TEMP: override DataClass.ToDict()

This commit is contained in:
InsanePrawn 2023-03-21 20:53:17 +01:00
parent 53ef22d6b8
commit 72f4d4948e

View file

@ -2,23 +2,27 @@ from __future__ import annotations
from dataclasses import dataclass
from munch import Munch
from typing import ClassVar, Optional, Union, Mapping, Any, get_type_hints, get_origin, get_args, Iterable
from typing import ClassVar, Optional, Union, Mapping, Any, get_type_hints, get_origin, get_args, GenericAlias, Iterable
from types import UnionType
NoneType = type(None)
def munchclass(*args, init=False, **kwargs):
return dataclass(*args, init=init, slots=True, **kwargs)
def resolve_type_hint(hint: type) -> Iterable[type]:
def resolve_type_hint(hint: type, ignore_origins: list[type] = []) -> Iterable[type]:
origin = get_origin(hint)
args: Iterable[type] = get_args(hint)
if origin in ignore_origins:
return [hint]
if origin is Optional:
args = set(list(args) + [type(None)])
args = set(list(args) + [NoneType])
if origin in [Union, UnionType, Optional]:
results: list[type] = []
for arg in args:
results += resolve_type_hint(arg)
results += resolve_type_hint(arg, ignore_origins=ignore_origins)
return results
return [origin or hint]
@ -26,6 +30,8 @@ def resolve_type_hint(hint: type) -> Iterable[type]:
class DataClass(Munch):
_type_hints: ClassVar[dict[str, Any]]
_strip_hidden: ClassVar[bool] = False
_sparse: ClassVar[bool] = False
def __init__(self, d: dict = {}, validate: bool = True, **kwargs):
self.update(d | kwargs, validate=validate)
@ -39,7 +45,7 @@ class DataClass(Munch):
type_hints = cls._type_hints
if key in type_hints:
_classes = tuple[type](resolve_type_hint(type_hints[key]))
optional = type(None) in _classes
optional = NoneType in _classes
if issubclass(_classes[0], dict):
assert isinstance(value, dict) or optional
target_class = _classes[0]
@ -89,7 +95,20 @@ class DataClass(Munch):
@classmethod
def fromDict(cls, values: Mapping[str, Any], validate: bool = True):
return cls(**cls.transform(values, validate))
return cls(d=values, validate=validate)
def toDict(
self,
strip_hidden: Optional[bool] = None,
sparse: Optional[bool] = None,
):
return strip_dict(
self,
hints=self._type_hints,
strip_hidden=self._strip_hidden if strip_hidden is None else strip_hidden,
sparse=self._sparse if sparse is None else sparse,
recursive=True,
)
def update(self, d: Mapping[str, Any], validate: bool = True):
Munch.update(self, type(self).transform(d, validate))
@ -100,3 +119,92 @@ class DataClass(Munch):
def __repr__(self):
return f'{type(self)}{dict.__repr__(self.toDict())}'
def toYaml(self, strip_hidden: bool = False, sparse: bool = False, **yaml_args) -> str:
import yaml
return yaml.dump(
self.toDict(strip_hidden=strip_hidden, sparse=sparse),
**yaml_args,
)
def toToml(self, strip_hidden: bool = False, sparse: bool = False, **toml_args) -> str:
import toml
return toml.dumps(
self.toDict(strip_hidden=strip_hidden, sparse=sparse),
**toml_args,
)
def flatten_hints(hints: Any) -> list[Any]:
if not isinstance(hints, (list, tuple)):
yield hints
return
for i in hints:
yield from flatten_hints(i)
def strip_dict(
d: dict[Any, Any],
hints: dict[str, Any],
strip_hidden: bool = False,
sparse: bool = False,
recursive: bool = True,
) -> dict[Any, Any]:
result = dict(d)
if not (strip_hidden or sparse or result):
print(f"shortcircuiting {d=}")
return result
print(f"Stripping {result} with hints: {hints}")
for k, v in d.items():
if not isinstance(k, str):
print(f"skipping unknown key type {k=}")
continue
if strip_hidden and k.startswith('_'):
result.pop(k)
continue
if sparse and (v is None and NoneType in resolve_type_hint(hints.get(k, "abc"))):
print(f"popping empty {k}")
result.pop(k)
continue
if recursive and isinstance(v, dict):
if not v:
result[k] = {}
continue
if isinstance(v, DataClass):
print(f"Dataclass detected in {k=}")
result[k] = v.toDict(strip_hidden=strip_hidden, sparse=sparse)
continue
if isinstance(v, Munch):
print(f"Converting munch {k=}")
result[k] = v.toDict()
if k not in hints:
print(f"skipping unknown {k=}")
continue
print(f"STRIPPING RECURSIVELY: {k}: {v}, parent hints: {hints[k]}")
_subhints = {}
_hints = resolve_type_hint(hints[k], [dict])
hints_flat = list(flatten_hints(_hints))
print(f"going over hints for {k}: {_hints=} {hints_flat=}")
for hint in hints_flat:
print(f"working on hint: {hint}")
if get_origin(hint) == dict:
_valtype = get_args(hint)[1]
_subhints = {n: _valtype for n in v.keys()}
print(f"generated {_subhints=} from {_valtype=}")
break
if isinstance(hint, type) and issubclass(hint, DataClass):
_subhints = hint._type_hints
print(f"found subhints: {_subhints}")
break
else:
print(f"ignoring {hint=}")
print(f"STRIPPING SUBDICT {k=} WITH {_subhints=}")
result[k] = strip_dict(
v,
hints=_subhints,
sparse=sparse,
strip_hidden=strip_hidden,
recursive=recursive,
)
return result