tudor/school_compare
1
0
Fork 0
Code Issues 2 Pull Requests Actions Packages Projects Releases Wiki Activity
463 Commits 70 Branches 0 Tags
4d226fd616f24f8e3663181b0774ea9aa5738a35
Commit Graph
5 Commits
Author SHA1 Message Date
TudorandClaude Fable 5 4d226fd616 test: drop unused fake exception helper
PR Checks / Frontend Typecheck + Tests (pull_request) Successful in 9m41s
Details
PR Checks / Backend Smoke (pull_request) Successful in 6s
Details
PR Checks / Build Backend (no push) (pull_request) Successful in 17s
Details
PR Checks / Build Frontend (no push) (pull_request) Successful in 47s
Details
PR Checks / Build Pipeline (no push) (pull_request) Successful in 53s
Details
PR Checks / AI Code Review (Claude) (pull_request) Successful in 3m17s
Details 
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-07 13:36:01 +01:00
TudorandClaude Fable 5 a524cdc591 fix(api): survive missing has_sixth_form column and numpy bool serialization 
- data_loader.load_school_data_as_dataframe now catches a ProgrammingError
  whose message mentions has_sixth_form (psycopg2 UndefinedColumn) and
  retries with a NULL-AS-has_sixth_form query variant, so the API keeps
  serving data (and the app.py column-fallback branch stays reachable)
  even before the nightly pipeline has rebuilt marts.dim_school.
- utils.convert_to_native now handles numpy.bool_ so GET /api/schools/{urn}
  doesn't 500 once has_sixth_form is a populated bool-dtype column.
- Update the now-stale comment on the app.py age-range fallback branch.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-07 13:33:25 +01:00
TudorandClaude Fable 5 1d149ffc48 feat(api): drive has_sixth_form filter and payloads from GIAS flag 
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-07 10:36:39 +01:00
TudorandClaude Opus 4.8 536832a524 chore: drop committed .pyc files, ignore __pycache__ everywhere
PR Checks / Frontend Typecheck + Tests (pull_request) Successful in 9m37s
Details
PR Checks / Backend Smoke (pull_request) Successful in 6s
Details
PR Checks / Build Backend (no push) (pull_request) Successful in 29s
Details
PR Checks / Build Frontend (no push) (pull_request) Successful in 42s
Details
PR Checks / Build Pipeline (no push) (pull_request) Successful in 10s
Details
PR Checks / AI Code Review (Claude) (pull_request) Successful in 1m54s
Details 
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-07-07 09:37:17 +01:00
TudorandClaude Opus 4.8 87642b7b06 fix(api): serialize schools that have no performance rows
PR Checks / Frontend Typecheck + Tests (pull_request) Successful in 9m39s
Details
PR Checks / Backend Smoke (pull_request) Successful in 8s
Details
PR Checks / Build Backend (no push) (pull_request) Successful in 30s
Details
PR Checks / Build Frontend (no push) (pull_request) Successful in 42s
Details
PR Checks / Build Pipeline (no push) (pull_request) Successful in 10s
Details
PR Checks / AI Code Review (Claude) (pull_request) Successful in 2m0s
Details 
Schools without KS2/KS4 results (special post-16 institutions, sixth-form
centres, PRUs, new schools) come back from the marts LEFT JOIN with NaN in
every numeric column. school_info passed those raw pandas values straight
into JSONResponse, which renders with allow_nan=False, so the detail
endpoint 500d and the frontend turned that into a 404 on every such SEO
landing page.

Run school_info values through convert_to_native (the same treatment
yearly_data already gets), add backend unit tests plus a pytest step in PR
checks, and an e2e journey that finds a results-less school via the search
API and asserts its page renders.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-07-07 09:22:54 +01:00