Content-hash-based change tracking for data imports

[jonathangreen]

Description

Replaces the timestamp-only change-detection logic in the data import pipeline
with a content-hash-based system. Previously, BibliographicData and
CirculationData used only the data source's "last updated" timestamp to decide
whether to re-apply incoming data to an Edition or LicensePool. This caused
two problems:

• Re-publishing the same content with a newer timestamp triggered unnecessary
  writes and work creation.
• A real change arriving with the same (or missing) timestamp was silently skipped.
  This branch reverts the original timestamp-throttling PR (Fix BibliographicData.has_changed to throttle updates when data sourc… #3198) and replaces it
  with a proper content-hash approach. A SHA-256 hash of the canonical, serialized
  form of the incoming data is stored on the database record after each import.
  Subsequent imports compare both the timestamp and the hash before deciding whether
  to apply an update.
  Key changes:
• New json_hash() / json_canonical() utilities (util/json.py) produce a
  stable, order-independent SHA-256 fingerprint of any JSON-serializable structure.
• BaseMutableData gains updated_at, created_at, as_of_timestamp,
  calculate_hash(), and should_apply_to(). The should_apply_to() method
  is now the single decision point for both bibliographic and circulation data.
• BibliographicData.has_changed() and CirculationData.has_changed() are
  removed and replaced by the shared should_apply_to() logic.
• Edition and LicensePool each gain an updated_at_data_hash column.
  LicensePool also gains created_at and updated_at columns to track when
  its CirculationData was first and most recently imported.
• Individual-license pools (e.g. ODL) always re-apply availability even when the
  hash matches, because license availability can change as licenses expire
  independently of feed content.
• Database migration f98e4049c87d adds all four new columns.

Motivation and Context

The original has_changed() implementation only compared timestamps, which is
insufficient: a data source can re-publish identical content with a newer timestamp,
or publish changed content with the same timestamp. Content hashing is the correct
primitive for detecting genuine data changes and avoiding redundant imports.

How Has This Been Tested?

• Updated unit tests for BibliographicData and CirculationData cover the
  new should_apply_to() logic, including the null-hash bootstrap case, the
  timestamp-is-older short-circuit, and the hash-match skip.
• New unit tests for json_canonical() and json_hash() verify ordering
  stability across dict keys, list items, and float precision.
• All existing integration tests for Boundless, OPDS, ODL, and Overdrive importers
  pass with the updated field names (updated_at in place of
  data_source_last_updated).
• Full test suite run via tox -e py312-docker -- --no-cov.

Checklist

• I have updated the documentation accordingly.
• All new and existing tests passed.

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 93.31%. Comparing base (c825a11) to head (f58ea44).

Additional details and impacted files

@@           Coverage Diff           @@
##             main    #3199   +/-   ##
=======================================
  Coverage   93.30%   93.31%           
=======================================
  Files         497      497           
  Lines       46144    46193   +49     
  Branches     6318     6322    +4     
=======================================
+ Hits        43055    43103   +48     
+ Misses       2004     2003    -1     
- Partials     1085     1087    +2     

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