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https://github.com/p2p-ld/numpydantic.git
synced 2024-11-14 18:54:28 +00:00
scratch work on serializing from a proxy
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parent
0d0b310b6e
commit
1f7955d6ef
GPG key ID:
6DCB96EF1E4D232D
1 changed files with 69 additions and 72 deletions
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@ -50,14 +50,13 @@ from typing import (
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NamedTuple,
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Optional,
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Tuple,
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TypedDict,
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TypeVar,
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Union,
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)
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import numpy as np
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from pydantic import GetCoreSchemaHandler, SerializationInfo
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from pydantic_core import CoreSchema, core_schema
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from pydantic import SerializationInfo
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from pydantic_core import SchemaSerializer, core_schema
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from numpydantic.interface.interface import Interface, JsonDict
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from numpydantic.types import DtypeType, NDArrayType
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@ -88,17 +87,6 @@ class H5ArrayPath(NamedTuple):
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"""Refer to a specific field within a compound dtype"""
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class H5ArrayPathDict(TypedDict):
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"""Location specifier for arrays within an HDF5 file"""
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file: Union[Path, str]
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"""Location of HDF5 file"""
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path: str
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"""Path within the HDF5 file"""
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field: Optional[Union[str, List[str]]] = None
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"""Refer to a specific field within a compound dtype"""
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class H5JsonDict(JsonDict):
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"""Round-trip Json-able version of an HDF5 dataset"""
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@ -113,6 +101,51 @@ class H5JsonDict(JsonDict):
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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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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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"""
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Proxy class to mimic numpy-like array behavior with an HDF5 array
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@ -135,6 +168,12 @@ class H5Proxy:
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annotation_dtype (dtype): Optional - the dtype of our type annotation
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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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to_json, when_used="json", info_arg=True
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)
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)
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def __init__(
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self,
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file: Union[Path, str],
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@ -179,7 +218,8 @@ class H5Proxy:
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return obj[:]
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def __getattr__(self, item: str):
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if item not in ("shape", "__pydantic_validator__"):
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pdb.set_trace()
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if item == "__name__":
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# special case for H5Proxies that don't refer to a real file during testing
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return "H5Proxy"
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@ -294,67 +334,24 @@ class H5Proxy:
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v = np.array(v).astype("S32")
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return v
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@classmethod
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def __get_pydantic_core_schema__(
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cls, source_type: Any, handler: GetCoreSchemaHandler
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) -> CoreSchema:
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pdb.set_trace()
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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=core_schema.plain_serializer_function_ser_schema(
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cls.to_json, when_used="json"
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),
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)
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# @classmethod
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# def __get_pydantic_core_schema__(
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# cls, source_type: Any, handler: GetCoreSchemaHandler
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# ) -> CoreSchema:
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# return cls._make_pydantic_schema()
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# file: Union[Path, str]
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# """Location of HDF5 file"""
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# path: str
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# """Path within the HDF5 file"""
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# field: Optional[Union[str, List[str]]] = None
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# """Refer to a specific field within a compound dtype"""
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# }
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# )
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#
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# file: Union[Path, str]
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# """Location of HDF5 file"""
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# path: str
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# """Path within the HDF5 file"""
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# field: Optional[Union[str, List[str]]] = None
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# """Refer to a specific field within a compound dtype"""
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# }
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# )
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#
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#
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# @model_serializer(when_used="json")
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@staticmethod
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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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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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class H5Interface(Interface):
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