WIP: core: remove outdated comment

Details:
- improve irrt model
- len() on ndarrays

flake.nix

@@ -13,6 +13,7 @@
           ''
           mkdir -p $out/bin
           ln -s ${pkgs.llvmPackages_14.clang-unwrapped}/bin/clang $out/bin/clang-irrt
+          ln -s ${pkgs.llvmPackages_14.clang}/bin/clang $out/bin/clang-irrt-test
           ln -s ${pkgs.llvmPackages_14.llvm.out}/bin/llvm-as $out/bin/llvm-as-irrt
           '';
         nac3artiq = pkgs.python3Packages.toPythonModule (
@@ -23,6 +24,7 @@
             cargoLock = {
               lockFile = ./Cargo.lock;
             };
+            cargoTestFlags = [ "--features" "test" ];
             passthru.cargoLock = cargoLock;
             nativeBuildInputs = [ pkgs.python3 pkgs.llvmPackages_14.clang llvm-tools-irrt pkgs.llvmPackages_14.llvm.out llvm-nac3 ];
             buildInputs = [ pkgs.python3 llvm-nac3 ];
@@ -161,7 +163,10 @@
           clippy
           pre-commit
           rustfmt
+          rust-analyzer
         ];
+        # https://nixos.wiki/wiki/Rust#Shell.nix_example
+        RUST_SRC_PATH = "${pkgs.rust.packages.stable.rustPlatform.rustLibSrc}";
       };
       devShells.x86_64-linux.msys2 = pkgs.mkShell {
         name = "nac3-dev-shell-msys2";

nac3core/Cargo.toml

@@ -1,3 +1,6 @@
+[features]
+test = []
+
 [package]
 name = "nac3core"
 version = "0.1.0"

nac3core/build.rs

@@ -3,20 +3,34 @@ use std::{
     env,
     fs::File,
     io::Write,
-    path::Path,
+    path::{Path, PathBuf},
     process::{Command, Stdio},
 };
 
-fn main() {
-    const FILE: &str = "src/codegen/irrt/irrt.cpp";
+const CMD_IRRT_CLANG: &str = "clang-irrt";
+const CMD_IRRT_CLANG_TEST: &str = "clang-irrt-test";
+const CMD_IRRT_LLVM_AS: &str = "llvm-as-irrt";
+
+fn get_out_dir() -> PathBuf {
+    PathBuf::from(env::var("OUT_DIR").unwrap())
+}
+
+fn get_irrt_dir() -> &'static Path {
+    Path::new("irrt")
+}
+
+/// Compile `irrt.cpp` for use in `src/codegen`
+fn compile_irrt_cpp() {
+    let out_dir = get_out_dir();
+    let irrt_dir = get_irrt_dir();
 
     /*
      * HACK: Sadly, clang doesn't let us emit generic LLVM bitcode.
      * Compiling for WASM32 and filtering the output with regex is the closest we can get.
      */
+    let irrt_cpp_path = irrt_dir.join("irrt.cpp");
     let flags: &[&str] = &[
         "--target=wasm32",
-        FILE,
         "-x",
         "c++",
         "-fno-discard-value-names",
@@ -31,15 +45,19 @@ fn main() {
         "-S",
         "-Wall",
         "-Wextra",
+        "-Werror=return-type",
+        "-I",
+        irrt_dir.to_str().unwrap(),
         "-o",
         "-",
+        irrt_cpp_path.to_str().unwrap(),
     ];
 
-    println!("cargo:rerun-if-changed={FILE}");
-    let out_dir = env::var("OUT_DIR").unwrap();
-    let out_path = Path::new(&out_dir);
+    // Tell Cargo to rerun if any file under `irrt_dir` (recursive) changes
+    println!("cargo:rerun-if-changed={}", irrt_dir.to_str().unwrap());
 
-    let output = Command::new("clang-irrt")
+    // Compile IRRT and capture the LLVM IR output
+    let output = Command::new(CMD_IRRT_CLANG)
         .args(flags)
         .output()
         .map(|o| {
@@ -52,7 +70,17 @@ fn main() {
     let output = std::str::from_utf8(&output.stdout).unwrap().replace("\r\n", "\n");
     let mut filtered_output = String::with_capacity(output.len());
 
-    let regex_filter = Regex::new(r"(?ms:^define.*?\}$)|(?m:^declare.*?$)").unwrap();
+    // Filter out irrelevant IR
+    //
+    // Regex:
+    // - `(?ms:^define.*?\}$)` captures LLVM `define` blocks
+    // - `(?m:^declare.*?$)` captures LLVM `declare` lines
+    // - `(?m:^%.+?=\s*type\s*\{.+?\}$)` captures LLVM `type` declarations
+    // - `(?m:^@.+?=.+$)` captures global constants
+    let regex_filter = Regex::new(
+        r"(?ms:^define.*?\}$)|(?m:^declare.*?$)|(?m:^%.+?=\s*type\s*\{.+?\}$)|(?m:^@.+?=.+$)",
+    )
+    .unwrap();
     for f in regex_filter.captures_iter(&output) {
         assert_eq!(f.len(), 1);
         filtered_output.push_str(&f[0]);
@@ -63,20 +91,73 @@ fn main() {
         .unwrap()
         .replace_all(&filtered_output, "");
 
-    println!("cargo:rerun-if-env-changed=DEBUG_DUMP_IRRT");
-    if env::var("DEBUG_DUMP_IRRT").is_ok() {
-        let mut file = File::create(out_path.join("irrt.ll")).unwrap();
+    // For debugging
+    // Doing `DEBUG_DUMP_IRRT=1 cargo build -p nac3core` dumps the LLVM IR generated
+    const DEBUG_DUMP_IRRT: &str = "DEBUG_DUMP_IRRT";
+    println!("cargo:rerun-if-env-changed={DEBUG_DUMP_IRRT}");
+    if env::var(DEBUG_DUMP_IRRT).is_ok() {
+        let mut file = File::create(out_dir.join("irrt.ll")).unwrap();
         file.write_all(output.as_bytes()).unwrap();
-        let mut file = File::create(out_path.join("irrt-filtered.ll")).unwrap();
+
+        let mut file = File::create(out_dir.join("irrt-filtered.ll")).unwrap();
         file.write_all(filtered_output.as_bytes()).unwrap();
     }
 
-    let mut llvm_as = Command::new("llvm-as-irrt")
+    // Assemble the emitted and filtered IR to .bc
+    // That .bc will be integrated into nac3core's codegen
+    let mut llvm_as = Command::new(CMD_IRRT_LLVM_AS)
         .stdin(Stdio::piped())
         .arg("-o")
-        .arg(out_path.join("irrt.bc"))
+        .arg(out_dir.join("irrt.bc"))
         .spawn()
         .unwrap();
     llvm_as.stdin.as_mut().unwrap().write_all(filtered_output.as_bytes()).unwrap();
     assert!(llvm_as.wait().unwrap().success());
 }
+
+/// Compile `irrt_test.cpp` for testing
+fn compile_irrt_test_cpp() {
+    let out_dir = get_out_dir();
+    let irrt_dir = get_irrt_dir();
+
+    let exe_path = out_dir.join("irrt_test.out"); // Output path of the compiled test executable
+    let irrt_test_cpp_path = irrt_dir.join("irrt_test.cpp");
+    let flags: &[&str] = &[
+        irrt_test_cpp_path.to_str().unwrap(),
+        "-x",
+        "c++",
+        "-I",
+        irrt_dir.to_str().unwrap(),
+        "-g",
+        "-fno-discard-value-names",
+        "-O0",
+        "-Wall",
+        "-Wextra",
+        "-Werror=return-type",
+        "-lm", // for `tgamma()`, `lgamma()`
+        "-I",
+        irrt_dir.to_str().unwrap(),
+        "-o",
+        exe_path.to_str().unwrap(),
+    ];
+
+    Command::new(CMD_IRRT_CLANG_TEST)
+        .args(flags)
+        .output()
+        .map(|o| {
+            assert!(o.status.success(), "{}", std::str::from_utf8(&o.stderr).unwrap());
+            o
+        })
+        .unwrap();
+    println!("cargo:rerun-if-changed={}", irrt_dir.to_str().unwrap());
+}
+
+fn main() {
+    compile_irrt_cpp();
+
+    // https://github.com/rust-lang/cargo/issues/2549
+    // `cargo test -F test` to also build `irrt_test.cpp
+    if cfg!(feature = "test") {
+        compile_irrt_test_cpp();
+    }
+}

nac3core/irrt/irrt.cpp

@@ -0,0 +1,9 @@
+#define IRRT_DEFINE_TYPEDEF_INTS
+#include <irrt_everything.hpp>
+
+/*
+    All IRRT implementations.
+
+    We don't have any pre-compiled objects, so we are writing all implementations in headers and
+    concatenate them with `#include` into one massive source file that contains all the IRRT stuff.
+*/

nac3core/irrt/irrt/core.hpp

@@ -1,9 +1,7 @@
-using int8_t = _BitInt(8);
-using uint8_t = unsigned _BitInt(8);
-using int32_t = _BitInt(32);
-using uint32_t = unsigned _BitInt(32);
-using int64_t = _BitInt(64);
-using uint64_t = unsigned _BitInt(64);
+#pragma once
+
+#include <irrt/utils.hpp>
+#include <irrt/int_defs.hpp>
 
 // NDArray indices are always `uint32_t`.
 using NDIndex = uint32_t;
@@ -11,16 +9,6 @@ using NDIndex = uint32_t;
 using SliceIndex = int32_t;
 
 namespace {
-template <typename T>
-const T& max(const T& a, const T& b) {
-    return a > b ? a : b;
-}
-
-template <typename T>
-const T& min(const T& a, const T& b) {
-    return a > b ? b : a;
-}
-
 // adapted from GNU Scientific Library: https://git.savannah.gnu.org/cgit/gsl.git/tree/sys/pow_int.c
 // need to make sure `exp >= 0` before calling this function
 template <typename T>

nac3core/irrt/irrt/error_context.hpp

@@ -0,0 +1,85 @@
+#pragma once
+
+#include <irrt/int_defs.hpp>
+#include <irrt/utils.hpp>
+
+namespace {
+    // nac3core's "str" struct type definition
+    template <typename SizeT>
+    struct Str {
+        const char* content;
+        SizeT length;
+    };
+
+    // A limited set of errors IRRT could use.
+    typedef uint32_t ErrorId;
+    struct ErrorIds {
+        ErrorId index_error;
+        ErrorId value_error;
+        ErrorId assertion_error;
+        ErrorId runtime_error;
+        ErrorId type_error;
+    };
+
+    struct ErrorContext {
+        // Context
+        const ErrorIds* error_ids;
+
+        // Error thrown by IRRT
+        ErrorId error_id;
+        const char* message_template; // MUST BE `&'static`
+        int64_t param1;
+        int64_t param2;
+        int64_t param3;
+
+        void initialize(const ErrorIds* error_ids) {
+            this->error_ids = error_ids;
+            clear_error();
+        }
+
+        void clear_error() {
+            // Point the message_template to an empty str. Don't set it to nullptr as a sentinel
+            this->message_template = "";
+        }
+
+        void set_error(ErrorId error_id, const char* message, int64_t param1 = 0, int64_t param2 = 0, int64_t param3 = 0) {
+            this->error_id = error_id;
+            this->message_template = message;
+            this->param1 = param1;
+            this->param2 = param2;
+            this->param3 = param3;
+        }
+
+        bool has_error() {
+            return !cstr_utils::is_empty(message_template);
+        }
+
+        template <typename SizeT>
+        void get_error_str(Str<SizeT> *dst_str) {
+            dst_str->content = message_template;
+            dst_str->length = (SizeT) cstr_utils::length(message_template);
+        }
+    };
+}
+
+extern "C" {
+    void __nac3_error_context_initialize(ErrorContext* errctx, const ErrorIds* error_ids) {
+        errctx->initialize(error_ids);
+    }
+
+    bool __nac3_error_context_has_no_error(ErrorContext* errctx) {
+        return !errctx->has_error();
+    }
+
+    void __nac3_error_context_get_error_str(ErrorContext* errctx, Str<int32_t> *dst_str) {
+        errctx->get_error_str<int32_t>(dst_str);
+    }
+
+    void __nac3_error_context_get_error_str64(ErrorContext* errctx, Str<int64_t> *dst_str) {
+        errctx->get_error_str<int64_t>(dst_str);
+    }
+
+    void __nac3_error_dummy_raise(ErrorContext* errctx) {
+        errctx->set_error(errctx->error_ids->runtime_error, "THROWN FROM __nac3_error_dummy_raise!!!!!!");
+    }
+}

nac3core/irrt/irrt/int_defs.hpp

@@ -0,0 +1,12 @@
+#pragma once
+
+// This is made toggleable since `irrt_test.cpp` itself would include
+// headers that define these typedefs
+#ifdef IRRT_DEFINE_TYPEDEF_INTS
+typedef _BitInt(8) int8_t;
+typedef unsigned _BitInt(8) uint8_t;
+typedef _BitInt(32) int32_t;
+typedef unsigned _BitInt(32) uint32_t;
+typedef _BitInt(64) int64_t;
+typedef unsigned _BitInt(64) uint64_t;
+#endif

nac3core/irrt/irrt/numpy/ndarray_basic.hpp

@@ -0,0 +1,221 @@
+#pragma once
+
+#include <irrt/int_defs.hpp>
+#include <irrt/error_context.hpp>
+#include <irrt/numpy/ndarray_def.hpp>
+
+namespace { namespace ndarray { namespace basic {
+    namespace util {
+        // throw an error if there is an axis with negative dimension
+        template <typename SizeT>
+        void assert_shape_no_negative(ErrorContext* errctx, SizeT ndims, const SizeT* shape) {
+            for (SizeT axis = 0; axis < ndims; axis++) {
+                if (shape[axis] < 0) {
+                    errctx->set_error(
+                        errctx->error_ids->value_error,
+                        "negative dimensions are not allowed; axis {0} has dimension {1}",
+                        axis, shape[axis]
+                    );
+                    return;
+                }
+            }
+        }
+
+        // compute the size/# of elements of an ndarray given its shape
+        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;
+        }
+
+        // compute the strides of an ndarray given an ndarray `shape`
+        // and assuming that the ndarray is *fully c-contagious*.
+        //
+        // you might want to read up on https://ajcr.net/stride-guide-part-1/.
+        //
+        // this function might be used in isolation without an ndarray. that's
+        // why it separated out into its own util function.
+        template <typename SizeT>
+        void set_strides_by_shape(SizeT itemsize, SizeT ndims, SizeT* dst_strides, const SizeT* shape) {
+            SizeT stride_product = 1;
+            for (SizeT i = 0; i < ndims; i++) {
+                int axis = ndims - i - 1;
+                dst_strides[axis] = stride_product * itemsize;
+                stride_product *= shape[axis];
+            }
+        }
+
+        template <typename SizeT>
+        void set_indices_by_nth(SizeT ndims, const SizeT* shape, SizeT* indices, SizeT nth) {
+            for (int32_t i = 0; i < ndims; i++) {
+                int32_t axis = ndims - i - 1;
+                int32_t dim = shape[axis];
+
+                indices[axis] = nth % dim;
+                nth /= dim;
+            }
+        }
+    }
+
+    // calculate the size/# of elements of an `ndarray`.
+    // this function corresponds to `np.size(<ndarray>)` or `ndarray.size`
+    template <typename SizeT>
+    SizeT size(NDArray<SizeT>* ndarray) {
+        return util::calc_size_from_shape(ndarray->ndims, ndarray->shape);
+    }
+
+    // calculate the number of bytes of its content of an `ndarray` *in its view*.
+    // this function corresponds to `ndarray.nbytes`
+    template <typename SizeT>
+    SizeT nbytes(NDArray<SizeT>* ndarray) {
+        return size(ndarray) * ndarray->itemsize;
+    }
+
+    template <typename SizeT>
+    void set_strides_by_shape(NDArray<SizeT>* ndarray) {
+        util::set_strides_by_shape(ndarray->itemsize, ndarray->ndims, ndarray->strides, ndarray->shape);
+    }
+
+    template <typename SizeT>
+    uint8_t* get_pelement_by_indices(NDArray<SizeT>* ndarray, const SizeT* indices) {
+        uint8_t* element = ndarray->data;
+        for (SizeT dim_i = 0; dim_i < ndarray->ndims; dim_i++)
+            element += indices[dim_i] * ndarray->strides[dim_i];
+        return element;
+    }
+
+    template <typename SizeT>
+    uint8_t* get_nth_pelement(NDArray<SizeT>* ndarray, SizeT nth) {
+        SizeT* indices = (SizeT*) __builtin_alloca(sizeof(SizeT) * ndarray->ndims);
+        util::set_indices_by_nth(ndarray->ndims, ndarray->shape, indices, nth);
+        return get_pelement_by_indices(ndarray, indices);
+    }
+
+    // get the pointer to the nth element of the ndarray as if it were flattened.
+    template <typename SizeT>
+    uint8_t* checked_get_nth_pelement(NDArray<SizeT>* ndarray, ErrorContext* errctx, SizeT nth) {
+        SizeT arr_size = ndarray->size();
+        if (!(0 <= nth && nth < arr_size)) {
+            errctx->set_error(
+                errctx->error_ids->index_error,
+                "index {0} is out of bounds, valid range is {1} <= index < {2}",
+                nth, 0, arr_size
+            );
+            return 0;
+        }
+        return get_nth_pelement(ndarray, nth);
+    }
+
+    template <typename SizeT>
+    void set_pelement_value(NDArray<SizeT>* ndarray, uint8_t* pelement, const uint8_t* pvalue) {
+        __builtin_memcpy(pelement, pvalue, ndarray->itemsize);
+    }
+
+    template <typename SizeT>
+    void len(ErrorContext* errctx, NDArray<SizeT>* ndarray, SliceIndex* dst_length) {
+        // Error if the ndarray is "unsized" (i.e, ndims == 0)
+        if (ndarray->ndims == 0) {
+            // Error copied from python by doing `len(np.zeros(()))`
+            errctx->set_error(
+                errctx->error_ids->type_error,
+                "len() of unsized object"
+            );
+            return; // Terminate
+        }
+
+        *dst_length = (SliceIndex) ndarray->shape[0];
+    }
+
+    // Copy data from one ndarray to another *OF THE EXACT SAME* ndims, shape, and itemsize.
+    template <typename SizeT>
+    void copy_data(const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
+        __builtin_assume(src_ndarray->ndims == dst_ndarray->ndims);
+        __builtin_assume(src_ndarray->itemsize == dst_ndarray->itemsize);
+
+        for (SizeT i = 0; i < src_ndarray->size; 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);
+        }
+    }
+
+    // `copy_data()` with assertions to check ndims, shape, and itemsize between the two ndarrays.
+    template <typename SizeT>
+    void copy_data_checked(ErrorContext* errctx, const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
+        // NOTE: Out of all error types, runtime error seems appropriate
+
+        // Check ndims
+        if (src_ndarray->ndims != dst_ndarray->ndims) {
+            errctx->set_error(
+                errctx->error_ids->runtime_error,
+                "IRRT copy_data_checked input arrays `ndims` are mismatched"
+            );
+            return; // Terminate
+        }
+
+        // Check shape
+        if (!arrays_match(src_ndarray->ndims, src_ndarray->shape, dst_ndarray->shape)) {
+            errctx->set_error(
+                errctx->error_ids->runtime_error,
+                "IRRT copy_data_checked input arrays `shape` are mismatched"
+            );
+            return; // Terminate
+        }
+
+        // Check itemsize
+        if (src_ndarray->itemsize != dst_ndarray->itemsize) {
+            errctx->set_error(
+                errctx->error_ids->runtime_error,
+                "IRRT copy_data_checked input arrays `itemsize` are mismatched"
+            );
+            return; // Terminate
+        }
+
+        copy_data(src_ndarray, dst_ndarray);
+    }
+} } }
+
+extern "C" {
+    using namespace ndarray::basic;
+
+    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);
+    }
+
+    void __nac3_ndarray_len(ErrorContext* errctx, NDArray<int32_t>* ndarray, SliceIndex* dst_len) {
+        return len(errctx, ndarray, dst_len);
+    }
+
+    void __nac3_ndarray_len64(ErrorContext* errctx, NDArray<int64_t>* ndarray, SliceIndex* dst_len) {
+        return len(errctx, ndarray, dst_len);
+    }
+
+    void __nac3_ndarray_util_assert_shape_no_negative(ErrorContext* errctx, int32_t ndims, int32_t* shape) {
+        util::assert_shape_no_negative(errctx, ndims, shape);
+    }
+
+    void __nac3_ndarray_util_assert_shape_no_negative64(ErrorContext* errctx, int64_t ndims, int64_t* shape) {
+        util::assert_shape_no_negative(errctx, ndims, shape);
+    }
+
+    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);
+    }
+}

nac3core/irrt/irrt/numpy/ndarray_broadcast.hpp

@@ -0,0 +1,135 @@
+#include <irrt/numpy/ndarray_def.hpp>
+
+namespace { namespace ndarray { namespace broadcast {
+    namespace util {
+        template <typename SizeT>
+        void assert_broadcast_shape_to(
+            ErrorContext* errctx,
+            const SizeT target_ndims,
+            const SizeT* target_shape,
+            const SizeT src_ndims,
+            const SizeT* src_shape
+        ) {
+            /*
+                // See https://numpy.org/doc/stable/user/basics.broadcasting.html
+
+                This function handles this example:
+                ```
+                Image  (3d array): 256 x 256 x 3
+                Scale  (1d array):             3
+                Result (3d array): 256 x 256 x 3
+                ```
+
+                Other interesting examples to consider:
+                - `can_broadcast_shape_to([3], [1, 1, 1, 1, 3]) ... ok`
+                - `can_broadcast_shape_to([3], [3, 1]) == false`
+                - `can_broadcast_shape_to([256, 256, 3], [256, 1, 3]) ... ok`
+
+                In cases when the shapes contain zero(es):
+                - `can_broadcast_shape_to([0], [1]) ... ok`
+                - `can_broadcast_shape_to([0], [2]) == false`
+                - `can_broadcast_shape_to([0, 4, 0, 0], [1]) ... ok`
+                - `can_broadcast_shape_to([0, 4, 0, 0], [1, 1, 1, 1]) ... ok`
+                - `can_broadcast_shape_to([0, 4, 0, 0], [1, 4, 1, 1]) ... ok`
+                - `can_broadcast_shape_to([4, 3], [0, 3]) == false`
+                - `can_broadcast_shape_to([4, 3], [0, 0]) == false`
+            */
+
+            // Target ndims must not be smaller than source ndims
+            // e.g., `np.broadcast_to(np.zeros((1, 1, 1, 1)), (1, ))` is prohibited by numpy
+            if (target_ndims < src_ndims) {
+                // Error copied from python by doing the `np.broadcast_to(np.zeros((1, 1, 1, 1)), (1, ))`
+                errctx->set_error(
+                    errctx->error_ids->value_error,
+                    "input operand has more dimensions than allowed by the axis remapping"
+                );
+                return; // Terminate
+            }
+
+            // Implements the rules in https://numpy.org/doc/stable/user/basics.broadcasting.html
+            for (SizeT i = 0; i < src_ndims; i++) {
+                SizeT target_axis = target_ndims - i - 1;
+                SizeT src_axis = src_ndims - i - 1;
+
+                bool target_dim_exists = target_axis >= 0;
+                bool src_dim_exists = src_axis >= 0;
+
+                SizeT target_dim = target_dim_exists ? target_shape[target_axis] : 1;
+                SizeT src_dim = src_dim_exists ? src_shape[src_axis] : 1;
+
+                bool ok = src_dim == 1 || target_dim == src_dim;
+                if (!ok) {
+                    // Error copied from python by doing `np.broadcast_to(np.zeros((3, 1)), (1, 1)),
+                    // but this is the true numpy error:
+                    // "ValueError: operands could not be broadcast together with remapped shapes [original->remapped]: (3,1)  and requested shape (1,1)"
+                    // TODO: we cannot show more than 3 parameters!!
+                    errctx->set_error(
+                        errctx->error_ids->value_error,
+                        "operands could not be broadcast together with remapping shapes [original->remapped]"
+                    );
+                    return; // Terminate
+                }
+            }
+        }
+    }
+
+    // Similar to `np.broadcast_to(<ndarray>, <target_shape>)`
+    // Assumptions:
+    //   - `src_ndarray` has to be fully initialized.
+    //   - `dst_ndarray->ndims` has to be set.
+    //   - `dst_ndarray->shape` has to be set, this determines the shape `this` broadcasts to.
+    //
+    // Other notes:
+    //   - `dst_ndarray->data` does not have to be set, it will be set to `src_ndarray->data`.
+    //   - `dst_ndarray->itemsize` does not have to be set, it will be set to `src_ndarray->data`.
+    //   - `dst_ndarray->strides` does not have to be set, it will be overwritten.
+    //
+    // Cautions:
+    //   ```
+    //   xs = np.zeros((4,))
+    //   ys = np.zero((4, 1))
+    //   ys[:] = xs # ok
+    // 
+    //   xs = np.zeros((1, 4))
+    //   ys = np.zero((4,))
+    //   ys[:] = xs # allowed
+    //   # However `np.broadcast_to(xs, (4,))` would fails, as per numpy's broadcasting rule.
+    //   # and apparently numpy will "deprecate" this? SEE https://github.com/numpy/numpy/issues/21744
+    //   # This implementation will NOT support this assignment.
+    //   ```
+    template <typename SizeT>
+    void broadcast_to(ErrorContext* errctx, NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
+        dst_ndarray->data = src_ndarray->data;
+        dst_ndarray->itemsize = src_ndarray->itemsize;
+
+        ndarray::broadcast::util::assert_broadcast_shape_to(
+            errctx,
+            dst_ndarray->ndims,
+            dst_ndarray->shape,
+            src_ndarray->ndims,
+            src_ndarray->shape
+        );
+        if (errctx->has_error()) {
+            return; // Propagate error
+        }
+
+        SizeT stride_product = 1;
+        for (SizeT i = 0; i < max(src_ndarray->ndims, dst_ndarray->ndims); i++) {
+            SizeT this_dim_i = src_ndarray->ndims - i - 1;
+            SizeT dst_dim_i = dst_ndarray->ndims - i - 1;
+
+            bool this_dim_exists = this_dim_i >= 0;
+            bool dst_dim_exists = dst_dim_i >= 0;
+
+            // TODO: Explain how this works
+            bool c1 = this_dim_exists && src_ndarray->shape[this_dim_i] == 1;
+            bool c2 = dst_dim_exists && dst_ndarray->shape[dst_dim_i] != 1;
+            if (!this_dim_exists || (c1 && c2)) {
+                dst_ndarray->strides[dst_dim_i] = 0; // Freeze it in-place
+            } else {
+                dst_ndarray->strides[dst_dim_i] = stride_product * src_ndarray->itemsize;
+                stride_product *= src_ndarray->shape[this_dim_i]; // NOTE: this_dim_exist must be true here.
+            }
+        }
+    }
+} } }

nac3core/irrt/irrt/numpy/ndarray_def.hpp

@@ -0,0 +1,55 @@
+#pragma once
+
+namespace {
+    // The NDArray object. `SizeT` is the *signed* size type of this ndarray.
+    //
+    // NOTE: The order of fields is IMPORTANT. DON'T TOUCH IT
+    //
+    // Some resources you might find helpful:
+    // - The official numpy implementations:
+    //   - https://github.com/numpy/numpy/blob/735a477f0bc2b5b84d0e72d92f224bde78d4e069/doc/source/reference/c-api/types-and-structures.rst
+    // - On strides (about reshaping, slicing, C-contagiousness, etc)
+    //   - https://ajcr.net/stride-guide-part-1/.
+    //   - https://ajcr.net/stride-guide-part-2/.
+    //   - https://ajcr.net/stride-guide-part-3/.
+    template <typename SizeT>
+    struct NDArray {
+        // The underlying data this `ndarray` is pointing to.
+        //
+        // NOTE: Formally this should be of type `void *`, but clang
+        // translates `void *` to `i8 *` when run with `-S -emit-llvm`,
+        // so we will put `uint8_t *` here for clarity.
+        //
+        // This pointer should point to the first element of the ndarray directly
+        uint8_t *data;
+
+        // The number of bytes of a single element in `data`.
+        //
+        // The `SizeT` is treated as `unsigned`.
+        SizeT itemsize;
+
+        // The number of dimensions of this shape.
+        //
+        // The `SizeT` is treated as `unsigned`.
+        SizeT ndims;
+
+        // Array shape, with length equal to `ndims`.
+        //
+        // The `SizeT` is treated as `unsigned`.
+        //
+        // NOTE: `shape` can contain 0.
+        //   (those appear when the user makes an out of bounds slice into an ndarray, e.g., `np.zeros((3, 3))[400:].shape == (0, 3)`)
+        SizeT *shape;
+
+        // Array strides (stride value is in number of bytes, NOT number of elements), with length equal to `ndims`.
+        //
+        // The `SizeT` is treated as `signed`.
+        //
+        // NOTE: `strides` can have negative numbers.
+        //   (those appear when there is a slice with a negative step, e.g., `my_array[::-1]`)
+        SizeT *strides;
+    };
+
+    // Because ndarray is so complicated, its functions are splitted into
+    // different files and namespaces.
+}

nac3core/irrt/irrt/numpy/ndarray_fill.hpp

@@ -0,0 +1,28 @@
+#pragma once
+
+#include <irrt/numpy/ndarray_def.hpp>
+#include <irrt/numpy/ndarray_basic.hpp>
+
+namespace { namespace ndarray { namespace fill {
+    // Fill the ndarray with a value
+    template <typename SizeT>
+    void fill_generic(NDArray<SizeT>* ndarray, const uint8_t* pvalue) {
+        const SizeT size = ndarray::basic::size(ndarray);
+        for (SizeT i = 0; i < size; i++) {
+            uint8_t* pelement = ndarray::basic::get_nth_pelement(ndarray, i); // No need for checked_get_nth_pelement
+            ndarray::basic::set_pelement_value(ndarray, pelement, pvalue);
+        }
+    }
+} } }
+
+extern "C" {
+    using namespace ndarray::fill;
+
+    void __nac3_ndarray_fill_generic(NDArray<int32_t>* ndarray, uint8_t* pvalue) {
+        fill_generic(ndarray, pvalue);
+    }
+
+    void __nac3_ndarray_fill_generic64(NDArray<int64_t>* ndarray, uint8_t* pvalue) {
+        fill_generic(ndarray, pvalue);
+    }
+}

nac3core/irrt/irrt/numpy/ndarray_subscript.hpp

@@ -0,0 +1,169 @@
+#pragma once
+
+#include <irrt/slice.hpp>
+#include <irrt/numpy/ndarray_def.hpp>
+#include <irrt/numpy/ndarray_basic.hpp>
+#include <irrt/error_context.hpp>
+
+namespace {
+    typedef uint8_t NDSubscriptType;
+
+    const NDSubscriptType INPUT_SUBSCRIPT_TYPE_INDEX = 0;
+    const NDSubscriptType INPUT_SUBSCRIPT_TYPE_SLICE = 1;
+
+    struct NDSubscript {
+        // A poor-man's enum variant type
+        NDSubscriptType type;
+
+        /*
+            if type == INPUT_SUBSCRIPT_TYPE_INDEX => `slice` points to a single `SliceIndex`
+            if type == INPUT_SUBSCRIPT_TYPE_SLICE => `slice` points to a single `UserRange`
+
+            `SizeT` is controlled by the caller: `NDSubscript` only cares about where that
+            slice is (the pointer), `NDSubscript` does not care/know about the actual `sizeof()`
+            of the slice value.
+        */
+        uint8_t* data;
+    };
+}
+
+namespace { namespace ndarray { namespace subscript {
+    namespace util {
+        template<typename SizeT>
+        void deduce_ndims_after_slicing(ErrorContext* errctx, SizeT* result, SizeT ndims, SizeT num_ndsubscripts, const NDSubscript* ndsubscripts) {
+            if (num_ndsubscripts > ndims) {
+                // Error copied from python by doing `np.zeros((3, 4))[:, :, :]`
+                errctx->set_error(
+                    errctx->error_ids->index_error,
+                    "too many indices for array: array is {0}-dimensional, but {1} were indexed",
+                    ndims, num_ndsubscripts
+                );
+                return; // Terminate
+            }
+
+            SizeT final_ndims = ndims;
+            for (SizeT i = 0; i < num_ndsubscripts; i++) {
+                if (ndsubscripts[i].type == INPUT_SUBSCRIPT_TYPE_INDEX) {
+                    final_ndims--; // An index demotes the rank by 1
+                }
+            }
+
+            *result = final_ndims;
+        }
+    }
+
+    // To support numpy "basic indexing" https://numpy.org/doc/stable/user/basics.indexing.html#basic-indexing
+    // "Advanced indexing" https://numpy.org/doc/stable/user/basics.indexing.html#advanced-indexing is not supported
+    //
+    // This function supports:
+    //   - "scalar indexing",
+    //   - "slicing and strides",
+    //   - and "dimensional indexing tools" (TODO, but this is really easy to implement).
+    //
+    // Things assumed by this function:
+    // - `dst_ndarray` is allocated by the caller
+    // - `dst_ndarray.ndims` has the correct value (according to `ndarray::util::deduce_ndims_after_slicing`).
+    //   - ... and `dst_ndarray.shape` and `dst_ndarray.strides` have been allocated by the caller as well
+    //
+    // Other notes:
+    // - `dst_ndarray->data` does not have to be set, it will be derived.
+    // - `dst_ndarray->itemsize` does not have to be set, it will be set to `src_ndarray->itemsize`
+    // - `dst_ndarray->shape` and `dst_ndarray.strides` can contain empty values
+    template <typename SizeT>
+    void subscript(ErrorContext* errctx, SliceIndex num_subscripts, NDSubscript* subscripts, NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
+        // REFERENCE CODE (check out `_index_helper` in `__getitem__`):
+        //   https://github.com/wadetb/tinynumpy/blob/0d23d22e07062ffab2afa287374c7b366eebdda1/tinynumpy/tinynumpy.py#L652
+
+        // irrt_assert(dst_ndarray->ndims == ndarray::util::deduce_ndims_after_slicing(src_ndarray->ndims, num_subscripts, subscripts));
+
+        dst_ndarray->data = src_ndarray->data;
+        dst_ndarray->itemsize = src_ndarray->itemsize;
+
+        SizeT src_axis = 0;
+        SizeT dst_axis = 0;
+
+        for (SliceIndex i = 0; i < num_subscripts; i++) {
+            NDSubscript *ndsubscript = &subscripts[i];
+            if (ndsubscript->type == INPUT_SUBSCRIPT_TYPE_INDEX) {
+                // Handle when the ndsubscript is just a single (possibly negative) integer
+                // e.g., `my_array[::2, -5, ::-1]`
+                //                      ^^------ like this
+                SliceIndex input_index = *((SliceIndex*) ndsubscript->data);
+
+                SliceIndex index = slice::resolve_index_in_length(src_ndarray->shape[src_axis], input_index);
+                if (index == slice::OUT_OF_BOUNDS) {
+                    // Error message copied from numpy by doing `np.zeros((3, 4))[100]`
+                    errctx->set_error(
+                        errctx->error_ids->index_error,
+                        "index {0} is out of bounds for axis {1} with size {2}",
+                        input_index, src_axis, src_ndarray->shape[src_axis]
+                    );
+                    return; // Terminate
+                }
+
+                dst_ndarray->data += index * src_ndarray->strides[src_axis]; // Add offset
+
+                // Next
+                src_axis++;
+            } else if (ndsubscript->type == INPUT_SUBSCRIPT_TYPE_SLICE) {
+                // Handle when the ndsubscript is a slice (represented by UserSlice in IRRT)
+                // e.g., `my_array[::2, -5, ::-1]`
+                //                 ^^^------^^^^----- like these
+                UserSlice* input_user_slice = (UserSlice*) ndsubscript->data;
+
+                // TODO: use checked indices
+                Slice slice;
+                input_user_slice->indices_checked(errctx, src_ndarray->shape[src_axis], &slice); // To resolve negative indices and other funny stuff written by the user
+                if (errctx->has_error()) {
+                    return; // Propagate error
+                }
+
+                // NOTE: There is no need to write special code to handle negative steps/strides.
+                // This simple implementation meticulously handles both positive and negative steps/strides.
+                // Check out the tinynumpy and IRRT's test cases if you are not convinced.
+                dst_ndarray->data += (SizeT) slice.start * src_ndarray->strides[src_axis]; // Add offset (NOTE: no need to `* itemsize`, strides count in # of bytes)
+                dst_ndarray->strides[dst_axis] = ((SizeT) slice.step) * src_ndarray->strides[src_axis]; // Determine stride
+                dst_ndarray->shape[dst_axis] = (SizeT) slice.len(); // Determine shape dimension
+
+                // Next
+                dst_axis++;
+                src_axis++;
+            } else {
+                __builtin_unreachable();
+            }
+        }
+
+        /*
+            Reference python code:
+            ```python
+            dst_ndarray.shape.extend(src_ndarray.shape[src_axis:])
+            dst_ndarray.strides.extend(src_ndarray.strides[src_axis:])
+            ```
+        */
+
+        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];
+        }
+    }
+} } }
+
+extern "C" {
+    using namespace ndarray::subscript;
+
+    void __nac3_ndarray_subscript_deduce_ndims_after_slicing(ErrorContext* errctx, int32_t* result, int32_t ndims, int32_t num_ndsubscripts, const NDSubscript* ndsubscripts) {
+        ndarray::subscript::util::deduce_ndims_after_slicing(errctx, result, ndims, num_ndsubscripts, ndsubscripts);
+    }
+
+    void __nac3_ndarray_subscript_deduce_ndims_after_slicing64(ErrorContext* errctx, int64_t* result, int64_t ndims, int64_t num_ndsubscripts, const NDSubscript* ndsubscripts) {
+        ndarray::subscript::util::deduce_ndims_after_slicing(errctx, result, ndims, num_ndsubscripts, ndsubscripts);
+    }
+
+    void __nac3_ndarray_subscript(ErrorContext* errctx, SliceIndex num_subscripts, NDSubscript* subscripts, NDArray<int32_t>* src_ndarray, NDArray<int32_t> *dst_ndarray) {
+        subscript(errctx, num_subscripts, subscripts, src_ndarray, dst_ndarray);
+    }
+
+    void __nac3_ndarray_subscript64(ErrorContext* errctx, SliceIndex num_subscripts, NDSubscript* subscripts, NDArray<int64_t>* src_ndarray, NDArray<int64_t> *dst_ndarray) {
+        subscript(errctx, num_subscripts, subscripts, src_ndarray, dst_ndarray);
+    }
+}

nac3core/irrt/irrt/slice.hpp

@@ -0,0 +1,143 @@
+#pragma once
+
+#include <irrt/int_defs.hpp>
+#include <irrt/slice.hpp>
+
+namespace {
+    struct Slice {
+        SliceIndex start;
+        SliceIndex stop;
+        SliceIndex step;
+
+        // The length/The number of elements of the slice if it were a range,
+        // i.e., the value of `len(range(this->start, this->stop, this->end))`
+        SliceIndex len() {
+            SliceIndex diff = stop - 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 slice {
+        // "Resolve" an index value under a length in Python lists.
+        // If you have a `list` of length 100, `list[-1]` would resolve to `list[100-1] == list[99]`.
+        //
+        // If length == 0, this function returns 0
+        //
+        // If index is out of bounds, this function clamps the value
+        // (to `list[0]` or `list[-1]` in the context of a list and depending on if index is + or -)
+        SliceIndex resolve_index_in_length_clamped(SliceIndex length, SliceIndex index) {
+            if (index < 0) {
+                // Remember that index is negative, so do a plus here
+                return max<SliceIndex>(length + index, 0);
+            } else {
+                return min<SliceIndex>(length, index);
+            }
+        }
+
+        const SliceIndex OUT_OF_BOUNDS = -1;
+
+        // Like `resolve_index_in_length`.
+        // But also checks if the resolved index is in
+        // bounds (function returns true) or out of bounds
+        // (function returns false); `0 <= resolved index < length` is false).
+        SliceIndex resolve_index_in_length(SliceIndex length, SliceIndex index) {
+            SliceIndex resolved = index < 0 ? length + index : index;
+
+            bool in_bounds = 0 <= resolved && resolved < length;
+            return in_bounds ? resolved : OUT_OF_BOUNDS;
+        }
+    }
+
+    // A user-written Python-like slice.
+    //
+    // i.e., this slice is a triple of either an int or nothing. (e.g., `my_array[:10:2]`, `start` is None)
+    //
+    // You can "resolve" a `UserSlice` by using `user_slice.indices(<length>)`
+    struct UserSlice {
+        // Did the user specify `start`? If 0, `start` is undefined (and contains an empty value)
+        bool start_defined;
+        SliceIndex start;
+
+        // Similar to `start_defined`
+        bool stop_defined;
+        SliceIndex stop;
+
+        // Similar to `start_defined`
+        bool step_defined;
+        SliceIndex step;
+
+        // Convenient constructor for C++ internal use only (say testing)
+        UserSlice() {
+            this->reset();
+        }
+
+        void reset() {
+            this->start_defined = false;
+            this->stop_defined = false;
+            this->step_defined = false;
+        }
+
+        void set_start(SliceIndex start) {
+            this->start_defined = true;
+            this->start = start;
+        }
+
+        void set_stop(SliceIndex stop) {
+            this->stop_defined = true;
+            this->stop = stop;
+        }
+
+        void set_step(SliceIndex step) {
+            this->step_defined = true;
+            this->step = step;
+        }
+
+        // Like Python's `slice(start, stop, step).indices(length)`
+        void indices(SliceIndex length, Slice* result) {
+            // NOTE: This function implements Python's `slice.indices` *FAITHFULLY*.
+            // SEE: https://github.com/python/cpython/blob/f62161837e68c1c77961435f1b954412dd5c2b65/Objects/sliceobject.c#L546
+            result->step = step_defined ? step : 1;
+            bool step_is_negative = result->step < 0;
+
+            if (start_defined) {
+                result->start = slice::resolve_index_in_length_clamped(length, start);
+            } else {
+                result->start = step_is_negative ? length - 1 : 0;
+            }
+            
+            if (stop_defined) {
+                result->stop = slice::resolve_index_in_length_clamped(length, stop);
+            } else {
+                result->stop = step_is_negative ? -1 : length;
+            }
+        }
+
+        // `indices()` but asserts `this->step != 0` and `this->length >= 0`
+        void indices_checked(ErrorContext* errctx, SliceIndex length, Slice* result) {
+            if (length < 0) {
+                errctx->set_error(
+                    errctx->error_ids->value_error,
+                    "length should not be negative, got {0}", // Edited. Error message copied from python by doing `slice(0, 0, 0).indices(100)`
+                    length
+                );
+                return;
+            }
+
+            if (this->step_defined && this->step == 0) {
+                // Error message
+                errctx->set_error(
+                    errctx->error_ids->value_error,
+                    "slice step cannot be zero" // Error message copied from python by doing `slice(0, 0, 0).indices(100)`
+                );
+                return;
+            }
+            this->indices(length, result);
+        }
+    };
+}

nac3core/irrt/irrt/utils.hpp

@@ -0,0 +1,78 @@
+#pragma once
+
+#include <irrt/int_defs.hpp>
+
+namespace {
+    template <typename T>
+    const T& max(const T& a, const T& b) {
+        return a > b ? a : b;
+    }
+
+    template <typename T>
+    const T& min(const T& a, const T& b) {
+        return a > b ? b : a;
+    }
+
+    template <typename T>
+    bool arrays_match(int len, T* as, T* bs) {
+        for (int i = 0; i < len; i++) {
+            if (as[i] != bs[i]) return false;
+        }
+        return true;
+    }
+
+    namespace cstr_utils {
+        bool is_empty(const char* str) {
+            return str[0] == '\0';
+        }
+
+        int8_t compare(const char* a, const char* b) {
+            uint32_t i = 0;
+            while (true) {
+                if (a[i] < b[i]) {
+                    return -1;
+                } else if (a[i] > b[i]) {
+                    return 1;
+                } else { // a[i] == b[i]
+                    if (a[i] == '\0') {
+                        return 0;
+                    } else {
+                        i++;
+                    }
+                }
+            }
+        }
+
+        int8_t equal(const char* a, const char* b) {
+            return compare(a, b) == 0;
+        }
+
+        uint32_t length(const char* str) {
+            uint32_t length = 0;
+            while (*str != '\0') {
+                length++;
+                str++;
+            }
+            return length;
+        }
+
+        bool copy(const char* src, char* dst, uint32_t dst_max_size) {
+            for (uint32_t i = 0; i < dst_max_size; i++) {
+                bool is_last = i + 1 == dst_max_size;
+                if (is_last && src[i] != '\0') {
+                    dst[i] = '\0';
+                    return false;
+                }
+
+                if (src[i] == '\0') {
+                    dst[i] = '\0';
+                    return true;
+                }
+
+                dst[i] = src[i];
+            }
+
+            __builtin_unreachable();
+        }
+    }
+}

nac3core/irrt/irrt_everything.hpp

@@ -0,0 +1,12 @@
+#pragma once
+
+#include <irrt/core.hpp>
+#include <irrt/error_context.hpp>
+#include <irrt/int_defs.hpp>
+#include <irrt/numpy/ndarray_basic.hpp>
+#include <irrt/numpy/ndarray_broadcast.hpp>
+#include <irrt/numpy/ndarray_def.hpp>
+#include <irrt/numpy/ndarray_fill.hpp>
+#include <irrt/numpy/ndarray_subscript.hpp>
+#include <irrt/slice.hpp>
+#include <irrt/utils.hpp>

nac3core/irrt/irrt_test.cpp

@@ -0,0 +1,25 @@
+// This file will be compiled like a real C++ program,
+// and we do have the luxury to use the standard libraries.
+// That is if the nix flakes do not have issues... especially on msys2...
+#include <cstdint>
+#include <cstdio>
+#include <cstdlib>
+
+#include <irrt_everything.hpp>
+
+#include <test/core.hpp>
+#include <test/test_core.hpp>
+#include <test/test_ndarray_basic.hpp>
+#include <test/test_ndarray_subscript.hpp>
+#include <test/test_ndarray_broadcast.hpp>
+#include <test/test_slice.hpp>
+
+int main() {
+    // Be wise about the order of suites!!
+    test::core::run();
+    test::slice::run();
+    test::ndarray_basic::run();
+    test::ndarray_subscript::run();
+    test::ndarray_broadcast::run();
+    return 0;
+}

nac3core/irrt/test/core.hpp

@@ -0,0 +1,143 @@
+#pragma once
+
+// Include this header for every test_*.cpp
+
+#include <cstdint>
+#include <cstdio>
+#include <cstdlib>
+
+#include <test/print.hpp>
+
+// Some utils can be used here
+#include <irrt/utils.hpp>
+
+void __begin_test(const char* function_name, const char* file, int line) {
+    printf("######### Running %s @ %s:%d\n", function_name, file, line);
+}
+
+#define BEGIN_TEST() __begin_test(__FUNCTION__, __FILE__, __LINE__)
+
+void test_fail() {
+    printf("[!] Test failed. Exiting with status code 1.\n");
+    exit(1);
+}
+
+void print_assertion_passed(const char* file, int line) {
+    printf("[*] Assertion passed on %s:%d\n", file, line);
+}
+
+void print_assertion_failed(const char* file, int line) {
+    printf("[!] Assertion failed on %s:%d\n", file, line);
+}
+
+void __assert_true(const char* file, int line, bool cond) {
+    if (cond) {
+        print_assertion_passed(file, line);
+    } else {
+        print_assertion_failed(file, line);
+        test_fail();
+    }
+}
+
+#define assert_true(cond) __assert_true(__FILE__, __LINE__, cond)
+
+template <typename T>
+void __assert_arrays_match(const char* file, int line, int len, const T* expected, const T* got) {
+    if (arrays_match(len, expected, got)) {
+        print_assertion_passed(file, line);
+    } else {
+        print_assertion_failed(file, line);
+        printf("Expect = ");
+        print_array(len, expected);
+        printf("\n");
+        printf("   Got = ");
+        print_array(len, got);
+        printf("\n");
+        test_fail();
+    }
+}
+
+#define assert_arrays_match(len, expected, got) __assert_arrays_match(__FILE__, __LINE__, len, expected, got)
+
+template <typename T>
+void __assert_values_match(const char* file, int line, T expected, T got) {
+    if (expected == got) {
+        print_assertion_passed(file, line);
+    } else {
+        print_assertion_failed(file, line);
+        printf("Expect = ");
+        print_value(expected);
+        printf("\n");
+        printf("   Got = ");
+        print_value(got);
+        printf("\n");
+        test_fail();
+    }
+}
+
+#define assert_values_match(expected, got) __assert_values_match(__FILE__, __LINE__, expected, got)
+
+// A fake set of ErrorIds for testing only
+const ErrorIds TEST_ERROR_IDS = {
+    .index_error = 0,
+    .value_error = 1,
+    .assertion_error = 2,
+    .runtime_error = 3,
+};
+
+ErrorContext create_testing_errctx() {
+    // Everything is global so it is fine to directly return a struct ErrorContext
+    ErrorContext errctx;
+    errctx.initialize(&TEST_ERROR_IDS);
+    return errctx;
+}
+
+void print_errctx_content(ErrorContext* errctx) {
+    if (errctx->has_error()) {
+        printf(
+            "(Error ID %d): %s ... where param1 = %ld, param2 = %ld, param3 = %ld\n",
+            errctx->error_id,
+            errctx->message_template,
+            errctx->param1,
+            errctx->param2,
+            errctx->param3
+        );
+    } else {
+        printf("<no error>\n");
+    }
+}
+
+void __assert_errctx_no_error(const char* file, int line, ErrorContext* errctx) {
+    if (errctx->has_error()) {
+        print_assertion_failed(file, line);
+        printf("Expecting no error but caught the following:\n\n");
+        print_errctx_content(errctx);
+        test_fail();
+    }
+}
+
+#define assert_errctx_no_error(errctx) __assert_errctx_no_error(__FILE__, __LINE__, errctx)
+
+void __assert_errctx_has_error(const char* file, int line, ErrorContext* errctx, ErrorId expected_error_id) {
+    if (errctx->has_error()) {
+        if (errctx->error_id == expected_error_id) {
+            // OK
+        } else {
+            // Otherwise it got the wrong kind of error
+            print_assertion_failed(file, line);
+            printf(
+                "Expecting error id %d but got error id %d. Error caught:\n\n",
+                expected_error_id,
+                errctx->error_id
+            );
+            print_errctx_content(errctx);
+            test_fail();
+        }
+    } else {
+        print_assertion_failed(file, line);
+        printf("Expecting an error, but there is none.");
+        test_fail();
+    }
+}
+
+#define assert_errctx_has_error(errctx, expected_error_id) __assert_errctx_has_error(__FILE__, __LINE__, errctx, expected_error_id)

nac3core/irrt/test/print.hpp

@@ -0,0 +1,118 @@
+#pragma once
+
+#include <cstdlib>
+#include <cstdio>
+
+template <class T>
+void print_value(const T& value);
+
+template <>
+void print_value(const bool& value) {
+    printf("%s", value ? "true" : "false");
+}
+
+template <>
+void print_value(const int8_t& value) {
+    printf("%d", value);
+}
+
+template <>
+void print_value(const int32_t& value) {
+    printf("%d", value);
+}
+
+template <>
+void print_value(const uint8_t& value) {
+    printf("%u", value);
+}
+
+template <>
+void print_value(const uint32_t& value) {
+    printf("%u", value);
+}
+
+template <>
+void print_value(const float& value) {
+    printf("%f", value);
+}
+
+template <>
+void print_value(const double& value) {
+    printf("%f", value);
+}
+
+void print_repeated(const char *str, int count) {
+    for (int i = 0; i < count; i++) {
+        printf("%s", str);
+    }
+}
+
+template <typename T>
+void print_array(int len, const T* as) {
+    printf("[");
+    for (int i = 0; i < len; i++) {
+        if (i != 0) printf(", ");
+        print_value(as[i]);
+    }
+    printf("]");
+}
+
+template<typename ElementT, typename SizeT>
+void __print_ndarray_aux(bool first, bool last, SizeT* cursor, SizeT depth, NDArray<SizeT>* ndarray) {
+    // A really lazy recursive implementation
+    
+    // Add left padding unless its the first entry (since there would be "[[[" before it)
+    if (!first) {
+        print_repeated(" ", depth);
+    }
+
+    const SizeT dim = ndarray->shape[depth];
+    if (depth + 1 == ndarray->ndims) {
+        // Recursed down to last dimension, print the values in a nice list
+        printf("[");
+
+        SizeT* indices = (SizeT*) __builtin_alloca(sizeof(SizeT) * ndarray->ndims);
+        for (SizeT i = 0; i < dim; i++) {
+            ndarray::basic::util::set_indices_by_nth(ndarray->ndims, ndarray->shape, indices, *cursor);
+            ElementT* pelement = (ElementT*) ndarray::basic::get_pelement_by_indices<SizeT>(ndarray, indices);
+            ElementT element = *pelement;
+
+            if (i != 0) printf(", "); // List delimiter
+            print_value(element);
+            printf("(@");
+            print_array(ndarray->ndims, indices);
+            printf(")");
+
+            (*cursor)++;
+        }
+        printf("]");
+    } else {
+        printf("[");
+        for (SizeT i = 0; i < ndarray->shape[depth]; i++) {
+            __print_ndarray_aux<ElementT, SizeT>(
+                i == 0, // first?
+                i + 1 == dim, // last?
+                cursor,
+                depth + 1,
+                ndarray
+            );
+        }
+        printf("]");
+    }
+
+    // Add newline unless its the last entry (since there will be "]]]" after it)
+    if (!last) {
+        print_repeated("\n", depth);
+    }
+}
+
+template <typename ElementT, typename SizeT>
+void print_ndarray(NDArray<SizeT>* ndarray) {
+    if (ndarray->ndims == 0) {
+        printf("<empty ndarray>");
+    } else {
+        SizeT cursor = 0;
+        __print_ndarray_aux<ElementT, SizeT>(true, true, &cursor, 0, ndarray);
+    }
+    printf("\n");
+}

nac3core/irrt/test/test_core.hpp

@@ -0,0 +1,19 @@
+#pragma once
+
+#include <test/core.hpp>
+#include <irrt_everything.hpp>
+
+namespace test {
+namespace core {
+void test_int_exp() {
+    BEGIN_TEST();
+
+    assert_values_match(125, __nac3_int_exp_impl<int32_t>(5, 3));
+    assert_values_match(3125, __nac3_int_exp_impl<int32_t>(5, 5));
+}
+
+void run() {
+    test_int_exp();
+}
+}
+}

nac3core/irrt/test/test_ndarray_basic.hpp

@@ -0,0 +1,47 @@
+#pragma once
+
+#include <test/core.hpp>
+#include <irrt_everything.hpp>
+
+namespace test {
+namespace ndarray_basic {
+void test_calc_size_from_shape_normal() {
+    // Test shapes with normal values
+    BEGIN_TEST();
+
+    int32_t shape[4] = { 2, 3, 5, 7 };
+    assert_values_match(210, ndarray::basic::util::calc_size_from_shape<int32_t>(4, shape));
+}
+
+void test_calc_size_from_shape_has_zero() {
+    // Test shapes with 0 in them
+    BEGIN_TEST();
+
+    int32_t shape[4] = { 2, 0, 5, 7 };
+    assert_values_match(0, ndarray::basic::util::calc_size_from_shape<int32_t>(4, shape));
+}
+
+void test_set_strides_by_shape() {
+    // Test `set_strides_by_shape()`
+    BEGIN_TEST();
+
+    int32_t shape[4] = { 99, 3, 5, 7 };
+    int32_t strides[4] = { 0 };
+    ndarray::basic::util::set_strides_by_shape((int32_t) sizeof(int32_t), 4, strides, shape);
+
+    int32_t expected_strides[4] = {
+        105 * sizeof(int32_t),
+        35 * sizeof(int32_t),
+        7 * sizeof(int32_t),
+        1 * sizeof(int32_t)
+    };
+    assert_arrays_match(4, expected_strides, strides);
+}
+
+void run() {
+    test_calc_size_from_shape_normal();
+    test_calc_size_from_shape_has_zero();
+    test_set_strides_by_shape();
+}
+}
+}

nac3core/irrt/test/test_ndarray_broadcast.hpp

@@ -0,0 +1,72 @@
+#pragma once
+
+#include <test/core.hpp>
+#include <irrt_everything.hpp>
+
+namespace test { namespace ndarray_broadcast {
+    void test_ndarray_broadcast_1() {
+        /*
+            ```python
+            array = np.array([[19.9, 29.9, 39.9, 49.9]], dtype=np.float64)
+            >>> [[19.9 29.9 39.9 49.9]]
+            
+            array = np.broadcast_to(array, (2, 3, 4))
+            >>> [[[19.9 29.9 39.9 49.9]
+            >>>   [19.9 29.9 39.9 49.9]
+            >>>   [19.9 29.9 39.9 49.9]]
+            >>>  [[19.9 29.9 39.9 49.9]
+            >>>   [19.9 29.9 39.9 49.9]
+            >>>   [19.9 29.9 39.9 49.9]]]
+            
+            assert array.strides == (0, 0, 8)
+            # and then pick some values in `array` and check them...
+            ```
+        */
+        BEGIN_TEST();
+
+        // Prepare src_ndarray
+        double src_data[4] = { 19.9, 29.9, 39.9, 49.9 };
+        const int32_t src_ndims = 2;
+        int32_t src_shape[src_ndims] = {1, 4};
+        int32_t src_strides[src_ndims] = {};
+        NDArray<int32_t> src_ndarray = {
+            .data = (uint8_t*) src_data,
+            .itemsize = sizeof(double),
+            .ndims = src_ndims,
+            .shape = src_shape,
+            .strides = src_strides
+        };
+        ndarray::basic::set_strides_by_shape(&src_ndarray);
+
+        // Prepare dst_ndarray
+        const int32_t dst_ndims = 3;
+        int32_t dst_shape[dst_ndims] = {2, 3, 4};
+        int32_t dst_strides[dst_ndims] = {};
+        NDArray<int32_t> dst_ndarray = {
+            .ndims = dst_ndims,
+            .shape = dst_shape,
+            .strides = dst_strides
+        };
+
+        // Broadcast
+        ErrorContext errctx = create_testing_errctx();
+        ndarray::broadcast::broadcast_to(&errctx, &src_ndarray, &dst_ndarray);
+        assert_errctx_no_error(&errctx);
+
+        assert_arrays_match(dst_ndims, ((int32_t[]) { 0, 0, 8 }), dst_ndarray.strides);
+
+        assert_values_match(19.9, *((double*) ndarray::basic::get_pelement_by_indices(&dst_ndarray, ((int32_t[]) {0, 0, 0}))));
+        assert_values_match(29.9, *((double*) ndarray::basic::get_pelement_by_indices(&dst_ndarray, ((int32_t[]) {0, 0, 1}))));
+        assert_values_match(39.9, *((double*) ndarray::basic::get_pelement_by_indices(&dst_ndarray, ((int32_t[]) {0, 0, 2}))));
+        assert_values_match(49.9, *((double*) ndarray::basic::get_pelement_by_indices(&dst_ndarray, ((int32_t[]) {0, 0, 3}))));
+        assert_values_match(19.9, *((double*) ndarray::basic::get_pelement_by_indices(&dst_ndarray, ((int32_t[]) {0, 1, 0}))));
+        assert_values_match(29.9, *((double*) ndarray::basic::get_pelement_by_indices(&dst_ndarray, ((int32_t[]) {0, 1, 1}))));
+        assert_values_match(39.9, *((double*) ndarray::basic::get_pelement_by_indices(&dst_ndarray, ((int32_t[]) {0, 1, 2}))));
+        assert_values_match(49.9, *((double*) ndarray::basic::get_pelement_by_indices(&dst_ndarray, ((int32_t[]) {0, 1, 3}))));
+        assert_values_match(49.9, *((double*) ndarray::basic::get_pelement_by_indices(&dst_ndarray, ((int32_t[]) {1, 2, 3}))));
+    }
+
+    void run() {
+        test_ndarray_broadcast_1();
+    }
+}}

nac3core/irrt/test/test_ndarray_subscript.hpp

@@ -0,0 +1,233 @@
+#pragma once
+
+#include <test/core.hpp>
+#include <irrt_everything.hpp>
+
+namespace test { namespace ndarray_subscript {
+    void test_ndsubscript_normal_1() {
+        /*
+            Reference Python code:
+            ```python
+            ndarray = np.arange(12, dtype=np.float64).reshape((3, 4));
+            # array([[ 0.,  1.,  2.,  3.],
+            #        [ 4.,  5.,  6.,  7.],
+            #        [ 8.,  9., 10., 11.]])
+
+            dst_ndarray = ndarray[-2:, 1::2]
+            # array([[ 5.,  7.],
+            #        [ 9., 11.]])
+
+            assert dst_ndarray.shape == (2, 2)
+            assert dst_ndarray.strides == (32, 16)
+            assert dst_ndarray[0, 0] == 5.0
+            assert dst_ndarray[0, 1] == 7.0
+            assert dst_ndarray[1, 0] == 9.0
+            assert dst_ndarray[1, 1] == 11.0
+            ```
+        */
+        BEGIN_TEST();
+
+        // Prepare src_ndarray
+        double src_data[12] = { 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 };
+        int32_t src_itemsize = sizeof(double);
+        const int32_t src_ndims = 2;
+        int32_t src_shape[src_ndims] = { 3, 4 };
+        int32_t src_strides[src_ndims] = {};
+        NDArray<int32_t> src_ndarray = {
+            .data = (uint8_t*) src_data,
+            .itemsize = src_itemsize,
+            .ndims = src_ndims,
+            .shape = src_shape,
+            .strides = src_strides
+        };
+        ndarray::basic::set_strides_by_shape(&src_ndarray);
+
+        // Prepare dst_ndarray
+        const int32_t dst_ndims = 2;
+        int32_t dst_shape[dst_ndims] = {999, 999}; // Empty values
+        int32_t dst_strides[dst_ndims] = {999, 999}; // Empty values
+        NDArray<int32_t> dst_ndarray = {
+            .data = nullptr,
+            .ndims = dst_ndims,
+            .shape = dst_shape,
+            .strides = dst_strides
+        };
+
+        // Create the subscripts in `ndarray[-2::, 1::2]`
+        UserSlice subscript_1;
+        subscript_1.set_start(-2);
+
+        UserSlice subscript_2;
+        subscript_2.set_start(1);
+        subscript_2.set_step(2);
+
+        const int32_t num_ndsubscripts = 2;
+        NDSubscript ndsubscripts[num_ndsubscripts] = {
+            { .type = INPUT_SUBSCRIPT_TYPE_SLICE, .data = (uint8_t*) &subscript_1 },
+            { .type = INPUT_SUBSCRIPT_TYPE_SLICE, .data = (uint8_t*) &subscript_2 }
+        };
+
+        ErrorContext errctx = create_testing_errctx();
+        ndarray::subscript::subscript(&errctx, num_ndsubscripts, ndsubscripts, &src_ndarray, &dst_ndarray);
+        assert_errctx_no_error(&errctx);
+
+        int32_t expected_shape[dst_ndims] = { 2, 2 };
+        int32_t expected_strides[dst_ndims] = { 32, 16 };
+
+        assert_arrays_match(dst_ndims, expected_shape, dst_ndarray.shape);
+        assert_arrays_match(dst_ndims, expected_strides, dst_ndarray.strides);
+
+        // dst_ndarray[0, 0]
+        assert_values_match(
+            5.0,
+            *((double *) ndarray::basic::get_pelement_by_indices(&dst_ndarray, (int32_t[dst_ndims]) { 0, 0 }))
+        );
+        // dst_ndarray[0, 1]
+        assert_values_match(
+            7.0,
+            *((double *) ndarray::basic::get_pelement_by_indices(&dst_ndarray, (int32_t[dst_ndims]) { 0, 1 }))
+        );
+        // dst_ndarray[1, 0]
+        assert_values_match(
+            9.0,
+            *((double *) ndarray::basic::get_pelement_by_indices(&dst_ndarray, (int32_t[dst_ndims]) { 1, 0 }))
+        );
+        // dst_ndarray[1, 1]
+        assert_values_match(
+            11.0,
+            *((double *) ndarray::basic::get_pelement_by_indices(&dst_ndarray, (int32_t[dst_ndims]) { 1, 1 }))
+        );
+    }
+
+    void test_ndsubscript_normal_2() {
+        /*
+            ```python
+            ndarray = np.arange(12, dtype=np.float64).reshape((3, 4))
+            # array([[ 0.,  1.,  2.,  3.],
+            #        [ 4.,  5.,  6.,  7.],
+            #        [ 8.,  9., 10., 11.]])
+
+            dst_ndarray = ndarray[2, ::-2]
+            # array([11.,  9.])
+
+            assert dst_ndarray.shape == (2,)
+            assert dst_ndarray.strides == (-16,)
+            assert dst_ndarray[0] == 11.0
+            assert dst_ndarray[1] == 9.0
+            ```
+        */
+        BEGIN_TEST();
+
+        // Prepare src_ndarray
+        double src_data[12] = { 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 };
+        int32_t src_itemsize = sizeof(double);
+        const int32_t src_ndims = 2;
+        int32_t src_shape[src_ndims] = { 3, 4 };
+        int32_t src_strides[src_ndims] = {};
+        NDArray<int32_t> src_ndarray = {
+            .data = (uint8_t*) src_data,
+            .itemsize = src_itemsize,
+            .ndims = src_ndims,
+            .shape = src_shape,
+            .strides = src_strides
+        };
+        ndarray::basic::set_strides_by_shape(&src_ndarray);
+
+        // Prepare dst_ndarray
+        const int32_t dst_ndims = 1;
+        int32_t dst_shape[dst_ndims] = {999}; // Empty values
+        int32_t dst_strides[dst_ndims] = {999}; // Empty values
+        NDArray<int32_t> dst_ndarray = {
+            .data = nullptr,
+            .ndims = dst_ndims,
+            .shape = dst_shape,
+            .strides = dst_strides
+        };
+
+        // Create the subscripts in `ndarray[2, ::-2]`
+        int32_t subscript_1 = 2;
+
+        UserSlice subscript_2;
+        subscript_2.set_step(-2);
+
+        const int32_t num_ndsubscripts = 2;
+        NDSubscript ndsubscripts[num_ndsubscripts] = {
+            { .type = INPUT_SUBSCRIPT_TYPE_INDEX, .data = (uint8_t*) &subscript_1 },
+            { .type = INPUT_SUBSCRIPT_TYPE_SLICE, .data = (uint8_t*) &subscript_2 }
+        };
+
+        ErrorContext errctx = create_testing_errctx();
+        ndarray::subscript::subscript(&errctx, num_ndsubscripts, ndsubscripts, &src_ndarray, &dst_ndarray);
+        assert_errctx_no_error(&errctx);
+
+        int32_t expected_shape[dst_ndims] = { 2 };
+        int32_t expected_strides[dst_ndims] = { -16 };
+        assert_arrays_match(dst_ndims, expected_shape, dst_ndarray.shape);
+        assert_arrays_match(dst_ndims, expected_strides, dst_ndarray.strides);
+
+        assert_values_match(
+            11.0,
+            *((double *) ndarray::basic::get_pelement_by_indices(&dst_ndarray, (int32_t[dst_ndims]) { 0 }))
+        );
+        assert_values_match(
+            9.0,
+            *((double *) ndarray::basic::get_pelement_by_indices(&dst_ndarray, (int32_t[dst_ndims]) { 1 }))
+        );
+    }
+
+    void test_ndsubscript_index_subscript_out_of_bounds() {
+        /*
+            # Consider `my_array`
+
+            print(my_array.shape)
+            # (4, 5, 6)
+
+            my_array[2, 100] # error, index subscript at axis 1 is out of bounds
+        */
+        BEGIN_TEST();
+
+        // Prepare src_ndarray
+        const int32_t src_ndims = 2;
+        int32_t src_shape[src_ndims] = { 3, 4 };
+        int32_t src_strides[src_ndims] = {};
+        NDArray<int32_t> src_ndarray = {
+            .data = (uint8_t*) nullptr, // placeholder, we wouldn't access it
+            .itemsize = sizeof(double), // placeholder
+            .ndims = src_ndims,
+            .shape = src_shape,
+            .strides = src_strides
+        };
+        ndarray::basic::set_strides_by_shape(&src_ndarray);
+
+        // Create the subscripts in `my_array[2, 100]`
+        int32_t subscript_1 = 2;
+        int32_t subscript_2 = 100;
+
+        const int32_t num_ndsubscripts = 2;
+        NDSubscript ndsubscripts[num_ndsubscripts] = {
+            { .type = INPUT_SUBSCRIPT_TYPE_INDEX, .data = (uint8_t*) &subscript_1 },
+            { .type = INPUT_SUBSCRIPT_TYPE_INDEX, .data = (uint8_t*) &subscript_2 }
+        };
+
+        // Prepare dst_ndarray
+        const int32_t dst_ndims = 0;
+        int32_t dst_shape[dst_ndims] = {};
+        int32_t dst_strides[dst_ndims] = {};
+        NDArray<int32_t> dst_ndarray = {
+            .data = nullptr, // placehloder
+            .ndims = dst_ndims,
+            .shape = dst_shape,
+            .strides = dst_strides
+        };
+
+        ErrorContext errctx = create_testing_errctx();
+        ndarray::subscript::subscript(&errctx, num_ndsubscripts, ndsubscripts, &src_ndarray, &dst_ndarray);
+        assert_errctx_has_error(&errctx, errctx.error_ids->index_error);
+    }
+
+    void run() {
+        test_ndsubscript_normal_1();
+        test_ndsubscript_normal_2();
+        test_ndsubscript_index_subscript_out_of_bounds();
+    }
+} }

nac3core/irrt/test/test_slice.hpp

@@ -0,0 +1,96 @@
+#pragma once
+
+#include <test/core.hpp>
+#include <irrt_everything.hpp>
+
+namespace test {
+namespace slice {
+void test_slice_normal() {
+    // Normal situation
+    BEGIN_TEST();
+
+    UserSlice user_slice;
+    user_slice.set_stop(5);
+
+    Slice slice;
+    user_slice.indices(100, &slice);
+
+    printf("%d, %d, %d\n", slice.start, slice.stop, slice.step);
+
+    assert_values_match(0, slice.start);
+    assert_values_match(5, slice.stop);
+    assert_values_match(1, slice.step);
+}
+
+void test_slice_start_too_large() {
+    // Start is too large and should be clamped to length
+    BEGIN_TEST();
+
+    UserSlice user_slice;
+    user_slice.set_start(400);
+
+    Slice slice;
+    user_slice.indices(100, &slice);
+
+    assert_values_match(100, slice.start);
+    assert_values_match(100, slice.stop);
+    assert_values_match(1, slice.step);
+}
+
+void test_slice_negative_start_stop() {
+    // Negative start/stop should be resolved
+    BEGIN_TEST();
+
+    UserSlice user_slice;
+    user_slice.set_start(-10);
+    user_slice.set_stop(-5);
+
+    Slice slice;
+    user_slice.indices(100, &slice);
+
+    assert_values_match(90, slice.start);
+    assert_values_match(95, slice.stop);
+    assert_values_match(1, slice.step);
+}
+
+void test_slice_only_negative_step() {
+    // Things like `[::-5]` should be handled correctly
+    BEGIN_TEST();
+
+    UserSlice user_slice;
+    user_slice.set_step(-5);
+
+    Slice slice;
+    user_slice.indices(100, &slice);
+
+    assert_values_match(99, slice.start);
+    assert_values_match(-1, slice.stop);
+    assert_values_match(-5, slice.step);
+}
+
+void test_slice_step_zero() {
+    // Step = 0 is a value error
+    BEGIN_TEST();
+
+    ErrorContext errctx = create_testing_errctx();
+
+    UserSlice user_slice;
+    user_slice.set_start(2);
+    user_slice.set_stop(12);
+    user_slice.set_step(0);
+
+    Slice slice;
+    user_slice.indices_checked(&errctx, 100, &slice);
+
+    assert_errctx_has_error(&errctx, errctx.error_ids->value_error);
+}
+
+void run() {
+    test_slice_normal();
+    test_slice_start_too_large();
+    test_slice_negative_start_stop();
+    test_slice_only_negative_step();
+    test_slice_step_zero();
+}
+}
+}

nac3core/src/codegen/expr.rs

@@ -4,11 +4,18 @@ use crate::{
     codegen::{
         classes::{
             ArrayLikeIndexer, ArrayLikeValue, ListType, ListValue, NDArrayValue, ProxyType,
-            ProxyValue, RangeValue, TypedArrayLikeAccessor, UntypedArrayLikeAccessor,
+            ProxyValue, RangeValue, UntypedArrayLikeAccessor,
         },
         concrete_type::{ConcreteFuncArg, ConcreteTypeEnum, ConcreteTypeStore},
         gen_in_range_check, get_llvm_abi_type, get_llvm_type,
-        irrt::*,
+        irrt::{
+            numpy::{
+                ndarray::{self, alloca_ndarray_and_init},
+                slice::{RustUserSlice, SliceIndexModel},
+                subscript::{call_nac3_ndarray_subscript, RustNDSubscript},
+            },
+            *,
+        },
         llvm_intrinsics::{
             call_expect, call_float_floor, call_float_pow, call_float_powi, call_int_smax,
             call_memcpy_generic,
@@ -18,31 +25,33 @@ use crate::{
             gen_for_callback_incrementing, gen_if_callback, gen_if_else_expr_callback, gen_raise,
             gen_var,
         },
-        CodeGenContext, CodeGenTask, CodeGenerator,
+        CodeGenContext, CodeGenTask, CodeGenerator, Int32,
     },
     symbol_resolver::{SymbolValue, ValueEnum},
-    toplevel::{
-        helper::PrimDef,
-        numpy::{make_ndarray_ty, unpack_ndarray_var_tys},
-        DefinitionId, TopLevelDef,
-    },
+    toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, DefinitionId, TopLevelDef},
     typecheck::{
         magic_methods::{Binop, BinopVariant, HasOpInfo},
-        typedef::{FunSignature, FuncArg, Type, TypeEnum, TypeVarId, Unifier, VarMap},
+        typedef::{
+            iter_type_vars, FunSignature, FuncArg, Type, TypeEnum, TypeVarId, Unifier, VarMap,
+        },
     },
 };
 use inkwell::{
     attributes::{Attribute, AttributeLoc},
     types::{AnyType, BasicType, BasicTypeEnum},
-    values::{BasicValueEnum, CallSiteValue, FunctionValue, IntValue, PointerValue},
+    values::{
+        AnyValue, BasicValue, BasicValueEnum, CallSiteValue, FunctionValue, IntValue, PointerValue,
+    },
     AddressSpace, IntPredicate, OptimizationLevel,
 };
 use itertools::{chain, izip, Either, Itertools};
 use nac3parser::ast::{
-    self, Boolop, Cmpop, Comprehension, Constant, Expr, ExprKind, Location, Operator, StrRef,
-    Unaryop,
+    self, Boolop, Cmpop, Comprehension, Constant, Expr, ExprKind, Located, Location, Operator,
+    StrRef, Unaryop,
 };
 
+use super::{irrt::numpy::ndarray::NpArray, IntModel, Model, Pointer, PointerModel, StructModel};
+
 pub fn get_subst_key(
     unifier: &mut Unifier,
     obj: Option<Type>,
@@ -576,6 +585,21 @@ impl<'ctx, 'a> CodeGenContext<'ctx, 'a> {
         params: [Option<IntValue<'ctx>>; 3],
         loc: Location,
     ) {
+        let error_id = self.resolver.get_string_id(name);
+        let error_id = self.ctx.i32_type().const_int(error_id as u64, false);
+        self.raise_exn_by_id(generator, error_id, msg, params, loc);
+    }
+
+    pub fn raise_exn_by_id<G: CodeGenerator + ?Sized>(
+        &mut self,
+        generator: &mut G,
+        error_id: IntValue<'ctx>,
+        msg: BasicValueEnum<'ctx>,
+        params: [Option<IntValue<'ctx>>; 3],
+        loc: Location,
+    ) {
+        assert_eq!(error_id.get_type().get_bit_width(), 32);
+
         let zelf = if let Some(exception_val) = self.exception_val {
             exception_val
         } else {
@@ -588,8 +612,7 @@ impl<'ctx, 'a> CodeGenContext<'ctx, 'a> {
         let zero = int32.const_zero();
         unsafe {
             let id_ptr = self.builder.build_in_bounds_gep(zelf, &[zero, zero], "exn.id").unwrap();
-            let id = self.resolver.get_string_id(name);
-            self.builder.build_store(id_ptr, int32.const_int(id as u64, false)).unwrap();
+            self.builder.build_store(id_ptr, error_id).unwrap();
             let ptr = self
                 .builder
                 .build_in_bounds_gep(zelf, &[zero, int32.const_int(5, false)], "exn.msg")
@@ -652,6 +675,32 @@ impl<'ctx, 'a> CodeGenContext<'ctx, 'a> {
         self.raise_exn(generator, err_name, err_msg, params, loc);
         self.builder.position_at_end(then_block);
     }
+
+    pub fn make_assert_impl_by_id<G: CodeGenerator + ?Sized>(
+        &mut self,
+        generator: &mut G,
+        cond: IntValue<'ctx>,
+        err_id: IntValue<'ctx>,
+        err_msg: BasicValueEnum<'ctx>,
+        params: [Option<IntValue<'ctx>>; 3],
+        loc: Location,
+    ) {
+        let i1 = self.ctx.bool_type();
+        let i1_true = i1.const_all_ones();
+        // we assume that the condition is most probably true, so the normal path is the most
+        // probable path
+        // even if this assumption is violated, it does not matter as exception unwinding is
+        // slow anyway...
+        let cond = call_expect(self, cond, i1_true, Some("expect"));
+        let current_bb = self.builder.get_insert_block().unwrap();
+        let current_fun = current_bb.get_parent().unwrap();
+        let then_block = self.ctx.insert_basic_block_after(current_bb, "succ");
+        let exn_block = self.ctx.append_basic_block(current_fun, "fail");
+        self.builder.build_conditional_branch(cond, then_block, exn_block).unwrap();
+        self.builder.position_at_end(exn_block);
+        self.raise_exn_by_id(generator, err_id, err_msg, params, loc);
+        self.builder.position_at_end(then_block);
+    }
 }
 
 /// See [`CodeGenerator::gen_constructor`].
@@ -1014,11 +1063,59 @@ pub fn gen_comprehension<'ctx, G: CodeGenerator>(
     ctx.builder.build_store(index, zero_size_t).unwrap();
 
     let elem_ty = ctx.get_llvm_type(generator, elt.custom.unwrap());
-    let is_range = ctx.unifier.unioned(iter.custom.unwrap(), ctx.primitives.range);
     let list;
     let list_content;
 
-    if is_range {
+    // The implementation of the for loop logic depends on
+    // the typechecker type of `iter`.
+    let iter_ty = iter.custom.unwrap();
+    match &*ctx.unifier.get_ty(iter_ty) {
+        TypeEnum::TObj { obj_id, params, .. }
+            if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
+        {
+            // `iter` is a `List[T]`, and `T` is the element type
+
+            // Get the `T` out of `List[T]` - it is defined to be the 1st param.
+            let list_elem_ty = iter_type_vars(params).nth(0).unwrap().ty;
+
+            let length = ctx
+                .build_gep_and_load(
+                    iter_val.into_pointer_value(),
+                    &[zero_size_t, int32.const_int(1, false)],
+                    Some("length"),
+                )
+                .into_int_value();
+            list = allocate_list(generator, ctx, Some(elem_ty), length, Some("listcomp"));
+            list_content = list.data().base_ptr(ctx, generator);
+            let counter = generator.gen_var_alloc(ctx, size_t.into(), Some("counter.addr"))?;
+            // counter = -1
+            ctx.builder.build_store(counter, size_t.const_int(u64::MAX, true)).unwrap();
+            ctx.builder.build_unconditional_branch(test_bb).unwrap();
+
+            ctx.builder.position_at_end(test_bb);
+            let tmp =
+                ctx.builder.build_load(counter, "i").map(BasicValueEnum::into_int_value).unwrap();
+            let tmp = ctx.builder.build_int_add(tmp, size_t.const_int(1, false), "inc").unwrap();
+            ctx.builder.build_store(counter, tmp).unwrap();
+            let cmp = ctx.builder.build_int_compare(IntPredicate::SLT, tmp, length, "cmp").unwrap();
+            ctx.builder.build_conditional_branch(cmp, body_bb, cont_bb).unwrap();
+
+            ctx.builder.position_at_end(body_bb);
+            let arr_ptr = ctx
+                .build_gep_and_load(
+                    iter_val.into_pointer_value(),
+                    &[zero_size_t, zero_32],
+                    Some("arr.addr"),
+                )
+                .into_pointer_value();
+            let val = ctx.build_gep_and_load(arr_ptr, &[tmp], Some("val"));
+            generator.gen_assign(ctx, target, val.into(), list_elem_ty)?;
+        }
+        TypeEnum::TObj { obj_id, .. }
+            if *obj_id == ctx.primitives.range.obj_id(&ctx.unifier).unwrap() =>
+        {
+            // `iter` is a `range(start, stop, step)`, and `int32` is the element type
+
             let iter_val = RangeValue::from_ptr_val(iter_val.into_pointer_value(), Some("range"));
             let (start, stop, step) = destructure_range(ctx, iter_val);
             let diff = ctx.builder.build_int_sub(stop, start, "diff").unwrap();
@@ -1026,7 +1123,8 @@ pub fn gen_comprehension<'ctx, G: CodeGenerator>(
             // the length may be 1 more than the actual length if the division is exact, but the
             // length is a upper bound only anyway so it does not matter.
             let length = ctx.builder.build_int_signed_div(diff, step, "div").unwrap();
-        let length = ctx.builder.build_int_add(length, int32.const_int(1, false), "add1").unwrap();
+            let length =
+                ctx.builder.build_int_add(length, int32.const_int(1, false), "add1").unwrap();
             // in case length is non-positive
             let is_valid =
                 ctx.builder.build_int_compare(IntPredicate::SGT, length, zero_32, "check").unwrap();
@@ -1035,7 +1133,9 @@ pub fn gen_comprehension<'ctx, G: CodeGenerator>(
                 .builder
                 .build_select(
                     is_valid,
-                ctx.builder.build_int_z_extend_or_bit_cast(length, size_t, "z_ext_len").unwrap(),
+                    ctx.builder
+                        .build_int_z_extend_or_bit_cast(length, size_t, "z_ext_len")
+                        .unwrap(),
                     zero_size_t,
                     "listcomp.alloc_size",
                 )
@@ -1055,7 +1155,11 @@ pub fn gen_comprehension<'ctx, G: CodeGenerator>(
                 .unwrap();
 
             ctx.builder
-            .build_conditional_branch(gen_in_range_check(ctx, start, stop, step), test_bb, cont_bb)
+                .build_conditional_branch(
+                    gen_in_range_check(ctx, start, stop, step),
+                    test_bb,
+                    cont_bb,
+                )
                 .unwrap();
 
             ctx.builder.position_at_end(test_bb);
@@ -1070,42 +1174,21 @@ pub fn gen_comprehension<'ctx, G: CodeGenerator>(
                 .unwrap();
             ctx.builder.build_store(i, tmp).unwrap();
             ctx.builder
-            .build_conditional_branch(gen_in_range_check(ctx, tmp, stop, step), body_bb, cont_bb)
+                .build_conditional_branch(
+                    gen_in_range_check(ctx, tmp, stop, step),
+                    body_bb,
+                    cont_bb,
+                )
                 .unwrap();
 
             ctx.builder.position_at_end(body_bb);
-    } else {
-        let length = ctx
-            .build_gep_and_load(
-                iter_val.into_pointer_value(),
-                &[zero_size_t, int32.const_int(1, false)],
-                Some("length"),
+        }
+        _ => {
+            panic!(
+                "unsupported iterator type in list comprehension: {}",
+                ctx.unifier.stringify(iter_ty)
             )
-            .into_int_value();
-        list = allocate_list(generator, ctx, Some(elem_ty), length, Some("listcomp"));
-        list_content = list.data().base_ptr(ctx, generator);
-        let counter = generator.gen_var_alloc(ctx, size_t.into(), Some("counter.addr"))?;
-        // counter = -1
-        ctx.builder.build_store(counter, size_t.const_int(u64::MAX, true)).unwrap();
-        ctx.builder.build_unconditional_branch(test_bb).unwrap();
-
-        ctx.builder.position_at_end(test_bb);
-        let tmp = ctx.builder.build_load(counter, "i").map(BasicValueEnum::into_int_value).unwrap();
-        let tmp = ctx.builder.build_int_add(tmp, size_t.const_int(1, false), "inc").unwrap();
-        ctx.builder.build_store(counter, tmp).unwrap();
-        let cmp = ctx.builder.build_int_compare(IntPredicate::SLT, tmp, length, "cmp").unwrap();
-        ctx.builder.build_conditional_branch(cmp, body_bb, cont_bb).unwrap();
-
-        ctx.builder.position_at_end(body_bb);
-        let arr_ptr = ctx
-            .build_gep_and_load(
-                iter_val.into_pointer_value(),
-                &[zero_size_t, zero_32],
-                Some("arr.addr"),
-            )
-            .into_pointer_value();
-        let val = ctx.build_gep_and_load(arr_ptr, &[tmp], Some("val"));
-        generator.gen_assign(ctx, target, val.into())?;
+        }
     }
 
     // Emits the content of `cont_bb`
@@ -2090,322 +2173,153 @@ pub fn gen_cmpop_expr<'ctx, G: CodeGenerator>(
 
 /// Generates code for a subscript expression on an `ndarray`.
 ///
-/// * `ty` - The `Type` of the `NDArray` elements.
+/// * `elem_ty` - The `Type` of the `NDArray` elements.
 /// * `ndims` - The `Type` of the `NDArray` number-of-dimensions `Literal`.
-/// * `v` - The `NDArray` value.
+/// * `src_ndarray` - The `NDArray` value.
 /// * `slice` - The slice expression used to subscript into the `ndarray`.
 fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
     generator: &mut G,
     ctx: &mut CodeGenContext<'ctx, '_>,
-    ty: Type,
+    elem_ty: Type,
     ndims: Type,
-    v: NDArrayValue<'ctx>,
+    src_ndarray: Pointer<'ctx, StructModel<NpArray<'ctx>>>,
     slice: &Expr<Option<Type>>,
 ) -> Result<Option<ValueEnum<'ctx>>, String> {
-    let llvm_i1 = ctx.ctx.bool_type();
-    let llvm_i32 = ctx.ctx.i32_type();
-    let llvm_usize = generator.get_size_type(ctx.ctx);
+    // TODO: Support https://numpy.org/doc/stable/user/basics.indexing.html#dimensional-indexing-tools
 
-    let TypeEnum::TLiteral { values, .. } = &*ctx.unifier.get_ty_immutable(ndims) else {
-        unreachable!()
+    let sizet = src_ndarray.element.0.sizet;
+    debug_assert_eq!(sizet.0, generator.get_size_type(ctx.ctx)); // If the ndarray's size_type somehow isn't that of `generator.get_size_type()`... there would be a bug
+
+    let slice_index_model = SliceIndexModel::default();
+
+    // 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 subscript_exprs = match &slice.node {
+        ExprKind::Tuple { elts, .. } => elts.iter().collect_vec(),
+        _ => vec![slice],
     };
 
-    let ndims = values
-        .iter()
-        .map(|ndim| u64::try_from(ndim.clone()).map_err(|()| ndim.clone()))
-        .collect::<Result<Vec<_>, _>>()
-        .map_err(|val| {
-            format!(
-                "Expected non-negative literal for ndarray.ndims, got {}",
-                i128::try_from(val).unwrap()
-            )
-        })?;
-
-    assert!(!ndims.is_empty());
-
-    // The number of dimensions subscripted by the index expression.
-    // Slicing a ndarray will yield the same number of dimensions, whereas indexing into a
-    // dimension will remove a dimension.
-    let subscripted_dims = match &slice.node {
-        ExprKind::Tuple { elts, .. } => elts.iter().fold(0, |acc, value_subexpr| {
-            if let ExprKind::Slice { .. } = &value_subexpr.node {
-                acc
-            } else {
-                acc + 1
-            }
-        }),
-
-        ExprKind::Slice { .. } => 0,
-        _ => 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();
-
-    // Check that len is non-zero
-    let len = v.load_ndims(ctx);
-    ctx.make_assert(
-        generator,
-        ctx.builder.build_int_compare(IntPredicate::SGT, len, llvm_usize.const_zero(), "").unwrap(),
-        "0:IndexError",
-        "too many indices for array: array is {0}-dimensional but 1 were indexed",
-        [Some(len), None, None],
-        slice.location,
-    );
-
-    // Normalizes a possibly-negative index to its corresponding positive index
-    let normalize_index = |generator: &mut G,
-                           ctx: &mut CodeGenContext<'ctx, '_>,
-                           index: IntValue<'ctx>,
-                           dim: u64| {
-        gen_if_else_expr_callback(
-            generator,
-            ctx,
-            |_, ctx| {
-                Ok(ctx
-                    .builder
-                    .build_int_compare(IntPredicate::SGE, index, index.get_type().const_zero(), "")
-                    .unwrap())
-            },
-            |_, _| Ok(Some(index)),
-            |generator, ctx| {
-                let llvm_i32 = ctx.ctx.i32_type();
-
-                let len = unsafe {
-                    v.dim_sizes().get_typed_unchecked(
-                        ctx,
-                        generator,
-                        &llvm_usize.const_int(dim, true),
-                        None,
-                    )
-                };
-
-                let index = ctx
-                    .builder
-                    .build_int_add(
-                        len,
-                        ctx.builder.build_int_s_extend(index, llvm_usize, "").unwrap(),
-                        "",
-                    )
-                    .unwrap();
-
-                Ok(Some(ctx.builder.build_int_truncate(index, llvm_i32, "").unwrap()))
-            },
-        )
-        .map(|v| v.map(BasicValueEnum::into_int_value))
-    };
-
-    // Converts a slice expression into a slice-range tuple
-    let expr_to_slice = |generator: &mut G,
-                         ctx: &mut CodeGenContext<'ctx, '_>,
-                         node: &ExprKind<Option<Type>>,
-                         dim: u64| {
-        match node {
-            ExprKind::Constant { value: Constant::Int(v), .. } => {
-                let Some(index) =
-                    normalize_index(generator, ctx, llvm_i32.const_int(*v as u64, true), dim)?
-                else {
-                    return Ok(None);
-                };
-
-                Ok(Some((index, index, llvm_i32.const_int(1, true))))
-            }
-
-            ExprKind::Slice { lower, upper, step } => {
-                let dim_sz = unsafe {
-                    v.dim_sizes().get_typed_unchecked(
-                        ctx,
-                        generator,
-                        &llvm_usize.const_int(dim, false),
-                        None,
-                    )
-                };
-
-                handle_slice_indices(lower, upper, step, ctx, generator, dim_sz)
-            }
-
-            _ => {
-                let Some(index) = generator.gen_expr(ctx, slice)? else { return Ok(None) };
-                let index = index
-                    .to_basic_value_enum(ctx, generator, slice.custom.unwrap())?
-                    .into_int_value();
-                let Some(index) = normalize_index(generator, ctx, index, dim)? else {
-                    return Ok(None);
-                };
-
-                Ok(Some((index, index, llvm_i32.const_int(1, true))))
-            }
-        }
-    };
-
-    let make_indices_arr = |generator: &mut G,
-                            ctx: &mut CodeGenContext<'ctx, '_>|
-     -> Result<_, String> {
-        Ok(if let ExprKind::Tuple { elts, .. } = &slice.node {
-            let llvm_int_ty = ctx.get_llvm_type(generator, elts[0].custom.unwrap());
-            let index_addr = generator.gen_array_var_alloc(
-                ctx,
-                llvm_int_ty,
-                llvm_usize.const_int(elts.len() as u64, false),
-                None,
-            )?;
-
-            for (i, elt) in elts.iter().enumerate() {
-                let Some(index) = generator.gen_expr(ctx, elt)? else {
-                    return Ok(None);
-                };
-
-                let index = index
-                    .to_basic_value_enum(ctx, generator, elt.custom.unwrap())?
-                    .into_int_value();
-                let Some(index) = normalize_index(generator, ctx, index, 0)? else {
-                    return Ok(None);
-                };
-
-                let store_ptr = unsafe {
-                    index_addr.ptr_offset_unchecked(
-                        ctx,
-                        generator,
-                        &llvm_usize.const_int(i as u64, false),
-                        None,
-                    )
-                };
-                ctx.builder.build_store(store_ptr, index).unwrap();
-            }
-
-            Some(index_addr)
-        } else if let Some(index) = generator.gen_expr(ctx, slice)? {
-            let llvm_int_ty = ctx.get_llvm_type(generator, slice.custom.unwrap());
-            let index_addr = generator.gen_array_var_alloc(
-                ctx,
-                llvm_int_ty,
-                llvm_usize.const_int(1u64, false),
-                None,
-            )?;
-
-            let index =
-                index.to_basic_value_enum(ctx, generator, slice.custom.unwrap())?.into_int_value();
-            let Some(index) = normalize_index(generator, ctx, index, 0)? else { return Ok(None) };
-
-            let store_ptr = unsafe {
-                index_addr.ptr_offset_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
-            };
-            ctx.builder.build_store(store_ptr, index).unwrap();
-
-            Some(index_addr)
-        } else {
-            None
+    // Process all subscript expressions in subscripts
+    let mut rust_ndsubscripts: Vec<RustNDSubscript> = Vec::with_capacity(subscript_exprs.len()); // Not using iterators here because `?` is used here.
+    for subscript_expr in subscript_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 ndsubscript =
+            if let ExprKind::Slice { lower: start, upper: stop, step } = &subscript_expr.node {
+                // Helper function here to deduce code duplication
+                type ValueExpr = Option<Box<Located<ExprKind<Option<Type>>, Option<Type>>>>;
+                let mut help = |value_expr: &ValueExpr| -> Result<_, String> {
+                    Ok(match value_expr {
+                        None => None,
+                        Some(value_expr) => Some(
+                            slice_index_model.review(
+                                ctx.ctx,
+                                generator
+                                    .gen_expr(ctx, value_expr)?
+                                    .unwrap()
+                                    .to_basic_value_enum(ctx, generator, ctx.primitives.int32)?
+                                    .as_any_value_enum(),
+                            ),
+                        ),
                     })
                 };
 
-    Ok(Some(if ndims.len() == 1 && ndims[0] - subscripted_dims == 0 {
-        let Some(index_addr) = make_indices_arr(generator, ctx)? else { return Ok(None) };
+                let start = help(start)?;
+                let stop = help(stop)?;
+                let step = help(step)?;
 
-        v.data().get(ctx, generator, &index_addr, None).into()
+                RustNDSubscript::Slice(RustUserSlice { start, stop, step })
             } else {
-        match &slice.node {
-            ExprKind::Tuple { elts, .. } => {
-                let slices = elts
-                    .iter()
-                    .enumerate()
-                    .map(|(dim, elt)| expr_to_slice(generator, ctx, &elt.node, dim as u64))
-                    .take_while_inclusive(|slice| slice.as_ref().is_ok_and(Option::is_some))
-                    .collect::<Result<Vec<_>, _>>()?;
-                if slices.len() < elts.len() {
-                    return Ok(None);
-                }
+                // Anything else that is not a slice (might be illegal values),
+                // For nac3core, this should be e.g., an int32 constant, an int32 variable, otherwise its an error
 
-                let slices = slices.into_iter().map(Option::unwrap).collect_vec();
+                let index = slice_index_model.review(
+                    ctx.ctx,
+                    generator
+                        .gen_expr(ctx, subscript_expr)?
+                        .unwrap()
+                        .to_basic_value_enum(ctx, generator, ctx.primitives.int32)?
+                        .as_any_value_enum(),
+                );
 
-                numpy::ndarray_sliced_copy(generator, ctx, ty, v, &slices)?.as_base_value().into()
-            }
-
-            ExprKind::Slice { .. } => {
-                let Some(slice) = expr_to_slice(generator, ctx, &slice.node, 0)? else {
-                    return Ok(None);
+                RustNDSubscript::Index(index)
             };
-
-                numpy::ndarray_sliced_copy(generator, ctx, ty, v, &[slice])?.as_base_value().into()
+        rust_ndsubscripts.push(ndsubscript);
     }
 
-            _ => {
-                // Accessing an element from a multi-dimensional `ndarray`
-
-                let Some(index_addr) = make_indices_arr(generator, ctx)? else { return Ok(None) };
-
-                // 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_ptr_val(subscripted_ndarray, 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_dim_sizes(ctx, llvm_usize, ndarray_num_dims);
-
-                let ndarray_num_dims = ndarray.load_ndims(ctx);
-                let v_dims_src_ptr = unsafe {
-                    v.dim_sizes().ptr_offset_unchecked(
-                        ctx,
-                        generator,
-                        &llvm_usize.const_int(1, false),
-                        None,
-                    )
+    // Extract the `ndims` from a `Type` to `i128`
+    // We *HAVE* to know this statically, this is used to determine
+    // whether the subscript returns a scalar or an ndarray
+    let TypeEnum::TLiteral { values: ndims_values, .. } = &*ctx.unifier.get_ty_immutable(ndims)
+    else {
+        unreachable!()
     };
-                call_memcpy_generic(
-                    ctx,
-                    ndarray.dim_sizes().base_ptr(ctx, generator),
-                    v_dims_src_ptr,
-                    ctx.builder
-                        .build_int_mul(ndarray_num_dims, llvm_usize.size_of(), "")
-                        .map(Into::into)
-                        .unwrap(),
-                    llvm_i1.const_zero(),
-                );
+    assert_eq!(ndims_values.len(), 1);
+    let src_ndims = i128::try_from(ndims_values[0].clone()).unwrap();
 
-                let ndarray_num_elems = call_ndarray_calc_size(
+    // Check for "too many indices for array: array is ..." error
+    if src_ndims < rust_ndsubscripts.len() as i128 {
+        ctx.make_assert(
+            generator,
+            ctx.ctx.bool_type().const_int(1, false),
+            "0:IndexError",
+            "too many indices for array: array is {0}-dimensional, but {1} were indexed",
+            [None, None, None],
+            ctx.current_loc,
+        );
+    }
+
+    // Statically determine `dst_ndims`
+    let dst_ndims =
+        RustNDSubscript::deduce_ndims_after_slicing(&rust_ndsubscripts, src_ndims as i32);
+
+    // Prepare dst_ndarray
+    let elem_llvm_ty = ctx.get_llvm_type(generator, elem_ty);
+    let dst_ndarray = alloca_ndarray_and_init(
         generator,
         ctx,
-                    &ndarray.dim_sizes().as_slice_value(ctx, generator),
-                    (None, None),
-                );
-                ndarray.create_data(ctx, llvm_ndarray_data_t, ndarray_num_elems);
-
-                let v_data_src_ptr = v.data().ptr_offset(ctx, generator, &index_addr, None);
-                call_memcpy_generic(
-                    ctx,
-                    ndarray.data().base_ptr(ctx, generator),
-                    v_data_src_ptr,
-                    ctx.builder
-                        .build_int_mul(
-                            ndarray_num_elems,
-                            llvm_ndarray_data_t.size_of().unwrap(),
-                            "",
+        elem_llvm_ty,
+        ndarray::NDArrayInitMode::NDims { ndims: sizet.constant(dst_ndims as u64) },
+        "subndarray",
     )
-                        .map(Into::into)
-                        .unwrap(),
-                    llvm_i1.const_zero(),
+    .unwrap();
+
+    // Prepare the subscripts
+    let ndsubscript_array = RustNDSubscript::alloca_subscripts(ctx, &rust_ndsubscripts);
+
+    // NOTE: IRRT does check for indexing errors
+    call_nac3_ndarray_subscript(
+        generator,
+        ctx,
+        ndsubscript_array.num_elements.signed_cast_to_fixed(ctx, Int32, "num_ndsubscripts"),
+        ndsubscript_array.pointer,
+        src_ndarray,
+        dst_ndarray,
     );
 
-                ndarray.as_base_value().into()
-            }
-        }
-    }))
+    // ...and return the result, with two cases
+    let result_llvm_value = if dst_ndims == 0 {
+        // 1) ndims == 0 (this happens when you do `np.zerps((3, 4))[1, 1]`), return *THE ELEMENT*
+        let element_ptr = dst_ndarray.gep(ctx, |f| f.data).load(ctx, "pelement"); // `*data` points to the first element by definition
+        element_ptr.cast_opaque_to(ctx, elem_llvm_ty, "").load_opaque(ctx, "element")
+    } else {
+        // 2) ndims > 0 (other cases), return subndarray
+        dst_ndarray.value.as_basic_value_enum()
+    };
+    Ok(Some(ValueEnum::Dynamic(result_llvm_value)))
 }
 
 /// See [`CodeGenerator::gen_expr`].
@@ -3048,17 +2962,26 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
                     }
                 }
                 TypeEnum::TObj { obj_id, params, .. } if *obj_id == PrimDef::NDArray.id() => {
-                    let (ty, ndims) = params.iter().map(|(_, ty)| ty).collect_tuple().unwrap();
+                    let (elem_ty, ndims) = params.iter().map(|(_, ty)| ty).collect_tuple().unwrap();
 
-                    let v = if let Some(v) = generator.gen_expr(ctx, value)? {
-                        v.to_basic_value_enum(ctx, generator, value.custom.unwrap())?
-                            .into_pointer_value()
+                    let ndarray_ptr = if let Some(v) = generator.gen_expr(ctx, value)? {
+                        let sizet = IntModel(generator.get_size_type(ctx.ctx));
+                        let ndarray_ptr_model = PointerModel(StructModel(NpArray { sizet }));
+
+                        let v = v.to_basic_value_enum(ctx, generator, value.custom.unwrap())?;
+                        ndarray_ptr_model.review(ctx.ctx, v.as_any_value_enum())
                     } else {
                         return Ok(None);
                     };
-                    let v = NDArrayValue::from_ptr_val(v, usize, None);
 
-                    return gen_ndarray_subscript_expr(generator, ctx, *ty, *ndims, v, slice);
+                    return gen_ndarray_subscript_expr(
+                        generator,
+                        ctx,
+                        *elem_ty,
+                        *ndims,
+                        ndarray_ptr,
+                        slice,
+                    );
                 }
                 TypeEnum::TTuple { .. } => {
                     let index: u32 =

nac3core/src/codegen/generator.rs

@@ -123,11 +123,12 @@ pub trait CodeGenerator {
         ctx: &mut CodeGenContext<'ctx, '_>,
         target: &Expr<Option<Type>>,
         value: ValueEnum<'ctx>,
+        value_ty: Type,
     ) -> Result<(), String>
     where
         Self: Sized,
     {
-        gen_assign(self, ctx, target, value)
+        gen_assign(self, ctx, target, value, value_ty)
     }
 
     /// Generate code for a while expression.

nac3core/src/codegen/irrt/error_context.rs

@@ -0,0 +1,187 @@
+use crate::codegen::{model::*, CodeGenContext, CodeGenerator};
+
+use super::util::{get_sized_dependent_function_name, FunctionBuilder};
+
+pub struct StrFields<'ctx> {
+    pub content: Field<PointerModel<FixedIntModel<Byte>>>,
+    pub length: Field<IntModel<'ctx>>,
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct Str<'ctx> {
+    pub sizet: IntModel<'ctx>,
+}
+
+impl<'ctx> IsStruct<'ctx> for Str<'ctx> {
+    type Fields = StrFields<'ctx>;
+
+    fn struct_name(&self) -> &'static str {
+        "Str"
+    }
+
+    fn build_fields(&self, builder: &mut FieldBuilder<'ctx>) -> Self::Fields {
+        Self::Fields {
+            content: builder.add_field_auto("content"),
+            length: builder.add_field("length", self.sizet),
+        }
+    }
+}
+
+type ErrorId = Int32;
+pub struct ErrorIdsFields {
+    pub index_error: Field<FixedIntModel<ErrorId>>,
+    pub value_error: Field<FixedIntModel<ErrorId>>,
+    pub assertion_error: Field<FixedIntModel<ErrorId>>,
+    pub runtime_error: Field<FixedIntModel<ErrorId>>,
+    pub type_error: Field<FixedIntModel<ErrorId>>,
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct ErrorIds;
+
+impl<'ctx> IsStruct<'ctx> for ErrorIds {
+    type Fields = ErrorIdsFields;
+
+    fn struct_name(&self) -> &'static str {
+        "ErrorIds"
+    }
+
+    fn build_fields(&self, builder: &mut FieldBuilder) -> Self::Fields {
+        Self::Fields {
+            index_error: builder.add_field_auto("index_error"),
+            value_error: builder.add_field_auto("value_error"),
+            assertion_error: builder.add_field_auto("assertion_error"),
+            runtime_error: builder.add_field_auto("runtime_error"),
+            type_error: builder.add_field_auto("type_error"),
+        }
+    }
+}
+
+pub struct ErrorContextFields {
+    pub error_id: Field<FixedIntModel<ErrorId>>,
+    pub message_template: Field<PointerModel<FixedIntModel<Byte>>>,
+    pub param1: Field<FixedIntModel<Int64>>,
+    pub param2: Field<FixedIntModel<Int64>>,
+    pub param3: Field<FixedIntModel<Int64>>,
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct ErrorContext;
+
+impl<'ctx> IsStruct<'ctx> for ErrorContext {
+    type Fields = ErrorContextFields;
+
+    fn struct_name(&self) -> &'static str {
+        "ErrorIds"
+    }
+
+    fn build_fields(&self, builder: &mut FieldBuilder) -> Self::Fields {
+        Self::Fields {
+            error_id: builder.add_field_auto("error_id"),
+            message_template: builder.add_field_auto("message_template"),
+            param1: builder.add_field_auto("param1"),
+            param2: builder.add_field_auto("param2"),
+            param3: builder.add_field_auto("param3"),
+        }
+    }
+}
+
+// Prepare ErrorIds
+fn build_error_ids<'ctx>(ctx: &CodeGenContext<'ctx, '_>) -> Pointer<'ctx, StructModel<ErrorIds>> {
+    // ErrorIdsLens.get_fields(ctx.ctx).assertion_error.
+    let error_ids = StructModel(ErrorIds).alloca(ctx, "error_ids");
+    let i32_model = FixedIntModel(Int32);
+    // i32_model.make_constant()
+
+    let get_string_id =
+        |string_id| i32_model.constant(ctx.ctx, ctx.resolver.get_string_id(string_id) as u64);
+
+    error_ids.gep(ctx, |f| f.index_error).store(ctx, get_string_id("0:IndexError"));
+    error_ids.gep(ctx, |f| f.value_error).store(ctx, get_string_id("0:ValueError"));
+    error_ids.gep(ctx, |f| f.assertion_error).store(ctx, get_string_id("0:AssertionError"));
+    error_ids.gep(ctx, |f| f.runtime_error).store(ctx, get_string_id("0:RuntimeError"));
+    error_ids.gep(ctx, |f| f.type_error).store(ctx, get_string_id("0:TypeError"));
+
+    error_ids
+}
+
+pub fn call_nac3_error_context_initialize<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+    perrctx: Pointer<'ctx, StructModel<ErrorContext>>,
+    perror_ids: Pointer<'ctx, StructModel<ErrorIds>>,
+) {
+    FunctionBuilder::begin(ctx, "__nac3_error_context_initialize")
+        .arg("errctx", PointerModel(StructModel(ErrorContext)), perrctx)
+        .arg("error_ids", PointerModel(StructModel(ErrorIds)), perror_ids)
+        .returning_void();
+}
+
+pub fn call_nac3_error_context_has_no_error<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+    errctx: Pointer<'ctx, StructModel<ErrorContext>>,
+) -> FixedInt<'ctx, Bool> {
+    FunctionBuilder::begin(ctx, "__nac3_error_context_has_no_error")
+        .arg("errctx", PointerModel(StructModel(ErrorContext)), errctx)
+        .returning("has_error", FixedIntModel(Bool))
+}
+
+pub fn call_nac3_error_context_get_error_str<'ctx>(
+    sizet: IntModel<'ctx>,
+    ctx: &CodeGenContext<'ctx, '_>,
+    errctx: Pointer<'ctx, StructModel<ErrorContext>>,
+    dst_str: Pointer<'ctx, StructModel<Str<'ctx>>>,
+) {
+    FunctionBuilder::begin(
+        ctx,
+        &get_sized_dependent_function_name(sizet, "__nac3_error_context_get_error_str"),
+    )
+    .arg("errctx", PointerModel(StructModel(ErrorContext)), errctx)
+    .arg("dst_str", PointerModel(StructModel(Str { sizet })), dst_str)
+    .returning_void();
+}
+
+pub fn prepare_error_context<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+) -> Pointer<'ctx, StructModel<ErrorContext>> {
+    let error_ids = build_error_ids(ctx);
+    let errctx_ptr = StructModel(ErrorContext).alloca(ctx, "errctx");
+    call_nac3_error_context_initialize(ctx, errctx_ptr, error_ids);
+    errctx_ptr
+}
+
+pub fn check_error_context<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    errctx_ptr: Pointer<'ctx, StructModel<ErrorContext>>,
+) {
+    let sizet = IntModel(generator.get_size_type(ctx.ctx));
+
+    let has_error = call_nac3_error_context_has_no_error(ctx, errctx_ptr);
+    let pstr = StructModel(Str { sizet }).alloca(ctx, "error_str");
+    call_nac3_error_context_get_error_str(sizet, ctx, errctx_ptr, pstr);
+
+    let error_id = errctx_ptr.gep(ctx, |f| f.error_id).load(ctx, "error_id");
+    let error_str = pstr.load(ctx, "error_str");
+    let param1 = errctx_ptr.gep(ctx, |f| f.param1).load(ctx, "param1");
+    let param2 = errctx_ptr.gep(ctx, |f| f.param2).load(ctx, "param2");
+    let param3 = errctx_ptr.gep(ctx, |f| f.param3).load(ctx, "param3");
+    ctx.make_assert_impl_by_id(
+        generator,
+        has_error.value,
+        error_id.value,
+        error_str.get_llvm_value(),
+        [Some(param1.value), Some(param2.value), Some(param3.value)],
+        ctx.current_loc,
+    );
+}
+
+pub fn call_nac3_dummy_raise<G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext,
+) {
+    let errctx = prepare_error_context(ctx);
+    FunctionBuilder::begin(ctx, "__nac3_error_dummy_raise")
+        .arg("errctx", PointerModel(StructModel(ErrorContext)), errctx)
+        .returning_void();
+    check_error_context(generator, ctx, errctx);
+}

nac3core/src/codegen/irrt/mod.rs

@@ -1,5 +1,10 @@
 use crate::typecheck::typedef::Type;
 
+pub mod error_context;
+pub mod numpy;
+mod test;
+mod util;
+
 use super::{
     classes::{
         ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayValue,

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

@@ -0,0 +1,4 @@
+pub mod ndarray;
+pub mod shape;
+pub mod slice;
+pub mod subscript;

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

@@ -0,0 +1,254 @@
+use inkwell::types::{BasicType, BasicTypeEnum};
+
+use crate::codegen::{
+    irrt::{
+        error_context::{check_error_context, prepare_error_context, ErrorContext},
+        util::{get_sized_dependent_function_name, FunctionBuilder},
+    },
+    model::*,
+    CodeGenContext, CodeGenerator,
+};
+
+use super::{
+    shape::Producer,
+    slice::{SliceIndex, SliceIndexModel},
+};
+
+pub struct NpArrayFields<'ctx> {
+    pub data: Field<PointerModel<ByteModel>>,
+    pub itemsize: Field<IntModel<'ctx>>,
+    pub ndims: Field<IntModel<'ctx>>,
+    pub shape: Field<PointerModel<IntModel<'ctx>>>,
+    pub strides: Field<PointerModel<IntModel<'ctx>>>,
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct NpArray<'ctx> {
+    pub sizet: IntModel<'ctx>,
+}
+
+impl<'ctx> IsStruct<'ctx> for NpArray<'ctx> {
+    type Fields = NpArrayFields<'ctx>;
+
+    fn struct_name(&self) -> &'static str {
+        "NDArray"
+    }
+
+    fn build_fields(&self, builder: &mut FieldBuilder<'ctx>) -> Self::Fields {
+        NpArrayFields {
+            data: builder.add_field_auto("data"),
+            itemsize: builder.add_field("itemsize", self.sizet),
+            ndims: builder.add_field("ndims", self.sizet),
+            shape: builder.add_field("shape", PointerModel(self.sizet)),
+            strides: builder.add_field("strides", PointerModel(self.sizet)),
+        }
+    }
+}
+
+impl<'ctx> Pointer<'ctx, StructModel<NpArray<'ctx>>> {
+    pub fn shape_slice(&self, ctx: &CodeGenContext<'ctx, '_>) -> ArraySlice<'ctx, IntModel<'ctx>> {
+        let ndims = self.gep(ctx, |f| f.ndims).load(ctx, "ndims");
+        let shape_base_ptr = self.gep(ctx, |f| f.shape).load(ctx, "shape");
+        ArraySlice { num_elements: ndims, pointer: shape_base_ptr }
+    }
+
+    pub fn strides_slice(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+    ) -> ArraySlice<'ctx, IntModel<'ctx>> {
+        let ndims = self.gep(ctx, |f| f.ndims).load(ctx, "ndims");
+        let strides_base_ptr = self.gep(ctx, |f| f.strides).load(ctx, "strides");
+        ArraySlice { num_elements: ndims, pointer: strides_base_ptr }
+    }
+}
+
+pub fn alloca_ndarray<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    elem_type: BasicTypeEnum<'ctx>,
+    ndims: Int<'ctx>,
+    name: &str,
+) -> Result<Pointer<'ctx, StructModel<NpArray<'ctx>>>, String>
+where
+    G: CodeGenerator + ?Sized,
+{
+    let sizet = IntModel(generator.get_size_type(ctx.ctx));
+
+    // Allocate ndarray
+    let ndarray_ptr = StructModel(NpArray { sizet }).alloca(ctx, name);
+
+    // Set ndims
+    ndarray_ptr.gep(ctx, |f| f.ndims).store(ctx, ndims);
+
+    // Set itemsize
+    let itemsize = Int(elem_type.size_of().unwrap());
+    ndarray_ptr.gep(ctx, |f| f.itemsize).store(ctx, itemsize.signed_cast_to_int(ctx, sizet, ""));
+
+    // Allocate and set shape
+    let shape_array = sizet.array_alloca(ctx, ndims, "shape");
+    ndarray_ptr.gep(ctx, |f| f.shape).store(ctx, shape_array.pointer);
+
+    // Allocate and set strides
+    let strides_array = sizet.array_alloca(ctx, ndims, "strides");
+    ndarray_ptr.gep(ctx, |f| f.strides).store(ctx, strides_array.pointer);
+
+    Ok(ndarray_ptr)
+}
+
+pub enum NDArrayInitMode<'ctx, G: CodeGenerator + ?Sized> {
+    NDims { ndims: Int<'ctx> },
+    Shape { shape: Producer<'ctx, G, IntModel<'ctx>> },
+    ShapeAndAllocaData { shape: Producer<'ctx, G, IntModel<'ctx>> },
+}
+
+/// TODO: DOCUMENT ME
+pub fn alloca_ndarray_and_init<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    elem_type: BasicTypeEnum<'ctx>,
+    init_mode: NDArrayInitMode<'ctx, G>,
+    name: &str,
+) -> Result<Pointer<'ctx, StructModel<NpArray<'ctx>>>, String>
+where
+    G: CodeGenerator + ?Sized,
+{
+    // It is implemented verbosely in order to make the initialization modes super clear in their intent.
+    match init_mode {
+        NDArrayInitMode::NDims { ndims } => {
+            let ndarray_ptr = alloca_ndarray(generator, ctx, elem_type, ndims, name)?;
+            Ok(ndarray_ptr)
+        }
+        NDArrayInitMode::Shape { shape } => {
+            let ndims = shape.count;
+            let ndarray_ptr = alloca_ndarray(generator, ctx, elem_type, ndims, name)?;
+
+            // Fill `ndarray.shape`
+            (shape.write_to_array)(generator, ctx, &ndarray_ptr.shape_slice(ctx))?;
+
+            // Check if `shape` has bad inputs
+            call_nac3_ndarray_util_assert_shape_no_negative(
+                generator,
+                ctx,
+                ndims,
+                ndarray_ptr.gep(ctx, |f| f.shape).load(ctx, "shape"),
+            );
+
+            // NOTE: DO NOT DO `set_strides_by_shape` HERE.
+            // Simply this is because we specified that `SetShape` wouldn't do `set_strides_by_shape`
+
+            Ok(ndarray_ptr)
+        }
+        NDArrayInitMode::ShapeAndAllocaData { shape } => {
+            let ndims = shape.count;
+            let ndarray_ptr = alloca_ndarray(generator, ctx, elem_type, ndims, name)?;
+
+            // Fill `ndarray.shape`
+            (shape.write_to_array)(generator, ctx, &ndarray_ptr.shape_slice(ctx))?;
+
+            // Check if `shape` has bad inputs
+            call_nac3_ndarray_util_assert_shape_no_negative(
+                generator,
+                ctx,
+                ndims,
+                ndarray_ptr.gep(ctx, |f| f.shape).load(ctx, "shape"),
+            );
+
+            // Now we populate `ndarray.data` by alloca-ing.
+            // But first, we need to know the size of the ndarray to know how many elements to alloca,
+            // since calculating nbytes of an ndarray requires `ndarray.shape` to be set.
+            let ndarray_nbytes = call_nac3_ndarray_nbytes(ctx, ndarray_ptr);
+
+            // Alloca `data` and assign it to `ndarray.data`
+            let data_array = FixedIntModel(Byte).array_alloca(ctx, ndarray_nbytes, "data");
+            ndarray_ptr.gep(ctx, |f| f.data).store(ctx, data_array.pointer);
+
+            // Finally, do `set_strides_by_shape`
+            // Check out https://ajcr.net/stride-guide-part-1/ to see what numpy "strides" are.
+            call_nac3_ndarray_set_strides_by_shape(ctx, ndarray_ptr);
+
+            Ok(ndarray_ptr)
+        }
+    }
+}
+
+fn call_nac3_ndarray_util_assert_shape_no_negative<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndims: Int<'ctx>,
+    shape_ptr: Pointer<'ctx, IntModel<'ctx>>,
+) {
+    let sizet = IntModel(generator.get_size_type(ctx.ctx));
+
+    let errctx = prepare_error_context(ctx);
+    FunctionBuilder::begin(
+        ctx,
+        &get_sized_dependent_function_name(sizet, "__nac3_ndarray_util_assert_shape_no_negative"),
+    )
+    .arg("errctx", PointerModel(StructModel(ErrorContext)), errctx)
+    .arg("ndims", sizet, ndims)
+    .arg("shape", PointerModel(sizet), shape_ptr)
+    .returning_void();
+    check_error_context(generator, ctx, errctx);
+}
+
+fn call_nac3_ndarray_set_strides_by_shape<'ctx>(
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray_ptr: Pointer<'ctx, StructModel<NpArray<'ctx>>>,
+) {
+    let sizet = ndarray_ptr.element.0.sizet;
+
+    FunctionBuilder::begin(
+        ctx,
+        &get_sized_dependent_function_name(sizet, "__nac3_ndarray_set_strides_by_shape"),
+    )
+    .arg("ndarray", PointerModel(StructModel(NpArray { sizet })), ndarray_ptr)
+    .returning_void();
+}
+
+pub fn call_nac3_ndarray_nbytes<'ctx>(
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray_ptr: Pointer<'ctx, StructModel<NpArray<'ctx>>>,
+) -> Int<'ctx> {
+    let sizet = ndarray_ptr.element.0.sizet;
+
+    FunctionBuilder::begin(ctx, &get_sized_dependent_function_name(sizet, "__nac3_ndarray_nbytes"))
+        .arg("ndarray", PointerModel(StructModel(NpArray { sizet })), ndarray_ptr)
+        .returning("nbytes", sizet)
+}
+
+pub fn call_nac3_ndarray_fill_generic<'ctx>(
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray_ptr: Pointer<'ctx, StructModel<NpArray<'ctx>>>,
+    fill_value_ptr: Pointer<'ctx, ByteModel>,
+) {
+    let sizet = ndarray_ptr.element.0.sizet;
+
+    FunctionBuilder::begin(
+        ctx,
+        &get_sized_dependent_function_name(sizet, "__nac3_ndarray_fill_generic"),
+    )
+    .arg("ndarray", PointerModel(StructModel(NpArray { sizet })), ndarray_ptr)
+    .arg("pvalue", PointerModel(FixedIntModel(Byte)), fill_value_ptr)
+    .returning_void();
+}
+
+pub fn call_nac3_ndarray_len<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray_ptr: Pointer<'ctx, StructModel<NpArray<'ctx>>>,
+) -> SliceIndex<'ctx> {
+    let sizet = ndarray_ptr.element.0.sizet;
+    let slice_index_model = SliceIndexModel::default();
+
+    let dst_len = slice_index_model.alloca(ctx, "dst_len");
+
+    let errctx = prepare_error_context(ctx);
+    FunctionBuilder::begin(ctx, &get_sized_dependent_function_name(sizet, "__nac3_ndarray_len"))
+        .arg("errctx", PointerModel(StructModel(ErrorContext)), errctx)
+        .arg("ndarray", PointerModel(StructModel(NpArray { sizet })), ndarray_ptr)
+        .arg("dst_len", PointerModel(slice_index_model), dst_len)
+        .returning_void();
+    check_error_context(generator, ctx, errctx);
+
+    dst_len.load(ctx, "len")
+}

nac3core/src/codegen/irrt/numpy/shape.rs

@@ -0,0 +1,162 @@
+use inkwell::values::BasicValueEnum;
+
+use crate::{
+    codegen::{
+        classes::{ListValue, UntypedArrayLikeAccessor},
+        model::*,
+        stmt::gen_for_callback_incrementing,
+        CodeGenContext, CodeGenerator,
+    },
+    typecheck::typedef::{Type, TypeEnum},
+};
+
+pub type ProducerWriteToArray<'ctx, G, E> = Box<
+    dyn Fn(&mut G, &mut CodeGenContext<'ctx, '_>, &ArraySlice<'ctx, E>) -> Result<(), String>
+        + 'ctx,
+>;
+
+pub struct Producer<'ctx, G: CodeGenerator + ?Sized, E: Model<'ctx>> {
+    pub count: Int<'ctx>,
+    pub write_to_array: ProducerWriteToArray<'ctx, G, E>,
+}
+
+/// TODO: UPDATE DOCUMENTATION
+/// LLVM-typed implementation for generating a [`Producer`] that sets a list of ints.
+///
+/// * `elem_ty` - The element type of the `NDArray`.
+/// * `shape` - The `shape` parameter used to construct the `NDArray`.
+///
+/// ### Notes on `shape`
+///
+/// Just like numpy, the `shape` argument can be:
+///   1. A list of `int32`;   e.g., `np.empty([600, 800, 3])`
+///   2. A tuple of `int32`;  e.g., `np.empty((600, 800, 3))`
+///   3. A scalar `int32`;     e.g., `np.empty(3)`, this is functionally equivalent to `np.empty([3])`
+///
+/// See also [`typecheck::type_inferencer::fold_numpy_function_call_shape_argument`] to
+/// learn how `shape` gets from being a Python user expression to here.
+pub fn parse_input_shape_arg<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    shape: BasicValueEnum<'ctx>,
+    shape_ty: Type,
+) -> Producer<'ctx, G, IntModel<'ctx>>
+where
+    G: CodeGenerator + ?Sized,
+{
+    let sizet = IntModel(generator.get_size_type(ctx.ctx));
+
+    match &*ctx.unifier.get_ty(shape_ty) {
+        TypeEnum::TObj { obj_id, .. }
+            if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
+        {
+            // 1. A list of ints; e.g., `np.empty([600, 800, 3])`
+
+            // A list has to be a PointerValue
+            let shape_list = ListValue::from_ptr_val(shape.into_pointer_value(), sizet.0, None);
+
+            // Create `Producer`
+            let ndims = Int(shape_list.load_size(ctx, Some("count")));
+            Producer {
+                count: ndims,
+                write_to_array: Box::new(move |ctx, generator, dst_array| {
+                    // Basically iterate through the list and write to `dst_slice` accordingly
+                    let init_val = sizet.constant(0).0;
+                    let max_val = (ndims.0, false);
+                    let incr_val = sizet.constant(1).0;
+                    gen_for_callback_incrementing(
+                        ctx,
+                        generator,
+                        init_val,
+                        max_val,
+                        |generator, ctx, _hooks, axis| {
+                            let axis = Int(axis);
+
+                            // Get the dimension at `axis`
+                            let dim = shape_list
+                                .data()
+                                .get(ctx, generator, &axis.0, None)
+                                .into_int_value();
+
+                            // Cast `dim` to SizeT
+                            let dim = ctx
+                                .builder
+                                .build_int_s_extend_or_bit_cast(dim, sizet.0, "dim_casted")
+                                .unwrap();
+
+                            // Write
+                            dst_array.ix(generator, ctx, axis, "dim").store(ctx, Int(dim));
+                            Ok(())
+                        },
+                        incr_val,
+                    )
+                }),
+            }
+        }
+        TypeEnum::TTuple { ty: tuple_types } => {
+            // 2. A tuple of ints; e.g., `np.empty((600, 800, 3))`
+
+            // Get the length/size of the tuple, which also happens to be the value of `ndims`.
+            let ndims = tuple_types.len();
+
+            // A tuple has to be a StructValue
+            // Read [`codegen::expr::gen_expr`] to see how `nac3core` translates a Python tuple into LLVM.
+            let shape_tuple = shape.into_struct_value();
+
+            Producer {
+                count: sizet.constant(ndims as u64),
+                write_to_array: Box::new(move |generator, ctx, dst_array| {
+                    for axis in 0..ndims {
+                        // Get the dimension at `axis`
+                        let dim = ctx
+                            .builder
+                            .build_extract_value(
+                                shape_tuple,
+                                axis as u32,
+                                format!("dim{axis}").as_str(),
+                            )
+                            .unwrap()
+                            .into_int_value();
+
+                        // Cast `dim` to SizeT
+                        let dim = ctx
+                            .builder
+                            .build_int_s_extend_or_bit_cast(dim, sizet.0, "dim_casted")
+                            .unwrap();
+
+                        // Write
+                        dst_array
+                            .ix(generator, ctx, sizet.constant(axis as u64), "dim")
+                            .store(ctx, Int(dim));
+                    }
+                    Ok(())
+                }),
+            }
+        }
+        TypeEnum::TObj { obj_id, .. }
+            if *obj_id == ctx.primitives.int32.obj_id(&ctx.unifier).unwrap() =>
+        {
+            // 3. A scalar int; e.g., `np.empty(3)`, this is functionally equivalent to `np.empty([3])`
+
+            // The value has to be an integer
+            let shape_int = shape.into_int_value();
+
+            Producer {
+                count: sizet.constant(1),
+                write_to_array: Box::new(move |generator, ctx, dst_array| {
+                    // Cast `shape_int` to SizeT
+                    let dim = ctx
+                        .builder
+                        .build_int_s_extend_or_bit_cast(shape_int, sizet.0, "dim_casted")
+                        .unwrap();
+
+                    // Set shape[0] = shape_int
+                    dst_array.ix(generator, ctx, sizet.constant(0), "dim").store(ctx, Int(dim));
+
+                    Ok(())
+                }),
+            }
+        }
+        _ => panic!("parse_input_shape_arg encountered unknown type"),
+    }
+}

nac3core/src/codegen/irrt/numpy/slice.rs

@@ -0,0 +1,86 @@
+use crate::codegen::{model::*, CodeGenContext};
+
+// nac3core's slicing index/length values are always int32_t
+pub type SliceIndexInt = Int32;
+pub type SliceIndexModel = FixedIntModel<SliceIndexInt>;
+pub type SliceIndex<'ctx> = FixedInt<'ctx, SliceIndexInt>;
+
+#[derive(Debug, Clone)]
+pub struct UserSliceFields {
+    pub start_defined: Field<BoolModel>,
+    pub start: Field<SliceIndexModel>,
+    pub stop_defined: Field<BoolModel>,
+    pub stop: Field<SliceIndexModel>,
+    pub step_defined: Field<BoolModel>,
+    pub step: Field<SliceIndexModel>,
+}
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct UserSlice;
+
+impl<'ctx> IsStruct<'ctx> for UserSlice {
+    type Fields = UserSliceFields;
+
+    fn struct_name(&self) -> &'static str {
+        "UserSlice"
+    }
+
+    fn build_fields(&self, builder: &mut FieldBuilder<'ctx>) -> Self::Fields {
+        Self::Fields {
+            start_defined: builder.add_field_auto("start_defined"),
+            start: builder.add_field_auto("start"),
+            stop_defined: builder.add_field_auto("stop_defined"),
+            stop: builder.add_field_auto("stop"),
+            step_defined: builder.add_field_auto("step_defined"),
+            step: builder.add_field_auto("step"),
+        }
+    }
+}
+
+#[derive(Debug, Clone)]
+pub struct RustUserSlice<'ctx> {
+    pub start: Option<SliceIndex<'ctx>>,
+    pub stop: Option<SliceIndex<'ctx>>,
+    pub step: Option<SliceIndex<'ctx>>,
+}
+
+impl<'ctx> RustUserSlice<'ctx> {
+    // Set the values of an LLVM UserSlice
+    // in the format of Python's `slice()`
+    pub fn write_to_user_slice(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        dst_slice_ptr: Pointer<'ctx, StructModel<UserSlice>>,
+    ) {
+        // TODO: make this neater, with a helper lambda?
+
+        let bool_model = BoolModel::default();
+
+        let false_ = bool_model.constant(ctx.ctx, 0);
+        let true_ = bool_model.constant(ctx.ctx, 1);
+
+        match self.start {
+            Some(start) => {
+                dst_slice_ptr.gep(ctx, |f| f.start_defined).store(ctx, true_);
+                dst_slice_ptr.gep(ctx, |f| f.start).store(ctx, start);
+            }
+            None => dst_slice_ptr.gep(ctx, |f| f.start_defined).store(ctx, false_),
+        }
+
+        match self.stop {
+            Some(stop) => {
+                dst_slice_ptr.gep(ctx, |f| f.stop_defined).store(ctx, true_);
+                dst_slice_ptr.gep(ctx, |f| f.stop).store(ctx, stop);
+            }
+            None => dst_slice_ptr.gep(ctx, |f| f.stop_defined).store(ctx, false_),
+        }
+
+        match self.step {
+            Some(step) => {
+                dst_slice_ptr.gep(ctx, |f| f.step_defined).store(ctx, true_);
+                dst_slice_ptr.gep(ctx, |f| f.step).store(ctx, step);
+            }
+            None => dst_slice_ptr.gep(ctx, |f| f.step_defined).store(ctx, false_),
+        }
+    }
+}

nac3core/src/codegen/irrt/numpy/subscript.rs

@@ -0,0 +1,181 @@
+use crate::codegen::{
+    irrt::{
+        error_context::{check_error_context, prepare_error_context, ErrorContext},
+        util::{get_sized_dependent_function_name, FunctionBuilder},
+    },
+    model::*,
+    CodeGenContext, CodeGenerator,
+};
+
+use super::{
+    ndarray::NpArray,
+    slice::{RustUserSlice, SliceIndex, SliceIndexModel, UserSlice},
+};
+
+#[derive(Debug, Clone, Copy)]
+pub struct NDSubscriptFields {
+    pub type_: Field<ByteModel>, // Defined to be uint8_t in IRRT
+    pub data: Field<PointerModel<ByteModel>>,
+}
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct NDSubscript;
+
+impl<'ctx> IsStruct<'ctx> for NDSubscript {
+    type Fields = NDSubscriptFields;
+
+    fn struct_name(&self) -> &'static str {
+        "NDSubscript"
+    }
+
+    fn build_fields(&self, builder: &mut FieldBuilder<'ctx>) -> Self::Fields {
+        Self::Fields { type_: builder.add_field_auto("type"), data: builder.add_field_auto("data") }
+    }
+}
+
+// An enum variant to store the content
+// and type of an NDSubscript in high level.
+#[derive(Debug, Clone)]
+pub enum RustNDSubscript<'ctx> {
+    Index(SliceIndex<'ctx>),
+    Slice(RustUserSlice<'ctx>),
+}
+
+impl<'ctx> RustNDSubscript<'ctx> {
+    fn irrt_subscript_id(&self) -> u64 {
+        // Defined in IRRT
+        match self {
+            RustNDSubscript::Index(_) => 0,
+            RustNDSubscript::Slice(_) => 1,
+        }
+    }
+
+    fn write_to_ndsubscript(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        dst_ndsubscript_ptr: Pointer<'ctx, StructModel<NDSubscript>>,
+    ) {
+        let byte_model = ByteModel::default();
+        let slice_index_model = SliceIndexModel::default();
+        let user_slice_model = StructModel(UserSlice);
+
+        // Set `dst_ndsubscript_ptr->type`
+        dst_ndsubscript_ptr
+            .gep(ctx, |f| f.type_)
+            .store(ctx, byte_model.constant(ctx.ctx, self.irrt_subscript_id()));
+
+        // Set `dst_ndsubscript_ptr->data`
+        let data = match self {
+            RustNDSubscript::Index(in_index) => {
+                let index_ptr = slice_index_model.alloca(ctx, "index");
+                index_ptr.store(ctx, *in_index);
+                index_ptr.cast_to(ctx, FixedIntModel(Byte), "")
+            }
+            RustNDSubscript::Slice(in_rust_slice) => {
+                let user_slice_ptr = user_slice_model.alloca(ctx, "user_slice");
+                in_rust_slice.write_to_user_slice(ctx, user_slice_ptr);
+                user_slice_ptr.cast_to(ctx, FixedIntModel(Byte), "")
+            }
+        };
+        dst_ndsubscript_ptr.gep(ctx, |f| f.data).store(ctx, data);
+    }
+
+    // Allocate an array of subscripts onto the stack and return its stack pointer
+    pub fn alloca_subscripts(
+        ctx: &CodeGenContext<'ctx, '_>,
+        subscripts: &[RustNDSubscript<'ctx>],
+    ) -> ArraySlice<'ctx, StructModel<NDSubscript>> {
+        let index_model = Int32Model::default();
+
+        let ndsubscript_model = StructModel(NDSubscript);
+        let ndsubscript_array = ndsubscript_model.array_alloca(
+            ctx,
+            index_model.constant(ctx.ctx, subscripts.len() as u64).to_int(),
+            "ndsubscripts",
+        );
+
+        for (i, rust_ndsubscript) in subscripts.iter().enumerate() {
+            let ndsubscript_ptr = ndsubscript_array.ix_unchecked(
+                ctx,
+                index_model.constant(ctx.ctx, i as u64).to_int(),
+                "",
+            );
+            rust_ndsubscript.write_to_ndsubscript(ctx, ndsubscript_ptr);
+        }
+
+        ndsubscript_array
+    }
+
+    #[must_use]
+    pub fn deduce_ndims_after_slicing(slices: &[RustNDSubscript], original_ndims: i32) -> i32 {
+        let mut final_ndims: i32 = original_ndims;
+        for slice in slices {
+            match slice {
+                RustNDSubscript::Index(_) => {
+                    // Index subscripts demotes the rank by 1
+                    final_ndims -= 1;
+                }
+                RustNDSubscript::Slice(_) => {
+                    // Nothing
+                }
+            }
+        }
+        final_ndims
+    }
+}
+
+pub fn call_nac3_ndarray_subscript_deduce_ndims_after_slicing<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    sizet: IntModel<'ctx>,
+    ndims: Int<'ctx>,
+    num_ndsubscripts: Int<'ctx>,
+    ndsubscripts: Pointer<'ctx, StructModel<NDSubscript>>,
+) -> Int<'ctx> {
+    let result = sizet.alloca(ctx, "result");
+
+    let errctx_ptr = prepare_error_context(ctx);
+    FunctionBuilder::begin(
+        ctx,
+        &get_sized_dependent_function_name(
+            sizet,
+            "__nac3_ndarray_subscript_deduce_ndims_after_slicing",
+        ),
+    )
+    .arg("errctx", PointerModel(StructModel(ErrorContext)), errctx_ptr)
+    .arg("result", PointerModel(sizet), result)
+    .arg("ndims", sizet, ndims)
+    .arg("num_ndsubscripts", sizet, num_ndsubscripts)
+    .arg("ndsubscripts", PointerModel(StructModel(NDSubscript)), ndsubscripts)
+    .returning_void();
+    check_error_context(generator, ctx, errctx_ptr);
+
+    result.load(ctx, "final_ndims")
+}
+
+pub fn call_nac3_ndarray_subscript<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    num_subscripts: SliceIndex<'ctx>,
+    subscripts: Pointer<'ctx, StructModel<NDSubscript>>,
+    src_ndarray: Pointer<'ctx, StructModel<NpArray<'ctx>>>,
+    dst_ndarray: Pointer<'ctx, StructModel<NpArray<'ctx>>>,
+) {
+    let sizet = src_ndarray.element.0.sizet;
+    assert!(sizet.same_as(dst_ndarray.element.0.sizet)); // SizeT of src_ndarray and dst_ndarray must match
+
+    let errctx_ptr = prepare_error_context(ctx);
+
+    FunctionBuilder::begin(
+        ctx,
+        &get_sized_dependent_function_name(sizet, "__nac3_ndarray_subscript"),
+    )
+    .arg("errctx", PointerModel(StructModel(ErrorContext)), errctx_ptr)
+    .arg("num_subscripts", SliceIndexModel::default(), num_subscripts)
+    .arg("subscripts", PointerModel(StructModel(NDSubscript)), subscripts)
+    .arg("src_ndarray", PointerModel(StructModel(NpArray { sizet })), src_ndarray)
+    .arg("dst_ndarray", PointerModel(StructModel(NpArray { sizet })), dst_ndarray)
+    .returning_void();
+
+    check_error_context(generator, ctx, errctx_ptr);
+}

nac3core/src/codegen/irrt/test.rs

@@ -0,0 +1,26 @@
+#[cfg(test)]
+mod tests {
+    use std::{path::Path, process::Command};
+
+    #[test]
+    fn run_irrt_test() {
+        assert!(
+            cfg!(feature = "test"),
+            "Please do `cargo test -F test` to compile `irrt_test.out` and run test"
+        );
+
+        let irrt_test_out_path = Path::new(concat!(env!("OUT_DIR"), "/irrt_test.out"));
+        let output = Command::new(irrt_test_out_path.to_str().unwrap()).output().unwrap();
+
+        if !output.status.success() {
+            eprintln!("irrt_test failed with status {}:", output.status);
+            eprintln!("====== stdout ======");
+            eprintln!("{}", String::from_utf8(output.stdout).unwrap());
+            eprintln!("====== stderr ======");
+            eprintln!("{}", String::from_utf8(output.stderr).unwrap());
+            eprintln!("====================");
+
+            panic!("irrt_test failed");
+        }
+    }
+}

nac3core/src/codegen/irrt/util.rs

@@ -0,0 +1,79 @@
+use inkwell::{
+    types::{BasicMetadataTypeEnum, BasicType, IntType},
+    values::{AnyValue, BasicMetadataValueEnum},
+};
+
+use crate::{
+    codegen::{model::*, CodeGenContext},
+    util::SizeVariant,
+};
+
+fn get_size_variant(ty: IntType) -> SizeVariant {
+    match ty.get_bit_width() {
+        32 => SizeVariant::Bits32,
+        64 => SizeVariant::Bits64,
+        _ => unreachable!("Unsupported int type bit width {}", ty.get_bit_width()),
+    }
+}
+
+#[must_use]
+pub fn get_sized_dependent_function_name(ty: IntModel, fn_name: &str) -> String {
+    let mut fn_name = fn_name.to_owned();
+    match get_size_variant(ty.0) {
+        SizeVariant::Bits32 => {
+            // Do nothing, `fn_name` already has the correct name
+        }
+        SizeVariant::Bits64 => {
+            // Append "64", this is the naming convention
+            fn_name.push_str("64");
+        }
+    }
+    fn_name
+}
+
+// TODO: Variadic argument?
+pub struct FunctionBuilder<'ctx, 'a> {
+    ctx: &'a CodeGenContext<'ctx, 'a>,
+    fn_name: &'a str,
+    arguments: Vec<(BasicMetadataTypeEnum<'ctx>, BasicMetadataValueEnum<'ctx>)>,
+}
+
+impl<'ctx, 'a> FunctionBuilder<'ctx, 'a> {
+    pub fn begin(ctx: &'a CodeGenContext<'ctx, 'a>, fn_name: &'a str) -> Self {
+        FunctionBuilder { ctx, fn_name, arguments: Vec::new() }
+    }
+
+    // The name is for self-documentation
+    #[must_use]
+    pub fn arg<M: Model<'ctx>>(mut self, _name: &'static str, model: M, value: M::Value) -> Self {
+        self.arguments
+            .push((model.get_llvm_type(self.ctx.ctx).into(), value.get_llvm_value().into()));
+        self
+    }
+
+    pub fn returning<M: Model<'ctx>>(self, name: &'static str, return_model: M) -> M::Value {
+        let (param_tys, param_vals): (Vec<_>, Vec<_>) = self.arguments.into_iter().unzip();
+
+        let function = self.ctx.module.get_function(self.fn_name).unwrap_or_else(|| {
+            let return_type = return_model.get_llvm_type(self.ctx.ctx);
+            let fn_type = return_type.fn_type(&param_tys, false);
+            self.ctx.module.add_function(self.fn_name, fn_type, None)
+        });
+
+        let ret = self.ctx.builder.build_call(function, &param_vals, name).unwrap();
+        return_model.review(self.ctx.ctx, ret.as_any_value_enum())
+    }
+
+    // TODO: Code duplication, but otherwise returning<S: Optic<'ctx>> cannot resolve S if return_optic = None
+    pub fn returning_void(self) {
+        let (param_tys, param_vals): (Vec<_>, Vec<_>) = self.arguments.into_iter().unzip();
+
+        let function = self.ctx.module.get_function(self.fn_name).unwrap_or_else(|| {
+            let return_type = self.ctx.ctx.void_type();
+            let fn_type = return_type.fn_type(&param_tys, false);
+            self.ctx.module.add_function(self.fn_name, fn_type, None)
+        });
+
+        self.ctx.builder.build_call(function, &param_vals, "").unwrap();
+    }
+}

nac3core/src/codegen/llvm_intrinsics.rs

@@ -35,6 +35,54 @@ fn get_float_intrinsic_repr(ctx: &Context, ft: FloatType) -> &'static str {
     unreachable!()
 }
 
+/// Invokes the [`llvm.lifetime.start`](https://releases.llvm.org/14.0.0/docs/LangRef.html#llvm-lifetime-start-intrinsic)
+/// intrinsic.
+pub fn call_lifetime_start<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+    size: IntValue<'ctx>,
+    ptr: PointerValue<'ctx>,
+) {
+    const FN_NAME: &str = "llvm.lifetime.start";
+    // NOTE: inkwell temporary workaround, see [`call_stackrestore`] for details
+    let intrinsic_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
+        let llvm_void = ctx.ctx.void_type();
+        let llvm_i64 = ctx.ctx.i64_type();
+        let llvm_p0i8 = ctx.ctx.i8_type().ptr_type(AddressSpace::default());
+        let fn_type = llvm_void.fn_type(&[llvm_i64.into(), llvm_p0i8.into()], false);
+
+        ctx.module.add_function(FN_NAME, fn_type, None)
+    });
+
+    ctx.builder
+        .build_call(intrinsic_fn, &[size.into(), ptr.into()], "")
+        .map(CallSiteValue::try_as_basic_value)
+        .unwrap();
+}
+
+/// Invokes the [`llvm.lifetime.end`](https://releases.llvm.org/14.0.0/docs/LangRef.html#llvm-lifetime-end-intrinsic)
+/// intrinsic.
+pub fn call_lifetime_end<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+    size: IntValue<'ctx>,
+    ptr: PointerValue<'ctx>,
+) {
+    const FN_NAME: &str = "llvm.lifetime.end";
+    // NOTE: inkwell temporary workaround, see [`call_stackrestore`] for details
+    let intrinsic_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
+        let llvm_void = ctx.ctx.void_type();
+        let llvm_i64 = ctx.ctx.i64_type();
+        let llvm_p0i8 = ctx.ctx.i8_type().ptr_type(AddressSpace::default());
+        let fn_type = llvm_void.fn_type(&[llvm_i64.into(), llvm_p0i8.into()], false);
+
+        ctx.module.add_function(FN_NAME, fn_type, None)
+    });
+
+    ctx.builder
+        .build_call(intrinsic_fn, &[size.into(), ptr.into()], "")
+        .map(CallSiteValue::try_as_basic_value)
+        .unwrap();
+}
+
 /// Invokes the [`llvm.stacksave`](https://llvm.org/docs/LangRef.html#llvm-stacksave-intrinsic)
 /// intrinsic.
 pub fn call_stacksave<'ctx>(

nac3core/src/codegen/mod.rs

@@ -1,7 +1,7 @@
 use crate::{
-    codegen::classes::{ListType, NDArrayType, ProxyType, RangeType},
+    codegen::classes::{ListType, ProxyType, RangeType},
     symbol_resolver::{StaticValue, SymbolResolver},
-    toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, TopLevelContext, TopLevelDef},
+    toplevel::{helper::PrimDef, TopLevelContext, TopLevelDef},
     typecheck::{
         type_inferencer::{CodeLocation, PrimitiveStore},
         typedef::{CallId, FuncArg, Type, TypeEnum, Unifier},
@@ -23,7 +23,9 @@ use inkwell::{
     values::{BasicValueEnum, FunctionValue, IntValue, PhiValue, PointerValue},
     AddressSpace, IntPredicate, OptimizationLevel,
 };
+use irrt::{error_context::Str, numpy::ndarray::NpArray};
 use itertools::Itertools;
+use model::*;
 use nac3parser::ast::{Location, Stmt, StrRef};
 use parking_lot::{Condvar, Mutex};
 use std::collections::{HashMap, HashSet};
@@ -41,7 +43,9 @@ pub mod extern_fns;
 mod generator;
 pub mod irrt;
 pub mod llvm_intrinsics;
+pub mod model;
 pub mod numpy;
+pub mod numpy_new;
 pub mod stmt;
 
 #[cfg(test)]
@@ -471,12 +475,8 @@ 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 element_type = get_llvm_type(
-                                ctx, module, generator, unifier, top_level, type_cache, dtype,
-                            );
-
-                            NDArrayType::new(generator, ctx, element_type).as_base_type().into()
+                            let sizet = IntModel(generator.get_size_type(ctx));
+                            PointerModel(StructModel(NpArray { sizet })).get_llvm_type(ctx)
                         }
 
                         _ => unreachable!(
@@ -646,7 +646,7 @@ pub fn gen_func_impl<
         ..primitives
     };
 
-    let mut type_cache: HashMap<_, _> = [
+    let mut type_cache: HashMap<_, BasicTypeEnum<'_>> = [
         (primitives.int32, context.i32_type().into()),
         (primitives.int64, context.i64_type().into()),
         (primitives.uint32, context.i32_type().into()),
@@ -654,19 +654,8 @@ pub fn gen_func_impl<
         (primitives.float, context.f64_type().into()),
         (primitives.bool, context.i8_type().into()),
         (primitives.str, {
-            let name = "str";
-            match module.get_struct_type(name) {
-                None => {
-                    let str_type = context.opaque_struct_type("str");
-                    let fields = [
-                        context.i8_type().ptr_type(AddressSpace::default()).into(),
-                        generator.get_size_type(context).into(),
-                    ];
-                    str_type.set_body(&fields, false);
-                    str_type.into()
-                }
-                Some(t) => t.as_basic_type_enum(),
-            }
+            let sizet = IntModel(generator.get_size_type(context));
+            StructModel(Str { sizet }).get_llvm_type(context)
         }),
         (primitives.range, RangeType::new(context).as_base_type().into()),
         (primitives.exception, {
@@ -674,10 +663,12 @@ pub fn gen_func_impl<
             if let Some(t) = module.get_struct_type(name) {
                 t.ptr_type(AddressSpace::default()).as_basic_type_enum()
             } else {
+                let sizet = IntModel(generator.get_size_type(context));
+                let str_ty = StructModel(Str { sizet }).get_llvm_type(context);
+
                 let exception = context.opaque_struct_type("Exception");
                 let int32 = context.i32_type().into();
                 let int64 = context.i64_type().into();
-                let str_ty = module.get_struct_type("str").unwrap().as_basic_type_enum();
                 let fields = [int32, str_ty, int32, int32, str_ty, str_ty, int64, int64, int64];
                 exception.set_body(&fields, false);
                 exception.ptr_type(AddressSpace::default()).as_basic_type_enum()

nac3core/src/codegen/model/core.rs

@@ -0,0 +1,70 @@
+use inkwell::{
+    context::Context,
+    types::{AnyTypeEnum, BasicTypeEnum},
+    values::{AnyValueEnum, BasicValueEnum},
+};
+
+use crate::codegen::CodeGenContext;
+
+use super::{slice::ArraySlice, Int, Pointer};
+
+pub trait ModelValue<'ctx>: Clone + Copy {
+    fn get_llvm_value(&self) -> BasicValueEnum<'ctx>;
+}
+
+// Should have been within [`Model<'ctx>`],
+// but rust object safety requirements made it necessary to
+// split this interface out
+pub trait CanCheckLLVMType<'ctx> {
+    /// Check if `scrutinee` matches the same LLVM type of this [`Model<'ctx>`].
+    ///
+    /// If they don't not match, a human-readable error message is returned.
+    fn check_llvm_type(
+        &self,
+        ctx: &'ctx Context,
+        scrutinee: AnyTypeEnum<'ctx>,
+    ) -> Result<(), String>;
+}
+
+/// A [`Model`] is a type-safe concrete representation of a complex LLVM type.
+pub trait Model<'ctx>: Clone + Copy + CanCheckLLVMType<'ctx> + Sized {
+    /// The values that inhabit this [`Model<'ctx>`].
+    ///
+    /// ...that is the type of wrapper that wraps the LLVM values that inhabit [`Model<'ctx>::get_llvm_type()`].
+    type Value: ModelValue<'ctx>;
+
+    /// Get the [`BasicTypeEnum<'ctx>`] this [`Model<'ctx>`] is representing.
+    fn get_llvm_type(&self, ctx: &'ctx Context) -> BasicTypeEnum<'ctx>;
+
+    /// Cast an [`AnyValueEnum<'ctx>`] into a [`Self::Value`].
+    ///
+    /// Panics if `value` cannot pass [`CanCheckLLVMType::check_llvm_type()`].
+    fn review(&self, ctx: &'ctx Context, value: AnyValueEnum<'ctx>) -> Self::Value;
+
+    /// Build an instruction to allocate a value of [`Model::get_llvm_type`].
+    fn alloca(&self, ctx: &CodeGenContext<'ctx, '_>, name: &str) -> Pointer<'ctx, Self> {
+        Pointer {
+            element: *self,
+            value: ctx.builder.build_alloca(self.get_llvm_type(ctx.ctx), name).unwrap(),
+        }
+    }
+
+    /// Build an instruction to allocate an array of [`Model::get_llvm_type`].
+    fn array_alloca(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        count: Int<'ctx>,
+        name: &str,
+    ) -> ArraySlice<'ctx, Self> {
+        ArraySlice {
+            num_elements: count,
+            pointer: Pointer {
+                element: *self,
+                value: ctx
+                    .builder
+                    .build_array_alloca(self.get_llvm_type(ctx.ctx), count.0, name)
+                    .unwrap(),
+            },
+        }
+    }
+}

nac3core/src/codegen/model/gep.rs

@@ -0,0 +1,220 @@
+use inkwell::{
+    context::Context,
+    types::{AnyType, AnyTypeEnum, BasicType, BasicTypeEnum, StructType},
+    values::{AnyValueEnum, BasicValue, BasicValueEnum, StructValue},
+};
+use itertools::{izip, Itertools};
+
+use crate::codegen::CodeGenContext;
+
+use super::{core::CanCheckLLVMType, Model, ModelValue, Pointer};
+
+#[derive(Debug, Clone, Copy)]
+pub struct Field<E> {
+    pub gep_index: u64,
+    pub name: &'static str,
+    pub element: E,
+}
+
+// Like [`Field<E>`] but element must be [`BasicTypeEnum<'ctx>`]
+struct FieldLLVM<'ctx> {
+    gep_index: u64,
+    name: &'ctx str,
+    llvm_type: BasicTypeEnum<'ctx>,
+
+    // Only CanCheckLLVMType is needed, dont put in the whole `Model<'ctx>`
+    llvm_type_model: Box<dyn CanCheckLLVMType<'ctx> + 'ctx>,
+}
+
+pub struct FieldBuilder<'ctx> {
+    pub ctx: &'ctx Context,
+    gep_index_counter: u64,
+    struct_name: &'ctx str,
+    fields: Vec<FieldLLVM<'ctx>>,
+}
+
+impl<'ctx> FieldBuilder<'ctx> {
+    #[must_use]
+    pub fn new(ctx: &'ctx Context, struct_name: &'ctx str) -> Self {
+        FieldBuilder { ctx, gep_index_counter: 0, struct_name, fields: Vec::new() }
+    }
+
+    fn next_gep_index(&mut self) -> u64 {
+        let index = self.gep_index_counter;
+        self.gep_index_counter += 1;
+        index
+    }
+
+    pub fn add_field<E: Model<'ctx> + 'ctx>(&mut self, name: &'static str, element: E) -> Field<E> {
+        let gep_index = self.next_gep_index();
+
+        self.fields.push(FieldLLVM {
+            gep_index,
+            name,
+            llvm_type: element.get_llvm_type(self.ctx),
+            llvm_type_model: Box::new(element),
+        });
+
+        Field { gep_index, name, element }
+    }
+
+    pub fn add_field_auto<E: Model<'ctx> + Default + 'ctx>(
+        &mut self,
+        name: &'static str,
+    ) -> Field<E> {
+        self.add_field(name, E::default())
+    }
+}
+
+/// A marker trait to mark singleton struct that describes a particular LLVM structure.
+pub trait IsStruct<'ctx>: Clone + Copy {
+    /// The type of the Rust `struct` that holds all the fields of this LLVM struct.
+    type Fields;
+
+    /// A cosmetic name for this struct.
+    /// TODO: Currently unused. To be used in error reporting.
+    fn struct_name(&self) -> &'static str;
+
+    fn build_fields(&self, builder: &mut FieldBuilder<'ctx>) -> Self::Fields;
+
+    fn get_fields(&self, ctx: &'ctx Context) -> Self::Fields {
+        let mut builder = FieldBuilder::new(ctx, self.struct_name());
+        self.build_fields(&mut builder)
+    }
+
+    /// Get the LLVM struct type this [`IsStruct<'ctx>`] is representing.
+    fn get_struct_type(&self, ctx: &'ctx Context) -> StructType<'ctx> {
+        let mut builder = FieldBuilder::new(ctx, self.struct_name());
+        self.build_fields(&mut builder); // Self::Fields is discarded
+
+        let field_types = builder.fields.iter().map(|f| f.llvm_type).collect_vec();
+        ctx.struct_type(&field_types, false)
+    }
+
+    /// Check if `scrutinee` matches the [`StructType<'ctx>`] this [`IsStruct<'ctx>`] is representing.
+    fn check_struct_type(
+        &self,
+        ctx: &'ctx Context,
+        scrutinee: StructType<'ctx>,
+    ) -> Result<(), String> {
+        // Details about scrutinee
+        let scrutinee_field_types = scrutinee.get_field_types();
+
+        // Details about the defined specifications of this struct
+        // We will access them through builder
+        let mut builder = FieldBuilder::new(ctx, self.struct_name());
+        self.build_fields(&mut builder);
+
+        // Check # of fields
+        if builder.fields.len() != scrutinee_field_types.len() {
+            return Err(format!(
+                "Expecting struct to have {} field(s), but scrutinee has {} field(s)",
+                builder.fields.len(),
+                scrutinee_field_types.len()
+            ));
+        }
+
+        // Check the types of each field
+        // TODO: Traceback?
+        for (f, scrutinee_field_type) in izip!(builder.fields, scrutinee_field_types) {
+            f.llvm_type_model.check_llvm_type(ctx, scrutinee_field_type.as_any_type_enum())?;
+        }
+
+        Ok(())
+    }
+}
+
+/// A [`Model<'ctx>`] that represents an LLVM struct.
+///
+/// `self.0` contains a [`IsStruct<'ctx>`] that gives the details of the LLVM struct.
+#[derive(Debug, Clone, Copy)]
+pub struct StructModel<S>(pub S);
+
+impl<'ctx, S: IsStruct<'ctx>> CanCheckLLVMType<'ctx> for StructModel<S> {
+    fn check_llvm_type(
+        &self,
+        ctx: &'ctx Context,
+        scrutinee: AnyTypeEnum<'ctx>,
+    ) -> Result<(), String> {
+        // Check if scrutinee is even a struct type
+        let AnyTypeEnum::StructType(scrutinee) = scrutinee else {
+            return Err(format!("Expecting a struct type, but got {scrutinee:?}"));
+        };
+
+        // Ok. now check the struct type *thoroughly*
+        self.0.check_struct_type(ctx, scrutinee)
+    }
+}
+
+impl<'ctx, S: IsStruct<'ctx>> Model<'ctx> for StructModel<S> {
+    type Value = Struct<'ctx, S>; // TODO: enrich it
+
+    fn get_llvm_type(&self, ctx: &'ctx Context) -> BasicTypeEnum<'ctx> {
+        self.0.get_struct_type(ctx).as_basic_type_enum()
+    }
+
+    fn review(&self, ctx: &'ctx Context, value: AnyValueEnum<'ctx>) -> Self::Value {
+        // Check that `value` is not some bogus values or an incorrect StructValue
+        self.check_llvm_type(ctx, value.get_type()).unwrap();
+
+        Struct { structure: self.0, value: value.into_struct_value() }
+    }
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct Struct<'ctx, S> {
+    pub structure: S,
+    pub value: StructValue<'ctx>,
+}
+
+impl<'ctx, S: IsStruct<'ctx>> ModelValue<'ctx> for Struct<'ctx, S> {
+    fn get_llvm_value(&self) -> BasicValueEnum<'ctx> {
+        self.value.as_basic_value_enum()
+    }
+}
+
+impl<'ctx, S: IsStruct<'ctx>> Pointer<'ctx, StructModel<S>> {
+    /// Build an instruction that does `getelementptr` on an LLVM structure referenced by this pointer.
+    ///
+    /// This provides a nice syntax to chain up `getelementptr` in an intuitive and type-safe way:
+    ///
+    /// ```ignore
+    /// let ctx: &CodeGenContext<'ctx, '_>;
+    /// let ndarray: Pointer<'ctx, StructModel<NpArray<'ctx>>>;
+    /// ndarray.gep(ctx, |f| f.ndims).store();
+    /// ```
+    ///
+    /// You might even write chains `gep`, i.e.,
+    /// ```ignore
+    /// my_struct
+    ///     .gep(ctx, |f| f.thing1)
+    ///     .gep(ctx, |f| f.value)
+    ///     .store(ctx, my_value) // Equivalent to `my_struct.thing1.value = my_value`
+    /// ```
+    pub fn gep<E, GetFieldFn>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        get_field: GetFieldFn,
+    ) -> Pointer<'ctx, E>
+    where
+        E: Model<'ctx>,
+        GetFieldFn: FnOnce(S::Fields) -> Field<E>,
+    {
+        let fields = self.element.0.get_fields(ctx.ctx);
+        let field = get_field(fields);
+
+        let llvm_i32 = ctx.ctx.i32_type(); // TODO: I think I'm not supposed to *just* use i32 for GEP like that
+
+        let ptr = unsafe {
+            ctx.builder
+                .build_in_bounds_gep(
+                    self.value,
+                    &[llvm_i32.const_zero(), llvm_i32.const_int(field.gep_index, false)],
+                    field.name,
+                )
+                .unwrap()
+        };
+
+        Pointer { element: field.element, value: ptr }
+    }
+}

nac3core/src/codegen/model/int.rs

@@ -0,0 +1,279 @@
+use inkwell::{
+    context::Context,
+    types::{AnyType, AnyTypeEnum, BasicType, BasicTypeEnum, IntType},
+    values::{AnyValueEnum, BasicValue, BasicValueEnum, IntValue},
+};
+
+use crate::codegen::CodeGenContext;
+
+use super::core::*;
+
+/// Helper function to check if `scrutinee` is the same as `expected_int_type`
+fn check_int_llvm_type<'ctx>(
+    scrutinee: AnyTypeEnum<'ctx>,
+    expected_int_type: IntType<'ctx>,
+) -> Result<(), String> {
+    // Check if llvm_type is int type
+    let AnyTypeEnum::IntType(scrutinee) = scrutinee else {
+        return Err(format!("Expecting an int type but got {scrutinee:?}"));
+    };
+
+    // Check bit width
+    if scrutinee.get_bit_width() != expected_int_type.get_bit_width() {
+        return Err(format!(
+            "Expecting an int type of {}-bit(s) but got int type {}-bit(s)",
+            expected_int_type.get_bit_width(),
+            scrutinee.get_bit_width()
+        ));
+    }
+
+    Ok(())
+}
+
+/// Helper function to cast `scrutinee` is into an [`IntValue<'ctx>`].
+/// The LLVM type of `scrutinee` will be checked with [`check_int_llvm_type`].
+fn review_int_llvm_value<'ctx>(
+    value: AnyValueEnum<'ctx>,
+    expected_int_type: IntType<'ctx>,
+) -> Result<IntValue<'ctx>, String> {
+    // Check if value is of int type, error if that is anything else
+    check_int_llvm_type(value.get_type().as_any_type_enum(), expected_int_type)?;
+
+    // Ok, it is must be an int
+    Ok(value.into_int_value())
+}
+
+/// A model representing an [`IntType<'ctx>`].
+///
+/// Also see [`FixedIntModel`], which is more constrained than [`IntModel`]
+/// but provides more type-safe mechanisms and even auto-derivation of [`BasicTypeEnum<'ctx>`]
+/// for creating LLVM structures.
+#[derive(Debug, Clone, Copy)]
+pub struct IntModel<'ctx>(pub IntType<'ctx>);
+
+/// An inhabitant of an [`IntModel<'ctx>`]
+#[derive(Debug, Clone, Copy)]
+pub struct Int<'ctx>(pub IntValue<'ctx>);
+
+impl<'ctx> CanCheckLLVMType<'ctx> for IntModel<'ctx> {
+    fn check_llvm_type(
+        &self,
+        _ctx: &'ctx Context,
+        scrutinee: AnyTypeEnum<'ctx>,
+    ) -> Result<(), String> {
+        check_int_llvm_type(scrutinee, self.0)
+    }
+}
+
+impl<'ctx> Model<'ctx> for IntModel<'ctx> {
+    type Value = Int<'ctx>;
+
+    fn get_llvm_type(&self, _ctx: &'ctx Context) -> BasicTypeEnum<'ctx> {
+        self.0.as_basic_type_enum()
+    }
+
+    fn review(&self, ctx: &'ctx Context, value: AnyValueEnum<'ctx>) -> Self::Value {
+        let int = value.into_int_value();
+        self.check_llvm_type(ctx, int.get_type().as_any_type_enum()).unwrap();
+        Int(int)
+    }
+}
+
+impl<'ctx> ModelValue<'ctx> for Int<'ctx> {
+    fn get_llvm_value(&self) -> BasicValueEnum<'ctx> {
+        self.0.as_basic_value_enum()
+    }
+}
+
+// Extra utilities for [`Int<'ctx>`]
+impl<'ctx> Int<'ctx> {
+    #[must_use]
+    pub fn signed_cast_to_int(
+        self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        target_int: IntModel<'ctx>,
+        name: &str,
+    ) -> Int<'ctx> {
+        Int(ctx.builder.build_int_s_extend_or_bit_cast(self.0, target_int.0, name).unwrap())
+    }
+
+    #[must_use]
+    pub fn signed_cast_to_fixed<T: IsFixedInt>(
+        self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        target_fixed: T,
+        name: &str,
+    ) -> FixedInt<'ctx, T> {
+        FixedInt {
+            int: target_fixed,
+            value: ctx
+                .builder
+                .build_int_s_extend_or_bit_cast(self.0, T::get_int_type(ctx.ctx), name)
+                .unwrap(),
+        }
+    }
+}
+
+// Extra utilities for [`IntModel<'ctx>`]
+impl<'ctx> IntModel<'ctx> {
+    /// Create a constant value that inhabits this [`IntModel<'ctx>`].
+    #[must_use]
+    pub fn constant(&self, value: u64) -> Int<'ctx> {
+        Int(self.0.const_int(value, false))
+    }
+
+    /// Check if `other` is fully compatible with this [`IntModel<'ctx>`].
+    ///
+    /// This simply checks if the underlying [`IntType<'ctx>`] has
+    /// the same number of bits.
+    #[must_use]
+    pub fn same_as(&self, other: IntModel<'ctx>) -> bool {
+        // TODO: or `self.0 == other.0` would also work?
+        self.0.get_bit_width() == other.0.get_bit_width()
+    }
+}
+
+/// A model representing a compile-time known [`IntType<'ctx>`].
+///
+/// Also see [`IntModel`], which is less constrained than [`FixedIntModel`],
+/// but enables one to handle [`IntType<'ctx>`] that could be dynamic
+#[derive(Debug, Clone, Copy, Default)]
+pub struct FixedIntModel<T>(pub T);
+
+impl<T: IsFixedInt> FixedIntModel<T> {
+    pub fn to_int_model(self, ctx: &Context) -> IntModel<'_> {
+        IntModel(T::get_int_type(ctx))
+    }
+}
+
+impl<'ctx, T: IsFixedInt> CanCheckLLVMType<'ctx> for FixedIntModel<T> {
+    fn check_llvm_type(
+        &self,
+        ctx: &'ctx Context,
+        scrutinee: AnyTypeEnum<'ctx>,
+    ) -> Result<(), String> {
+        check_int_llvm_type(scrutinee, T::get_int_type(ctx))
+    }
+}
+
+impl<'ctx, T: IsFixedInt> Model<'ctx> for FixedIntModel<T> {
+    type Value = FixedInt<'ctx, T>;
+
+    fn get_llvm_type(&self, ctx: &'ctx Context) -> BasicTypeEnum<'ctx> {
+        T::get_int_type(ctx).as_basic_type_enum()
+    }
+
+    fn review(&self, ctx: &'ctx Context, value: AnyValueEnum<'ctx>) -> Self::Value {
+        let value = review_int_llvm_value(value, T::get_int_type(ctx)).unwrap();
+        FixedInt { int: self.0, value }
+    }
+}
+
+impl<'ctx, T: IsFixedInt> FixedIntModel<T> {
+    pub fn constant(&self, ctx: &'ctx Context, value: u64) -> FixedInt<'ctx, T> {
+        FixedInt { int: self.0, value: T::get_int_type(ctx).const_int(value, false) }
+    }
+}
+
+/// An inhabitant of [`FixedIntModel<'ctx>`]
+#[derive(Debug, Clone, Copy)]
+pub struct FixedInt<'ctx, T: IsFixedInt> {
+    pub int: T,
+    pub value: IntValue<'ctx>,
+}
+
+/// A marker trait to mark singleton struct that describes a particular fixed integer type.
+/// See [`Bool`], [`Byte`], [`Int32`], etc.
+///
+/// The [`Default`] trait is to enable auto-derivations for utilities like
+/// [`FieldBuilder::add_field_auto`]
+pub trait IsFixedInt: Clone + Copy + Default {
+    fn get_int_type(ctx: &Context) -> IntType<'_>;
+    fn get_bit_width() -> u32; // This is required, instead of only relying on get_int_type
+}
+
+impl<'ctx, T: IsFixedInt> ModelValue<'ctx> for FixedInt<'ctx, T> {
+    fn get_llvm_value(&self) -> BasicValueEnum<'ctx> {
+        self.value.as_basic_value_enum()
+    }
+}
+
+// Extra utilities for [`FixedInt<'ctx, T>`]
+impl<'ctx, T: IsFixedInt> FixedInt<'ctx, T> {
+    pub fn to_int(self) -> Int<'ctx> {
+        Int(self.value)
+    }
+
+    pub fn signed_cast_to_fixed<R: IsFixedInt>(
+        self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        target_fixed_int: R,
+        name: &str,
+    ) -> FixedInt<'ctx, R> {
+        FixedInt {
+            int: target_fixed_int,
+            value: ctx
+                .builder
+                .build_int_s_extend_or_bit_cast(self.value, R::get_int_type(ctx.ctx), name)
+                .unwrap(),
+        }
+    }
+}
+
+// Some pre-defined fixed integers
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Bool;
+pub type BoolModel = FixedIntModel<Bool>;
+
+impl IsFixedInt for Bool {
+    fn get_int_type(ctx: &Context) -> IntType<'_> {
+        ctx.bool_type()
+    }
+
+    fn get_bit_width() -> u32 {
+        1
+    }
+}
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Byte;
+pub type ByteModel = FixedIntModel<Byte>;
+
+impl IsFixedInt for Byte {
+    fn get_int_type(ctx: &Context) -> IntType<'_> {
+        ctx.i8_type()
+    }
+
+    fn get_bit_width() -> u32 {
+        8
+    }
+}
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Int32;
+pub type Int32Model = FixedIntModel<Int32>;
+
+impl IsFixedInt for Int32 {
+    fn get_int_type(ctx: &Context) -> IntType<'_> {
+        ctx.i32_type()
+    }
+
+    fn get_bit_width() -> u32 {
+        32
+    }
+}
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Int64;
+pub type Int64Model = FixedIntModel<Int64>;
+
+impl IsFixedInt for Int64 {
+    fn get_int_type(ctx: &Context) -> IntType<'_> {
+        ctx.i64_type()
+    }
+
+    fn get_bit_width() -> u32 {
+        64
+    }
+}

nac3core/src/codegen/model/mod.rs

@@ -0,0 +1,11 @@
+pub mod core;
+pub mod gep;
+pub mod int;
+pub mod pointer;
+pub mod slice;
+
+pub use core::*;
+pub use gep::*;
+pub use int::*;
+pub use pointer::*;
+pub use slice::*;

nac3core/src/codegen/model/pointer.rs

@@ -0,0 +1,184 @@
+use inkwell::{
+    context::Context,
+    types::{AnyTypeEnum, BasicType, BasicTypeEnum},
+    values::{AnyValue, AnyValueEnum, BasicValue, BasicValueEnum, PointerValue},
+    AddressSpace,
+};
+
+use crate::codegen::CodeGenContext;
+
+use super::core::*;
+
+/// An inhabitant of [`PointerModel<E>`]
+#[derive(Debug, Clone, Copy)]
+pub struct Pointer<'ctx, E: Model<'ctx>> {
+    pub element: E,
+    pub value: PointerValue<'ctx>,
+}
+
+/// A [`Model<'ctx>`] representing an LLVM [`PointerType<'ctx>`]
+/// with *full* information on the element u
+///
+/// [`self.0`] contains [`Model<'ctx>`] that represents the
+/// LLVM type of element of the [`PointerType<'ctx>`] is pointing at
+/// (like `PointerType<'ctx>::get_element_type()`, but abstracted as a [`Model<'ctx>`]).
+#[derive(Debug, Clone, Copy, Default)]
+pub struct PointerModel<E>(pub E);
+
+impl<'ctx, E: Model<'ctx>> ModelValue<'ctx> for Pointer<'ctx, E> {
+    fn get_llvm_value(&self) -> BasicValueEnum<'ctx> {
+        self.value.as_basic_value_enum()
+    }
+}
+
+impl<'ctx, E: Model<'ctx>> Pointer<'ctx, E> {
+    /// Build an instruction to store a value into this pointer
+    pub fn store(&self, ctx: &CodeGenContext<'ctx, '_>, val: E::Value) {
+        ctx.builder.build_store(self.value, val.get_llvm_value()).unwrap();
+    }
+
+    /// Build an instruction to load a value from this pointer
+    pub fn load(&self, ctx: &CodeGenContext<'ctx, '_>, name: &str) -> E::Value {
+        let val = ctx.builder.build_load(self.value, name).unwrap();
+        self.element.review(ctx.ctx, val.as_any_value_enum())
+    }
+
+    pub fn to_opaque(self) -> OpaquePointer<'ctx> {
+        OpaquePointer(self.value)
+    }
+
+    pub fn cast_opaque_to(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        element_type: BasicTypeEnum<'ctx>,
+        name: &str,
+    ) -> OpaquePointer<'ctx> {
+        self.to_opaque().cast_opaque_to(ctx, element_type, name)
+    }
+
+    pub fn cast_to<R: Model<'ctx>>(
+        self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        element_model: R,
+        name: &str,
+    ) -> Pointer<'ctx, R> {
+        let casted_ptr =
+            self.to_opaque().cast_opaque_to(ctx, element_model.get_llvm_type(ctx.ctx), name).0;
+        Pointer { element: element_model, value: casted_ptr }
+    }
+}
+
+impl<'ctx, E: Model<'ctx>> CanCheckLLVMType<'ctx> for PointerModel<E> {
+    fn check_llvm_type(
+        &self,
+        ctx: &'ctx Context,
+        scrutinee: AnyTypeEnum<'ctx>,
+    ) -> Result<(), String> {
+        // Check if scrutinee is even a PointerValue
+        let AnyTypeEnum::PointerType(scrutinee) = scrutinee else {
+            return Err(format!("Expecting a pointer value, but got {scrutinee:?}"));
+        };
+
+        // Check the type of what the pointer is pointing at
+        // TODO: This will be deprecated by inkwell > llvm14 because `get_element_type()` will be gone
+        self.0.check_llvm_type(ctx, scrutinee.get_element_type())?; // TODO: Include backtrace?
+
+        Ok(())
+    }
+}
+
+impl<'ctx, E: Model<'ctx>> Model<'ctx> for PointerModel<E> {
+    type Value = Pointer<'ctx, E>;
+
+    fn get_llvm_type(&self, ctx: &'ctx Context) -> BasicTypeEnum<'ctx> {
+        self.0.get_llvm_type(ctx).ptr_type(AddressSpace::default()).as_basic_type_enum()
+    }
+
+    fn review(&self, ctx: &'ctx Context, value: AnyValueEnum<'ctx>) -> Self::Value {
+        self.check_llvm_type(ctx, value.get_type()).unwrap();
+
+        // TODO: Check get_element_type()? for LLVM 14 at least...
+        Pointer { element: self.0, value: value.into_pointer_value() }
+    }
+}
+
+// A pointer of which the element's model is unknown.
+#[derive(Debug, Clone, Copy)]
+pub struct OpaquePointer<'ctx>(pub PointerValue<'ctx>);
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct OpaquePointerModel;
+
+impl<'ctx> ModelValue<'ctx> for OpaquePointer<'ctx> {
+    fn get_llvm_value(&self) -> BasicValueEnum<'ctx> {
+        self.0.as_basic_value_enum()
+    }
+}
+
+impl<'ctx> CanCheckLLVMType<'ctx> for OpaquePointerModel {
+    fn check_llvm_type(
+        &self,
+        _ctx: &'ctx Context,
+        scrutinee: AnyTypeEnum<'ctx>,
+    ) -> Result<(), String> {
+        // OpaquePointerModel only cares that it is a pointer,
+        // but not what the pointer is pointing at
+        match scrutinee {
+            AnyTypeEnum::PointerType(_) => Ok(()),
+            _ => Err(format!("Expecting a pointer type, but got {scrutinee:?}")),
+        }
+    }
+}
+
+impl<'ctx> Model<'ctx> for OpaquePointerModel {
+    type Value = OpaquePointer<'ctx>;
+
+    fn get_llvm_type(&self, ctx: &'ctx Context) -> BasicTypeEnum<'ctx> {
+        ctx.i8_type().ptr_type(AddressSpace::default()).as_basic_type_enum()
+    }
+
+    fn review(&self, ctx: &'ctx Context, value: AnyValueEnum<'ctx>) -> Self::Value {
+        // Check if value is even of a pointer type
+        self.check_llvm_type(ctx, value.get_type()).unwrap();
+
+        OpaquePointer(value.into_pointer_value())
+    }
+}
+
+impl<'ctx> OpaquePointer<'ctx> {
+    pub fn load_opaque(&self, ctx: &CodeGenContext<'ctx, '_>, name: &str) -> BasicValueEnum<'ctx> {
+        ctx.builder.build_load(self.0, name).unwrap()
+    }
+
+    pub fn store_opaque(&self, ctx: &CodeGenContext<'ctx, '_>, value: BasicValueEnum<'ctx>) {
+        ctx.builder.build_store(self.0, value).unwrap();
+    }
+
+    #[must_use]
+    pub fn cast_opaque_to(
+        self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        element_llvm_type: BasicTypeEnum<'ctx>,
+        name: &str,
+    ) -> OpaquePointer<'ctx> {
+        OpaquePointer(
+            ctx.builder
+                .build_pointer_cast(
+                    self.0,
+                    element_llvm_type.ptr_type(AddressSpace::default()),
+                    name,
+                )
+                .unwrap(),
+        )
+    }
+
+    pub fn cast_to<E: Model<'ctx>>(
+        self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        element_model: E,
+        name: &str,
+    ) -> Pointer<'ctx, E> {
+        let ptr = self.cast_opaque_to(ctx, element_model.get_llvm_type(ctx.ctx), name).0;
+        Pointer { element: element_model, value: ptr }
+    }
+}

nac3core/src/codegen/model/slice.rs

@@ -0,0 +1,73 @@
+use crate::codegen::{CodeGenContext, CodeGenerator};
+
+use super::{Int, Model, Pointer};
+
+pub struct ArraySlice<'ctx, E: Model<'ctx>> {
+    pub num_elements: Int<'ctx>,
+    pub pointer: Pointer<'ctx, E>,
+}
+
+impl<'ctx, E: Model<'ctx>> ArraySlice<'ctx, E> {
+    pub fn ix_unchecked(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        idx: Int<'ctx>,
+        name: &str,
+    ) -> Pointer<'ctx, E> {
+        let element_addr =
+            unsafe { ctx.builder.build_in_bounds_gep(self.pointer.value, &[idx.0], name).unwrap() };
+        Pointer { value: element_addr, element: self.pointer.element }
+    }
+
+    pub fn ix<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        idx: Int<'ctx>,
+        name: &str,
+    ) -> Pointer<'ctx, E> {
+        let int_type = self.num_elements.0.get_type(); // NOTE: Weird get_type(), see comment under `trait Ixed`
+
+        assert_eq!(int_type.get_bit_width(), idx.0.get_type().get_bit_width()); // Might as well check bit width to catch bugs
+
+        // TODO: SGE or UGE? or make it defined by the implementee?
+
+        // Check `0 <= index`
+        let lower_bounded = ctx
+            .builder
+            .build_int_compare(
+                inkwell::IntPredicate::SLE,
+                int_type.const_zero(),
+                idx.0,
+                "lower_bounded",
+            )
+            .unwrap();
+
+        // Check `index < num_elements`
+        let upper_bounded = ctx
+            .builder
+            .build_int_compare(
+                inkwell::IntPredicate::SLT,
+                idx.0,
+                self.num_elements.0,
+                "upper_bounded",
+            )
+            .unwrap();
+
+        // Compute `0 <= index && index < num_elements`
+        let bounded = ctx.builder.build_and(lower_bounded, upper_bounded, "bounded").unwrap();
+
+        // Assert `bounded`
+        ctx.make_assert(
+            generator,
+            bounded,
+            "0:IndexError",
+            "nac3core LLVM codegen attempting to access out of bounds array index {0}. Must satisfy 0 <= index < {2}",
+            [ Some(idx.0), Some(self.num_elements.0), None],
+            ctx.current_loc
+        );
+
+        // ...and finally do indexing
+        self.ix_unchecked(ctx, idx, name)
+    }
+}

nac3core/src/codegen/numpy.rs

@@ -9,7 +9,7 @@ use crate::{
         irrt::{
             calculate_len_for_slice_range, call_ndarray_calc_broadcast,
             call_ndarray_calc_broadcast_index, call_ndarray_calc_nd_indices,
-            call_ndarray_calc_size,
+            call_ndarray_calc_size, error_context::call_nac3_dummy_raise,
         },
         llvm_intrinsics::{self, call_memcpy_generic},
         stmt::{gen_for_callback_incrementing, gen_for_range_callback, gen_if_else_expr_callback},
@@ -538,6 +538,8 @@ fn call_ndarray_zeros_impl<'ctx, G: CodeGenerator + ?Sized>(
     elem_ty: Type,
     shape: BasicValueEnum<'ctx>,
 ) -> Result<NDArrayValue<'ctx>, String> {
+    call_nac3_dummy_raise(generator, ctx);
+
     let supported_types = [
         ctx.primitives.int32,
         ctx.primitives.int64,

nac3core/src/codegen/numpy_new.rs

@@ -0,0 +1,195 @@
+use inkwell::values::{BasicValue, BasicValueEnum, PointerValue};
+use nac3parser::ast::StrRef;
+
+use crate::{
+    symbol_resolver::ValueEnum,
+    toplevel::DefinitionId,
+    typecheck::typedef::{FunSignature, Type},
+};
+
+use super::{
+    irrt::numpy::{
+        ndarray::{
+            alloca_ndarray_and_init, call_nac3_ndarray_fill_generic, NDArrayInitMode, NpArray,
+        },
+        shape::parse_input_shape_arg,
+    },
+    model::*,
+    CodeGenContext, CodeGenerator,
+};
+
+/// LLVM-typed implementation for generating the implementation for constructing an empty `NDArray`.
+fn call_ndarray_empty_impl<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    elem_ty: Type,
+    shape: BasicValueEnum<'ctx>,
+    shape_ty: Type,
+    name: &str,
+) -> Result<Pointer<'ctx, StructModel<NpArray<'ctx>>>, String>
+where
+    G: CodeGenerator + ?Sized,
+{
+    let elem_type = ctx.get_llvm_type(generator, elem_ty);
+    let shape = parse_input_shape_arg(generator, ctx, shape, shape_ty);
+    let ndarray_ptr = alloca_ndarray_and_init(
+        generator,
+        ctx,
+        elem_type,
+        NDArrayInitMode::ShapeAndAllocaData { shape },
+        name,
+    )?;
+    Ok(ndarray_ptr)
+}
+
+fn call_ndarray_full_impl<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    elem_ty: Type,
+    shape: BasicValueEnum<'ctx>,
+    shape_ty: Type,
+    fill_value: BasicValueEnum<'ctx>,
+    name: &str,
+) -> Result<Pointer<'ctx, StructModel<NpArray<'ctx>>>, String>
+where
+    G: CodeGenerator + ?Sized,
+{
+    let ndarray_ptr = call_ndarray_empty_impl(generator, ctx, elem_ty, shape, shape_ty, name)?;
+
+    // NOTE: fill_value's type is not checked!! so be careful with logics
+
+    // Allocate fill_value on the stack and give the corresponding stack pointer
+    // to call_nac3_ndarray_fill_generic
+    let fill_value_ptr = ctx.builder.build_alloca(fill_value.get_type(), "fill_value_ptr").unwrap();
+    let fill_value_ptr = OpaquePointer(fill_value_ptr);
+    fill_value_ptr.store_opaque(ctx, fill_value);
+
+    let fill_value_ptr = fill_value_ptr.cast_to(ctx, FixedIntModel(Byte), "");
+    call_nac3_ndarray_fill_generic(ctx, ndarray_ptr, fill_value_ptr);
+
+    Ok(ndarray_ptr)
+}
+
+/// Generates LLVM IR for `np.empty`.
+pub fn gen_ndarray_empty<'ctx>(
+    context: &mut CodeGenContext<'ctx, '_>,
+    obj: &Option<(Type, ValueEnum<'ctx>)>,
+    fun: (&FunSignature, DefinitionId),
+    args: &[(Option<StrRef>, ValueEnum<'ctx>)],
+    generator: &mut dyn CodeGenerator,
+) -> Result<PointerValue<'ctx>, String> {
+    assert!(obj.is_none());
+    assert_eq!(args.len(), 1);
+
+    // Parse arguments
+    let shape_ty = fun.0.args[0].ty;
+    let shape = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
+
+    // Implementation
+    let ndarray_ptr = call_ndarray_empty_impl(
+        generator,
+        context,
+        context.primitives.float,
+        shape,
+        shape_ty,
+        "ndarray",
+    )?;
+    Ok(ndarray_ptr.value)
+}
+
+/// Generates LLVM IR for `np.zeros`.
+pub fn gen_ndarray_zeros<'ctx>(
+    context: &mut CodeGenContext<'ctx, '_>,
+    obj: &Option<(Type, ValueEnum<'ctx>)>,
+    fun: (&FunSignature, DefinitionId),
+    args: &[(Option<StrRef>, ValueEnum<'ctx>)],
+    generator: &mut dyn CodeGenerator,
+) -> Result<PointerValue<'ctx>, String> {
+    assert!(obj.is_none());
+    assert_eq!(args.len(), 1);
+
+    // Parse arguments
+    let shape_ty = fun.0.args[0].ty;
+    let shape = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
+
+    // Implementation
+    // NOTE: Currently nac3's `np.zeros` is always `float64`.
+    let float64_ty = context.primitives.float;
+    let float64_llvm_type = context.get_llvm_type(generator, float64_ty).into_float_type();
+
+    let ndarray_ptr = call_ndarray_full_impl(
+        generator,
+        context,
+        float64_ty, // `elem_ty` is always `float64`
+        shape,
+        shape_ty,
+        float64_llvm_type.const_zero().as_basic_value_enum(),
+        "ndarray",
+    )?;
+    Ok(ndarray_ptr.value)
+}
+
+/// Generates LLVM IR for `np.ones`.
+pub fn gen_ndarray_ones<'ctx>(
+    context: &mut CodeGenContext<'ctx, '_>,
+    obj: &Option<(Type, ValueEnum<'ctx>)>,
+    fun: (&FunSignature, DefinitionId),
+    args: &[(Option<StrRef>, ValueEnum<'ctx>)],
+    generator: &mut dyn CodeGenerator,
+) -> Result<PointerValue<'ctx>, String> {
+    assert!(obj.is_none());
+    assert_eq!(args.len(), 1);
+
+    // Parse arguments
+    let shape_ty = fun.0.args[0].ty;
+    let shape = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
+
+    // Implementation
+    // NOTE: Currently nac3's `np.ones` is always `float64`.
+    let float64_ty = context.primitives.float;
+    let float64_llvm_type = context.get_llvm_type(generator, float64_ty).into_float_type();
+
+    let ndarray_ptr = call_ndarray_full_impl(
+        generator,
+        context,
+        float64_ty, // `elem_ty` is always `float64`
+        shape,
+        shape_ty,
+        float64_llvm_type.const_float(1.0).as_basic_value_enum(),
+        "ndarray",
+    )?;
+    Ok(ndarray_ptr.value)
+}
+
+/// Generates LLVM IR for `ndarray.full`.
+pub fn gen_ndarray_full<'ctx>(
+    context: &mut CodeGenContext<'ctx, '_>,
+    obj: &Option<(Type, ValueEnum<'ctx>)>,
+    fun: (&FunSignature, DefinitionId),
+    args: &[(Option<StrRef>, ValueEnum<'ctx>)],
+    generator: &mut dyn CodeGenerator,
+) -> Result<PointerValue<'ctx>, String> {
+    assert!(obj.is_none());
+    assert_eq!(args.len(), 2);
+
+    // Parse argument #1 shape
+    let shape_ty = fun.0.args[0].ty;
+    let shape_arg = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
+
+    // Parse argument #2 fill_value
+    let fill_value_ty = fun.0.args[1].ty;
+    let fill_value_arg =
+        args[1].1.clone().to_basic_value_enum(context, generator, fill_value_ty)?;
+
+    // Implementation
+    let ndarray_ptr = call_ndarray_full_impl(
+        generator,
+        context,
+        fill_value_ty,
+        shape_arg,
+        shape_ty,
+        fill_value_arg,
+        "ndarray",
+    )?;
+    Ok(ndarray_ptr.value)
+}

nac3core/src/codegen/stmt.rs

@@ -13,7 +13,7 @@ use crate::{
     toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, DefinitionId, TopLevelDef},
     typecheck::{
         magic_methods::Binop,
-        typedef::{FunSignature, Type, TypeEnum},
+        typedef::{iter_type_vars, FunSignature, Type, TypeEnum},
     },
 };
 use inkwell::{
@@ -189,10 +189,6 @@ pub fn gen_store_target<'ctx, G: CodeGenerator>(
                     v.data().ptr_offset(ctx, generator, &index, name)
                 }
 
-                TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
-                    todo!()
-                }
-
                 _ => unreachable!(),
             }
         }
@@ -206,11 +202,29 @@ pub fn gen_assign<'ctx, G: CodeGenerator>(
     ctx: &mut CodeGenContext<'ctx, '_>,
     target: &Expr<Option<Type>>,
     value: ValueEnum<'ctx>,
+    value_ty: Type,
 ) -> Result<(), String> {
+    /*
+        To handle assignment statements `target = value`, with
+        special care taken for targets `gen_store_target` cannot handle, these are:
+        - Case 1. target is a Tuple
+            - e.g., `(x, y, z, w) = value`
+        - Case 2. *Sliced* list assignment `list.__setitem__`
+            - e.g., `my_list[1:3] = [100, 101]`, BUT NOT `my_list[0] = 99` (gen_store_target knows how to handle these),
+        - Case 3. Indexed ndarray assignment `ndarray.__setitem__`
+            - e.g., `my_ndarray[::-1, :] = 3`, `my_ndarray[:, 3::-1] = their_ndarray[10::2]`
+            - NOTE: Technically speaking, if `target` is sliced in such as way that it is referencing a
+                    single element/scalar, we *could* implement gen_store_target for this special case
+                    (to point to the raw address of that scalar in the ndarray); but it is much,
+                    *much* simpler to generalize all indexed ndarray assignment without
+                    special handling on that edgecase.
+        - Otherwise, use `gen_store_target`
+    */
+
     let llvm_usize = generator.get_size_type(ctx.ctx);
 
-    match &target.node {
-        ExprKind::Tuple { elts, .. } => {
+    if let ExprKind::Tuple { elts, .. } = &target.node {
+        // Handle Case 1. target is a Tuple
         let BasicValueEnum::StructValue(v) =
             value.to_basic_value_enum(ctx, generator, target.custom.unwrap())?
         else {
@@ -218,26 +232,47 @@ pub fn gen_assign<'ctx, G: CodeGenerator>(
         };
 
         for (i, elt) in elts.iter().enumerate() {
+            let elem_ty = elt.custom.unwrap();
+
             let v = ctx
                 .builder
                 .build_extract_value(v, u32::try_from(i).unwrap(), "struct_elem")
                 .unwrap();
-                generator.gen_assign(ctx, elt, v.into())?;
+            generator.gen_assign(ctx, elt, v.into(), elem_ty)?;
         }
+
+        return Ok(()); // Terminate
     }
-        ExprKind::Subscript { value: ls, slice, .. }
-            if matches!(&slice.node, ExprKind::Slice { .. }) =>
+
+    // Else, try checking if it's Case 2 or 3, and they *ONLY*
+    // happen if `target.node` is a `ExprKind::Subscript`, so do a special check
+    if let ExprKind::Subscript { value: target_without_slice, slice, .. } = &target.node {
+        // Get the type of target
+        let target_ty = target.custom.unwrap();
+        let target_ty_enum = &*ctx.unifier.get_ty(target_ty);
+
+        // Pattern match on this pair.
+        // This is done like this because of Case 2 - slice.node has to be in a specific pattern
+        match (target_ty_enum, &slice.node) {
+            (TypeEnum::TObj { obj_id, .. }, ExprKind::Slice { lower, upper, step })
+                if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
             {
-            let ExprKind::Slice { lower, upper, step } = &slice.node else { unreachable!() };
+                // Case 2. *Sliced* list assignment
 
                 let ls = generator
-                .gen_expr(ctx, ls)?
+                    .gen_expr(ctx, target_without_slice)?
                     .unwrap()
-                .to_basic_value_enum(ctx, generator, ls.custom.unwrap())?
+                    .to_basic_value_enum(ctx, generator, target_without_slice.custom.unwrap())?
                     .into_pointer_value();
                 let ls = ListValue::from_ptr_val(ls, llvm_usize, None);
-            let Some((start, end, step)) =
-                handle_slice_indices(lower, upper, step, ctx, generator, ls.load_size(ctx, None))?
+                let Some((start, end, step)) = handle_slice_indices(
+                    lower,
+                    upper,
+                    step,
+                    ctx,
+                    generator,
+                    ls.load_size(ctx, None),
+                )?
                 else {
                     return Ok(());
                 };
@@ -268,8 +303,49 @@ pub fn gen_assign<'ctx, G: CodeGenerator>(
                     return Ok(());
                 };
                 list_slice_assignment(generator, ctx, ty, ls, (start, end, step), value, src_ind);
+
+                return Ok(()); // Terminate
+            }
+            (TypeEnum::TObj { obj_id, .. }, _)
+                if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
+            {
+                // Case 3. Indexed ndarray assignment
+
+                let target = generator.gen_expr(ctx, target)?.unwrap().to_basic_value_enum(
+                    ctx,
+                    generator,
+                    target.custom.unwrap(),
+                )?;
+
+                match &*ctx.unifier.get_ty(value_ty) {
+                    TypeEnum::TObj { obj_id, .. }
+                        if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
+                    {
+                        // `value` is an `ndarray[dtype, ndims]`
+                        todo!()
                     }
                     _ => {
+                        // TODO: Inferencer's assignment forces `target` and `value` to have the same type
+                        // NOTE: gen_assign() has already been extended, I will keep it in place
+                        // in participation for when this is extended to be no longer the case.
+                        todo!("support scalar assignment")
+                        // panic!(
+                        //     "Unsupported ndarray assignment value: {}",
+                        //     ctx.unifier.stringify(value_ty)
+                        // );
+                    }
+                }
+
+                return Ok(()); // Terminate
+            }
+            _ => {
+                // Fallthrough
+            }
+        }
+    }
+
+    // The assignment expression matches none of the special cases.
+    // We should actually use `gen_store_target`.
     let name = if let ExprKind::Name { id, .. } = &target.node {
         format!("{id}.addr")
     } else {
@@ -288,8 +364,6 @@ pub fn gen_assign<'ctx, G: CodeGenerator>(
     }
     let val = value.to_basic_value_enum(ctx, generator, target.custom.unwrap())?;
     ctx.builder.build_store(ptr, val).unwrap();
-        }
-    };
     Ok(())
 }
 
@@ -315,9 +389,6 @@ pub fn gen_for<G: CodeGenerator>(
     let orelse_bb =
         if orelse.is_empty() { cont_bb } else { ctx.ctx.append_basic_block(current, "for.orelse") };
 
-    // Whether the iterable is a range() expression
-    let is_iterable_range_expr = ctx.unifier.unioned(iter.custom.unwrap(), ctx.primitives.range);
-
     // The BB containing the increment expression
     let incr_bb = ctx.ctx.append_basic_block(current, "for.incr");
     // The BB containing the loop condition check
@@ -331,69 +402,20 @@ pub fn gen_for<G: CodeGenerator>(
     } else {
         return Ok(());
     };
-    if is_iterable_range_expr {
-        let iter_val = RangeValue::from_ptr_val(iter_val.into_pointer_value(), Some("range"));
-        // Internal variable for loop; Cannot be assigned
-        let i = generator.gen_var_alloc(ctx, int32.into(), Some("for.i.addr"))?;
-        // Variable declared in "target" expression of the loop; Can be reassigned *or* shadowed
-        let Some(target_i) = generator.gen_store_target(ctx, target, Some("for.target.addr"))?
-        else {
-            unreachable!()
-        };
-        let (start, stop, step) = destructure_range(ctx, iter_val);
-
-        ctx.builder.build_store(i, start).unwrap();
-
-        // Check "If step is zero, ValueError is raised."
-        let rangenez =
-            ctx.builder.build_int_compare(IntPredicate::NE, step, int32.const_zero(), "").unwrap();
-        ctx.make_assert(
-            generator,
-            rangenez,
-            "ValueError",
-            "range() arg 3 must not be zero",
-            [None, None, None],
-            ctx.current_loc,
-        );
-        ctx.builder.build_unconditional_branch(cond_bb).unwrap();
 
+    // The implementation of the for loop logic depends on
+    // the typechecker type of `iter`.
+    let iter_ty = iter.custom.unwrap();
+    match &*ctx.unifier.get_ty(iter_ty) {
+        TypeEnum::TObj { obj_id, params, .. }
+            if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
         {
-            ctx.builder.position_at_end(cond_bb);
-            ctx.builder
-                .build_conditional_branch(
-                    gen_in_range_check(
-                        ctx,
-                        ctx.builder.build_load(i, "").map(BasicValueEnum::into_int_value).unwrap(),
-                        stop,
-                        step,
-                    ),
-                    body_bb,
-                    orelse_bb,
-                )
-                .unwrap();
-        }
+            // `iter` is a `List[T]`, and `T` is the element type
 
-        ctx.builder.position_at_end(incr_bb);
-        let next_i = ctx
-            .builder
-            .build_int_add(
-                ctx.builder.build_load(i, "").map(BasicValueEnum::into_int_value).unwrap(),
-                step,
-                "inc",
-            )
-            .unwrap();
-        ctx.builder.build_store(i, next_i).unwrap();
-        ctx.builder.build_unconditional_branch(cond_bb).unwrap();
+            // Get the `T` out of `List[T]` - it is defined to be the 1st param.
+            let list_elem_ty = iter_type_vars(params).nth(0).unwrap().ty;
 
-        ctx.builder.position_at_end(body_bb);
-        ctx.builder
-            .build_store(
-                target_i,
-                ctx.builder.build_load(i, "").map(BasicValueEnum::into_int_value).unwrap(),
-            )
-            .unwrap();
-        generator.gen_block(ctx, body.iter())?;
-    } else {
+            // Implementation
             let index_addr = generator.gen_var_alloc(ctx, size_t.into(), Some("for.index.addr"))?;
             ctx.builder.build_store(index_addr, size_t.const_zero()).unwrap();
             let len = ctx
@@ -431,9 +453,86 @@ pub fn gen_for<G: CodeGenerator>(
                 .map(BasicValueEnum::into_int_value)
                 .unwrap();
             let val = ctx.build_gep_and_load(arr_ptr, &[index], Some("val"));
-        generator.gen_assign(ctx, target, val.into())?;
+            generator.gen_assign(ctx, target, val.into(), list_elem_ty)?;
             generator.gen_block(ctx, body.iter())?;
         }
+        TypeEnum::TObj { obj_id, .. }
+            if *obj_id == ctx.primitives.range.obj_id(&ctx.unifier).unwrap() =>
+        {
+            // `iter` is a `range(start, stop, step)`, and `int32` is the element type
+
+            let iter_val = RangeValue::from_ptr_val(iter_val.into_pointer_value(), Some("range"));
+            // Internal variable for loop; Cannot be assigned
+            let i = generator.gen_var_alloc(ctx, int32.into(), Some("for.i.addr"))?;
+            // Variable declared in "target" expression of the loop; Can be reassigned *or* shadowed
+            let Some(target_i) =
+                generator.gen_store_target(ctx, target, Some("for.target.addr"))?
+            else {
+                unreachable!()
+            };
+            let (start, stop, step) = destructure_range(ctx, iter_val);
+
+            ctx.builder.build_store(i, start).unwrap();
+
+            // Check "If step is zero, ValueError is raised."
+            let rangenez = ctx
+                .builder
+                .build_int_compare(IntPredicate::NE, step, int32.const_zero(), "")
+                .unwrap();
+            ctx.make_assert(
+                generator,
+                rangenez,
+                "ValueError",
+                "range() arg 3 must not be zero",
+                [None, None, None],
+                ctx.current_loc,
+            );
+            ctx.builder.build_unconditional_branch(cond_bb).unwrap();
+
+            {
+                ctx.builder.position_at_end(cond_bb);
+                ctx.builder
+                    .build_conditional_branch(
+                        gen_in_range_check(
+                            ctx,
+                            ctx.builder
+                                .build_load(i, "")
+                                .map(BasicValueEnum::into_int_value)
+                                .unwrap(),
+                            stop,
+                            step,
+                        ),
+                        body_bb,
+                        orelse_bb,
+                    )
+                    .unwrap();
+            }
+
+            ctx.builder.position_at_end(incr_bb);
+            let next_i = ctx
+                .builder
+                .build_int_add(
+                    ctx.builder.build_load(i, "").map(BasicValueEnum::into_int_value).unwrap(),
+                    step,
+                    "inc",
+                )
+                .unwrap();
+            ctx.builder.build_store(i, next_i).unwrap();
+            ctx.builder.build_unconditional_branch(cond_bb).unwrap();
+
+            ctx.builder.position_at_end(body_bb);
+            ctx.builder
+                .build_store(
+                    target_i,
+                    ctx.builder.build_load(i, "").map(BasicValueEnum::into_int_value).unwrap(),
+                )
+                .unwrap();
+            generator.gen_block(ctx, body.iter())?;
+        }
+        _ => {
+            panic!("unsupported iterator type in for loop: {}", ctx.unifier.stringify(iter_ty))
+        }
+    }
 
     for (k, (_, _, counter)) in &var_assignment {
         let (_, static_val, counter2) = ctx.var_assignment.get_mut(k).unwrap();
@@ -1575,14 +1674,18 @@ pub fn gen_stmt<G: CodeGenerator>(
         }
         StmtKind::AnnAssign { target, value, .. } => {
             if let Some(value) = value {
+                let value_ty = value.custom.unwrap();
                 let Some(value) = generator.gen_expr(ctx, value)? else { return Ok(()) };
-                generator.gen_assign(ctx, target, value)?;
+                generator.gen_assign(ctx, target, value, value_ty)?;
             }
         }
         StmtKind::Assign { targets, value, .. } => {
+            // TODO: Is the implementation wrong? It looks very strange.
+            let value_ty = value.custom.unwrap();
             let Some(value) = generator.gen_expr(ctx, value)? else { return Ok(()) };
+
             for target in targets {
-                generator.gen_assign(ctx, target, value.clone())?;
+                generator.gen_assign(ctx, target, value.clone(), value_ty)?;
             }
         }
         StmtKind::Continue { .. } => {
@@ -1596,6 +1699,7 @@ pub fn gen_stmt<G: CodeGenerator>(
         StmtKind::For { .. } => generator.gen_for(ctx, stmt)?,
         StmtKind::With { .. } => generator.gen_with(ctx, stmt)?,
         StmtKind::AugAssign { target, op, value, .. } => {
+            let value_ty = value.custom.unwrap();
             let value = gen_binop_expr(
                 generator,
                 ctx,
@@ -1604,7 +1708,7 @@ pub fn gen_stmt<G: CodeGenerator>(
                 value,
                 stmt.location,
             )?;
-            generator.gen_assign(ctx, target, value.unwrap())?;
+            generator.gen_assign(ctx, target, value.unwrap(), value_ty)?;
         }
         StmtKind::Try { .. } => gen_try(generator, ctx, stmt)?,
         StmtKind::Raise { exc, .. } => {

nac3core/src/lib.rs

@@ -23,3 +23,4 @@ pub mod codegen;
 pub mod symbol_resolver;
 pub mod toplevel;
 pub mod typecheck;
+pub(crate) mod util;

nac3core/src/toplevel/builtins.rs

@@ -5,7 +5,7 @@ use indexmap::IndexMap;
 use inkwell::{
     attributes::{Attribute, AttributeLoc},
     types::{BasicMetadataTypeEnum, BasicType},
-    values::{BasicMetadataValueEnum, BasicValue, CallSiteValue},
+    values::{AnyValue, BasicMetadataValueEnum, BasicValue, CallSiteValue},
     IntPredicate,
 };
 use itertools::Either;
@@ -14,15 +14,24 @@ use strum::IntoEnumIterator;
 use crate::{
     codegen::{
         builtin_fns,
-        classes::{ArrayLikeValue, NDArrayValue, ProxyValue, RangeValue, TypedArrayLikeAccessor},
+        classes::{ProxyValue, RangeValue},
         expr::destructure_range,
-        irrt::*,
-        numpy::*,
+        irrt::{
+            calculate_len_for_slice_range,
+            numpy::ndarray::{call_nac3_ndarray_len, NpArray},
+        },
+        model::*,
+        numpy::{
+            gen_ndarray_array, gen_ndarray_copy, gen_ndarray_eye, gen_ndarray_fill,
+            gen_ndarray_identity,
+        },
+        numpy_new,
         stmt::exn_constructor,
     },
     symbol_resolver::SymbolValue,
     toplevel::{helper::PrimDef, numpy::make_ndarray_ty},
     typecheck::typedef::{into_var_map, iter_type_vars, TypeVar, VarMap},
+    util::SizeVariant,
 };
 
 use super::*;
@@ -278,21 +287,12 @@ pub fn get_builtins(unifier: &mut Unifier, primitives: &PrimitiveStore) -> Built
         .collect()
 }
 
-/// A helper enum used by [`BuiltinBuilder`]
-#[derive(Clone, Copy)]
-enum SizeVariant {
-    Bits32,
-    Bits64,
-}
-
-impl SizeVariant {
-    fn of_int(self, primitives: &PrimitiveStore) -> Type {
-        match self {
+fn get_size_variant_of_int(size_variant: SizeVariant, primitives: &PrimitiveStore) -> Type {
+    match size_variant {
         SizeVariant::Bits32 => primitives.int32,
         SizeVariant::Bits64 => primitives.int64,
     }
 }
-}
 
 struct BuiltinBuilder<'a> {
     unifier: &'a mut Unifier,
@@ -1061,7 +1061,7 @@ impl<'a> BuiltinBuilder<'a> {
         );
 
         // The size variant of the function determines the size of the returned int.
-        let int_sized = size_variant.of_int(self.primitives);
+        let int_sized = get_size_variant_of_int(size_variant, self.primitives);
 
         let ndarray_int_sized =
             make_ndarray_ty(self.unifier, self.primitives, Some(int_sized), Some(common_ndim.ty));
@@ -1086,7 +1086,7 @@ impl<'a> BuiltinBuilder<'a> {
                 let arg_ty = fun.0.args[0].ty;
                 let arg = args[0].1.clone().to_basic_value_enum(ctx, generator, arg_ty)?;
 
-                let ret_elem_ty = size_variant.of_int(&ctx.primitives);
+                let ret_elem_ty = get_size_variant_of_int(size_variant, &ctx.primitives);
                 Ok(Some(builtin_fns::call_round(generator, ctx, (arg_ty, arg), ret_elem_ty)?))
             }),
         )
@@ -1127,7 +1127,7 @@ impl<'a> BuiltinBuilder<'a> {
             make_ndarray_ty(self.unifier, self.primitives, Some(float), Some(common_ndim.ty));
 
         // The size variant of the function determines the type of int returned
-        let int_sized = size_variant.of_int(self.primitives);
+        let int_sized = get_size_variant_of_int(size_variant, self.primitives);
         let ndarray_int_sized =
             make_ndarray_ty(self.unifier, self.primitives, Some(int_sized), Some(common_ndim.ty));
 
@@ -1150,7 +1150,7 @@ impl<'a> BuiltinBuilder<'a> {
                 let arg_ty = fun.0.args[0].ty;
                 let arg = args[0].1.clone().to_basic_value_enum(ctx, generator, arg_ty)?;
 
-                let ret_elem_ty = size_variant.of_int(&ctx.primitives);
+                let ret_elem_ty = get_size_variant_of_int(size_variant, &ctx.primitives);
                 let func = match kind {
                     Kind::Ceil => builtin_fns::call_ceil,
                     Kind::Floor => builtin_fns::call_floor,
@@ -1202,9 +1202,9 @@ impl<'a> BuiltinBuilder<'a> {
             &[(self.ndarray_factory_fn_shape_arg_tvar.ty, "shape")],
             Box::new(move |ctx, obj, fun, args, generator| {
                 let func = match prim {
-                    PrimDef::FunNpNDArray | PrimDef::FunNpEmpty => gen_ndarray_empty,
-                    PrimDef::FunNpZeros => gen_ndarray_zeros,
-                    PrimDef::FunNpOnes => gen_ndarray_ones,
+                    PrimDef::FunNpNDArray | PrimDef::FunNpEmpty => numpy_new::gen_ndarray_empty,
+                    PrimDef::FunNpZeros => numpy_new::gen_ndarray_zeros,
+                    PrimDef::FunNpOnes => numpy_new::gen_ndarray_ones,
                     _ => unreachable!(),
                 };
                 func(ctx, &obj, fun, &args, generator).map(|val| Some(val.as_basic_value_enum()))
@@ -1272,7 +1272,7 @@ impl<'a> BuiltinBuilder<'a> {
                     // type variable
                     &[(self.list_int32, "shape"), (tv.ty, "fill_value")],
                     Box::new(move |ctx, obj, fun, args, generator| {
-                        gen_ndarray_full(ctx, &obj, fun, &args, generator)
+                        numpy_new::gen_ndarray_full(ctx, &obj, fun, &args, generator)
                             .map(|val| Some(val.as_basic_value_enum()))
                     }),
                 )
@@ -1464,51 +1464,19 @@ impl<'a> BuiltinBuilder<'a> {
                                 }
                             }
                             TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
-                                let llvm_i32 = ctx.ctx.i32_type();
-                                let llvm_usize = generator.get_size_type(ctx.ctx);
+                                // Parse `arg`
+                                let sizet = IntModel(generator.get_size_type(ctx.ctx));
 
-                                let arg = NDArrayValue::from_ptr_val(
-                                    arg.into_pointer_value(),
-                                    llvm_usize,
-                                    None,
-                                );
+                                let ndarray_ptr_model =
+                                    PointerModel(StructModel(NpArray { sizet }));
+                                let ndarray_ptr =
+                                    ndarray_ptr_model.review(ctx.ctx, arg.as_any_value_enum());
 
-                                let ndims = arg.dim_sizes().size(ctx, generator);
-                                ctx.make_assert(
-                                    generator,
-                                    ctx.builder
-                                        .build_int_compare(
-                                            IntPredicate::NE,
-                                            ndims,
-                                            llvm_usize.const_zero(),
-                                            "",
-                                        )
-                                        .unwrap(),
-                                    "0:TypeError",
-                                    &format!("{name}() of unsized object", name = prim.name()),
-                                    [None, None, None],
-                                    ctx.current_loc,
-                                );
-
-                                let len = unsafe {
-                                    arg.dim_sizes().get_typed_unchecked(
-                                        ctx,
-                                        generator,
-                                        &llvm_usize.const_zero(),
-                                        None,
-                                    )
-                                };
-
-                                if len.get_type().get_bit_width() == 32 {
-                                    Some(len.into())
-                                } else {
-                                    Some(
-                                        ctx.builder
-                                            .build_int_truncate(len, llvm_i32, "len")
-                                            .map(Into::into)
-                                            .unwrap(),
-                                    )
-                                }
+                                // Calculate len
+                                // NOTE: Unsized object is asserted in IRRT
+                                let len = call_nac3_ndarray_len(generator, ctx, ndarray_ptr);
+                                let len = len.signed_cast_to_fixed(ctx, Int32, "len_i32");
+                                Some(len.value.as_basic_value_enum())
                             }
                             _ => unreachable!(),
                         }

nac3core/src/util.rs

@@ -0,0 +1,6 @@
+/// A helper enum used by [`BuiltinBuilder`]
+#[derive(Debug, Clone, Copy, PartialEq, Eq)]
+pub enum SizeVariant {
+    Bits32,
+    Bits64,
+}