Update to supporting Pydantic V2

dandischema/datacite.py

@@ -219,7 +219,7 @@
                     else:
                         continue
             elif rel_el.url is not None:
-                ident_id = rel_el.url
+                ident_id = str(rel_el.url)
                 ident_tp = "URL"
             rel_dict = {
                 "relatedIdentifier": ident_id.lower(),

dandischema/digests/zarr.py

@@ -2,6 +2,7 @@
 
 from functools import total_ordering
 import hashlib
+import json
 import re
 from typing import Dict, List, Optional, Tuple
 
@@ -109,7 +110,10 @@ def aggregate_digest(self, checksums: ZarrChecksums) -> str:
         """Generate an aggregated digest for a list of ZarrChecksums."""
         # Use the most compact separators possible
         # content = json.dumps([asdict(zarr_md5) for zarr_md5 in checksums], separators=(',', ':'))0
-        content = checksums.json(**ENCODING_KWARGS)  # type: ignore[arg-type]
+        content = json.dumps(
+            checksums.model_dump(mode="json"),
+            **ENCODING_KWARGS,  # type: ignore[arg-type]
+        )
         h = hashlib.md5()
         h.update(content.encode("utf-8"))
         md5 = h.hexdigest()
@@ -125,14 +129,17 @@ def aggregate_digest(self, checksums: ZarrChecksums) -> str:
     def serialize(self, zarr_checksum_listing: ZarrChecksumListing) -> str:
         """Serialize a ZarrChecksumListing into a string."""
         # return json.dumps(asdict(zarr_checksum_listing))
-        return zarr_checksum_listing.json(**ENCODING_KWARGS)  # type: ignore[arg-type]
+        return json.dumps(
+            zarr_checksum_listing.model_dump(mode="json"),
+            **ENCODING_KWARGS,  # type: ignore[arg-type]
+        )
 
     def deserialize(self, json_str: str) -> ZarrChecksumListing:
         """Deserialize a string into a ZarrChecksumListing."""
         # listing = ZarrChecksumListing(**json.loads(json_str))
         # listing.checksums = [ZarrChecksum(**checksum) for checksum in listing.checksums]
         # return listing
-        return ZarrChecksumListing.parse_raw(json_str)
+        return ZarrChecksumListing.model_validate_json(json_str)
 
     def generate_listing(
         self,

dandischema/metadata.py

@@ -1,7 +1,19 @@
 from copy import deepcopy
+from enum import Enum
+from inspect import isclass
 import json
 from pathlib import Path
-from typing import Any, Dict, Iterable, Optional, TypeVar, Union, cast
+from typing import (
+    Any,
+    Dict,
+    Iterable,
+    Optional,
+    TypeVar,
+    Union,
+    cast,
+    get_args,
+    get_origin,
+)
 
 import jsonschema
 import pydantic
@@ -15,7 +27,12 @@
 )
 from .exceptions import JsonschemaValidationError, PydanticValidationError
 from . import models
-from .utils import _ensure_newline, version2tuple
+from .utils import (
+    TransitionalGenerateJsonSchema,
+    _ensure_newline,
+    strip_top_level_optional,
+    version2tuple,
+)
 
 schema_map = {
     "Dandiset": "dandiset.json",
@@ -56,29 +73,53 @@ def generate_context() -> dict:
     fields: Dict[str, Any] = {}
     for val in dir(models):
         klass = getattr(models, val)
-        if not isinstance(klass, pydantic.main.ModelMetaclass):
+        if not isclass(klass) or not issubclass(klass, pydantic.BaseModel):
             continue
         if hasattr(klass, "_ldmeta"):
-            if "nskey" in klass._ldmeta:
+            if "nskey" in klass._ldmeta.default:
                 name = klass.__name__
-                fields[name] = f'{klass._ldmeta["nskey"]}:{name}'
-        for name, field in klass.__fields__.items():
+                fields[name] = f'{klass._ldmeta.default["nskey"]}:{name}'
+        for name, field in klass.model_fields.items():
             if name == "id":
                 fields[name] = "@id"
             elif name == "schemaKey":
                 fields[name] = "@type"
             elif name == "digest":
                 fields[name] = "@nest"
             elif name not in fields:
-                if "nskey" in field.field_info.extra:
-                    fields[name] = {"@id": field.field_info.extra["nskey"] + ":" + name}
+                if (
+                    isinstance(field.json_schema_extra, dict)
+                    and "nskey" in field.json_schema_extra
+                ):
+                    fields[name] = {
+                        "@id": cast(str, field.json_schema_extra["nskey"]) + ":" + name
+                    }
                 else:
                     fields[name] = {"@id": "dandi:" + name}
-                if "List" in str(field.outer_type_):
+
+                # The annotation without the top-level optional
+                stripped_annotation = strip_top_level_optional(field.annotation)
+
+                if get_origin(stripped_annotation) is list:
                     fields[name]["@container"] = "@set"
+
+                    # Handle the case where the type of the element of a list is
+                    # an Enum type
+                    type_args = get_args(stripped_annotation)
+                    if (
+                        len(type_args) == 1
+                        and isclass(type_args[0])
+                        and issubclass(type_args[0], Enum)
+                    ):
+                        fields[name]["@type"] = "@id"
+
                 if name == "contributor":
                     fields[name]["@container"] = "@list"
-                if "enum" in str(field.type_) or name in ["url", "hasMember"]:
+                if (
+                    isclass(stripped_annotation)
+                    and issubclass(stripped_annotation, Enum)
+                    or name in ["url", "hasMember"]
+                ):
                     fields[name]["@type"] = "@id"
 
     for item in models.DigestType:
@@ -96,7 +137,14 @@ def publish_model_schemata(releasedir: Union[str, Path]) -> Path:
     vdir.mkdir(exist_ok=True, parents=True)
     for class_, filename in schema_map.items():
         (vdir / filename).write_text(
-            _ensure_newline(getattr(models, class_).schema_json(indent=2))
+            _ensure_newline(
+                json.dumps(
+                    getattr(models, class_).model_json_schema(
+                        schema_generator=TransitionalGenerateJsonSchema
+                    ),
+                    indent=2,
+                )
+            )
         )
     (vdir / "context.json").write_text(
         _ensure_newline(json.dumps(generate_context(), indent=2))
@@ -177,7 +225,9 @@ def validate(
     if json_validation:
         if schema_version == DANDI_SCHEMA_VERSION:
             klass = getattr(models, schema_key)
-            schema = klass.schema()
+            schema = klass.model_json_schema(
+                schema_generator=TransitionalGenerateJsonSchema
+            )
         else:
             if schema_key not in schema_map:
                 raise ValueError(
@@ -196,7 +246,7 @@ def validate(
     except pydantic.ValidationError as exc:
         messages = []
         for el in exc.errors():
-            if not missing_ok or el["msg"] != "field required":
+            if not missing_ok or el["type"] != "missing":
                 messages.append(el)
         if messages:
             raise PydanticValidationError(messages)  # type: ignore[arg-type]
@@ -346,4 +396,4 @@ def aggregate_assets_summary(metadata: Iterable[Dict[str, Any]]) -> dict:
         len(stats.pop("tissuesample", [])) + len(stats.pop("slice", []))
     ) or None
     stats["numberOfCells"] = len(stats.pop("cell", [])) or None
-    return models.AssetsSummary(**stats).json_dict()
+    return models.AssetsSummary(**stats).model_dump(mode="json", exclude_none=True)