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## Summary Closes #3406 Add a regression matrix in `python/python/tests/test_nested_fields.py` that exercises the full nested field index lifecycle for both the sync and async Python table APIs. The tests will fail if any implementation regresses to leaf-only field names in `list_indices`, `index_stats`, search, or filter results. ## Test scenarios covered **Index types:** BTree scalar, IvfPq vector, FTS **Field-name edge cases (per acceptance criteria):** - `rowId` — camelCase top-level field - `` `row-id` `` — hyphenated top-level field (escaped) - `parent.`\``leaf.name`\`` ` — struct leaf whose name contains a literal dot - `MetaData.userId` — mixed-case nested path - `` `meta-data`.`user-id` `` — hyphenated struct with hyphenated leaf **Lifecycle operations per index type:** - `create_index` / `create_scalar_index` / `create_fts_index` - `list_indices` → verify canonical full dotted path (not leaf name) - `index_stats` → verify row count and index type - Filtered scan (`WHERE nested.field = value`) - Vector search via nested embedding column - FTS search via nested text column - `add` (append) then re-check index listing - `optimize` then re-check index listing **Both sync and async APIs** are covered in parallel test classes. ## Notes Lance forbids top-level field names that contain a literal `.`, so the `` `a.b` `` acceptance-criterion variant is exercised as a *struct leaf* field (`parent.`\``leaf.name`\``) rather than a top-level column.
LanceDB Python SDK
A Python library for LanceDB.
Installation
pip install lancedb
Preview Releases
Stable releases are created about every 2 weeks. For the latest features and bug fixes, you can install the preview release. These releases receive the same level of testing as stable releases, but are not guaranteed to be available for more than 6 months after they are released. Once your application is stable, we recommend switching to stable releases.
pip install --pre --extra-index-url https://pypi.fury.io/lancedb/ lancedb
Usage
Basic Example
import lancedb
db = lancedb.connect('<PATH_TO_LANCEDB_DATASET>')
table = db.open_table('my_table')
results = table.search([0.1, 0.3]).limit(20).to_list()
print(results)
Development
See CONTRIBUTING.md for information on how to contribute to LanceDB.