Simplify the use of Pydantic type adapter

[candleindark]

The use of Pydantic type adapters are quite unwieldy in the program at this point. It involves creation of a type adapter for each type that needed one but, for performance reason, one should avoid repeatedly creating adapters for the same type. Thus, for each type that currently needs a type adapter, an adapter is created at

dandisets-linkml-status-tools/src/dandisets_linkml_status_tools/models.py

Lines 235 to 240 in b4963c4

	DANDI_METADATA_ADAPTER = TypeAdapter(DandiMetadata)
	PYDANTIC_VALIDATION_ERRS_ADAPTER = TypeAdapter(PydanticValidationErrsType)
	LINKML_VALIDATION_ERRS_ADAPTER = TypeAdapter(LinkmlValidationErrsType)
	DANDI_METADATA_LIST_ADAPTER = TypeAdapter(list[DandiMetadata])
	DANDISET_PYDANTIC_REPORT_LIST_ADAPTER = TypeAdapter(list[DandisetValidationReport])
	ASSET_PYDANTIC_REPORT_LIST_ADAPTER = TypeAdapter(list[AssetValidationReport])

.

This set up is not sustainable if more types need a type adapter. Create some class that stores adapters in a dictionary keyed by the type they are intended for.

The following snipped exhibit properties they are useful in implementing such a class.

snippet exhibiting properties useful in implementing such a class

from typing import TypeAlias

t1 = list[str]
t2 = list[int]
t3 = list[str]
t4: TypeAlias = list[str]
t5: TypeAlias = list[str]

print(f't1: {t1}')

if t1 == t2:
    print('t1 == t2')

if t1 == t3:
    print('t1 == t3')

if t1 == t4:
    print('t1 == t4')

if t4 == t5:
    print('t4 == t5')

if t1 == list[str]:
    print('t1 == list[str]')

print("=====")

print(f"type(t1): {type(t1)}")
print(f"type(t2): {type(t2)}")
print(f"type(t3): {type(t3)}")
print(f"type(t4): {type(t4)}")
print(f"type(t5): {type(t5)}")
print(f"type(list[str]): {type(list[str])}")

print("=====")
s = {t1, t2, t3, t4, t5, list[str]}
print(f"s: {s}")