Optimize FindQuery.update() with partial writes

[lh0156]

Summary

Implements #777 by updating matching records without materializing full Pydantic models.

What changed

• Uses FT.SEARCH ... NOCONTENT to collect matching keys page by page.
• Validates and serializes update values once, including Pydantic constraints and Redis OM storage conversions.
• Uses partial HSET mappings for HashModel.
• Uses path-level JSON.SET commands for JsonModel, including nested __ paths.
• Preserves the use_transaction flag and returns the number of updated records.
• Keeps query projections out of the key-only search and preserves KNN state when copying queries.
• Documents the new return value.

Testing

• pytest -q tests --ignore tests/test_benchmarks.py: 265 passed.
• pytest -q tests/test_hash_model.py tests/test_json_model.py: 147 passed.
• Generated sync tests for the new coverage plus Hash/JSON model tests: 157 passed.
• ruff check and ruff format --check on changed source/tests.
• python -m compileall -q aredis_om tests.
• bandit -q -r aredis_om/model/model.py -s B608.

Redis Stack was run locally via Docker Compose for the integration tests; benchmark tests were excluded from the full run.

---

Note

Medium Risk
Bulk updates now bypass per-instance save() and write directly to Redis, so behavior differences (encoding, omitted null hash fields, TTL handling) could affect production data paths even though validation and tests were expanded.

Overview
FindQuery.update() no longer loads full models and calls save() per match. It validates and serializes update values once (Pydantic constraints plus Hash/JSON storage encoding), paginates FT.SEARCH … NOCONTENT to collect keys, then applies updates in a pipeline: HSET mappings for HashModel (with HEXPIRE to restore TTLs on updated fields when supported) and path-level JSON.SET for JsonModel, including nested __ paths.

The method now returns the number of records updated, honors use_transaction, and FindQuery.dict() copies knn so key-only search does not drop vector-query state. Docs note the return value; new unit and integration tests cover validation-before-search, pagination, JSON paths, and TTL preservation.

^{Reviewed by Cursor Bugbot for commit 46ec114. Bugbot is set up for automated code reviews on this repo. Configure here.}

[abrookins]

Thanks for opening, @lh0156! I'll take a look ASAP.

[cursor]

Cursor Bugbot has reviewed your changes using default effort and found 1 potential issue.

^{Reviewed by Cursor Bugbot for commit 46ec114. Configure here.}

[cursor]

Bool-to-string conversion unreachable after jsonable_encoder processes integers

Medium Severity

In _serialize_update_values for HashModel, the jsonable_encoder call returns booleans as-is because isinstance(False, int) is True in its (str, int, float, type(None)) check. However, the subsequent boolean-to-string conversion on line 2108 checks isinstance(value, bool), which works correctly for Python bool objects. The real issue is that jsonable_encoder processes dict values recursively and can convert certain nested or complex typed booleans inconsistently depending on the Pydantic model's encoder configuration. More importantly, updating a boolean field to False produces "0", which after if value is not None passes through but could be confused with integer 0 by downstream code. This inconsistency between int(0) staying as 0 and bool(False) becoming "0" could cause subtle data type mismatches on read-back if fields are typed as int but store boolean-like values.

 

^{Reviewed by Cursor Bugbot for commit 46ec114. Configure here.}