Drop Python 2/3 compatibility shim from util.py - #122
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Replace the version_info-gated import of subprocess.check_output /
getoutput (and the py3 / spop / branched fpath usage) with a direct
import of subprocess.getoutput. Also defines fpath unconditionally at
module level so the manylinux1 fallback no longer references an
undefined name on macOS/Windows.
Gate numpy .astype path with isinstance check in _FFIArray
The duck-typed try/except (TypeError, AttributeError) around
seq.astype(np.float64) caught two distinct conditions:
1. numpy arrays whose buffer wasn't writable (TypeError from
from_buffer) -- handled by retrying with from_buffer_copy.
2. array.array / list / tuple inputs that lack .astype entirely
(AttributeError) -- handled by falling through to
array_type.from_buffer(array("d", seq)).
Make the numpy vs non-numpy branch explicit with isinstance(seq,
np.ndarray) so the .astype call lives on a known-numpy path. Resolves
the ty 'possibly-missing-attribute' diagnostic on .astype without
changing runtime behaviour for any input type.
The two .astype calls carry # ty: ignore[no-matching-overload]
because ty's current numpy stubs can't unify any dtype argument form
(np.float64, "float64", np.dtype(...)) against the overloaded
signature -- a stubs limitation rather than a real type error.
Signed-off-by: Stephan Hügel <shugel@tcd.ie>
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Replace the version_info-gated import of subprocess.check_output / getoutput (and the py3 / spop / branched fpath usage) with a direct import of subprocess.getoutput. Also defines fpath unconditionally at module level so the manylinux1 fallback no longer references an undefined name on macOS/Windows.
Gate numpy .astype path with isinstance check in _FFIArray
The duck-typed try/except (TypeError, AttributeError) around seq.astype(np.float64) caught two distinct conditions:
Make the numpy vs non-numpy branch explicit with isinstance(seq, np.ndarray) so the .astype call lives on a known-numpy path. Resolves the ty 'possibly-missing-attribute' diagnostic on .astype without changing runtime behaviour for any input type.
The two .astype calls carry # ty: ignore[no-matching-overload] because ty's current numpy stubs can't unify any dtype argument form (np.float64, "float64", np.dtype(...)) against the overloaded signature -- a stubs limitation rather than a real type error.