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chore: quality cleanup — extract magic numbers, improve docs and naming (#29)

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- diversity.py: extract 3000/20/32 to _POOL_CAP/_POOL_SCALE/_EMBEDDING_BATCH_SIZE
- reconcile.py: extract (1,2,4,8) poll delays to _RECONCILE_POLL_DELAYS with comment
- immich_api.py: document dual response shape; debug-log skipped non-dict items
- frigate_api.py: rename `encoded` → `encoded_name` for clarity
- upload_tracker.py: atomic-write note on record_frigate_files_batch docstring;
  get_person_summary() uses setdefault to eliminate four repeated default dicts;
  _VALID_SCORE_COLS comment explains SQL-injection guard intent

Bump version to 0.5.5
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flan
2026-06-14 20:04:24 -04:00
committed by GitHub
parent 84ebd91929
commit 3a052db1ce
8 changed files with 64 additions and 31 deletions
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pyproject.toml
+1 -1
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@@ -1,6 +1,6 @@
[project]
name = "winnow"
version = "0.5.4"
version = "0.5.5"
description = "Selects diverse, high-quality photos from Immich as training data for Frigate face recognition."
license = "AGPL-3.0-or-later"
requires-python = ">=3.13"