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PyDoc: fix incorrect type for dynamic arrays in generated docs

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Correct types for dynamic arrays such as Image.pixels which was
documented as a `float` type instead of `bpy_prop_array[float]`.

Ref !158316
This commit is contained in:
Campbell Barton 2026-05-08 14:59:35 +10:00
parent 4b6d497189
commit 9b25f436c1
1 changed files with 26 additions and 11 deletions
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37
scripts/modules/_rna_info.py
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@ -285,6 +285,7 @@ class InfoPropertyRNA:
"max",
"array_length",
"array_dimensions",
"is_array",
"collection_type",
"type",
"fixed_type",
@ -314,7 +315,13 @@ class InfoPropertyRNA:
self.min = getattr(rna_prop, "hard_min", -1)
self.max = getattr(rna_prop, "hard_max", -1)
self.array_length = getattr(rna_prop, "array_length", 0)
self.array_dimensions = getattr(rna_prop, "array_dimensions", ())[:]
# Strip RNA's trailing zero padding so `len()` gives the dim count.
array_dimensions = tuple(getattr(rna_prop, "array_dimensions", ()))
while array_dimensions and array_dimensions[-1] == 0:
array_dimensions = array_dimensions[:-1]
self.array_dimensions = array_dimensions
# True for dynamic arrays too, where `array_length` is 0.
self.is_array = getattr(rna_prop, "is_array", bool(self.array_length))
self.collection_type = GetInfoStructRNA(rna_prop.srna)
self.subtype = getattr(rna_prop, "subtype", "")
self.is_required = rna_prop.is_required
@ -362,7 +369,7 @@ class InfoPropertyRNA:
if self.array_length:
self.default = tuple(getattr(rna_prop, "default_array", ()))
if self.array_dimensions[1] != 0: # Multi-dimensional array, convert default flat one accordingly.
if len(self.array_dimensions) > 1: # Multi-dimensional array, convert default flat one accordingly.
self.default_str = tuple(float_as_string(v) if self.type == "float" else str(v) for v in self.default)
for dim in self.array_dimensions[::-1]:
if dim != 0:
@ -394,7 +401,8 @@ class InfoPropertyRNA:
else:
self.default_str = repr(self.default)
elif self.array_length:
if self.array_dimensions[1] == 0: # single dimension array, we already took care of multi-dimensions ones.
# Single dimension array, we already took care of multi-dimensions ones.
if len(self.array_dimensions) == 1:
# Special case for floats.
if self.type == "float" and len(self.default) > 0:
self.default_str = seq_as_tuple_str(float_as_string(f) for f in self.default)
@ -445,13 +453,17 @@ class InfoPropertyRNA:
type_str += _RNA_TYPE_TO_PYTHON.get(self.type, self.type)
if self.type == "string" and self.subtype == "BYTE_STRING":
type_str = "bytes"
if self.array_length:
if self.array_dimensions[1] != 0:
type_info.append("multi-dimensional array of {:s} items".format(
" * ".join(str(d) for d in self.array_dimensions if d != 0)
))
if self.is_array:
array_dimensions_len = len(self.array_dimensions)
if self.array_length:
if array_dimensions_len > 1:
type_info.append("multi-dimensional array of {:s} items".format(
" * ".join(str(d) for d in self.array_dimensions)
))
else:
type_info.append("array of {:d} items".format(self.array_length))
else:
type_info.append("array of {:d} items".format(self.array_length))
type_info.append("dynamic array")
# Describe mathutils types; logic mirrors pyrna_math_object_from_array
base_type_str = type_str
@ -477,11 +489,14 @@ class InfoPropertyRNA:
# Array properties that didn't match a mathutils type above
# should not be typed as a bare scalar (e.g. ``float``).
if type_str == base_type_str:
# Wrap once per dimension (e.g. 2D -> `X[X[float]]`).
if as_arg:
type_str = "Sequence[{:s}]".format(base_type_str)
wrap_fmt = "Sequence[{:s}]"
else:
# Escape the space as: :class:`Class`[X] isn't valid RST.
type_str = class_fmt.format("bpy_prop_array") + "\\ [{:s}]".format(base_type_str)
wrap_fmt = class_fmt.format("bpy_prop_array") + "\\ [{:s}]"
for _ in range(max(array_dimensions_len, 1)):
type_str = wrap_fmt.format(type_str)
if self.type in {"float", "int"}:
type_info.append("in [{:s}, {:s}]".format(range_str(self.min), range_str(self.max)))