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Sydney RunkleandClaude Sonnet 4.6
ba12c8264d
Restores DeltaChannel as a standalone class in channels/delta.py and adds
a snapshot_frequency parameter that writes a full snapshot blob every N writes,
bounding the ancestor replay walk depth while preserving O(N) storage for
large N.
Key design decisions:
- Write-count based (not step-based): snapshot fires every N writes to the
channel, tracked via _write_count incremented in both update() and
replay_writes(). This ensures the snapshot always coincides with an actual
channel write (i.e., a new_versions entry in put()), so it is always stored.
- Snapshot blob format: {"__delta_v__": value, "__delta_wc__": n} embeds the
write count so from_checkpoint() can restore it across invocations, keeping
the cadence correct without any external state.
- _checkpoint.py simplified: DeltaChannel.checkpoint() now returns the right
thing (sentinel or snapshot dict) so create_checkpoint needs no special logic.
- _needs_replay updated: triggers on DELTA_SENTINEL / MISSING; snapshot dicts
and plain values (migration) resolve directly via from_checkpoint().
Benchmark shows correct tradeoffs across frequencies (500 turns):
freq=1 → 296 MB storage, ~7ms reads
freq=5 → 60 MB storage, ~4ms reads
freq=10 → 30 MB storage, ~4ms reads
freq=50 → 6.5 MB storage, ~3ms reads
freq=inf→ 290 KB storage, ~114ms reads
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>