feat: use pydantic models for making schemas

.gitignore

@@ -5,3 +5,4 @@ _build
 _bikeshed
 .tox
 .vscode
+.venv

latest/models.py

@@ -0,0 +1,77 @@
+from __future__ import annotations
+from typing import Literal, Optional
+from pydantic import BaseModel, ConfigDict, conlist
+from typing import Annotated, Hashable, List, TypeVar
+from pydantic_core import PydanticCustomError
+from pydantic import AfterValidator, Field, ValidationError
+
+T = TypeVar('T', bound=Hashable)
+
+def _validate_unique_list(v: list[T]) -> list[T]:
+    if len(v) != len(set(v)):
+        raise PydanticCustomError('unique_list', 'List must be unique')
+    return v
+
+UniqueList = Annotated[List[T], AfterValidator(_validate_unique_list), Field(json_schema_extra={'uniqueItems': True})]
+
+class Axis(BaseModel, frozen=True):
+    name: str
+    type: Optional[str] = None
+    unit: Optional[str] = None
+
+class ScaleTransform(BaseModel, frozen=True):
+    type: Literal["scale"]
+    scale: conlist(float, min_length=1)
+
+class TranslationTransform(BaseModel, frozen=True):
+    type: Literal["translation"]
+    translation: conlist(float, min_length=1)
+
+class Dataset(BaseModel, frozen=True):
+    path: str
+    coordinateTransformations: tuple[ScaleTransform] | tuple[ScaleTransform, TranslationTransform]
+
+class Multiscale(BaseModel, frozen=True):
+    """
+    The multiscale datasets for this image
+    """
+    name: Optional[str] = None
+    datasets: conlist(Dataset, min_length=1)
+    axes: UniqueList[Axis]
+    coordinateTransformations: Optional[tuple[ScaleTransform] | tuple[ScaleTransform, TranslationTransform]] = None
+    version: Literal['0.5-dev']
+
+class Window(BaseModel, frozen=True):
+    start: float
+    end: float
+    min: float
+    max: float
+
+class RenderingSettings(BaseModel, frozen=True):
+    window: Window
+    label: str
+    family: str
+    color: str
+    active: bool
+
+class Omero(BaseModel, frozen=True):
+    channels: list[RenderingSettings]
+
+class GroupMetadata(BaseModel, frozen=True):
+    """
+    JSON from OME-NGFF .zattrs
+    """
+    model_config = ConfigDict(title="NGFF Image")
+    multiscales: conlist(Multiscale, min_length=1)
+    omero: Optional[Omero] = None
+
+def make_schema():
+    import json
+    schema = GroupMetadata.model_json_schema()
+    schema["$schema"] = "https://json-schema.org/draft/2020-12/schema"
+    schema["$id"] = "https://ngff.openmicroscopy.org/latest/schemas/image.schema"
+
+    print(json.dumps(schema, indent=2))
+
+if __name__ == '__main__':
+    make_schema()