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cleanup
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2 changed files with 3 additions and 54 deletions
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@ -99,51 +99,6 @@ class H5JsonDict(JsonDict):
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)
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)
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# def to_json(self, info: SerializationInfo):
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# """
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# Serialize H5Proxy to JSON, as the interface does,
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# in cases when the interface is not able to be used
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# (eg. like when used as an `extra` field in a model without a type annotation)
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# """
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# from numpydantic.serialization import postprocess_json
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#
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# if info.round_trip:
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# as_json = {
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# "type": H5Interface.name,
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# }
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# as_json.update(self._h5arraypath._asdict())
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# else:
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# try:
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# dset = self.open()
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# as_json = dset[:].tolist()
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# finally:
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# self.close()
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# return postprocess_json(as_json, info)
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# def _make_pydantic_schema():
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# return core_schema.typed_dict_schema(
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# {
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# "file": core_schema.typed_dict_field(
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# core_schema.str_schema(), required=True
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# ),
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# "path": core_schema.typed_dict_field(
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# core_schema.str_schema(), required=True
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# ),
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# "field": core_schema.typed_dict_field(
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# core_schema.union_schema(
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# [
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# core_schema.str_schema(),
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# core_schema.list_schema(core_schema.str_schema()),
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# ],
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# ),
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# required=True,
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# ),
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# },
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# # serialization=
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# )
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class H5Proxy:
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class H5Proxy:
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"""
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"""
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Proxy class to mimic numpy-like array behavior with an HDF5 array
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Proxy class to mimic numpy-like array behavior with an HDF5 array
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@ -166,12 +121,6 @@ class H5Proxy:
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annotation_dtype (dtype): Optional - the dtype of our type annotation
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annotation_dtype (dtype): Optional - the dtype of our type annotation
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"""
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"""
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# __pydantic_serializer__ = SchemaSerializer(
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# core_schema.plain_serializer_function_ser_schema(
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# jsonize_array, when_used="json", info_arg=True
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# ),
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# )
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def __init__(
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def __init__(
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self,
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self,
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file: Union[Path, str],
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file: Union[Path, str],
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@ -148,7 +148,7 @@ def dtype_by_interface(request):
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@pytest.fixture()
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@pytest.fixture()
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def dtype_by_interface_instance(all_passing_cases, tmp_output_dir_func):
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def dtype_by_interface_instance(dtype_by_interface, tmp_output_dir_func):
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array = all_passing_cases.array(path=tmp_output_dir_func)
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array = dtype_by_interface.array(path=tmp_output_dir_func)
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instance = all_passing_cases.model(array=array)
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instance = dtype_by_interface.model(array=array)
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return instance
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return instance
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