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Harden serialization of temporal numpy types #1261

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Merged
merged 2 commits into from
Oct 24, 2025
Merged

Harden serialization of temporal numpy types #1261

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ee9556d
Harden serialization of temporal numpy types
robsdedude Oct 24, 2025
2508ccd
Merge branch '6.x' into harden-numpy-serializer
robsdedude Oct 24, 2025
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29 changes: 18 additions & 11 deletions src/neo4j/_codec/hydration/v1/temporal.py
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Original file line number Diff line number Diff line change
Expand Up @@ -216,16 +216,16 @@ def dehydrate_np_datetime(value):
"""
if np.isnat(value):
return None
year = value.astype("datetime64[Y]").astype(int) + 1970
year = value.astype("datetime64[Y]").astype(np.int64) + 1970
if not 0 < year <= 9999:
# while we could encode years outside the range, they would fail
# when retrieved from the database.
raise ValueError(
f"Year out of range ({MIN_YEAR:d}..{MAX_YEAR:d}) found {year}"
)
seconds = value.astype(np.dtype("datetime64[s]")).astype(int)
seconds = value.astype(np.dtype("datetime64[s]")).astype(np.int64)
nanoseconds = (
value.astype(np.dtype("datetime64[ns]")).astype(int)
value.astype(np.dtype("datetime64[ns]")).astype(np.int64)
% _NANO_SECONDS
)
return Structure(b"d", seconds, nanoseconds)
Expand Down Expand Up @@ -299,6 +299,7 @@ def dehydrate_timedelta(value):


if np is not None:
_NUMPY_DURATION_NS_FALLBACK = object()
_NUMPY_DURATION_UNITS = {
"Y": "years",
"M": "months",
Expand All @@ -310,6 +311,9 @@ def dehydrate_timedelta(value):
"ms": "milliseconds",
"us": "microseconds",
"ns": "nanoseconds",
"ps": _NUMPY_DURATION_NS_FALLBACK,
"fs": _NUMPY_DURATION_NS_FALLBACK,
"as": _NUMPY_DURATION_NS_FALLBACK,
}

def dehydrate_np_timedelta(value):
Expand All @@ -323,14 +327,17 @@ def dehydrate_np_timedelta(value):
if np.isnat(value):
return None
unit, step_size = np.datetime_data(value)
numer = int(value.astype(int))
# raise RuntimeError((type(numer), type(step_size)))
kwarg = _NUMPY_DURATION_UNITS.get(unit)
if kwarg is not None:
return dehydrate_duration(Duration(**{kwarg: numer * step_size}))
return dehydrate_duration(
Duration(nanoseconds=value.astype("timedelta64[ns]").astype(int))
)
numer = int(value.astype(np.int64))
try:
kwarg = _NUMPY_DURATION_UNITS[unit]
except KeyError:
raise TypeError(
f"Unsupported numpy.timedelta64 unit: {unit!r}"
) from None
if kwarg is _NUMPY_DURATION_NS_FALLBACK:
nanoseconds = value.astype("timedelta64[ns]").astype(np.int64)
return dehydrate_duration(Duration(nanoseconds=nanoseconds))
return dehydrate_duration(Duration(**{kwarg: numer * step_size}))


if pd is not None:
Expand Down