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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: 3 retries (4 total 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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