[python] Simplify LeRobot metadata tables and training tags - #9676
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Store info and stats in companion tables with JSON string values, and support optional named tags for imported or current component snapshots. Co-Authored-By: Codex <noreply@anthropic.com> AI-Model: gpt-6 Co-Authored-By: Codex <noreply@ai-tool.com> AI-Contributed/Feature: 278/278 AI-Contributed/UT: 290/290
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| ```python | ||
| version_id = conn.load_from_lerobot( | ||
| snapshot_id = conn.load_from_lerobot( |
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Suggestion: Maybe just return None?
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Purpose
Decouple LeRobot ingestion from dataset version publication. Store dataset info and optional statistics in companion tables with
key STRING, value STRING, using JSON-encoded values to preserve nested metadata without a fixed schema.load_from_lerobotreturns the committed frame snapshot ID and accepts an optionaltag_name.create_lerobot_tagpins the current snapshots of all recorded components under a shared name for training, checks conflicts before creating tags, and supports retries while snapshots remain unchanged.Cross-table tagging is not atomic: callers must pause group writes until the call succeeds and read every component through the same tag. Documentation and regression tests cover this contract.
Tests
git diff --checkpassed.LeRobot tests ran with Python 3.12, LeRobot 0.4.4, PyArrow 19.0.1, and NumPy 2.3.5. NumPy 2.5 fails in the existing SDK fixture's array-to-scalar conversion; project dependencies are unchanged.