1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
|
from __future__ import annotations
import warnings
from dataclasses import replace
from decimal import Decimal
from typing import Any, Generator, Generic, List, Optional, TypeVar
from msgspec import Meta
from typing_extensions import Annotated
from litestar.dto import AbstractDTO, DTOField, Mark
from litestar.dto.data_structures import DTOFieldDefinition
from litestar.exceptions import LitestarWarning, MissingDependencyException
from litestar.types import Empty
from litestar.typing import FieldDefinition
from litestar.utils import warn_deprecation
try:
from piccolo.columns import Column, column_types
from piccolo.table import Table
except ImportError as e:
raise MissingDependencyException("piccolo") from e
T = TypeVar("T", bound=Table)
__all__ = ("PiccoloDTO",)
def __getattr__(name: str) -> Any:
warn_deprecation(
deprecated_name=f"litestar.contrib.piccolo.{name}",
version="2.3.2",
kind="import",
removal_in="3.0.0",
info="importing from 'litestar.contrib.piccolo' is deprecated and will be removed in 3.0, please import from 'litestar_piccolo' package directly instead",
)
return getattr(name, name)
def _parse_piccolo_type(column: Column, extra: dict[str, Any]) -> FieldDefinition:
is_optional = not column._meta.required
if isinstance(column, (column_types.Decimal, column_types.Numeric)):
column_type: Any = Decimal
meta = Meta(extra=extra)
elif isinstance(column, (column_types.Email, column_types.Varchar)):
column_type = str
if is_optional:
meta = Meta(extra=extra)
warnings.warn(
f"Dropping max_length constraint for column {column!r} because the " "column is optional",
category=LitestarWarning,
stacklevel=2,
)
else:
meta = Meta(max_length=column.length, extra=extra)
elif isinstance(column, column_types.Array):
column_type = List[column.base_column.value_type] # type: ignore[name-defined]
meta = Meta(extra=extra)
elif isinstance(column, (column_types.JSON, column_types.JSONB)):
column_type = str
meta = Meta(extra={**extra, "format": "json"})
elif isinstance(column, column_types.Text):
column_type = str
meta = Meta(extra={**extra, "format": "text-area"})
else:
column_type = column.value_type
meta = Meta(extra=extra)
if is_optional:
column_type = Optional[column_type]
return FieldDefinition.from_annotation(Annotated[column_type, meta])
def _create_column_extra(column: Column) -> dict[str, Any]:
extra: dict[str, Any] = {}
if column._meta.help_text:
extra["description"] = column._meta.help_text
if column._meta.get_choices_dict():
extra["enum"] = column._meta.get_choices_dict()
return extra
class PiccoloDTO(AbstractDTO[T], Generic[T]):
@classmethod
def generate_field_definitions(cls, model_type: type[Table]) -> Generator[DTOFieldDefinition, None, None]:
for column in model_type._meta.columns:
mark = Mark.WRITE_ONLY if column._meta.secret else Mark.READ_ONLY if column._meta.primary_key else None
yield replace(
DTOFieldDefinition.from_field_definition(
field_definition=_parse_piccolo_type(column, _create_column_extra(column)),
dto_field=DTOField(mark=mark),
model_name=model_type.__name__,
default_factory=None,
),
default=Empty if column._meta.required else None,
name=column._meta.name,
)
@classmethod
def detect_nested_field(cls, field_definition: FieldDefinition) -> bool:
return field_definition.is_subclass_of(Table)
|
