Faster search-engine indexing for the ~14k climate/city/record URLs:
- IndexNow (backend/indexnow.py): instantly notify Bing/DuckDuckGo/Yandex of new
or changed URLs. Per-host key resolved env → gitignored file → generated (mirrors
push.py), served at /{key}.txt, and echoed in submissions. `submit_all()` + a
`make indexnow` CLI push every indexable URL, batched under the 10k cap. Google
doesn't use IndexNow, so it stays on the sitemap.
- Sitemap: replace the per-request today() <lastmod> (which churns every fetch and
trains crawlers to ignore lastmod) with a stable content-build date; factor the
URL list into public_paths() shared with IndexNow so the two never drift.
- Search-console verification: render google-site-verification + msvalidate.01
<meta> tags from env into every page's <head> — the SEO pages via base.html.j2
and the static pages (incl. the homepage Google verifies) via _page().
- Docs: env example documents the three new vars; .gitignore ignores the key.
Tests: key-file route, stable single-date lastmod, IndexNow payload/batching, and
verification meta on both SEO and static pages.
The server-rendered SEO pages shared base.html.j2's nav but carried no JS, so
they lacked the °F/°C toggle and account/bell, and their temperatures were baked
as dual-unit strings that couldn't respond to a toggle.
- Load units.js + account.js + climate.js on base.html.j2, so every SEO page gets
the same header as the interactive pages (nav + °F/°C toggle + account + bell).
- Emit each temperature as <span class="temp" data-temp-f> (default °F text, real
for crawlers/no-JS); climate.js rewrites them to the active unit on load and on
toggle. Tint classes stay pinned to absolute °F. Drops the inline "(NN°C)".
- Make account.js base-aware: derive the app base from import.meta.url so its
api/v2 fetches and the alerts links resolve from deep /climate/{slug} URLs
instead of 404ing. Equivalent on the depth-1 interactive pages.
- Default the unit from the browser locale for first-time visitors (no stored
pref): en-US → °F, everyone else → °C. A stored choice always wins.
The per-month records section listed only the warmest and coldest temperature.
Extend it to a card per metric (High, Low, Feels-like, Humidity, Wind, Gust,
Precip), each showing that calendar month's record high and low with the date.
Precip is special-cased: a per-day record low is just zero, and the dry-streak
helper would bridge year boundaries on month-filtered rows, so the wettest and
driest sides use the month's largest and smallest total accumulation, dated to
the year. Partial current months (< 26 days) are excluded so an unfinished month
can't win "driest" on a fraction of its rainfall.
Reuses the records page's card grid, so it's already vertical on mobile.
Claude-Session: https://claude.ai/code/session_01XXxmNFy9cZ6Gh8Y9thZn62
The month and season records tables showed only the record high (of the daytime
high) and the record low (of the overnight low) — one extreme each. Show both
ends of both metrics: for the daytime high, its record hottest (▲) and the
coldest a day ever stayed (▼, its record-low high); for the overnight low, its
mildest night (▲, its record-high low) and its record low (▼). All four already
came out of all_time_records; they were just being dropped.
Restructure each table to Period · Daytime high · Overnight low, with each metric
cell carrying two tinted, dated chips (▲ warmest / ▼ coldest). Fits mobile in
three columns; the all-time cards already showed both extremes, so this brings
the per-period tables in line.
* SEO: monthly & seasonal records on the city records page
The /climate/<city>/records page showed only all-time records per metric.
Expand it into a full records page: record high/low for each of the 12
months (each linking its month page) and for each meteorological season,
alongside the existing all-time table.
Seasons are hemisphere-aware — Dec–Feb reads as winter for northern cities
and summer for southern ones (picked from the city's latitude). Records
reuse grading.all_time_records over a month-filtered archive, so no new
data fetching or warming is needed. Adds a Dataset + breadcrumb JSON-LD
block and richer title/description for the expanded coverage.
* SEO: colour-code climate & records pages (heat-map + range strip)
The city, records and month pages were plain muted tables — generic climate-site
styling. Bring the interactive grader's diverging cold→hot palette onto them so
they read as heat maps in the site's own visual language:
- Map absolute °F to the 9-tier palette (temp_class, a Jinja global) and tint the
temperature cells across the monthly-normals, monthly/seasonal/all-time records
tables. The value stays in the ink token; the tint is a wash behind it. Non-temp
rows (humidity/wind/precip) and date columns stay untinted.
- Add a monthly temperature-range strip on the city page: one gradient bar per
month spanning the average low→high on a shared −10..115°F axis, so a city's
whole-year rhythm (and hot-vs-cold character) reads at a glance.
- Tint the month page's hero high/low and its record values inline.
Palette, light/dark, and 390–1920px layouts verified by rendering hot (Phoenix)
and cold (Anchorage) cities.
Auto-sourcing a notable weather event from Wikipedia search proved unreliable
(wrong matches, low coverage), so city_events.py is a small, fact-checked list of
one iconic event per city (Katrina/New Orleans, Harvey/Houston, the 1952 Great
Smog/London, the 2021 heat dome/Seattle, ...) — 31 cities, each with a Wikipedia
link. The city page shows a 'Notable weather in {city}' callout when one exists and
otherwise just the flavor blurb. Tests check the curated slugs are all valid and the
callout renders (and is absent for uncurated cities).
Add unique editorial content so the programmatic pages don't read as templated:
- gen_flavor.py seeds backend/cities_flavor.json with a short descriptive blurb per
city from Wikipedia's free REST summary API (no key), validating each match by
comparing article coordinates to the city's lat/lon so the wrong 'Springfield'
never attaches. Retries + modest concurrency; ~700/750 cities get a blurb, the
rest render without one. Text is CC BY-SA, attributed with a 'via Wikipedia' link.
- City pages show the blurb under the intro and a travel callout that deep-links to
the compare page with the city pre-loaded (/compare#loc=lat,lon) — the visitor
just adds their own city. Month pages get the same seasonal 'visiting in {month}?'
compare link. Both add unique per-page text and internal links.
- cities.py gains flavor(slug); tests cover the blurb + attribution + compare CTA.
* SEO: generate curated city set for crawlable climate pages
gen_cities.py reuses the GeoNames index places.py already parses to select the top
~500 metros by population, assigns each a stable URL-safe slug (dropping admin1 when
it repeats the city name), and writes committed backend/cities.json. cities.py loads
it lazily with slug lookup, all_slugs(), display_name(), and by_country() grouping
for the upcoming hub + sitemap.
* SEO: rendering core, robots.txt, sitemap.xml, and metadata hygiene
- content.py: Jinja2 environment + HTML responder (ETag/304), dynamic /robots.txt
(disallows /api and /alerts, points at the sitemap) and /sitemap.xml (enumerates
the home/static pages plus every city, month, and records URL from cities.py).
Registered on the app before the StaticFiles mount so the routes win.
- templates/base.html.j2: shared layout with unique title/description, self-
referential canonical, Open Graph, favicon/manifest, header nav (adds a Climate
link) and a footer link graph.
- Give each existing page a unique <meta description> (were 5x identical) and a
self-referential <link rel=canonical>; add WebApplication JSON-LD to the home page.
- Pin jinja2.
* SEO: server-rendered per-city climate page (/climate/{slug})
The keystone crawlable page: for a city it snaps to the grid cell, loads the
archive (fetching once if missing, self-healing), and renders as real HTML — a
'how today compares' block (grade + percentile per metric from grade_day, tinted
by tier), a monthly normals table (climatology at each month's 15th, shown in °F
and °C), all-time records (new grading.all_time_records helper), a breadcrumb,
Dataset+Place+BreadcrumbList JSON-LD, self-referential canonical, and links into
the interactive tool + month/records pages. Content-page CSS added to style.css
(renamed the table class to avoid colliding with the app's .normals flex row).
* SEO: month (/climate/{slug}/{month}) and records (/climate/{slug}/records) pages
Month pages render the exact-month long-tail ('average weather in {city} in
{month}') with that month's average high/low, typical p10-p90 range, month-specific
records, and prev/next month links. Records pages show all-time record highs/lows
per metric with dates (grading.all_time_records). Shared _resolve_city helper; the
literal /records route is registered before the {month} param and month names are
validated (unknown month -> 404).
* SEO: climate hub, weather glossary, and about/methodology pages
- /climate: crawlable directory of all ~500 cities grouped by country — the
internal-link graph that lets search engines discover every city page.
- /glossary + /glossary/{term}: plain-language definitions (climate normal,
percentile, temperature anomaly, feels-like, heat index, wind chill, humidity,
reanalysis) with DefinedTerm JSON-LD and cross-links into the tool.
- /about: methodology page (ERA5 data source, 45-year baseline, +/-7-day window,
percentile grading) for E-E-A-T. All linked from the shared footer.
* SEO: archive warmer, content-page tests, and deploy docs
- warm_cities.py: paced, idempotent offline warmer that pre-fetches each city
cell's archive so /climate pages serve from cache and a crawl can't burst the
archive quota (pages self-heal if hit before warming).
- tests/test_content.py: city-set slug uniqueness/lookup, robots.txt, sitemap
enumerating city/month/records URLs, and that a rendered city page carries the
stats + canonical + Dataset JSON-LD in the HTML; plus month/records/hub/glossary/
about routing and 404s.
- DEPLOY.md: document the content pages, the warm step, and submitting the sitemap.
