'ctx>,
+    ) {
+        assert_eq!(self.dtype, src.dtype, "self and src dtype should match");
+        irrt::ndarray::call_nac3_ndarray_copy_data(generator, ctx, src, *self);
+    }
+
+    /// Returns true if this ndarray is unsized - `ndims == 0` and only contains a scalar.
+    #[must_use]
+    pub fn is_unsized(&self) -> Option<bool> {
+        self.ndims.map(|ndims| ndims == 0)
+    }
+
+    /// If this ndarray is unsized, return its sole value as an [`AnyObject`].
+    /// Otherwise, do nothing and return the ndarray itself.
+    // TODO: Rename to get_unsized_element
+    pub fn split_unsized<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> ScalarOrNDArray<'ctx> {
+        let Some(is_unsized) = self.is_unsized() else { todo!() };
+
+        if is_unsized {
+            // NOTE: `np.size(self) == 0` here is never possible.
+            let zero = generator.get_size_type(ctx.ctx).const_zero();
+            let value = unsafe { self.data().get_unchecked(ctx, generator, &zero, None) };
+
+            ScalarOrNDArray::Scalar(value)
+        } else {
+            ScalarOrNDArray::NDArray(*self)
+        }
+    }
 }
 
 impl<'ctx> ProxyValue<'ctx> for NDArrayValue<'ctx> {
@@ -159,7 +439,12 @@ impl<'ctx> ProxyValue<'ctx> for NDArrayValue<'ctx> {
     type Type = NDArrayType<'ctx>;
 
     fn get_type(&self) -> Self::Type {
-        NDArrayType::from_type(self.as_base_value().get_type(), self.dtype, self.llvm_usize)
+        NDArrayType::from_type(
+            self.as_base_value().get_type(),
+            self.dtype,
+            self.ndims,
+            self.llvm_usize,
+        )
     }
 
     fn as_base_value(&self) -> Self::Base {
@@ -173,7 +458,7 @@ impl<'ctx> From<NDArrayValue<'ctx>> for PointerValue<'ctx> {
     }
 }
 
-/// Proxy type for accessing the `dims` array of an `NDArray` instance in LLVM.
+/// Proxy type for accessing the `shape` array of an `NDArray` instance in LLVM.
 #[derive(Copy, Clone)]
 pub struct NDArrayShapeProxy<'ctx, 'a>(&'a NDArrayValue<'ctx>);
 
@@ -265,6 +550,98 @@ impl<'ctx> TypedArrayLikeMutator<'ctx, IntValue<'ctx>> for NDArrayShapeProxy<'ct
     }
 }
 
+/// Proxy type for accessing the `strides` array of an `NDArray` instance in LLVM.
+#[derive(Copy, Clone)]
+pub struct NDArrayStridesProxy<'ctx, 'a>(&'a NDArrayValue<'ctx>);
+
+impl<'ctx> ArrayLikeValue<'ctx> for NDArrayStridesProxy<'ctx, '_> {
+    fn element_type<G: CodeGenerator + ?Sized>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        generator: &G,
+    ) -> AnyTypeEnum<'ctx> {
+        self.0.strides().base_ptr(ctx, generator).get_type().get_element_type()
+    }
+
+    fn base_ptr<G: CodeGenerator + ?Sized>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        _: &G,
+    ) -> PointerValue<'ctx> {
+        self.0.strides_field(ctx).get(ctx, self.0.as_base_value(), self.0.name)
+    }
+
+    fn size<G: CodeGenerator + ?Sized>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        _: &G,
+    ) -> IntValue<'ctx> {
+        self.0.load_ndims(ctx)
+    }
+}
+
+impl<'ctx> ArrayLikeIndexer<'ctx, IntValue<'ctx>> for NDArrayStridesProxy<'ctx, '_> {
+    unsafe fn ptr_offset_unchecked<G: CodeGenerator + ?Sized>(
+        &self,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        generator: &mut G,
+        idx: &IntValue<'ctx>,
+        name: Option<&str>,
+    ) -> PointerValue<'ctx> {
+        let var_name = name.map(|v| format!("{v}.addr")).unwrap_or_default();
+
+        unsafe {
+            ctx.builder
+                .build_in_bounds_gep(self.base_ptr(ctx, generator), &[*idx], var_name.as_str())
+                .unwrap()
+        }
+    }
+
+    fn ptr_offset<G: CodeGenerator + ?Sized>(
+        &self,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        generator: &mut G,
+        idx: &IntValue<'ctx>,
+        name: Option<&str>,
+    ) -> PointerValue<'ctx> {
+        let size = self.size(ctx, generator);
+        let in_range = ctx.builder.build_int_compare(IntPredicate::ULT, *idx, size, "").unwrap();
+        ctx.make_assert(
+            generator,
+            in_range,
+            "0:IndexError",
+            "index {0} is out of bounds for axis 0 with size {1}",
+            [Some(*idx), Some(self.0.load_ndims(ctx)), None],
+            ctx.current_loc,
+        );
+
+        unsafe { self.ptr_offset_unchecked(ctx, generator, idx, name) }
+    }
+}
+
+impl<'ctx> UntypedArrayLikeAccessor<'ctx, IntValue<'ctx>> for NDArrayStridesProxy<'ctx, '_> {}
+impl<'ctx> UntypedArrayLikeMutator<'ctx, IntValue<'ctx>> for NDArrayStridesProxy<'ctx, '_> {}
+
+impl<'ctx> TypedArrayLikeAccessor<'ctx, IntValue<'ctx>> for NDArrayStridesProxy<'ctx, '_> {
+    fn downcast_to_type(
+        &self,
+        _: &mut CodeGenContext<'ctx, '_>,
+        value: BasicValueEnum<'ctx>,
+    ) -> IntValue<'ctx> {
+        value.into_int_value()
+    }
+}
+
+impl<'ctx> TypedArrayLikeMutator<'ctx, IntValue<'ctx>> for NDArrayStridesProxy<'ctx, '_> {
+    fn upcast_from_type(
+        &self,
+        _: &mut CodeGenContext<'ctx, '_>,
+        value: IntValue<'ctx>,
+    ) -> BasicValueEnum<'ctx> {
+        value.into()
+    }
+}
+
 /// Proxy type for accessing the `data` array of an `NDArray` instance in LLVM.
 #[derive(Copy, Clone)]
 pub struct NDArrayDataProxy<'ctx, 'a>(&'a NDArrayValue<'ctx>);
@@ -291,7 +668,12 @@ impl<'ctx> ArrayLikeValue<'ctx> for NDArrayDataProxy<'ctx, '_> {
         ctx: &CodeGenContext<'ctx, '_>,
         generator: &G,
     ) -> IntValue<'ctx> {
-        call_ndarray_calc_size(generator, ctx, &self.as_slice_value(ctx, generator), (None, None))
+        irrt::ndarray::call_ndarray_calc_size(
+            generator,
+            ctx,
+            &self.as_slice_value(ctx, generator),
+            (None, None),
+        )
     }
 }
 
@@ -400,7 +782,7 @@ impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> ArrayLikeIndexer<'ctx, Index>
             indices_elem_ty.get_bit_width()
         );
 
-        let index = call_ndarray_flatten_index(generator, ctx, *self.0, indices);
+        let index = irrt::ndarray::call_ndarray_flatten_index(generator, ctx, *self.0, indices);
         let sizeof_elem = ctx
             .builder
             .build_int_truncate_or_bit_cast(
@@ -516,3 +898,36 @@ impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> UntypedArrayLikeMutator<'ctx,
     for NDArrayDataProxy<'ctx, '_>
 {
 }
+
+/// A version of [`call_nac3_ndarray_set_strides_by_shape`] in Rust.
+///
+/// This function is used generating strides for globally defined contiguous ndarrays.
+#[must_use]
+pub fn make_contiguous_strides(itemsize: u64, ndims: u64, shape: &[u64]) -> Vec<u64> {
+    let mut strides = Vec::with_capacity(ndims as usize);
+    let mut stride_product = 1u64;
+    for i in 0..ndims {
+        let axis = ndims - i - 1;
+        strides[axis as usize] = stride_product * itemsize;
+        stride_product *= shape[axis as usize];
+    }
+    strides
+}
+
+/// A convenience enum for implementing functions that acts on scalars or ndarrays or both.
+#[derive(Clone, Copy)]
+pub enum ScalarOrNDArray<'ctx> {
+    Scalar(BasicValueEnum<'ctx>),
+    NDArray(NDArrayValue<'ctx>),
+}
+
+impl<'ctx> ScalarOrNDArray<'ctx> {
+    /// Get the underlying [`BasicValueEnum<'ctx>`] of this [`ScalarOrNDArray`].
+    #[must_use]
+    pub fn to_basic_value_enum(self) -> BasicValueEnum<'ctx> {
+        match self {
+            ScalarOrNDArray::Scalar(scalar) => scalar,
+            ScalarOrNDArray::NDArray(ndarray) => ndarray.as_base_value().into(),
+        }
+    }
+}

nac3core/src/codegen/values/ndarray/nditer.rs

@@ -0,0 +1,176 @@
+use inkwell::{
+    types::{BasicType, IntType},
+    values::{BasicValueEnum, IntValue, PointerValue},
+    AddressSpace,
+};
+
+use super::{NDArrayValue, ProxyValue, TypedArrayLikeAccessor, TypedArrayLikeMutator};
+use crate::codegen::{
+    irrt,
+    stmt::{gen_for_callback, BreakContinueHooks},
+    types::{ndarray::NDIterType, structure::StructField},
+    values::{ArraySliceValue, TypedArrayLikeAdapter},
+    CodeGenContext, CodeGenerator,
+};
+
+#[derive(Copy, Clone)]
+pub struct NDIterValue<'ctx> {
+    value: PointerValue<'ctx>,
+    parent: NDArrayValue<'ctx>,
+    indices: ArraySliceValue<'ctx>,
+    llvm_usize: IntType<'ctx>,
+    name: Option<&'ctx str>,
+}
+
+impl<'ctx> NDIterValue<'ctx> {
+    /// Checks whether `value` is an instance of `NDArray`, returning [Err] if `value` is not an
+    /// instance.
+    pub fn is_representable(
+        value: PointerValue<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> Result<(), String> {
+        <Self as ProxyValue>::Type::is_representable(value.get_type(), llvm_usize)
+    }
+
+    /// Creates an [`NDArrayValue`] from a [`PointerValue`].
+    #[must_use]
+    pub fn from_pointer_value(
+        ptr: PointerValue<'ctx>,
+        parent: NDArrayValue<'ctx>,
+        indices: ArraySliceValue<'ctx>,
+        llvm_usize: IntType<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> Self {
+        debug_assert!(Self::is_representable(ptr, llvm_usize).is_ok());
+
+        Self { value: ptr, parent, indices, llvm_usize, name }
+    }
+
+    /// Is the current iteration valid?
+    ///
+    /// If true, then `element`, `indices` and `nth` contain details about the current element.
+    ///
+    /// If `ndarray` is unsized, this returns true only for the first iteration.
+    /// If `ndarray` is 0-sized, this always returns false.
+    #[must_use]
+    pub fn has_element<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &CodeGenContext<'ctx, '_>,
+    ) -> IntValue<'ctx> {
+        irrt::ndarray::call_nac3_nditer_has_element(generator, ctx, *self)
+    }
+
+    /// Go to the next element. If `has_element()` is false, then this has undefined behavior.
+    ///
+    /// If `ndarray` is unsized, this can only be called once.
+    /// If `ndarray` is 0-sized, this can never be called.
+    pub fn next<G: CodeGenerator + ?Sized>(&self, generator: &G, ctx: &CodeGenContext<'ctx, '_>) {
+        irrt::ndarray::call_nac3_nditer_next(generator, ctx, *self);
+    }
+
+    fn element(&self, ctx: &CodeGenContext<'ctx, '_>) -> StructField<'ctx, PointerValue<'ctx>> {
+        self.get_type().get_fields(ctx.ctx).element
+    }
+
+    /// Get pointer to the current element.
+    #[must_use]
+    pub fn get_pointer(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
+        let elem_ty = self.parent.dtype;
+
+        let p = self.element(ctx).get(ctx, self.as_base_value(), None);
+        ctx.builder
+            .build_pointer_cast(p, elem_ty.ptr_type(AddressSpace::default()), "element")
+            .unwrap()
+    }
+
+    /// Get the value of the current element.
+    #[must_use]
+    pub fn get_scalar(&self, ctx: &CodeGenContext<'ctx, '_>) -> BasicValueEnum<'ctx> {
+        let p = self.get_pointer(ctx);
+        ctx.builder.build_load(p, "value").unwrap()
+    }
+
+    fn nth(&self, ctx: &CodeGenContext<'ctx, '_>) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields(ctx.ctx).nth
+    }
+
+    /// Get the index of the current element if this ndarray were a flat ndarray.
+    #[must_use]
+    pub fn get_index(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
+        self.nth(ctx).get(ctx, self.as_base_value(), None)
+    }
+
+    /// Get the indices of the current element.
+    #[must_use]
+    pub fn get_indices(
+        &'ctx self,
+    ) -> impl TypedArrayLikeAccessor<'ctx, IntValue<'ctx>> + TypedArrayLikeMutator<'ctx, IntValue<'ctx>>
+    {
+        TypedArrayLikeAdapter::from(
+            self.indices,
+            Box::new(|ctx, val| {
+                ctx.builder
+                    .build_int_z_extend_or_bit_cast(val.into_int_value(), self.llvm_usize, "")
+                    .unwrap()
+            }),
+            Box::new(|_, val| val.into()),
+        )
+    }
+}
+
+impl<'ctx> ProxyValue<'ctx> for NDIterValue<'ctx> {
+    type Base = PointerValue<'ctx>;
+    type Type = NDIterType<'ctx>;
+
+    fn get_type(&self) -> Self::Type {
+        NDIterType::from_type(self.as_base_value().get_type(), self.llvm_usize)
+    }
+
+    fn as_base_value(&self) -> Self::Base {
+        self.value
+    }
+}
+
+impl<'ctx> From<NDIterValue<'ctx>> for PointerValue<'ctx> {
+    fn from(value: NDIterValue<'ctx>) -> Self {
+        value.as_base_value()
+    }
+}
+
+impl<'ctx> NDArrayValue<'ctx> {
+    /// Iterate through every element in the ndarray.
+    ///
+    /// `body` has access to [`BreakContinueHooks`] to short-circuit and [`NDIterValue`] to
+    /// get properties of the current iteration (e.g., the current element, indices, etc.)
+    pub fn foreach<'a, G, F>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, 'a>,
+        body: F,
+    ) -> Result<(), String>
+    where
+        G: CodeGenerator + ?Sized,
+        F: FnOnce(
+            &mut G,
+            &mut CodeGenContext<'ctx, 'a>,
+            BreakContinueHooks<'ctx>,
+            NDIterValue<'ctx>,
+        ) -> Result<(), String>,
+    {
+        gen_for_callback(
+            generator,
+            ctx,
+            Some("ndarray_foreach"),
+            |generator, ctx| {
+                Ok(NDIterType::new(generator, ctx.ctx).construct(generator, ctx, *self))
+            },
+            |generator, ctx, nditer| Ok(nditer.has_element(generator, ctx)),
+            |generator, ctx, hooks, nditer| body(generator, ctx, hooks, nditer),
+            |generator, ctx, nditer| {
+                nditer.next(generator, ctx);
+                Ok(())
+            },
+        )
+    }
+}

nac3core/src/codegen/values/ndarray/view.rs

@@ -0,0 +1,36 @@
+use std::iter::{once, repeat_n};
+
+use itertools::Itertools;
+
+use crate::codegen::{
+    values::ndarray::{NDArrayValue, RustNDIndex},
+    CodeGenContext, CodeGenerator,
+};
+
+impl<'ctx> NDArrayValue<'ctx> {
+    /// Make sure the ndarray is at least `ndmin`-dimensional.
+    ///
+    /// If this ndarray's `ndims` is less than `ndmin`, a view is created on this with 1s prepended
+    /// to the shape. Otherwise, this function does nothing and return this ndarray.
+    #[must_use]
+    pub fn atleast_nd<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ndmin: u64,
+    ) -> Self {
+        assert!(self.ndims.is_some(), "NDArrayValue::atleast_nd is only supported for instances with compile-time known ndims (self.ndims = Some(...))");
+
+        let ndims = self.ndims.unwrap();
+
+        if ndims < ndmin {
+            // Extend the dimensions with np.newaxis.
+            let indices = repeat_n(RustNDIndex::NewAxis, (ndmin - ndims) as usize)
+                .chain(once(RustNDIndex::Ellipsis))
+                .collect_vec();
+            self.index(generator, ctx, &indices)
+        } else {
+            *self
+        }
+    }
+}

nac3core/src/codegen/values/utils/mod.rs

@@ -0,0 +1,3 @@
+pub use slice::*;
+
+mod slice;

nac3core/src/codegen/values/utils/slice.rs

@@ -0,0 +1,231 @@
+use inkwell::{
+    types::IntType,
+    values::{IntValue, PointerValue},
+};
+
+use nac3parser::ast::Expr;
+
+use crate::{
+    codegen::{
+        types::{structure::StructField, utils::SliceType},
+        values::ProxyValue,
+        CodeGenContext, CodeGenerator,
+    },
+    typecheck::typedef::Type,
+};
+
+/// An IRRT representation of an (unresolved) slice.
+#[derive(Copy, Clone)]
+pub struct SliceValue<'ctx> {
+    value: PointerValue<'ctx>,
+    int_ty: IntType<'ctx>,
+    llvm_usize: IntType<'ctx>,
+    name: Option<&'ctx str>,
+}
+
+impl<'ctx> SliceValue<'ctx> {
+    /// Checks whether `value` is an instance of `ContiguousNDArray`, returning [Err] if `value` is
+    /// not an instance.
+    pub fn is_representable(
+        value: PointerValue<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> Result<(), String> {
+        <Self as ProxyValue<'ctx>>::Type::is_representable(value.get_type(), llvm_usize)
+    }
+
+    /// Creates an [`SliceValue`] from a [`PointerValue`].
+    #[must_use]
+    pub fn from_pointer_value(
+        ptr: PointerValue<'ctx>,
+        int_ty: IntType<'ctx>,
+        llvm_usize: IntType<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> Self {
+        debug_assert!(Self::is_representable(ptr, llvm_usize).is_ok());
+
+        Self { value: ptr, int_ty, llvm_usize, name }
+    }
+
+    fn start_defined_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields().start_defined
+    }
+
+    pub fn load_start_defined(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
+        self.start_defined_field().get(ctx, self.value, self.name)
+    }
+
+    fn start_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields().start
+    }
+
+    pub fn load_start(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
+        self.start_field().get(ctx, self.value, self.name)
+    }
+
+    pub fn store_start(&self, ctx: &CodeGenContext<'ctx, '_>, value: Option<IntValue<'ctx>>) {
+        match value {
+            Some(start) => {
+                self.start_defined_field().set(
+                    ctx,
+                    self.value,
+                    ctx.ctx.bool_type().const_all_ones(),
+                    self.name,
+                );
+                self.start_field().set(ctx, self.value, start, self.name);
+            }
+
+            None => self.start_defined_field().set(
+                ctx,
+                self.value,
+                ctx.ctx.bool_type().const_zero(),
+                self.name,
+            ),
+        }
+    }
+
+    fn stop_defined_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields().stop_defined
+    }
+
+    pub fn load_stop_defined(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
+        self.stop_defined_field().get(ctx, self.value, self.name)
+    }
+
+    fn stop_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields().stop
+    }
+
+    pub fn load_stop(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
+        self.stop_field().get(ctx, self.value, self.name)
+    }
+
+    pub fn store_stop(&self, ctx: &CodeGenContext<'ctx, '_>, value: Option<IntValue<'ctx>>) {
+        match value {
+            Some(stop) => {
+                self.stop_defined_field().set(
+                    ctx,
+                    self.value,
+                    ctx.ctx.bool_type().const_all_ones(),
+                    self.name,
+                );
+                self.stop_field().set(ctx, self.value, stop, self.name);
+            }
+
+            None => self.stop_defined_field().set(
+                ctx,
+                self.value,
+                ctx.ctx.bool_type().const_zero(),
+                self.name,
+            ),
+        }
+    }
+
+    fn step_defined_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields().step_defined
+    }
+
+    pub fn load_step_defined(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
+        self.step_defined_field().get(ctx, self.value, self.name)
+    }
+
+    fn step_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields().step
+    }
+
+    pub fn load_step(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
+        self.step_field().get(ctx, self.value, self.name)
+    }
+
+    pub fn store_step(&self, ctx: &CodeGenContext<'ctx, '_>, value: Option<IntValue<'ctx>>) {
+        match value {
+            Some(step) => {
+                self.step_defined_field().set(
+                    ctx,
+                    self.value,
+                    ctx.ctx.bool_type().const_all_ones(),
+                    self.name,
+                );
+                self.step_field().set(ctx, self.value, step, self.name);
+            }
+
+            None => self.step_defined_field().set(
+                ctx,
+                self.value,
+                ctx.ctx.bool_type().const_zero(),
+                self.name,
+            ),
+        }
+    }
+}
+
+impl<'ctx> ProxyValue<'ctx> for SliceValue<'ctx> {
+    type Base = PointerValue<'ctx>;
+    type Type = SliceType<'ctx>;
+
+    fn get_type(&self) -> Self::Type {
+        Self::Type::from_type(self.value.get_type(), self.int_ty, self.llvm_usize)
+    }
+
+    fn as_base_value(&self) -> Self::Base {
+        self.value
+    }
+}
+
+impl<'ctx> From<SliceValue<'ctx>> for PointerValue<'ctx> {
+    fn from(value: SliceValue<'ctx>) -> Self {
+        value.as_base_value()
+    }
+}
+
+/// A slice represented in compile-time by `start`, `stop` and `step`, all held as LLVM values.
+// TODO: Rename this to CTConstSlice
+#[derive(Debug, Copy, Clone)]
+pub struct RustSlice<'ctx> {
+    int_ty: IntType<'ctx>,
+    start: Option<IntValue<'ctx>>,
+    stop: Option<IntValue<'ctx>>,
+    step: Option<IntValue<'ctx>>,
+}
+
+impl<'ctx> RustSlice<'ctx> {
+    /// Generate LLVM IR for an [`ExprKind::Slice`] and convert it into a [`RustSlice`].
+    #[allow(clippy::type_complexity)]
+    pub fn from_slice_expr<G: CodeGenerator>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        lower: &Option<Box<Expr<Option<Type>>>>,
+        upper: &Option<Box<Expr<Option<Type>>>>,
+        step: &Option<Box<Expr<Option<Type>>>>,
+    ) -> Result<RustSlice<'ctx>, String> {
+        let mut value_mapper = |value_expr: &Option<Box<Expr<Option<Type>>>>| -> Result<_, String> {
+            Ok(match value_expr {
+                None => None,
+                Some(value_expr) => {
+                    let value_expr = generator
+                        .gen_expr(ctx, value_expr)?
+                        .map(|value| {
+                            value.to_basic_value_enum(ctx, generator, ctx.primitives.int32)
+                        })
+                        .unwrap()?;
+
+                    Some(value_expr.into_int_value())
+                }
+            })
+        };
+
+        let start = value_mapper(lower)?;
+        let stop = value_mapper(upper)?;
+        let step = value_mapper(step)?;
+
+        Ok(RustSlice { int_ty: ctx.ctx.i32_type(), start, stop, step })
+    }
+
+    /// Write the contents to an LLVM [`SliceValue`].
+    pub fn write_to_slice(&self, ctx: &CodeGenContext<'ctx, '_>, dst_slice_ptr: SliceValue<'ctx>) {
+        assert_eq!(self.int_ty, dst_slice_ptr.int_ty);
+
+        dst_slice_ptr.store_start(ctx, self.start);
+        dst_slice_ptr.store_stop(ctx, self.stop);
+        dst_slice_ptr.store_step(ctx, self.step);
+    }
+}

nix/windows/msys2_packages.nix

@@ -1,15 +1,15 @@
 { pkgs } : [
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libunwind-18.1.8-2-any.pkg.tar.zst";
-  sha256 = "0f9m76dx40iy794nfks0360gvjhdg6yngb2lyhwp4xd76rn5081m";
-  name = "mingw-w64-clang-x86_64-libunwind-18.1.8-2-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libunwind-19.1.4-1-any.pkg.tar.zst";
+  sha256 = "0frb5k16bbxdf8g379d16vl3qrh7n9pydn83gpfxpvwf3qlvnzyl";
+  name = "mingw-w64-clang-x86_64-libunwind-19.1.4-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libc++-18.1.8-2-any.pkg.tar.zst";
-  sha256 = "17savj9wys9my2ji7vyba7wwqkvzdjwnkb3k4858wxrjbzbfa6lk";
-  name = "mingw-w64-clang-x86_64-libc++-18.1.8-2-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libc++-19.1.4-1-any.pkg.tar.zst";
+  sha256 = "0wh5km0v8j50pqz9bxb4f0w7r8zhsvssrjvc94np53iq8wjagk86";
+  name = "mingw-w64-clang-x86_64-libc++-19.1.4-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
@@ -31,9 +31,9 @@
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-xz-5.6.2-2-any.pkg.tar.zst";
-  sha256 = "0phb9hwqksk1rg29yhwlc7si78zav19c2kac0i841pc7mc2n9gzx";
-  name = "mingw-w64-clang-x86_64-xz-5.6.2-2-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-xz-5.6.3-3-any.pkg.tar.zst";
+  sha256 = "1a7gc462gnrjy5qb0zfkr9qm8bsnnf02y6wp3c59n618dhsq7rcf";
+  name = "mingw-w64-clang-x86_64-xz-5.6.3-3-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
@@ -43,9 +43,9 @@
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libxml2-2.12.9-1-any.pkg.tar.zst";
-  sha256 = "0cjz2vj9yz6k5xj601cp0yk631rrr0z94ciamwqrvclb0yhakf25";
-  name = "mingw-w64-clang-x86_64-libxml2-2.12.9-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libxml2-2.12.9-2-any.pkg.tar.zst";
+  sha256 = "1b1r5llgqv88id8iwhqh23qwqmn5ic9hdamdc8xzij9hmcvdmmci";
+  name = "mingw-w64-clang-x86_64-libxml2-2.12.9-2-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
@@ -55,75 +55,87 @@
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-llvm-libs-18.1.8-1-any.pkg.tar.zst";
-  sha256 = "0rpbgvvinsqflhd3nhfxk0g0yy8j80zzw5yx6573ak0m78a9fa06";
-  name = "mingw-w64-clang-x86_64-llvm-libs-18.1.8-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-llvm-libs-19.1.4-1-any.pkg.tar.zst";
+  sha256 = "1clrbm8dk893byj8s15pgcgqqijm2zkd10zgyakamd8m354kj9q4";
+  name = "mingw-w64-clang-x86_64-llvm-libs-19.1.4-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-llvm-18.1.8-1-any.pkg.tar.zst";
-  sha256 = "185g5h8q3x3rav9lp2njln58ny2idh2067fd02j3nsbik6glshpf";
-  name = "mingw-w64-clang-x86_64-llvm-18.1.8-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-llvm-19.1.4-1-any.pkg.tar.zst";
+  sha256 = "1iz2c9475h8p20ydpp0znbhyb62rlrk7wr7xl7cmwbam7wkwr8rn";
+  name = "mingw-w64-clang-x86_64-llvm-19.1.4-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-clang-libs-18.1.8-1-any.pkg.tar.zst";
-  sha256 = "089hji3yd7wsd03v9mdfgc99l5k1dql8kg7p3hy13vrbgfsabxhc";
-  name = "mingw-w64-clang-x86_64-clang-libs-18.1.8-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-clang-libs-19.1.4-1-any.pkg.tar.zst";
+  sha256 = "1hidciwlakxrp4kyb0j2v6g4lv76nn834g6b88w1j94fk3qc765d";
+  name = "mingw-w64-clang-x86_64-clang-libs-19.1.4-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-compiler-rt-18.1.8-1-any.pkg.tar.zst";
-  sha256 = "1dwcxnv1k5ljim5ys4h1c3jlrdpi0054z094ynav7if65i8zjj4a";
-  name = "mingw-w64-clang-x86_64-compiler-rt-18.1.8-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-compiler-rt-19.1.4-1-any.pkg.tar.zst";
+  sha256 = "1m1yhjkgzlbk10sv966qk4yji009ga0lr25gpgj2w7mcd2wixcr3";
+  name = "mingw-w64-clang-x86_64-compiler-rt-19.1.4-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-headers-git-12.0.0.r250.gc6bf4bdf6-1-any.pkg.tar.zst";
-  sha256 = "0163jzjlvq7inpafy3h48pkwag3ysk6x56xm84yfcz5q52fnfzq5";
-  name = "mingw-w64-clang-x86_64-headers-git-12.0.0.r250.gc6bf4bdf6-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-headers-git-12.0.0.r423.g8bcd5fc1a-1-any.pkg.tar.zst";
+  sha256 = "08gxc7h2achckknn6fz3p6yi7gxxvbaday8fpm4j56c4sa04n0df";
+  name = "mingw-w64-clang-x86_64-headers-git-12.0.0.r423.g8bcd5fc1a-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-crt-git-12.0.0.r250.gc6bf4bdf6-1-any.pkg.tar.zst";
-  sha256 = "00cn1mi29mfys7qy4hvgnjd0smqvnkdn3ibnrr6a3wy1h2vaykgq";
-  name = "mingw-w64-clang-x86_64-crt-git-12.0.0.r250.gc6bf4bdf6-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-crt-git-12.0.0.r423.g8bcd5fc1a-1-any.pkg.tar.zst";
+  sha256 = "0fxd1pb197ki0gzw6z8gmd6wgpd9d28js6cp5d31d55kw7d1vz13";
+  name = "mingw-w64-clang-x86_64-crt-git-12.0.0.r423.g8bcd5fc1a-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-lld-18.1.8-1-any.pkg.tar.zst";
-  sha256 = "1vpij5d06m4kjy3qv8bizwlkl21gcv6fv0r2f1j9bclgm6k3144x";
-  name = "mingw-w64-clang-x86_64-lld-18.1.8-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-lld-19.1.4-1-any.pkg.tar.zst";
+  sha256 = "1a8pjyhrzpc2z3784xxwix4i7yrz03ygnsk1wv9k0yq8m8wi9nbw";
+  name = "mingw-w64-clang-x86_64-lld-19.1.4-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libwinpthread-git-12.0.0.r250.gc6bf4bdf6-1-any.pkg.tar.zst";
-  sha256 = "1zkzqqd31xpkv817wja3qssjjx891bsdxw07037hv2sk0qr4ffn9";
-  name = "mingw-w64-clang-x86_64-libwinpthread-git-12.0.0.r250.gc6bf4bdf6-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libwinpthread-git-12.0.0.r423.g8bcd5fc1a-1-any.pkg.tar.zst";
+  sha256 = "140m312jx1sywqjkvfij69d268m4jpdmilq5bb8khkf0ayb16036";
+  name = "mingw-w64-clang-x86_64-libwinpthread-git-12.0.0.r423.g8bcd5fc1a-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-winpthreads-git-12.0.0.r250.gc6bf4bdf6-1-any.pkg.tar.zst";
-  sha256 = "02ynia88ad3l03r08nyldmnajwqkyxcjd191lyamkbj4d6zck323";
-  name = "mingw-w64-clang-x86_64-winpthreads-git-12.0.0.r250.gc6bf4bdf6-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-winpthreads-git-12.0.0.r423.g8bcd5fc1a-1-any.pkg.tar.zst";
+  sha256 = "017j4h511wg37bacym73f8g6s0jcfgzbzabzxpc6anr3gy4kkpbg";
+  name = "mingw-w64-clang-x86_64-winpthreads-git-12.0.0.r423.g8bcd5fc1a-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-clang-18.1.8-1-any.pkg.tar.zst";
-  sha256 = "1qny934nv4g75k9gb5sf31v24bgafkg6qw7r35xv3in491w6annq";
-  name = "mingw-w64-clang-x86_64-clang-18.1.8-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-clang-19.1.4-1-any.pkg.tar.zst";
+  sha256 = "11f4i4ai2bzvq6f06vxk1ymv7056c9707vdw489f1i2bdrf0c0ii";
+  name = "mingw-w64-clang-x86_64-clang-19.1.4-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-c-ares-1.33.1-1-any.pkg.tar.zst";
-  sha256 = "14r6jjsvfbapbkv2zqp2yglva4vz4srzkgk7f186ri3kcafjspgq";
-  name = "mingw-w64-clang-x86_64-c-ares-1.33.1-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-rust-1.83.0-3-any.pkg.tar.zst";
+  sha256 = "0nxs571vb4f1i5vp91134p5blns9ml2r25nx6kdlg0zhd5x85kvm";
+  name = "mingw-w64-clang-x86_64-rust-1.83.0-3-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-brotli-1.1.0-2-any.pkg.tar.zst";
-  sha256 = "1q01lz9lcyrjmkhv9rddgjazmk7warlcmwhc4qkq9y6h0yfsb71n";
-  name = "mingw-w64-clang-x86_64-brotli-1.1.0-2-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-cppdap-1.65-1-any.pkg.tar.zst";
+  sha256 = "0phhwkcqp30dsyj5vr6w99sgm1jfm5rzg0w5x5mv9md4x7lm9lmh";
+  name = "mingw-w64-clang-x86_64-cppdap-1.65-1-any.pkg.tar.zst";
+})
+
+(pkgs.fetchurl {
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-c-ares-1.34.3-1-any.pkg.tar.zst";
+  sha256 = "1mpn397qsdz3l2fav6ymwjlj96ialn9m8sldii3ymbcyhranl3xx";
+  name = "mingw-w64-clang-x86_64-c-ares-1.34.3-1-any.pkg.tar.zst";
+})
+
+(pkgs.fetchurl {
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-brotli-1.1.0-4-any.pkg.tar.zst";
+  sha256 = "0hx9gjzibacfx3fzk11n2vzz2pmnb956babh2ig8avx3hk7vlqrg";
+  name = "mingw-w64-clang-x86_64-brotli-1.1.0-4-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
@@ -139,9 +151,9 @@
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libpsl-0.21.5-2-any.pkg.tar.zst";
-  sha256 = "1mpx77q5g8pj45s8wgc52c4ww2r93080p6d559p56f558a3cl317";
-  name = "mingw-w64-clang-x86_64-libpsl-0.21.5-2-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libpsl-0.21.5-3-any.pkg.tar.zst";
+  sha256 = "0hb7wgdliic3d7fa0cvr5pj946pmwfc0apmyb0yfb5d0hc1afwsc";
+  name = "mingw-w64-clang-x86_64-libpsl-0.21.5-3-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
@@ -163,57 +175,45 @@
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-openssl-3.3.2-1-any.pkg.tar.zst";
-  sha256 = "1djgpcz447yvhdy1yq5wh8l5d0821izxklx9afyszbw0pbr7f24y";
-  name = "mingw-w64-clang-x86_64-openssl-3.3.2-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-openssl-3.4.0-1-any.pkg.tar.zst";
+  sha256 = "0cgiqjmgdnwnv9r88z634dmqrzh06dmsfncyzymw0s16nnv2k7k2";
+  name = "mingw-w64-clang-x86_64-openssl-3.4.0-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libssh2-1.11.0-2-any.pkg.tar.zst";
-  sha256 = "0l2m823gm1rvnjmqm5ads17mxz1bhpzai5ixyhnkpzrsjxd1ygy5";
-  name = "mingw-w64-clang-x86_64-libssh2-1.11.0-2-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libssh2-1.11.1-1-any.pkg.tar.zst";
+  sha256 = "01l23cn5brficjzba7ldscqkdvk4rdcvvdyybd90qr2hqzligmhn";
+  name = "mingw-w64-clang-x86_64-libssh2-1.11.1-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-nghttp2-1.63.0-1-any.pkg.tar.zst";
-  sha256 = "0lfqrlmapsc7ilxjmhr7hxi578vclqlhpqimbvzq0c70c0iwk864";
-  name = "mingw-w64-clang-x86_64-nghttp2-1.63.0-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-nghttp2-1.64.0-1-any.pkg.tar.zst";
+  sha256 = "1hv8fp496l018s5dx5v8nvxc0a6rswskwk1jsrfd94rh3kbq2ilc";
+  name = "mingw-w64-clang-x86_64-nghttp2-1.64.0-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-nghttp3-1.5.0-1-any.pkg.tar.zst";
-  sha256 = "1ljl9kdasf91bxkqcmbbjchp5g00ahv8jn2zab38899z6j3x43nz";
-  name = "mingw-w64-clang-x86_64-nghttp3-1.5.0-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-nghttp3-1.6.0-1-any.pkg.tar.zst";
+  sha256 = "1p7q47fin12vzyf126v1azbbpgpa0y6ighfh6mbfdb6zcyq74kbd";
+  name = "mingw-w64-clang-x86_64-nghttp3-1.6.0-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-curl-8.9.1-2-any.pkg.tar.zst";
-  sha256 = "1zr6kgqp9i4qqrfckh3kfmz4x1cwv4xis9sfqsx7xji88priax64";
-  name = "mingw-w64-clang-x86_64-curl-8.9.1-2-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-curl-8.11.1-1-any.pkg.tar.zst";
+  sha256 = "16yvyqjzxyzawgv26r1g145wphvhjil2b0pyhy4nj7v5d19n6wvh";
+  name = "mingw-w64-clang-x86_64-curl-8.11.1-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-rust-1.80.1-1-any.pkg.tar.zst";
-  sha256 = "1dm4vlrfi9m6xl09zpn0yjr7qcjjr4x738z1rjfwysfnc0awq4x8";
-  name = "mingw-w64-clang-x86_64-rust-1.80.1-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-expat-2.6.4-1-any.pkg.tar.zst";
+  sha256 = "03fp2yacv7gk0g049lffz6pbj93vpjmzqxxa312d4gxczi57nqdv";
+  name = "mingw-w64-clang-x86_64-expat-2.6.4-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-cppdap-1.65-1-any.pkg.tar.zst";
-  sha256 = "0phhwkcqp30dsyj5vr6w99sgm1jfm5rzg0w5x5mv9md4x7lm9lmh";
-  name = "mingw-w64-clang-x86_64-cppdap-1.65-1-any.pkg.tar.zst";
-})
-
-(pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-expat-2.6.3-1-any.pkg.tar.zst";
-  sha256 = "19xfl1q78q1k8j0lr5aspcf668pmfg01fgib73zq7ff7y5y5fcyi";
-  name = "mingw-w64-clang-x86_64-expat-2.6.3-1-any.pkg.tar.zst";
-})
-
-(pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-jsoncpp-1.9.5-3-any.pkg.tar.zst";
-  sha256 = "1a8mdn4ram9pgqpx5fwxmhcmzc6bh1fq1s4m37xh0d8p6fpncv10";
-  name = "mingw-w64-clang-x86_64-jsoncpp-1.9.5-3-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-jsoncpp-1.9.6-3-any.pkg.tar.zst";
+  sha256 = "1ipilhiza17vz5dhgi61l80w2klw9f21w6jbyhi9wmfd6nxqv13c";
+  name = "mingw-w64-clang-x86_64-jsoncpp-1.9.6-3-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
@@ -235,27 +235,27 @@
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libtre-git-r177.07e66d0-2-any.pkg.tar.zst";
-  sha256 = "0fc9hxsdks1xy5fv0rcna433hlzf6jhs77hg0hfzkzhn06f9alp4";
-  name = "mingw-w64-clang-x86_64-libtre-git-r177.07e66d0-2-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libtre-0.9.0-1-any.pkg.tar.zst";
+  sha256 = "1y5d2cbkpd0ngqlsv6hvz47nxb1wry33i5s1clg2k53yhgjkg8vv";
+  name = "mingw-w64-clang-x86_64-libtre-0.9.0-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libsystre-1.0.1-5-any.pkg.tar.zst";
-  sha256 = "05qsn8fkks4f93jkas43s47axqqgx5m64b45p462si3nlb8cjirq";
-  name = "mingw-w64-clang-x86_64-libsystre-1.0.1-5-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libsystre-1.0.1-6-any.pkg.tar.zst";
+  sha256 = "19c71fs5gqjrf88mv7l702fjg228xd9lfbxg0mkzm3ljvv4ljn0q";
+  name = "mingw-w64-clang-x86_64-libsystre-1.0.1-6-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libarchive-3.7.4-1-any.pkg.tar.zst";
-  sha256 = "1ykw6imllgxv6lsgwxx1miqjr4l1iryqkrj286jcbfrb8ghpzhv5";
-  name = "mingw-w64-clang-x86_64-libarchive-3.7.4-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libarchive-3.7.7-1-any.pkg.tar.zst";
+  sha256 = "01glychb0k1yd878aq4y2fn08lqh2bjydh90xmq03z5qhig66mmn";
+  name = "mingw-w64-clang-x86_64-libarchive-3.7.7-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libuv-1.48.0-1-any.pkg.tar.zst";
-  sha256 = "0kfzanvx7hg7bvy35h2z2vcfxvwn44sikd36mvzhkv6c3c6y84sn";
-  name = "mingw-w64-clang-x86_64-libuv-1.48.0-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libuv-1.49.2-1-any.pkg.tar.zst";
+  sha256 = "1b9slshbcprxjaj2qqypaywr0f2pgajg1bgspjk83hk65sx6sklb";
+  name = "mingw-w64-clang-x86_64-libuv-1.49.2-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
@@ -277,9 +277,9 @@
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-cmake-3.30.3-1-any.pkg.tar.zst";
-  sha256 = "0fjwf6xxzli6rcsbzr1razldmm538ibkyf5kw132lpaz5wma9bj8";
-  name = "mingw-w64-clang-x86_64-cmake-3.30.3-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-cmake-3.31.2-3-any.pkg.tar.zst";
+  sha256 = "139f91r392c68hsajm0c81690pmzkywb0p4x8ms8ms53ncxnz6gz";
+  name = "mingw-w64-clang-x86_64-cmake-3.31.2-3-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
@@ -289,9 +289,9 @@
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-ncurses-6.4.20231217-1-any.pkg.tar.zst";
-  sha256 = "00046d52zsr8zjifl7h22jfihhh53h20ipvbqmvf9myssw2fwjza";
-  name = "mingw-w64-clang-x86_64-ncurses-6.4.20231217-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-ncurses-6.5.20240831-1-any.pkg.tar.zst";
+  sha256 = "1hlfj9g4s767s502sawwbcv4a0xd3ym3ip4jswmhq48wh5050iyb";
+  name = "mingw-w64-clang-x86_64-ncurses-6.5.20240831-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
@@ -307,15 +307,15 @@
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-tcl-8.6.13-1-any.pkg.tar.zst";
-  sha256 = "0paaqwk0sfy2zxwlxkmxf2bqq46lyg0sx7cqgzknvazwx8xa2z4x";
-  name = "mingw-w64-clang-x86_64-tcl-8.6.13-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-sqlite3-3.47.2-1-any.pkg.tar.zst";
+  sha256 = "10pavblv9yjirlm5hix9aikpswhiamry097clba6jcvsajlx4azy";
+  name = "mingw-w64-clang-x86_64-sqlite3-3.47.2-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-sqlite3-3.46.1-1-any.pkg.tar.zst";
-  sha256 = "1axplxyjnaz411qzjjqwbj55fbrh4akq3plm2p1sx64jp844xpyq";
-  name = "mingw-w64-clang-x86_64-sqlite3-3.46.1-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-tcl-8.6.13-1-any.pkg.tar.zst";
+  sha256 = "0paaqwk0sfy2zxwlxkmxf2bqq46lyg0sx7cqgzknvazwx8xa2z4x";
+  name = "mingw-w64-clang-x86_64-tcl-8.6.13-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
@@ -325,44 +325,38 @@
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-tzdata-2024a-1-any.pkg.tar.zst";
-  sha256 = "1lsfn3759cyf56zlmfvgy6ihs4iks6zhlnrbfmnq5wml02k936ji";
-  name = "mingw-w64-clang-x86_64-tzdata-2024a-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-tzdata-2024b-1-any.pkg.tar.zst";
+  sha256 = "0jihnr1i7vyzczxz60ds1x3gcm3p4ad2pq9d5vvpwjdwrxkvxmkc";
+  name = "mingw-w64-clang-x86_64-tzdata-2024b-1-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-python3.12-3.12.1-2-any.pkg.tar.zst";
-  sha256 = "0wmd39wl9z237w093a7c6hl5pclca9yvwxn0kiw6i2njk3sjv51a";
-  name = "mingw-w64-clang-x86_64-python3.12-3.12.1-2-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-python-3.12.7-3-any.pkg.tar.zst";
+  sha256 = "1v15j2pzy9wj4n1rjngdi2hf8h0l9z4lri3xb86yvdv1xl2msj6h";
+  name = "mingw-w64-clang-x86_64-python-3.12.7-3-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-python-3.11.9-1-any.pkg.tar.zst";
-  sha256 = "0ah1idjqxg7jc07a1gz9z766rjjd0f0c6ri4hpcsimsrbj1zjd3c";
-  name = "mingw-w64-clang-x86_64-python-3.11.9-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-llvm-openmp-19.1.4-2-any.pkg.tar.zst";
+  sha256 = "1pn1fbj74rx837s9z8gqs4b0cr7kqi5m1m2mi9ibjpw64m1aqwxv";
+  name = "mingw-w64-clang-x86_64-llvm-openmp-19.1.4-2-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-llvm-openmp-18.1.8-1-any.pkg.tar.zst";
-  sha256 = "0cy2v0l4af24j34mzj5q5nlzcqhackfajlfj1rpf6mb3rbz23qw9";
-  name = "mingw-w64-clang-x86_64-llvm-openmp-18.1.8-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-openblas-0.3.28-2-any.pkg.tar.zst";
+  sha256 = "18p1zhf7h3k3phf3bl483jg3k7y9zq375z6ww75g62158ic9lfyc";
+  name = "mingw-w64-clang-x86_64-openblas-0.3.28-2-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-openblas-0.3.28-1-any.pkg.tar.zst";
-  sha256 = "1pskcqc1lg9p8m8rk7bw3mz7mn7vw5fpl7zxa23bhjn02p5b79qq";
-  name = "mingw-w64-clang-x86_64-openblas-0.3.28-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-python-numpy-2.1.1-2-any.pkg.tar.zst";
+  sha256 = "1kiy7ail04ias47xbbhl9vpsz02g0g3f29ncgx5gcks9vgqldp6m";
+  name = "mingw-w64-clang-x86_64-python-numpy-2.1.1-2-any.pkg.tar.zst";
 })
 
 (pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-python-numpy-2.0.1-1-any.pkg.tar.zst";
-  sha256 = "0ks6q8v58h4wmr2pzsjl2xm4f63g0psvfm0jwlz24mqfxp8gqfcc";
-  name = "mingw-w64-clang-x86_64-python-numpy-2.0.1-1-any.pkg.tar.zst";
-})
-
-(pkgs.fetchurl {
-  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-python-setuptools-74.0.0-1-any.pkg.tar.zst";
-  sha256 = "0xc95z5jzzjf5lw35bs4yn5rlwkrkmrh78yi5rranqpz5nn0wsa0";
-  name = "mingw-w64-clang-x86_64-python-setuptools-74.0.0-1-any.pkg.tar.zst";
+  url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-python-setuptools-75.6.0-1-any.pkg.tar.zst";
+  sha256 = "03l04kjmy5p9whaw0h619gdg7yw1gxbz8phifq4pzh3c1wlw7yfd";
+  name = "mingw-w64-clang-x86_64-python-setuptools-75.6.0-1-any.pkg.tar.zst";
 })
 ]