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from pathlib import Path
from typing import (
Any,
ClassVar,
DefaultDict,
Dict,
List,
Optional,
Sequence,
Set,
Tuple,
)
from datamodel_code_generator import DatetimeClassType, PythonVersion
from datamodel_code_generator.imports import (
IMPORT_DATE,
IMPORT_DATETIME,
IMPORT_TIME,
IMPORT_TIMEDELTA,
Import,
)
from datamodel_code_generator.model import DataModel, DataModelFieldBase
from datamodel_code_generator.model.base import UNDEFINED
from datamodel_code_generator.model.imports import IMPORT_DATACLASS, IMPORT_FIELD
from datamodel_code_generator.model.pydantic.base_model import Constraints
from datamodel_code_generator.model.types import DataTypeManager as _DataTypeManager
from datamodel_code_generator.model.types import type_map_factory
from datamodel_code_generator.reference import Reference
from datamodel_code_generator.types import DataType, StrictTypes, Types, chain_as_tuple
def _has_field_assignment(field: DataModelFieldBase) -> bool:
return bool(field.field) or not (
field.required
or (field.represented_default == 'None' and field.strip_default_none)
)
class DataClass(DataModel):
TEMPLATE_FILE_PATH: ClassVar[str] = 'dataclass.jinja2'
DEFAULT_IMPORTS: ClassVar[Tuple[Import, ...]] = (IMPORT_DATACLASS,)
def __init__(
self,
*,
reference: Reference,
fields: List[DataModelFieldBase],
decorators: Optional[List[str]] = None,
base_classes: Optional[List[Reference]] = None,
custom_base_class: Optional[str] = None,
custom_template_dir: Optional[Path] = None,
extra_template_data: Optional[DefaultDict[str, Dict[str, Any]]] = None,
methods: Optional[List[str]] = None,
path: Optional[Path] = None,
description: Optional[str] = None,
default: Any = UNDEFINED,
nullable: bool = False,
keyword_only: bool = False,
) -> None:
super().__init__(
reference=reference,
fields=sorted(fields, key=_has_field_assignment, reverse=False),
decorators=decorators,
base_classes=base_classes,
custom_base_class=custom_base_class,
custom_template_dir=custom_template_dir,
extra_template_data=extra_template_data,
methods=methods,
path=path,
description=description,
default=default,
nullable=nullable,
keyword_only=keyword_only,
)
class DataModelField(DataModelFieldBase):
_FIELD_KEYS: ClassVar[Set[str]] = {
'default_factory',
'init',
'repr',
'hash',
'compare',
'metadata',
'kw_only',
}
constraints: Optional[Constraints] = None
@property
def imports(self) -> Tuple[Import, ...]:
field = self.field
if field and field.startswith('field('):
return chain_as_tuple(super().imports, (IMPORT_FIELD,))
return super().imports
def self_reference(self) -> bool: # pragma: no cover
return isinstance(self.parent, DataClass) and self.parent.reference.path in {
d.reference.path for d in self.data_type.all_data_types if d.reference
}
@property
def field(self) -> Optional[str]:
"""for backwards compatibility"""
result = str(self)
if result == '':
return None
return result
def __str__(self) -> str:
data: Dict[str, Any] = {
k: v for k, v in self.extras.items() if k in self._FIELD_KEYS
}
if self.default != UNDEFINED and self.default is not None:
data['default'] = self.default
if self.required:
data = {
k: v
for k, v in data.items()
if k
not in (
'default',
'default_factory',
)
}
if not data:
return ''
if len(data) == 1 and 'default' in data:
default = data['default']
if isinstance(default, (list, dict)):
return f'field(default_factory=lambda :{repr(default)})'
return repr(default)
kwargs = [
f'{k}={v if k == "default_factory" else repr(v)}' for k, v in data.items()
]
return f'field({", ".join(kwargs)})'
class DataTypeManager(_DataTypeManager):
def __init__(
self,
python_version: PythonVersion = PythonVersion.PY_38,
use_standard_collections: bool = False,
use_generic_container_types: bool = False,
strict_types: Optional[Sequence[StrictTypes]] = None,
use_non_positive_negative_number_constrained_types: bool = False,
use_union_operator: bool = False,
use_pendulum: bool = False,
target_datetime_class: DatetimeClassType = DatetimeClassType.Datetime,
):
super().__init__(
python_version,
use_standard_collections,
use_generic_container_types,
strict_types,
use_non_positive_negative_number_constrained_types,
use_union_operator,
use_pendulum,
target_datetime_class,
)
datetime_map = (
{
Types.time: self.data_type.from_import(IMPORT_TIME),
Types.date: self.data_type.from_import(IMPORT_DATE),
Types.date_time: self.data_type.from_import(IMPORT_DATETIME),
Types.timedelta: self.data_type.from_import(IMPORT_TIMEDELTA),
}
if target_datetime_class is DatetimeClassType.Datetime
else {}
)
self.type_map: Dict[Types, DataType] = {
**type_map_factory(self.data_type),
**datetime_map,
}
|
