ARA temporal ML feature store — Python SDK
Project description
ARA Python SDK
Python client for the ARA temporal ML feature store.
Quick Start
pip install ara-labs-sdk
from ara_store import ARAStore
store = ARAStore() # localhost:50051-50055, 5 partitions
# Write features
store.write(entity_id=42, features={"score": 0.97, "clicks": 14})
# Read latest
vals = store.get_latest(entity_id=42, feature_names=["score", "clicks"])
# Point-in-time read
from datetime import datetime, timezone
snap = store.get_snapshot(42, ["score"], as_of=datetime(2025, 11, 1, tzinfo=timezone.utc))
Requirements
- Python 3.9+
- ARA server running (see quickstart)
flatbuffers>=23.5.26
Retry Contract
Read APIs (get_latest, get_snapshot, get_snapshot_batch) already perform
internal SDK retries for transient transport failures.
- Default:
3retries (4total attempts) - Configure:
ARA_SDK_READ_MAX_RETRIES - Disable metadata injection (regression testing only):
ARA_SDK_NO_METADATA=true
Recommendation: avoid wrapping these read APIs in an additional generic retry loop unless you intentionally want a larger total retry budget, since stacked retries can multiply request volume.
License
ARA Proprietary — see LICENSE.
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