The notification dropdown is anchored to the bell button, which on mobile sits
left of the account button rather than at the screen edge, so the wide panel
overflowed off the left of the viewport (title/text cut off). On narrow screens,
drop .notif's positioning context so the dropdown anchors to the .acct cluster at
the header's right edge, keeping it fully on-screen.
Also add route-level tests for the accounts feature (auth flow, subscription CRUD,
duplicate/validation, ownership 404s, notifications), plus a
THERMOGRAPH_ACCOUNTS_DB override so the suite writes to a throwaway DB and stays
hermetic.
* Migrate backend dataframe layer from pandas to polars
Replace pandas with polars across the backend, dropping both pandas and its
pyarrow parquet engine from the dependency set. numpy stays (the grading
percentile math is unchanged).
- climate.py: parquet IO, source→frame mappings, cache read/topup on polars.
New _normalize_read casts the cached `date` column to pl.Date (older files
were written by pandas as datetime64[ns]); frames now unify missing values as
null so the grading boundary drops them consistently across sources.
- grading.py: keep the numpy percentile core; swap the frame→numpy bridge to
.to_numpy()/.drop_nulls(), day-of-year/year to polars dt expressions, and the
per-row loop to iter_rows(named=True).
- views.py: filter/anti-join/concat replace boolean-mask, isin and pd.concat;
scalar dates are stdlib datetime.date; a local _months_before helper replaces
DateOffset(months=) for the calendar-range default.
- app.py, migrate.py: request-date parsing uses datetime.date, removing pandas
from the endpoint and migrate layers entirely.
- The date column is pl.Date end to end, eliminating the pandas normalize() calls
and comparing cleanly against stdlib dates.
Payloads are unchanged: calendar, day, grade and forecast responses are
byte-for-byte identical to the pandas implementation on the same cached record.
Tests ported to polars fixtures, with added coverage for the combined feels-like
fallback, calendar month-offset (month-end/leap), and the concat/dedup
"fresher source wins" rule.
* Port notify.py to polars after merging dev's account system
Merge origin/dev (accounts + notification subscriptions) and carry the pandas→
polars migration into the newly added notify.py, which the merge brought in still
using pandas — with pandas removed from requirements this broke its import.
- notify.py: _candidate_rows filters/sorts the recent bundle with polars
expressions and returns iter_rows dicts; date scalars are datetime.date;
history/recent emptiness via is_empty().
- test_notify.py: synthetic history/rows built with polars + datetime.
- backend/tests: 74 hermetic tests (no network, no repo data//logs/ writes)
covering grid snapping/round-trips, grading percentiles/bands/windows/
dry streaks, the places index (norm, one-edit matchers, search,
corrections), the derived store (token validity, cache=False, degraded
mode), and route-level API tests over a faked climate layer — routing,
validation, ETag/304 revalidation, store replay, the /cell bundle, and
the v1/v2 aliases. The API tests would have caught the /place
AttributeError regression.
- requirements-dev.txt + make test (venv prefers uv-pinned 3.12, matching
deploy-dev.sh — pyarrow wheels stop at 3.12 and some pyenv builds lack
sqlite).
- CI: extract the build job into a reusable build.yml, add the test run
and an API health probe (page-only curl can't catch route wiring
faults); deploy-dev.yml now runs the same build gate before deploying
direct pushes, which previously deployed with no CI at all.
- Deploys serialize under one dev-lan-deploy concurrency group across
both workflows (previously per-PR groups could interleave two deploys
to the same checkout), and are never cancelled mid-restart.
- deploy-dev.sh health check also probes /api/v2/place — best-effort
externals mean a failure there is a genuine server bug.
