Depend on fastfields-helpers for enums and argument normalisation

CLAUDE.md

@@ -12,7 +12,8 @@ bindings.
  layer wraps them so every function accepts numpy arrays and **returns a fresh
  numpy array** (inputs untouched unless `inplace=True`).
 - Adds validation, zero-copy batch broadcasting, and output allocation.
-- Depends only on `fastfields-dlpack` + numpy.
+- Depends on `fastfields-dlpack` (compiled bindings) + `fastfields-helpers`
+ (the `Spline`/`Bound` enums and argument normalisers) + numpy.
 
 ## Exposed capabilities (feature level)
 - **Distance**: `dt_euclidean`, `dt_l1` (along

fastfields/numpy/__init__.py

@@ -36,7 +36,7 @@
 
 from __future__ import annotations
 
-from fastfields.dlpack import Bound, Spline
+from fastfields.helpers import Bound, Spline
 
 from ._dt import (
  dt_euclidean,

fastfields/numpy/_resample.py

@@ -5,7 +5,7 @@
 from typing import Sequence
 
 import fastfields.dlpack as _ff
-from fastfields.dlpack import (
+from fastfields.helpers import (
  anchor_scale_shift,
  infer_ndim,
  resolve_out_spatial,
@@ -82,7 +82,7 @@ def _resize_shapes(
  """Return the batch, input-spatial, and output-spatial shapes.
 
  The output spatial shape is resolved via
- :func:`fastfields.dlpack.resolve_out_spatial` so every backend shares one
+ :func:`fastfields.helpers.resolve_out_spatial` so every backend shares one
  implementation. Raises ``ValueError`` if ``factor``/``shape`` do not have
  length ``ndim``.
  """

fastfields/numpy/_util.py

@@ -9,11 +9,11 @@
 
 from typing import Any
 
-# `order`/`bound` normalisation is centralised in fastfields.dlpack so
+# `order`/`bound` normalisation is centralised in fastfields.helpers so
 # every backend shares one implementation; re-export under the private
 # names the numpy modules (_dt, _resample) already import.
-from fastfields.dlpack import as_bound as _as_bound # noqa: F401
-from fastfields.dlpack import as_spline as _as_spline # noqa: F401
+from fastfields.helpers import as_bound as _as_bound # noqa: F401
+from fastfields.helpers import as_spline as _as_spline # noqa: F401
 
 import numpy as np
 

pyproject.toml

@@ -41,8 +41,13 @@ classifiers = [
 # (fires when `git describe` can't find a tag, e.g. a shallow-clone CI
 # misconfiguration) would also satisfy `==0.*` if it were ever accidentally
 # published. That's an accepted risk, not something this pin tries to solve.
+# fastfields-helpers is the pure-Python enums/normalisation package this
+# wrapper's argument handling is built on (fastfields.helpers.Bound/Spline/
+# as_bound/...) -- same bare-wildcard convention as fastfields-dlpack above,
+# for the same reason: it moves on the same 0.x line.
 dependencies = [
  "fastfields-dlpack==0.*",
+ "fastfields-helpers==0.*",
  "numpy",
 ]
 

tests/test_numpy.py

@@ -647,7 +647,7 @@ def test_restriction_runs_and_shapes():
 
 
 def test_anchor_scale_shift_mapping():
- from fastfields.dlpack import anchor_scale_shift as _anchor_scale_shift
+ from fastfields.helpers import anchor_scale_shift as _anchor_scale_shift
 
  # 8 -> 4 downsample; scale/shift per torch-interpol convention.
  for name, abbr, exp_scale, exp_shift in [
@@ -664,7 +664,7 @@ def test_anchor_scale_shift_mapping():
 
 
 def test_anchor_unknown_raises():
- from fastfields.dlpack import anchor_scale_shift as _anchor_scale_shift
+ from fastfields.helpers import anchor_scale_shift as _anchor_scale_shift
 
  with pytest.raises(ValueError, match="anchor"):
  _anchor_scale_shift("nope", (8,), (4,), 1)