Store denormalized review statistics (#982)

[IshanA2007]

Closes #982

⚠️ Draft — substantial refactor; requires a one-time backfill after migrating

The performance win only lands after recompute_review_stats runs (see Deploy steps). Until then everything falls back to live computation (correct, just not faster).

Problem

Course/instructor review averages (rating, difficulty, enjoyability, recommendability, hours, reading/writing/group/homework) were aggregated from all Review rows on every request — Course.average_*, Course.with_stats, Instructor.average_*_for_course, and the course-instructor view.

Fix

Denormalized storage, mirroring the existing CourseGrade / CourseInstructorGrade split:

• New CourseStats (OneToOne → Course, course-level rollup) and CourseInstructorStats (per course+instructor), sharing an abstract base with review_count + a stored average for every aggregated Review field. Composite rating is derived from its 3 stored components (single source of truth, matching the historic formula). Only non-hidden reviews are counted.
• post_save / post_delete / pre_save signals on Review recompute the affected (course, instructor) pair + course rollup on every create / edit / delete / re-point / hide; rows with zero remaining reviews are deleted.
• python manage.py recompute_review_stats backfills / rebuilds all rows from existing reviews.
• All read paths rewritten to use stored stats with a safe fallback to live aggregation when a row is missing — so nothing breaks pre-backfill. Public method names/return types are unchanged; templates untouched.

Migration: 0029_coursestats_courseinstructorstats_and_more.py.

Deploy steps

1. Apply migration 0029.
2. Run python manage.py recompute_review_stats once.

Verification (run against a disposable Postgres)

• makemigrations --check --dry-run — no changes detected (models match migration 0029).
• manage.py check clean; ruff check / ruff format --check clean.
• Full suite manage.py test tcf_website — 267 OK, incl. 10 new tests (signal maintenance on create/edit/delete/move, hidden-review exclusion, stored-vs-live numeric equivalence, backfill command).

Risks for review

• with_stats now LEFT JOINs the stats OneToOne with Coalesce to correlated subqueries (fallback dormant post-backfill) — worth an EXPLAIN on prod-sized data.
• Bulk imports that bypass ORM save()/signals (e.g. load_review_drive) won't update stats incrementally — re-run the backfill afterward.
• No-arg Instructor.average_rating() / average_difficulty() (all-courses; no current consumers) intentionally left as live computation.
• Confirm the signals compose with the existing Cachalot/Redis cache as desired.

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🤖 Implemented with Claude Code.

[coderabbitai]

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Review details

⚙️ Run configuration

Configuration used: defaults

Review profile: CHILL

Plan: Pro

Run ID: a104b256-b8c6-46c2-907a-ace2cca3217d

📥 Commits

Reviewing files that changed from the base of the PR and between ed955fb and 23c0c0a.

📒 Files selected for processing (9)

• tcf_website/apps.py
• tcf_website/management/commands/recompute_review_stats.py
• tcf_website/migrations/0029_coursestats_courseinstructorstats_and_more.py
• tcf_website/models/__init__.py
• tcf_website/models/models.py
• tcf_website/models/stats.py
• tcf_website/signals.py
• tcf_website/tests/test_review_stats.py
• tcf_website/views/courses/course_instructor.py

✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Commit unit tests in branch 982-store-course-statistics

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