feat(python): add Pydantic model instance auto-conversion and from_pydantic_model() classmethod

[vinaysurtani]

Summary

Closes #1106

This PR adds first-class Pydantic model support to Lance so users no longer need to manually call .model_dump() before writing data.

Two changes:

• write_dataset() now auto-converts a list of Pydantic BaseModel instances by calling .model_dump() on each item and inferring the PyArrow schema from the resulting dicts
• New LanceDataset.from_pydantic_model(model_class, data, uri=None, **kwargs) classmethod that infers the dataset URI from the model class name (snake_case) and delegates to write_dataset()

Before (required manual conversion):

from pydantic import BaseModel
import pyarrow as pa, lance

class MyModel(BaseModel):
    name: str
    score: float

data = [MyModel(name="alice", score=0.9)]
schema = pa.schema([pa.field("name", pa.string()), pa.field("score", pa.float64())])
lance.write_dataset([m.model_dump() for m in data], "/tmp/test.lance", schema=schema)

After (just works):

lance.write_dataset(data, "/tmp/test.lance")
# or
ds = lance.LanceDataset.from_pydantic_model(MyModel, data, uri="/tmp/test.lance")

Files Changed

• python/python/lance/dependencies.py — added _PYDANTIC_AVAILABLE flag and _check_for_pydantic() helper, following the same optional-dependency pattern used for pandas and HuggingFace
• python/python/lance/types.py — added Pydantic branch in _coerce_reader() before the generic Iterable branch; handles both Pydantic v1 (.dict()) and v2 (.model_dump())
• python/python/lance/dataset.py — added from_pydantic_model() classmethod to LanceDataset
• python/python/tests/test_dataset.py — added Pydantic instances to the existing test_input_data parametrized suite and added test_from_pydantic_model

Test Results

python/python/tests/test_dataset.py: 196 passed, 1 skipped, 4 failed

The 4 failures (test_random_dataset_recall_accelerated, test_random_dataset_recall_accelerated_one_pass, test_count_index_rows_accelerated, test_count_index_rows_accelerated_one_pass) all fail with PermissionError: [Errno 13] Permission denied: 'nvcc' — these require the CUDA compiler toolkit and are pre-existing failures unrelated to this change. They do not touch any code modified in this PR.

New tests added:

• test_input_data[NoneType-pydantic] — Pydantic instances auto-convert correctly in write_dataset()
• test_from_pydantic_model — classmethod writes data, infers schema, round-trips correctly

Checklist

• Pydantic instances can be passed directly to write_dataset() without manual .model_dump()
• LanceDataset.from_pydantic_model() classmethod exists and works
• Pydantic is treated as an optional dependency (no unconditional import)
• Both Pydantic v1 and v2 are supported
• All existing test_input_data parametrized cases still pass
• New tests cover both new entry points
• Rebased cleanly on upstream/main with no conflicts

[github-actions]

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