From 58ac3120b29c488ba3fba8aeef78ae19399b6aa3 Mon Sep 17 00:00:00 2001 From: Emi Griffith Date: Wed, 15 Jul 2026 16:53:11 -0700 Subject: [PATCH] SEO: crawlable programmatic climate pages + technical hygiene (#96) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * 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 (were 5x identical) and a self-referential ; 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. --- app.py | 6 + cities.json | 5002 +++++++++++++++++++++++++++++++ cities.py | 54 + content.py | 506 ++++ gen_cities.py | 82 + grading.py | 21 + requirements.txt | 2 + templates/about.html.j2 | 36 + templates/base.html.j2 | 58 + templates/city.html.j2 | 75 + templates/glossary.html.j2 | 19 + templates/glossary_term.html.j2 | 21 + templates/hub.html.j2 | 23 + templates/month.html.j2 | 39 + templates/records.html.j2 | 33 + tests/test_content.py | 74 + warm_cities.py | 48 + 17 files changed, 6099 insertions(+) create mode 100644 cities.json create mode 100644 cities.py create mode 100644 content.py create mode 100644 gen_cities.py create mode 100644 templates/about.html.j2 create mode 100644 templates/base.html.j2 create mode 100644 templates/city.html.j2 create mode 100644 templates/glossary.html.j2 create mode 100644 templates/glossary_term.html.j2 create mode 100644 templates/hub.html.j2 create mode 100644 templates/month.html.j2 create mode 100644 templates/records.html.j2 create mode 100644 tests/test_content.py create mode 100644 warm_cities.py diff --git a/app.py b/app.py index 5d9bed0..d0b4092 100644 --- a/app.py +++ b/app.py @@ -18,6 +18,7 @@ from fastapi.staticfiles import StaticFiles import api_accounts import audit import climate +import content import db import grid import notify @@ -617,6 +618,11 @@ app.add_api_route(f"{BASE}/compare", _page("compare.html"), methods=["GET", "HEA app.add_api_route(f"{BASE}/legend", _page("legend.html"), methods=["GET", "HEAD"], include_in_schema=False) app.add_api_route(f"{BASE}/alerts", _page("subscriptions.html"), methods=["GET", "HEAD"], include_in_schema=False) +# Crawlable, server-rendered SEO pages (climate hub / per-city / month / records / +# glossary / about) + robots.txt + sitemap.xml. Registered before the static mount +# so these explicit routes win. +content.register(app) + # Everything else under BASE (app.js, style.css, nav.js, …) is a static asset. # Registered last so the explicit page routes above win. Mounts must start with # "/", so at the root (BASE == "") mount at "/" — the earlier routes still win diff --git a/cities.json b/cities.json new file mode 100644 index 0000000..bc2b0a7 --- /dev/null +++ b/cities.json @@ -0,0 +1,5002 @@ +[ +{ +"slug":"shanghai-cn", +"name":"Shanghai", +"admin1":"Shanghai", +"country":"China", +"country_code":"CN", +"lat":31.22222, +"lon":121.45806, +"population":24874500 +}, +{ +"slug":"beijing-cn", +"name":"Beijing", +"admin1":"Beijing", +"country":"China", +"country_code":"CN", +"lat":39.9075, +"lon":116.39723, +"population":18960744 +}, +{ +"slug":"shenzhen-guangdong-cn", +"name":"Shenzhen", +"admin1":"Guangdong", +"country":"China", +"country_code":"CN", +"lat":22.54554, +"lon":114.0683, +"population":17494398 +}, +{ +"slug":"guangzhou-guangdong-cn", +"name":"Guangzhou", +"admin1":"Guangdong", +"country":"China", +"country_code":"CN", +"lat":23.11667, +"lon":113.25, +"population":16096724 +}, +{ +"slug":"kinshasa-cd", +"name":"Kinshasa", +"admin1":"Kinshasa", +"country":"Democratic Republic of the Congo", +"country_code":"CD", +"lat":-4.32758, +"lon":15.31357, +"population":16000000 +}, +{ +"slug":"istanbul-tr", +"name":"Istanbul", +"admin1":"Istanbul", +"country":"Turkey", +"country_code":"TR", +"lat":41.01384, +"lon":28.94966, +"population":15701602 +}, +{ +"slug":"lagos-ng", +"name":"Lagos", +"admin1":"Lagos", +"country":"Nigeria", +"country_code":"NG", +"lat":6.45407, +"lon":3.39467, +"population":15388000 +}, +{ +"slug":"ho-chi-minh-city-ho-chi-minh-city-hcmc-vn", +"name":"Ho Chi Minh City", +"admin1":"Ho Chi Minh City (HCMC)", +"country":"Vietnam", +"country_code":"VN", +"lat":10.82302, +"lon":106.62965, +"population":14002598 +}, +{ +"slug":"chengdu-sichuan-cn", +"name":"Chengdu", +"admin1":"Sichuan", +"country":"China", +"country_code":"CN", +"lat":30.66667, +"lon":104.06667, +"population":13568357 +}, +{ +"slug":"lahore-punjab-pk", +"name":"Lahore", +"admin1":"Punjab", +"country":"Pakistan", +"country_code":"PK", +"lat":31.558, +"lon":74.35071, +"population":13004135 +}, +{ +"slug":"mumbai-maharashtra-in", +"name":"Mumbai", +"admin1":"Maharashtra", +"country":"India", +"country_code":"IN", +"lat":19.07283, +"lon":72.88261, +"population":12691836 +}, +{ +"slug":"sao-paulo-br", +"name":"São Paulo", +"admin1":"São Paulo", +"country":"Brazil", +"country_code":"BR", +"lat":-23.5475, +"lon":-46.63611, +"population":12400232 +}, +{ +"slug":"mexico-city-mx", +"name":"Mexico City", +"admin1":"Mexico City", +"country":"Mexico", +"country_code":"MX", +"lat":19.42847, +"lon":-99.12766, +"population":12294193 +}, +{ +"slug":"karachi-sindh-pk", +"name":"Karachi", +"admin1":"Sindh", +"country":"Pakistan", +"country_code":"PK", +"lat":24.8608, +"lon":67.0104, +"population":11624219 +}, +{ +"slug":"tianjin-cn", +"name":"Tianjin", +"admin1":"Tianjin", +"country":"China", +"country_code":"CN", +"lat":39.14222, +"lon":117.17667, +"population":11090314 +}, +{ +"slug":"delhi-in", +"name":"Delhi", +"admin1":"Delhi", +"country":"India", +"country_code":"IN", +"lat":28.65195, +"lon":77.23149, +"population":11034555 +}, +{ +"slug":"wuhan-hubei-cn", +"name":"Wuhan", +"admin1":"Hubei", +"country":"China", +"country_code":"CN", +"lat":30.58333, +"lon":114.26667, +"population":10392693 +}, +{ +"slug":"moscow-ru", +"name":"Moscow", +"admin1":"Moscow", +"country":"Russia", +"country_code":"RU", +"lat":55.75204, +"lon":37.61781, +"population":10381222 +}, +{ +"slug":"dhaka-dhaka-division-bd", +"name":"Dhaka", +"admin1":"Dhaka Division", +"country":"Bangladesh", +"country_code":"BD", +"lat":23.7104, +"lon":90.40744, +"population":10356500 +}, +{ +"slug":"seoul-kr", +"name":"Seoul", +"admin1":"Seoul", +"country":"South Korea", +"country_code":"KR", +"lat":37.566, +"lon":126.9784, +"population":10349312 +}, +{ +"slug":"tokyo-jp", +"name":"Tokyo", +"admin1":"Tokyo", +"country":"Japan", +"country_code":"JP", +"lat":35.6895, +"lon":139.69171, +"population":9733276 +}, +{ +"slug":"dongguan-guangdong-cn", +"name":"Dongguan", +"admin1":"Guangdong", +"country":"China", +"country_code":"CN", +"lat":23.01797, +"lon":113.74866, +"population":9644871 +}, +{ +"slug":"cairo-eg", +"name":"Cairo", +"admin1":"Cairo", +"country":"Egypt", +"country_code":"EG", +"lat":30.06263, +"lon":31.24967, +"population":9606916 +}, +{ +"slug":"xian-shaanxi-cn", +"name":"Xi’an", +"admin1":"Shaanxi", +"country":"China", +"country_code":"CN", +"lat":34.25833, +"lon":108.92861, +"population":9600000 +}, +{ +"slug":"johannesburg-gauteng-za", +"name":"Johannesburg", +"admin1":"Gauteng", +"country":"South Africa", +"country_code":"ZA", +"lat":-26.20227, +"lon":28.04363, +"population":9418183 +}, +{ +"slug":"nanjing-jiangsu-cn", +"name":"Nanjing", +"admin1":"Jiangsu", +"country":"China", +"country_code":"CN", +"lat":32.06167, +"lon":118.77778, +"population":9314685 +}, +{ +"slug":"hangzhou-zhejiang-cn", +"name":"Hangzhou", +"admin1":"Zhejiang", +"country":"China", +"country_code":"CN", +"lat":30.29365, +"lon":120.16142, +"population":9236032 +}, +{ +"slug":"foshan-guangdong-cn", +"name":"Foshan", +"admin1":"Guangdong", +"country":"China", +"country_code":"CN", +"lat":23.02677, +"lon":113.13148, +"population":9042509 +}, +{ +"slug":"london-england-gb", +"name":"London", +"admin1":"England", +"country":"United Kingdom", +"country_code":"GB", +"lat":51.50853, +"lon":-0.12574, +"population":8961989 +}, +{ +"slug":"new-york-city-new-york-us", +"name":"New York City", +"admin1":"New York", +"country":"United States", +"country_code":"US", +"lat":40.71427, +"lon":-74.00597, +"population":8804190 +}, +{ +"slug":"jakarta-id", +"name":"Jakarta", +"admin1":"Jakarta", +"country":"Indonesia", +"country_code":"ID", +"lat":-6.21462, +"lon":106.84513, +"population":8540121 +}, +{ +"slug":"bengaluru-karnataka-in", +"name":"Bengaluru", +"admin1":"Karnataka", +"country":"India", +"country_code":"IN", +"lat":12.97194, +"lon":77.59369, +"population":8495492 +}, +{ +"slug":"hanoi-vn", +"name":"Hanoi", +"admin1":"Hanoi", +"country":"Vietnam", +"country_code":"VN", +"lat":21.0245, +"lon":105.84117, +"population":8053663 +}, +{ +"slug":"taipei-taiwan-tw", +"name":"Taipei", +"admin1":"Taiwan", +"country":"Taiwan", +"country_code":"TW", +"lat":25.05306, +"lon":121.52639, +"population":7871900 +}, +{ +"slug":"lima-lima-province-pe", +"name":"Lima", +"admin1":"Lima Province", +"country":"Peru", +"country_code":"PE", +"lat":-12.04318, +"lon":-77.02824, +"population":7737002 +}, +{ +"slug":"bogota-bogota-d-c-co", +"name":"Bogotá", +"admin1":"Bogota D.C.", +"country":"Colombia", +"country_code":"CO", +"lat":4.60971, +"lon":-74.08175, +"population":7674366 +}, +{ +"slug":"chongqing-cn", +"name":"Chongqing", +"admin1":"Chongqing", +"country":"China", +"country_code":"CN", +"lat":29.56026, +"lon":106.55771, +"population":7457599 +}, +{ +"slug":"hong-kong-hk", +"name":"Hong Kong", +"admin1":null, +"country":"Hong Kong", +"country_code":"HK", +"lat":22.27832, +"lon":114.17469, +"population":7396076 +}, +{ +"slug":"baghdad-iq", +"name":"Baghdad", +"admin1":"Baghdad", +"country":"Iraq", +"country_code":"IQ", +"lat":33.34058, +"lon":44.40088, +"population":7216000 +}, +{ +"slug":"wuzhong-ningxia-cn", +"name":"Wuzhong", +"admin1":"Ningxia", +"country":"China", +"country_code":"CN", +"lat":37.9867, +"lon":106.201, +"population":7202654 +}, +{ +"slug":"qingdao-shandong-cn", +"name":"Qingdao", +"admin1":"Shandong", +"country":"China", +"country_code":"CN", +"lat":36.06488, +"lon":120.38042, +"population":7172451 +}, +{ +"slug":"tehran-ir", +"name":"Tehran", +"admin1":"Tehran", +"country":"Iran", +"country_code":"IR", +"lat":35.69439, +"lon":51.42151, +"population":7153309 +}, +{ +"slug":"shenyang-liaoning-cn", +"name":"Shenyang", +"admin1":"Liaoning", +"country":"China", +"country_code":"CN", +"lat":41.79222, +"lon":123.43278, +"population":7050000 +}, +{ +"slug":"hyderabad-telangana-in", +"name":"Hyderabad", +"admin1":"Telangana", +"country":"India", +"country_code":"IN", +"lat":17.38405, +"lon":78.45636, +"population":6993262 +}, +{ +"slug":"rio-de-janeiro-br", +"name":"Rio de Janeiro", +"admin1":"Rio de Janeiro", +"country":"Brazil", +"country_code":"BR", +"lat":-22.90642, +"lon":-43.18223, +"population":6747815 +}, +{ +"slug":"suzhou-jiangsu-cn", +"name":"Suzhou", +"admin1":"Jiangsu", +"country":"China", +"country_code":"CN", +"lat":31.30408, +"lon":120.59538, +"population":6715559 +}, +{ +"slug":"puxi-shanghai-cn", +"name":"Puxi", +"admin1":"Shanghai", +"country":"China", +"country_code":"CN", +"lat":31.24414, +"lon":121.46592, +"population":6683712 +}, +{ +"slug":"ahmedabad-gujarat-in", +"name":"Ahmedabad", +"admin1":"Gujarat", +"country":"India", +"country_code":"IN", +"lat":23.02579, +"lon":72.58727, +"population":6357693 +}, +{ +"slug":"abidjan-abidjan-autonomous-district-ci", +"name":"Abidjan", +"admin1":"Abidjan Autonomous District", +"country":"Ivory Coast", +"country_code":"CI", +"lat":5.35444, +"lon":-4.00167, +"population":6321017 +}, +{ +"slug":"pudong-shanghai-cn", +"name":"Pudong", +"admin1":"Shanghai", +"country":"China", +"country_code":"CN", +"lat":31.23995, +"lon":121.50094, +"population":5681512 +}, +{ +"slug":"sydney-new-south-wales-au", +"name":"Sydney", +"admin1":"New South Wales", +"country":"Australia", +"country_code":"AU", +"lat":-33.86785, +"lon":151.20732, +"population":5638830 +}, +{ +"slug":"singapore-sg", +"name":"Singapore", +"admin1":null, +"country":"Singapore", +"country_code":"SG", +"lat":1.28967, +"lon":103.85007, +"population":5638700 +}, +{ +"slug":"melbourne-victoria-au", +"name":"Melbourne", +"admin1":"Victoria", +"country":"Australia", +"country_code":"AU", +"lat":-37.814, +"lon":144.96332, +"population":5435590 +}, +{ +"slug":"dar-es-salaam-dar-es-salaam-region-tz", +"name":"Dar es Salaam", +"admin1":"Dar es Salaam Region", +"country":"Tanzania", +"country_code":"TZ", +"lat":-6.82349, +"lon":39.26951, +"population":5383728 +}, +{ +"slug":"saint-petersburg-st-petersburg-ru", +"name":"Saint Petersburg", +"admin1":"St.-Petersburg", +"country":"Russia", +"country_code":"RU", +"lat":59.93863, +"lon":30.31413, +"population":5351935 +}, +{ +"slug":"alexandria-eg", +"name":"Alexandria", +"admin1":"Alexandria", +"country":"Egypt", +"country_code":"EG", +"lat":31.20176, +"lon":29.91582, +"population":5263542 +}, +{ +"slug":"harbin-heilongjiang-cn", +"name":"Harbin", +"admin1":"Heilongjiang", +"country":"China", +"country_code":"CN", +"lat":45.75, +"lon":126.65, +"population":5242897 +}, +{ +"slug":"bangkok-th", +"name":"Bangkok", +"admin1":"Bangkok", +"country":"Thailand", +"country_code":"TH", +"lat":13.75398, +"lon":100.50144, +"population":5104476 +}, +{ +"slug":"hefei-anhui-cn", +"name":"Hefei", +"admin1":"Anhui", +"country":"China", +"country_code":"CN", +"lat":31.86389, +"lon":117.28083, +"population":5050000 +}, +{ +"slug":"dalian-liaoning-cn", +"name":"Dalian", +"admin1":"Liaoning", +"country":"China", +"country_code":"CN", +"lat":38.91222, +"lon":121.60222, +"population":4913879 +}, +{ +"slug":"kano-kano-state-ng", +"name":"Kano", +"admin1":"Kano State", +"country":"Nigeria", +"country_code":"NG", +"lat":12.00012, +"lon":8.51672, +"population":4910000 +}, +{ +"slug":"santiago-santiago-metropolitan-cl", +"name":"Santiago", +"admin1":"Santiago Metropolitan", +"country":"Chile", +"country_code":"CL", +"lat":-33.45694, +"lon":-70.64827, +"population":4837295 +}, +{ +"slug":"cape-town-western-cape-za", +"name":"Cape Town", +"admin1":"Western Cape", +"country":"South Africa", +"country_code":"ZA", +"lat":-33.92584, +"lon":18.42322, +"population":4772846 +}, +{ +"slug":"peshawar-khyber-pakhtunkhwa-pk", +"name":"Peshawar", +"admin1":"Khyber Pakhtunkhwa", +"country":"Pakistan", +"country_code":"PK", +"lat":34.008, +"lon":71.57849, +"population":4758762 +}, +{ +"slug":"changchun-jilin-cn", +"name":"Changchun", +"admin1":"Jilin", +"country":"China", +"country_code":"CN", +"lat":43.88, +"lon":125.32278, +"population":4714996 +}, +{ +"slug":"jeddah-mecca-region-sa", +"name":"Jeddah", +"admin1":"Mecca Region", +"country":"Saudi Arabia", +"country_code":"SA", +"lat":21.49012, +"lon":39.18624, +"population":4697000 +}, +{ +"slug":"chennai-tamil-nadu-in", +"name":"Chennai", +"admin1":"Tamil Nadu", +"country":"India", +"country_code":"IN", +"lat":13.08784, +"lon":80.27847, +"population":4681087 +}, +{ +"slug":"kolkata-west-bengal-in", +"name":"Kolkata", +"admin1":"West Bengal", +"country":"India", +"country_code":"IN", +"lat":22.56263, +"lon":88.36304, +"population":4631392 +}, +{ +"slug":"xiamen-fujian-cn", +"name":"Xiamen", +"admin1":"Fujian", +"country":"China", +"country_code":"CN", +"lat":24.47979, +"lon":118.08187, +"population":4617251 +}, +{ +"slug":"surat-gujarat-in", +"name":"Surat", +"admin1":"Gujarat", +"country":"India", +"country_code":"IN", +"lat":21.19594, +"lon":72.83023, +"population":4591246 +}, +{ +"slug":"yangon-mm", +"name":"Yangon", 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+"slug":"ghaziabad-uttar-pradesh-in", +"name":"Ghāziābād", +"admin1":"Uttar Pradesh", +"country":"India", +"country_code":"IN", +"lat":28.66535, +"lon":77.43915, +"population":1199191 +}, +{ +"slug":"matola-maputo-province-mz", +"name":"Matola", +"admin1":"Maputo Province", +"country":"Mozambique", +"country_code":"MZ", +"lat":-25.96222, +"lon":32.45889, +"population":1198988 +}, +{ +"slug":"dhanbad-jharkhand-in", +"name":"Dhanbad", +"admin1":"Jharkhand", +"country":"India", +"country_code":"IN", +"lat":23.79759, +"lon":86.42992, +"population":1196214 +}, +{ +"slug":"arequipa-pe", +"name":"Arequipa", +"admin1":"Arequipa", +"country":"Peru", +"country_code":"PE", +"lat":-16.39899, +"lon":-71.53747, +"population":1195700 +}, +{ +"slug":"hong-kong-island-hk", +"name":"Hong Kong Island", +"admin1":null, +"country":"Hong Kong", +"country_code":"HK", +"lat":22.26302, +"lon":114.18419, +"population":1195529 +}, +{ +"slug":"fes-fes-meknes-ma", +"name":"Fes", +"admin1":"Fes-Meknes", +"country":"Morocco", +"country_code":"MA", +"lat":34.03313, +"lon":-5.00028, +"population":1191905 +}, +{ +"slug":"gustavo-adolfo-madero-mexico-city-mx", +"name":"Gustavo Adolfo Madero", +"admin1":"Mexico City", +"country":"Mexico", +"country_code":"MX", +"lat":19.49392, +"lon":-99.11075, +"population":1185772 +}, +{ +"slug":"nouakchott-mr", +"name":"Nouakchott", +"admin1":null, +"country":"Mauritania", +"country_code":"MR", +"lat":18.08581, +"lon":-15.9785, +"population":1184530 +}, +{ +"slug":"kisangani-tshopo-cd", +"name":"Kisangani", +"admin1":"Tshopo", +"country":"Democratic Republic of the Congo", +"country_code":"CD", +"lat":0.51528, +"lon":25.19099, +"population":1181788 +}, +{ +"slug":"jiaxing-zhejiang-cn", +"name":"Jiaxing", +"admin1":"Zhejiang", +"country":"China", +"country_code":"CN", +"lat":30.7522, +"lon":120.75, +"population":1180000 +}, +{ +"slug":"aurangabad-maharashtra-in", +"name":"Aurangabad", +"admin1":"Maharashtra", +"country":"India", +"country_code":"IN", +"lat":19.87757, +"lon":75.34226, +"population":1175116 +}, +{ +"slug":"zhongwei-ningxia-cn", +"name":"Zhongwei", +"admin1":"Ningxia", +"country":"China", +"country_code":"CN", +"lat":37.51129, +"lon":105.19067, +"population":1174600 +}, +{ +"slug":"omsk-omsk-oblast-ru", +"name":"Omsk", +"admin1":"Omsk Oblast", +"country":"Russia", +"country_code":"RU", +"lat":54.99244, +"lon":73.36859, +"population":1172070 +}, +{ +"slug":"pikine-dakar-sn", +"name":"Pikine", +"admin1":"Dakar", +"country":"Senegal", +"country_code":"SN", +"lat":14.76457, +"lon":-17.39071, +"population":1170791 +}, +{ +"slug":"pekanbaru-riau-id", +"name":"Pekanbaru", +"admin1":"Riau", +"country":"Indonesia", +"country_code":"ID", +"lat":0.51667, +"lon":101.44167, +"population":1167599 +}, +{ +"slug":"panjin-liaoning-cn", +"name":"Panjin", +"admin1":"Liaoning", +"country":"China", +"country_code":"CN", +"lat":41.121, +"lon":122.0739, +"population":1166481 +}, +{ +"slug":"bandar-lampung-lampung-id", +"name":"Bandar Lampung", +"admin1":"Lampung", +"country":"Indonesia", +"country_code":"ID", +"lat":-5.42917, +"lon":105.26111, +"population":1166066 +}, +{ +"slug":"prague-cz", +"name":"Prague", +"admin1":"Prague", +"country":"Czechia", +"country_code":"CZ", +"lat":50.08804, +"lon":14.42076, +"population":1165581 +}, +{ +"slug":"varanasi-uttar-pradesh-in", +"name":"Varanasi", +"admin1":"Uttar Pradesh", +"country":"India", +"country_code":"IN", +"lat":25.31668, +"lon":83.01041, +"population":1164404 +}, +{ +"slug":"jiujiang-jiangxi-cn", +"name":"Jiujiang", +"admin1":"Jiangxi", +"country":"China", +"country_code":"CN", +"lat":29.70475, +"lon":116.00206, +"population":1164268 +}, +{ +"slug":"samara-samara-oblast-ru", +"name":"Samara", +"admin1":"Samara Oblast", +"country":"Russia", +"country_code":"RU", +"lat":53.20767, +"lon":50.13553, +"population":1163399 +}, +{ +"slug":"aba-abia-state-ng", +"name":"Aba", +"admin1":"Abia State", +"country":"Nigeria", +"country_code":"NG", +"lat":5.10658, +"lon":7.36667, +"population":1160000 +}, +{ +"slug":"amritsar-punjab-in", +"name":"Amritsar", +"admin1":"Punjab", +"country":"India", +"country_code":"IN", +"lat":31.62234, +"lon":74.87534, +"population":1159227 +}, +{ +"slug":"birmingham-england-gb", +"name":"Birmingham", +"admin1":"England", +"country":"United Kingdom", +"country_code":"GB", +"lat":52.48142, +"lon":-1.89983, +"population":1157603 +}, +{ +"slug":"copenhagen-capital-region-dk", +"name":"Copenhagen", +"admin1":"Capital Region", +"country":"Denmark", +"country_code":"DK", +"lat":55.67594, +"lon":12.56553, +"population":1153615 +}, +{ +"slug":"sofia-sofia-capital-bg", +"name":"Sofia", +"admin1":"Sofia-Capital", +"country":"Bulgaria", +"country_code":"BG", +"lat":42.69751, +"lon":23.32415, +"population":1152556 +}, +{ +"slug":"anyang-henan-cn", +"name":"Anyang", +"admin1":"Henan", +"country":"China", +"country_code":"CN", +"lat":36.096, +"lon":114.38278, +"population":1146839 +}, +{ +"slug":"yerevan-am", +"name":"Yerevan", +"admin1":"Yerevan", +"country":"Armenia", +"country_code":"AM", +"lat":40.17765, +"lon":44.5126, +"population":1144700 +}, +{ +"slug":"luohu-district-guangdong-cn", +"name":"Luohu District", +"admin1":"Guangdong", +"country":"China", +"country_code":"CN", +"lat":22.54721, +"lon":114.13149, +"population":1143801 +}, +{ +"slug":"vijayawada-andhra-pradesh-in", +"name":"Vijayawada", +"admin1":"Andhra Pradesh", +"country":"India", +"country_code":"IN", +"lat":16.50745, +"lon":80.6466, +"population":1143232 +}, +{ +"slug":"fengxiang-shanghai-cn", +"name":"Fengxiang", +"admin1":"Shanghai", +"country":"China", +"country_code":"CN", +"lat":30.85841, +"lon":121.46779, +"population":1140872 +}, +{ +"slug":"bijie-guizhou-cn", +"name":"Bijie", +"admin1":"Guizhou", +"country":"China", +"country_code":"CN", +"lat":27.30193, +"lon":105.28627, +"population":1137383 +}, +{ +"slug":"monterrey-nuevo-leon-mx", +"name":"Monterrey", +"admin1":"Nuevo León", +"country":"Mexico", +"country_code":"MX", +"lat":25.68435, +"lon":-100.31721, +"population":1135512 +}, +{ +"slug":"kigali-rw", +"name":"Kigali", +"admin1":"Kigali", +"country":"Rwanda", +"country_code":"RW", +"lat":-1.94995, +"lon":30.05885, +"population":1132686 +}, +{ +"slug":"rostov-on-don-rostov-ru", +"name":"Rostov-on-Don", +"admin1":"Rostov", +"country":"Russia", +"country_code":"RU", +"lat":47.21997, +"lon":39.70769, +"population":1130305 +}, +{ +"slug":"zhuzhou-hunan-cn", +"name":"Zhuzhou", +"admin1":"Hunan", +"country":"China", +"country_code":"CN", +"lat":27.83333, +"lon":113.15, +"population":1129687 +}, +{ +"slug":"malingao-soccsksargen-ph", +"name":"Malingao", +"admin1":"Soccsksargen", +"country":"Philippines", +"country_code":"PH", +"lat":7.16083, +"lon":124.475, +"population":1121974 +}, +{ +"slug":"touba-diourbel-region-sn", +"name":"Touba", +"admin1":"Diourbel Region", +"country":"Senegal", +"country_code":"SN", +"lat":14.86229, +"lon":-15.87532, +"population":1120824 +}, +{ +"slug":"ufa-bashkortostan-republic-ru", +"name":"Ufa", +"admin1":"Bashkortostan Republic", +"country":"Russia", +"country_code":"RU", +"lat":54.74306, +"lon":55.96779, +"population":1120547 +}, +{ +"slug":"ranchi-jharkhand-in", +"name":"Ranchi", +"admin1":"Jharkhand", +"country":"India", +"country_code":"IN", +"lat":23.34316, +"lon":85.3094, +"population":1120374 +}, +{ +"slug":"shangrao-jiangxi-cn", +"name":"Shangrao", +"admin1":"Jiangxi", +"country":"China", +"country_code":"CN", +"lat":28.45179, +"lon":117.94287, +"population":1116486 +}, +{ +"slug":"lilongwe-central-region-mw", +"name":"Lilongwe", +"admin1":"Central Region", +"country":"Malawi", +"country_code":"MW", +"lat":-13.96692, +"lon":33.78725, +"population":1115815 +}, +{ +"slug":"huaibei-anhui-cn", +"name":"Huaibei", +"admin1":"Anhui", +"country":"China", +"country_code":"CN", +"lat":33.97444, +"lon":116.79167, +"population":1113321 +}, +{ +"slug":"maiduguri-borno-state-ng", +"name":"Maiduguri", +"admin1":"Borno State", +"country":"Nigeria", +"country_code":"NG", +"lat":11.84692, +"lon":13.15712, +"population":1110000 +}, +{ +"slug":"xuhui-shanghai-cn", +"name":"Xuhui", +"admin1":"Shanghai", +"country":"China", +"country_code":"CN", +"lat":31.19594, +"lon":121.44709, +"population":1109800 +}, +{ +"slug":"meishan-sichuan-cn", +"name":"Meishan", +"admin1":"Sichuan", +"country":"China", +"country_code":"CN", +"lat":30.04392, +"lon":103.83696, +"population":1107742 +}, +{ +"slug":"mwanza-tz", +"name":"Mwanza", +"admin1":"Mwanza", +"country":"Tanzania", +"country_code":"TZ", +"lat":-2.51667, +"lon":32.9, +"population":1104521 +} +] diff --git a/cities.py b/cities.py new file mode 100644 index 0000000..6aa9b0f --- /dev/null +++ b/cities.py @@ -0,0 +1,54 @@ +"""Access to the curated city set (backend/cities.json) that gets crawlable +climate pages. Loaded once, lazily; regenerate the JSON with gen_cities.py.""" +import json +import os + +_PATH = os.path.join(os.path.dirname(__file__), "cities.json") +_CITIES: list[dict] | None = None +_BY_SLUG: dict[str, dict] | None = None + + +def _load() -> list[dict]: + global _CITIES, _BY_SLUG + if _CITIES is None: + with open(_PATH, encoding="utf-8") as f: + _CITIES = json.load(f) + _BY_SLUG = {c["slug"]: c for c in _CITIES} + return _CITIES + + +def all_cities() -> list[dict]: + return _load() + + +def all_slugs() -> list[str]: + return [c["slug"] for c in _load()] + + +def get(slug: str) -> dict | None: + """The city for a slug, or None (→ 404).""" + _load() + return _BY_SLUG.get(slug) + + +def display_name(city: dict) -> str: + """Human label: 'Seattle, Washington, United States' (drops repeated admin1).""" + parts = [city["name"]] + if city.get("admin1") and city["admin1"] != city["name"]: + parts.append(city["admin1"]) + if city.get("country"): + parts.append(city["country"]) + return ", ".join(parts) + + +def by_country() -> dict[str, list[dict]]: + """Cities grouped by country (population-descending within each), country keys + ordered by their largest city — for the /climate hub's crawlable link graph.""" + groups: dict[str, list[dict]] = {} + for c in _load(): + key = c.get("country") or c.get("country_code") or "Other" + groups.setdefault(key, []).append(c) + for v in groups.values(): + v.sort(key=lambda x: -x["population"]) + # order countries by their biggest city's population (most prominent first) + return dict(sorted(groups.items(), key=lambda kv: -kv[1][0]["population"])) diff --git a/content.py b/content.py new file mode 100644 index 0000000..5b7ba77 --- /dev/null +++ b/content.py @@ -0,0 +1,506 @@ +"""Server-rendered, crawlable content pages (climate hub / per-city / month / +records / glossary / about) plus robots.txt and sitemap.xml. + +These are the SEO surface: real URLs with the climate stats in the HTML, rendered +with Jinja2 from the same builders the API uses, linking into the interactive tool. +Registered on the app (via register()) BEFORE the StaticFiles mount so they win. +""" +import datetime +import hashlib +import json +import os + +import polars as pl +from fastapi import HTTPException, Request, Response +from fastapi.responses import PlainTextResponse +from jinja2 import Environment, FileSystemLoader, select_autoescape + +import cities +import climate +import grading +import grid +from views import OBS_COLS + +_BASE = os.environ.get("THERMOGRAPH_BASE", "/thermograph").strip("/") +BASE = f"/{_BASE}" if _BASE else "" + +TEMPLATES_DIR = os.path.join(os.path.dirname(__file__), "templates") +_env = Environment( + loader=FileSystemLoader(TEMPLATES_DIR), + autoescape=select_autoescape(["html", "xml", "j2"]), + trim_blocks=True, + lstrip_blocks=True, +) + +MONTHS = ["january", "february", "march", "april", "may", "june", + "july", "august", "september", "october", "november", "december"] +MONTHS_TITLE = [m.capitalize() for m in MONTHS] +MONTH_INDEX = {m: i + 1 for i, m in enumerate(MONTHS)} + +# Display labels for the graded metrics (order = how they appear on the page). +METRIC_LABELS = [ + ("tmax", "High"), ("tmin", "Low"), ("feels", "Feels-like"), + ("humid", "Humidity"), ("wind", "Wind"), ("gust", "Gust"), ("precip", "Precip"), +] +_TEMP_METRICS = {"tmax", "tmin", "feels"} + + +def _c(f: float) -> int: + return round((f - 32) * 5 / 9) + + +def _temp(f) -> str: + """A Fahrenheit value shown in both units: '72°F (22°C)'.""" + if f is None: + return "—" + return f"{round(f)}°F ({_c(f)}°C)" + + +def _fmt(metric: str, v) -> str: + if v is None: + return "—" + if metric in _TEMP_METRICS: + return _temp(v) + if metric == "precip": + return f"{v:.2f} in" + if metric == "humid": + return f"{v:.1f} g/m³" + return f"{round(v)} mph" # wind, gust + + +def _month_doy(month_idx: int) -> int: + return datetime.date(2001, month_idx, 15).timetuple().tm_yday + + +# --- helpers ----------------------------------------------------------------- +def origin(request: Request) -> str: + proto = request.headers.get("x-forwarded-proto") or request.url.scheme + host = request.headers.get("host") or request.url.netloc + return f"{proto}://{host}" + + +def _respond_html(request: Request, template: str, **ctx) -> Response: + o = origin(request) + html = _env.get_template(template).render(base=BASE, origin=o, base_url=f"{o}{BASE}", **ctx) + etag = f'W/"{hashlib.sha1(html.encode()).hexdigest()[:20]}"' + inm = request.headers.get("if-none-match") + if inm and etag in {t.strip() for t in inm.split(",")}: + return Response(status_code=304, headers={"ETag": etag}) + return Response(html, media_type="text/html", headers={"ETag": etag}) + + +# --- robots.txt & sitemap.xml ------------------------------------------------- +def robots_txt(request: Request) -> Response: + base_url = f"{origin(request)}{BASE}" + body = ( + "User-agent: *\n" + "Allow: /\n" + f"Disallow: {BASE}/api/\n" # JSON endpoints, nothing to index + f"Disallow: {BASE}/alerts\n" # per-user, requires login + f"Sitemap: {base_url}/sitemap.xml\n" + ) + return PlainTextResponse(body) + + +def sitemap_xml(request: Request) -> Response: + base_url = f"{origin(request)}{BASE}" + today = datetime.date.today().isoformat() + urls: list[tuple[str, str, str]] = [] # (loc, changefreq, priority) + + def add(path: str, changefreq: str, priority: str) -> None: + urls.append((f"{base_url}{path}", changefreq, priority)) + + add("/", "daily", "1.0") + for p in ("/climate", "/about", "/glossary", "/calendar", "/compare", "/legend"): + add(p, "weekly", "0.6") + for slug in cities.all_slugs(): + add(f"/climate/{slug}", "daily", "0.8") + add(f"/climate/{slug}/records", "monthly", "0.5") + for m in MONTHS: + add(f"/climate/{slug}/{m}", "monthly", "0.5") + + parts = ['', + ''] + for loc, cf, pr in urls: + parts.append( + f"{loc}{today}" + f"{cf}{pr}" + ) + parts.append("") + return Response("\n".join(parts), media_type="application/xml") + + +# --- per-city climate pages --------------------------------------------------- +def _history_for(cell: dict): + """Cached archive for a cell, fetching once if missing (self-heals like the + notifier). Returns a polars frame or None.""" + hist = climate.load_cached_history(cell) + if hist is not None and not hist.is_empty(): + return hist + try: + hist, _ = climate.get_history(cell) + except Exception: # noqa: BLE001 - upstream unavailable: caller renders a 503 + return None + return hist if (hist is not None and not hist.is_empty()) else None + + +def _monthly_normals(history) -> list[dict]: + """One row per month: average high/low and average precip, from the ±7-day + climatology around each month's 15th.""" + rows = [] + for i, name in enumerate(MONTHS_TITLE, start=1): + clim = grading.climatology(history, _month_doy(i)) + tmax, tmin, precip = clim.get("tmax"), clim.get("tmin"), clim.get("precip") + rows.append({ + "name": name, + "slug": MONTHS[i - 1], + "high": _temp(tmax["mean"]) if tmax else "—", + "high_f": tmax["mean"] if tmax else None, + "low": _temp(tmin["mean"]) if tmin else "—", + "low_f": tmin["mean"] if tmin else None, + "precip": f"{precip['mean']:.2f} in" if precip else "—", + "precip_v": precip["mean"] if precip else None, + }) + return rows + + +def _today_vs_normal(history, cell) -> dict | None: + """Grade the latest recorded day against its climatology, for the hero block.""" + try: + recent = climate.get_recent_forecast(cell) + except Exception: # noqa: BLE001 + return None + if recent is None or recent.is_empty() or "date" not in recent.columns: + return None + today = datetime.date.today() + observed = recent.filter(pl.col("date") <= today).sort("date") + if observed.is_empty(): + return None + row = observed.row(observed.height - 1, named=True) + obs = {k: row[k] for k in OBS_COLS if k in row} + graded = grading.grade_day(history, row["date"], obs) + cards = [] + for key, label in METRIC_LABELS: + g = graded.get(key) + if not g: + continue + cards.append({ + "label": label, "metric": key, + "value": _fmt(key, g.get("value")), + "percentile": g.get("percentile"), + "grade": g.get("grade"), "cls": g.get("class"), + }) + date = row["date"] + return { + "date": date.isoformat() if hasattr(date, "isoformat") else str(date), + "cards": cards, + } + + +def _city_context(request, city, cell, history) -> dict: + name = city["name"] + display = cities.display_name(city) + years = history["date"].dt.year() + year_range = [int(years.min()), int(years.max())] + months = _monthly_normals(history) + warmest = max((m for m in months if m["high_f"] is not None), key=lambda m: m["high_f"], default=None) + coldest = min((m for m in months if m["low_f"] is not None), key=lambda m: m["low_f"], default=None) + wettest = max((m for m in months if m["precip_v"] is not None), key=lambda m: m["precip_v"], default=None) + records = grading.all_time_records(history) + tool_hash = f"{city['lat']:.5f},{city['lon']:.5f}" + + breadcrumb = [("Home", f"{BASE}/"), ("Climate", f"{BASE}/climate")] + if city.get("country"): + breadcrumb.append((city["country"], None)) + breadcrumb.append((name, None)) + + o = origin(request) + page_url = f"{o}{BASE}/climate/{city['slug']}" + jsonld = { + "@context": "https://schema.org", + "@graph": [ + {"@type": "Dataset", + "name": f"{display} climate normals and records", + "description": f"Average temperatures, precipitation and record highs and lows for " + f"{display}, from ~{year_range[1] - year_range[0]} years of daily climate history.", + "url": page_url, + "temporalCoverage": f"{year_range[0]}/{year_range[1]}", + "spatialCoverage": {"@type": "Place", "name": display, + "geo": {"@type": "GeoCoordinates", + "latitude": city["lat"], "longitude": city["lon"]}}, + "creator": {"@type": "Organization", "name": "Thermograph"}, + "isBasedOn": "https://open-meteo.com/ (ERA5 reanalysis)"}, + {"@type": "BreadcrumbList", + "itemListElement": [ + {"@type": "ListItem", "position": i + 1, "name": nm, + **({"item": f"{o}{href}"} if href else {})} + for i, (nm, href) in enumerate(breadcrumb)]}, + ], + } + return { + "section": "climate", + "city": city, "display": display, "name": name, + "year_range": year_range, "n_years": year_range[1] - year_range[0], + "months": months, "warmest": warmest, "coldest": coldest, "wettest": wettest, + "records": records, "today": _today_vs_normal(history, cell), + "tool_hash": tool_hash, + "breadcrumb": breadcrumb, + "canonical_path": f"/climate/{city['slug']}", + "page_title": f"{display} climate: average temperatures, records & how today compares", + "page_description": (f"Average monthly high and low temperatures, rainfall, and all-time records " + f"for {display}, plus how today's weather compares — graded against " + f"~{year_range[1] - year_range[0]} years of local climate history."), + "jsonld_str": json.dumps(jsonld, ensure_ascii=False, separators=(",", ":")), + } + + +def _resolve_city(slug: str): + """(city, cell, history) for a slug, or raise 404 (unknown) / 503 (warming).""" + city = cities.get(slug) + if city is None: + raise HTTPException(status_code=404, detail="Unknown city.") + cell = grid.snap(city["lat"], city["lon"]) + history = _history_for(cell) + if history is None: + raise HTTPException(status_code=503, detail="Climate data is warming up; please retry shortly.") + return city, cell, history + + +def city_page(request: Request, slug: str) -> Response: + city, cell, history = _resolve_city(slug) + return _respond_html(request, "city.html.j2", **_city_context(request, city, cell, history)) + + +# --- month & records pages ---------------------------------------------------- +def _month_context(request, city, history, month_idx: int) -> dict: + display = cities.display_name(city) + name = city["name"] + month_name = MONTHS_TITLE[month_idx - 1] + month_slug = MONTHS[month_idx - 1] + years = history["date"].dt.year() + year_range = [int(years.min()), int(years.max())] + + clim = grading.climatology(history, _month_doy(month_idx)) + tmax, tmin, precip = clim.get("tmax"), clim.get("tmin"), clim.get("precip") + mdf = history.filter(pl.col("date").dt.month() == month_idx) + mrec = grading.all_time_records(mdf) if not mdf.is_empty() else {} + + stats = [] + if tmax: + stats.append(("Average high", _temp(tmax["mean"]))) + stats.append(("Typical high range", f"{_temp(tmax['p10'])} to {_temp(tmax['p90'])}")) + if tmin: + stats.append(("Average low", _temp(tmin["mean"]))) + stats.append(("Typical low range", f"{_temp(tmin['p10'])} to {_temp(tmin['p90'])}")) + if precip: + stats.append(("Average daily precipitation", f"{precip['mean']:.2f} in")) + records = [] + if mrec.get("tmax"): + records.append(("Warmest on record", _temp(mrec["tmax"]["max"]), mrec["tmax"]["max_date"])) + if mrec.get("tmin"): + records.append(("Coldest on record", _temp(mrec["tmin"]["min"]), mrec["tmin"]["min_date"])) + + prev_i = 12 if month_idx == 1 else month_idx - 1 + next_i = 1 if month_idx == 12 else month_idx + 1 + breadcrumb = [("Home", f"{BASE}/"), ("Climate", f"{BASE}/climate"), + (name, f"{BASE}/climate/{city['slug']}"), (month_name, None)] + return { + "section": "climate", "city": city, "display": display, "name": name, + "month_name": month_name, "month_slug": month_slug, + "year_range": year_range, "n_years": year_range[1] - year_range[0], + "avg_high": _temp(tmax["mean"]) if tmax else "—", + "avg_low": _temp(tmin["mean"]) if tmin else "—", + "stats": stats, "records": records, + "tool_hash": f"{city['lat']:.5f},{city['lon']:.5f}", + "prev": {"name": MONTHS_TITLE[prev_i - 1], "slug": MONTHS[prev_i - 1]}, + "next": {"name": MONTHS_TITLE[next_i - 1], "slug": MONTHS[next_i - 1]}, + "breadcrumb": breadcrumb, + "canonical_path": f"/climate/{city['slug']}/{month_slug}", + "page_title": f"Average weather in {display} in {month_name}", + "page_description": (f"Average high and low temperatures, typical range, records and rainfall for " + f"{display} in {month_name}, from ~{year_range[1] - year_range[0]} years of local records."), + } + + +def month_page(request: Request, slug: str, month: str) -> Response: + if month not in MONTH_INDEX: + raise HTTPException(status_code=404, detail="Unknown month.") + city, cell, history = _resolve_city(slug) + return _respond_html(request, "month.html.j2", **_month_context(request, city, history, MONTH_INDEX[month])) + + +def _records_context(request, city, history) -> dict: + display = cities.display_name(city) + name = city["name"] + years = history["date"].dt.year() + year_range = [int(years.min()), int(years.max())] + rec = grading.all_time_records(history) + rows = [] + for key, label in METRIC_LABELS: + r = rec.get(key) + if not r: + continue + rows.append({ + "label": label, + "high": _fmt(key, r["max"]), "high_date": r["max_date"], + "low": _fmt(key, r["min"]), "low_date": r["min_date"], + }) + breadcrumb = [("Home", f"{BASE}/"), ("Climate", f"{BASE}/climate"), + (name, f"{BASE}/climate/{city['slug']}"), ("Records", None)] + return { + "section": "climate", "city": city, "display": display, "name": name, + "year_range": year_range, "n_years": year_range[1] - year_range[0], + "rows": rows, + "canonical_path": f"/climate/{city['slug']}/records", + "breadcrumb": breadcrumb, + "page_title": f"{display} weather records: hottest and coldest days on record", + "page_description": (f"All-time record high and low temperatures (and the dates they occurred) for " + f"{display}, from ~{year_range[1] - year_range[0]} years of daily climate history."), + } + + +def records_page(request: Request, slug: str) -> Response: + city, cell, history = _resolve_city(slug) + return _respond_html(request, "records.html.j2", **_records_context(request, city, history)) + + +# --- hub / glossary / about --------------------------------------------------- +def _breadcrumb(*items): + return list(items) + + +def hub_page(request: Request) -> Response: + groups = cities.by_country() + ctx = { + "section": "climate", + "groups": groups, + "n_cities": sum(len(v) for v in groups.values()), + "n_countries": len(groups), + "canonical_path": "/climate", + "breadcrumb": [("Home", f"{BASE}/"), ("Climate", None)], + "page_title": "City climate pages — averages, records and how today compares", + "page_description": ("Browse climate pages for hundreds of cities worldwide: average temperatures by " + "month, all-time records, and how today's weather compares to local history."), + } + return _respond_html(request, "hub.html.j2", **ctx) + + +# Weather-terms glossary. Each entry: slug -> (term, short definition, body HTML). +GLOSSARY: dict[str, dict] = { + "climate-normal": { + "term": "Climate normal", + "short": "The typical value of a weather metric for a place and time of year, averaged over decades.", + "body": "A climate normal is the long-term average of a weather variable (say, the daily high) " + "for a specific place and time of year. Thermograph builds each day's normal from every " + "historical day within ±7 days of that day-of-year, across ~45 years — so a day is judged " + "against its own season, not a single annual average.", + }, + "percentile": { + "term": "Percentile", + "short": "Where a value ranks within a distribution — the 90th percentile is warmer than 90% of days.", + "body": "A percentile says where a value falls within a range of past values. If today's high is at " + "the 97th percentile, only about 3% of comparable days in this location's history were warmer. " + "Thermograph grades every day by its percentile against the local ±7-day seasonal distribution.", + }, + "temperature-anomaly": { + "term": "Temperature anomaly", + "short": "How far a temperature departs from normal — the difference from the long-term average.", + "body": "A temperature anomaly is how much warmer or colder it is than the local normal for the " + "time of year. Thermograph expresses the same idea as a percentile and a grade (from “Below " + "Normal” to “Near Record”), so an anomaly is easy to read at a glance for any location.", + }, + "feels-like": { + "term": "Feels-like temperature", + "short": "What the air actually feels like once humidity and wind are accounted for.", + "body": "Feels-like (apparent temperature) combines air temperature with humidity and wind. In heat " + "it uses the heat index; in cold it uses " + "wind chill. Thermograph grades feels-like against its " + "own local history, so “Near Record” means extreme for that place.", + }, + "heat-index": { + "term": "Heat index", + "short": "How hot it feels when humidity is factored into the air temperature.", + "body": "The heat index is the apparent temperature on a hot, humid day: high humidity slows sweat " + "evaporation, so it feels hotter than the thermometer reads. Thermograph folds it into the " + "feels-like metric and grades how unusual it is locally.", + }, + "wind-chill": { + "term": "Wind chill", + "short": "How cold it feels when wind is factored into the air temperature.", + "body": "Wind chill is the apparent temperature on a cold, windy day: wind strips away body heat, so " + "it feels colder than the air temperature. It's the cold-weather half of " + "feels-like.", + }, + "humidity": { + "term": "Absolute humidity", + "short": "The actual mass of water vapor in the air, in grams per cubic meter.", + "body": "Thermograph reports absolute humidity (g/m³) — the real amount of water vapor in the " + "air — rather than relative humidity, which shifts with temperature. Graded against local history, " + "it shows genuinely muggy or unusually dry days.", + }, + "reanalysis": { + "term": "Reanalysis (ERA5)", + "short": "A gridded, physically-consistent record of past weather for anywhere on Earth.", + "body": "A reanalysis blends historical observations with a weather model to produce a consistent " + "record of past conditions everywhere — even where no station exists. Thermograph's ~45-year history " + "comes from ECMWF's ERA5 reanalysis (via Open-Meteo), which is why it works for any point on Earth.", + }, +} + + +def _glossary_body(entry: dict) -> str: + return entry["body"].replace("{base}", BASE) + + +def glossary_index(request: Request) -> Response: + ctx = { + "terms": [{"slug": s, **e} for s, e in GLOSSARY.items()], + "canonical_path": "/glossary", + "breadcrumb": [("Home", f"{BASE}/"), ("Glossary", None)], + "page_title": "Weather & climate glossary — heat index, feels-like, percentile, and more", + "page_description": ("Plain-language definitions of weather and climate terms: climate normal, percentile, " + "temperature anomaly, feels-like, heat index, wind chill, humidity, and reanalysis."), + } + return _respond_html(request, "glossary.html.j2", **ctx) + + +def glossary_term(request: Request, term: str) -> Response: + entry = GLOSSARY.get(term) + if entry is None: + raise HTTPException(status_code=404, detail="Unknown term.") + ctx = { + "term": entry["term"], "body": _glossary_body(entry), + "canonical_path": f"/glossary/{term}", + "breadcrumb": [("Home", f"{BASE}/"), ("Glossary", f"{BASE}/glossary"), (entry["term"], None)], + "page_title": f"{entry['term']} — what it means | Thermograph", + "page_description": entry["short"], + "others": [{"slug": s, "term": e["term"]} for s, e in GLOSSARY.items() if s != term], + } + return _respond_html(request, "glossary_term.html.j2", **ctx) + + +def about_page(request: Request) -> Response: + ctx = { + "canonical_path": "/about", + "breadcrumb": [("Home", f"{BASE}/"), ("About", None)], + "page_title": "About Thermograph — how the weather grades are calculated", + "page_description": ("How Thermograph works: ~45 years of ERA5 climate history, a ±7-day seasonal " + "window, and empirical percentiles that grade each day relative to its own location."), + } + return _respond_html(request, "about.html.j2", **ctx) + + +# --- registration ------------------------------------------------------------ +def register(app) -> None: + """Attach all content routes. Call from app.py BEFORE the StaticFiles mount.""" + app.add_api_route(f"{BASE}/robots.txt", robots_txt, methods=["GET"], include_in_schema=False) + app.add_api_route(f"{BASE}/sitemap.xml", sitemap_xml, methods=["GET"], include_in_schema=False) + app.add_api_route(f"{BASE}/about", about_page, methods=["GET", "HEAD"], include_in_schema=False) + app.add_api_route(f"{BASE}/glossary", glossary_index, methods=["GET", "HEAD"], include_in_schema=False) + app.add_api_route(f"{BASE}/glossary/{{term}}", glossary_term, methods=["GET", "HEAD"], include_in_schema=False) + # Hub before /climate/{slug} so the literal path wins. + app.add_api_route(f"{BASE}/climate", hub_page, methods=["GET", "HEAD"], include_in_schema=False) + app.add_api_route(f"{BASE}/climate/{{slug}}", city_page, methods=["GET", "HEAD"], include_in_schema=False) + # Records before the {month} param so the literal path wins. + app.add_api_route(f"{BASE}/climate/{{slug}}/records", records_page, methods=["GET", "HEAD"], include_in_schema=False) + app.add_api_route(f"{BASE}/climate/{{slug}}/{{month}}", month_page, methods=["GET", "HEAD"], include_in_schema=False) diff --git a/gen_cities.py b/gen_cities.py new file mode 100644 index 0000000..693ecf6 --- /dev/null +++ b/gen_cities.py @@ -0,0 +1,82 @@ +"""Offline generator for backend/cities.json — the finite set of cities that get +crawlable climate pages (/climate/). Run occasionally to refresh the list: + + python gen_cities.py [N] # default N=500 top metros by population + +It reuses the GeoNames index that places.py already downloads/parses (calling +places._load() synchronously fills places._data), takes the top-N places by +population, and assigns each a stable, unique, URL-safe slug. Committing the output +keeps the routable city set explicit and reviewable, and decouples page-serving +from the async place-name loader. +""" +import json +import os +import re +import sys +import unicodedata + +import places + +OUT_PATH = os.path.join(os.path.dirname(__file__), "cities.json") + +# GeoNames entry tuple layout (see places._load): the fields we keep. +_NAME, _ADMIN1, _COUNTRY, _CC, _LAT, _LON, _POP = 1, 2, 3, 4, 5, 6, 7 + + +def slugify(*parts: str) -> str: + """ASCII, lowercase, hyphenated slug from name/admin/country parts.""" + text = " ".join(p for p in parts if p) + text = unicodedata.normalize("NFKD", text).encode("ascii", "ignore").decode() + text = re.sub(r"[^a-zA-Z0-9]+", "-", text).strip("-").lower() + return re.sub(r"-{2,}", "-", text) + + +def build(n: int = 500) -> list[dict]: + places._load() # synchronous parse; fills places._data (entries are pop-desc) + if not places._data: + raise SystemExit("GeoNames index failed to load (see logs); cannot generate cities.") + entries = places._data[0] + + out: list[dict] = [] + seen_slugs: set[str] = set() + for e in entries: + if len(out) >= n: + break + name, admin1, country, cc = e[_NAME], e[_ADMIN1], e[_COUNTRY], e[_CC] + # Drop admin1 from the slug when it just repeats the city name + # (e.g. Tokyo/Tokyo, Singapore/Singapore) to avoid "tokyo-tokyo-jp". + admin_part = admin1 if admin1 and slugify(admin1) != slugify(name) else "" + base = slugify(name, admin_part, cc or "") + if not base: + continue + slug = base + i = 2 + while slug in seen_slugs: # disambiguate the rare collision + slug = f"{base}-{i}" + i += 1 + seen_slugs.add(slug) + out.append({ + "slug": slug, + "name": name, + "admin1": admin1, + "country": country, + "country_code": cc, + "lat": round(e[_LAT], 5), + "lon": round(e[_LON], 5), + "population": e[_POP], + }) + return out + + +def main() -> None: + n = int(sys.argv[1]) if len(sys.argv) > 1 else 500 + cities = build(n) + with open(OUT_PATH, "w", encoding="utf-8") as f: + json.dump(cities, f, ensure_ascii=False, indent=0, separators=(",", ":")) + f.write("\n") + print(f"wrote {len(cities)} cities -> {OUT_PATH}") + print("sample:", ", ".join(c["slug"] for c in cities[:8])) + + +if __name__ == "__main__": + main() diff --git a/grading.py b/grading.py index 12f4920..eb55041 100644 --- a/grading.py +++ b/grading.py @@ -161,6 +161,27 @@ def climatology(df: pl.DataFrame, target_doy: int) -> dict: return out +def all_time_records(df: pl.DataFrame) -> dict: + """All-time record high/low (and the date each occurred) per metric across the + full archive — the raw material for the records page and the city teaser.""" + out: dict = {} + for var in CLIMO_METRICS: + if var not in df.columns: + continue + sub = df.select(["date", var]).drop_nulls(var) + if sub.is_empty(): + continue + hi = sub.row(int(sub[var].arg_max()), named=True) + lo = sub.row(int(sub[var].arg_min()), named=True) + out[var] = { + "max": round(float(hi[var]), 2), + "max_date": hi["date"].isoformat() if hasattr(hi["date"], "isoformat") else str(hi["date"]), + "min": round(float(lo[var]), 2), + "min_date": lo["date"].isoformat() if hasattr(lo["date"], "isoformat") else str(lo["date"]), + } + return out + + def _band_stats(samples: np.ndarray) -> dict | None: if samples.size == 0: return None diff --git a/requirements.txt b/requirements.txt index 70b76c0..1f14143 100644 --- a/requirements.txt +++ b/requirements.txt @@ -9,3 +9,5 @@ aiosqlite==0.22.1 # Web Push (VAPID) delivery of notifications (see backend/push.py). Pulls in # py-vapid, cryptography, and http-ece. pywebpush==2.0.0 +# Server-rendered SEO content pages (see backend/content.py, templates/). +jinja2==3.1.6 diff --git a/templates/about.html.j2 b/templates/about.html.j2 new file mode 100644 index 0000000..3467de2 --- /dev/null +++ b/templates/about.html.j2 @@ -0,0 +1,36 @@ +{% extends "base.html.j2" %} +{% block title %}{{ page_title }}{% endblock %} +{% block description %}{{ page_description }}{% endblock %} +{% block canonical_path %}{{ canonical_path }}{% endblock %} +{% block content %} + +
+

About Thermograph

+

Thermograph answers one question for any point on Earth: how unusual is this + weather? Instead of an absolute temperature, it shows where a day falls in that exact + location's own climate history.

+ +

Where the data comes from

+

The ~45-year daily record — high, low, feels-like, humidity, wind, gust and precipitation — + comes from the ERA5 reanalysis (ECMWF), served via Open-Meteo. + Because reanalysis is a gridded, model-consistent record, Thermograph works even where there's + no weather station — anywhere on the ~4 sq mi grid.

+ +

How a day is graded

+

For each metric and date, Thermograph builds a reference distribution from every historical day + within ±7 days of that day-of-year — a 15-day seasonal window across all years. The + observed value is placed on that distribution as an empirical + percentile, then mapped to a grade from “Below Normal” through “High” to “Near Record”.

+

Everything is relative to the location: a 60°F day can be “Above Normal” in one place and + “Below Normal” in another. Precipitation is graded only among days that actually rained, so “Heavy” + means heavy for a rainy day here. See the grade guide for the full scale.

+ +

Freshness

+

The historical archive updates as new days are added; recent and forecast conditions refresh hourly. + City climate pages show the latest recorded day graded against the local normal.

+ +

Open the weather grader →

+
+{% endblock %} diff --git a/templates/base.html.j2 b/templates/base.html.j2 new file mode 100644 index 0000000..e100d1c --- /dev/null +++ b/templates/base.html.j2 @@ -0,0 +1,58 @@ + + + + + + {% block title %}Thermograph{% endblock %} + + + + + + + + + + + + + + + + + + {% block jsonld %}{% endblock %} + + +
+
+ +
+

Thermograph

+

How unusual is the weather? Graded against ~45 years of local climate history.

+
+ +
+
+ +
+ {% block content %}{% endblock %} +
+ + + + diff --git a/templates/city.html.j2 b/templates/city.html.j2 new file mode 100644 index 0000000..59cf87a --- /dev/null +++ b/templates/city.html.j2 @@ -0,0 +1,75 @@ +{% extends "base.html.j2" %} +{% block title %}{{ page_title }}{% endblock %} +{% block description %}{{ page_description }}{% endblock %} +{% block canonical_path %}{{ canonical_path }}{% endblock %} +{% block jsonld %}{% endblock %} +{% block content %} + + +
+

{{ display }} climate

+

Average temperatures, precipitation and all-time records for {{ display }}, + with every day graded against ~{{ n_years }} years of local climate history + ({{ year_range[0] }}–{{ year_range[1] }}). See where {% if warmest %}the warmest month is + {{ warmest.name }} ({{ warmest.high }} average high){% endif %}{% if coldest %} and the coldest + is {{ coldest.name }} ({{ coldest.low }} average low){% endif %}.

+ + {% if today %} +
+

How today compares

+

Latest recorded day: {{ today.date }} — each reading placed on {{ display }}'s + own ±7-day seasonal distribution.

+
+ {% for c in today.cards %} +
+ {{ c.label }} + {{ c.value }} + {% if c.percentile is not none %}{{ c.grade }} · {{ c.percentile }}th pct + {% else %}{{ c.grade }}{% endif %} +
+ {% endfor %} +
+

Open {{ name }} in the live weather grader →

+
+ {% endif %} + +
+

{{ name }} average temperatures by month

+

Typical daily high and low, and average precipitation, for each month in {{ display }}, + based on {{ year_range[0] }}–{{ year_range[1] }} records. + {% if wettest %}The wettest month is {{ wettest.name }} ({{ wettest.precip }} on an average day).{% endif %}

+
+ + + + {% for m in months %} + + + + + {% endfor %} + +
MonthAvg highAvg lowAvg precip
{{ m.name }}{{ m.high }}{{ m.low }}{{ m.precip }}
+
+
+ + {% if records.tmax or records.tmin %} +
+

Record extremes

+
    + {% if records.tmax %}
  • Hottest day on record: {{ records.tmax.max | round | int }}°F + ({{ ((records.tmax.max - 32) * 5 / 9) | round | int }}°C) on {{ records.tmax.max_date }}
    • {% endif %} + {% if records.tmin %}
  • Coldest day on record: {{ records.tmin.min | round | int }}°F + ({{ ((records.tmin.min - 32) * 5 / 9) | round | int }}°C) on {{ records.tmin.min_date }}
    • {% endif %} +
+

All {{ name }} weather records →

+
+ {% endif %} + +

Percentiles compare each day to {{ display }}'s own history, so grades are + relative to this location — a “Near Record” day here isn't the same temperature as elsewhere. + How the grades work →

+
+{% endblock %} diff --git a/templates/glossary.html.j2 b/templates/glossary.html.j2 new file mode 100644 index 0000000..65a7c71 --- /dev/null +++ b/templates/glossary.html.j2 @@ -0,0 +1,19 @@ +{% extends "base.html.j2" %} +{% block title %}{{ page_title }}{% endblock %} +{% block description %}{{ page_description }}{% endblock %} +{% block canonical_path %}{{ canonical_path }}{% endblock %} +{% block content %} + +
+

Weather & climate glossary

+

Plain-language definitions of the terms Thermograph uses to grade the weather.

+ {% for t in terms %} +
+

{{ t.term }}

+

{{ t.short }}

+
+ {% endfor %} +
+{% endblock %} diff --git a/templates/glossary_term.html.j2 b/templates/glossary_term.html.j2 new file mode 100644 index 0000000..8febad1 --- /dev/null +++ b/templates/glossary_term.html.j2 @@ -0,0 +1,21 @@ +{% extends "base.html.j2" %} +{% block title %}{{ page_title }}{% endblock %} +{% block description %}{{ page_description }}{% endblock %} +{% block canonical_path %}{{ canonical_path }}{% endblock %} +{% block jsonld %}{% endblock %} +{% block content %} + + +{% endblock %} diff --git a/templates/hub.html.j2 b/templates/hub.html.j2 new file mode 100644 index 0000000..1180b1b --- /dev/null +++ b/templates/hub.html.j2 @@ -0,0 +1,23 @@ +{% extends "base.html.j2" %} +{% block title %}{{ page_title }}{% endblock %} +{% block description %}{{ page_description }}{% endblock %} +{% block canonical_path %}{{ canonical_path }}{% endblock %} +{% block content %} + +
+

City climates

+

Average temperatures by month, all-time records, and how today compares — for + {{ n_cities }} cities across {{ n_countries }} countries. Every day is graded against that + location's own ~45 years of climate history.

+ {% for country, cs in groups.items() %} +
+

{{ country }}

+ +
+ {% endfor %} +
+{% endblock %} diff --git a/templates/month.html.j2 b/templates/month.html.j2 new file mode 100644 index 0000000..3c38f1e --- /dev/null +++ b/templates/month.html.j2 @@ -0,0 +1,39 @@ +{% extends "base.html.j2" %} +{% block title %}{{ page_title }}{% endblock %} +{% block description %}{{ page_description }}{% endblock %} +{% block canonical_path %}{{ canonical_path }}{% endblock %} +{% block content %} + + +
+

Weather in {{ display }} in {{ month_name }}

+

In an average {{ month_name }}, {{ name }} sees a daily high around {{ avg_high }} + and a low around {{ avg_low }}, based on {{ year_range[0] }}–{{ year_range[1] }} of local + climate records.

+ + + + {% for label, value in stats %} + + {% endfor %} + +
{{ label }}{{ value }}
+ + {% if records %} +

{{ month_name }} records

+
    + {% for label, value, date in records %}
  • {{ label }}: {{ value }} on {{ date }}
    • {% endfor %} +
+ {% endif %} + +

See {{ name }}'s live weather grade →

+ +

+ ‹ {{ prev.name }} · + {{ name }} climate overview · + {{ next.name }} › +

+
+{% endblock %} diff --git a/templates/records.html.j2 b/templates/records.html.j2 new file mode 100644 index 0000000..55345a0 --- /dev/null +++ b/templates/records.html.j2 @@ -0,0 +1,33 @@ +{% extends "base.html.j2" %} +{% block title %}{{ page_title }}{% endblock %} +{% block description %}{{ page_description }}{% endblock %} +{% block canonical_path %}{{ canonical_path }}{% endblock %} +{% block content %} + + +
+

{{ display }} weather records

+

All-time record highs and lows for {{ display }}, and the dates they occurred, across + {{ year_range[0] }}–{{ year_range[1] }} of daily climate history.

+ +
+ + + + {% for r in rows %} + + + + + + {% endfor %} + +
MetricRecord highOnRecord lowOn
{{ r.label }}{{ r.high }}{{ r.high_date }}{{ r.low }}{{ r.low_date }}
+
+ +

Grade {{ name }}'s weather now →

+

‹ Back to {{ name }} climate

+
+{% endblock %} diff --git a/tests/test_content.py b/tests/test_content.py new file mode 100644 index 0000000..0b9d265 --- /dev/null +++ b/tests/test_content.py @@ -0,0 +1,74 @@ +"""Tests for the crawlable SEO content pages: the city set, robots/sitemap, and +that the server-rendered pages contain the stats in the HTML (with the weather +layer faked, like test_api.py).""" +import pytest +from fastapi.testclient import TestClient + +import app as appmod +import cities +import climate + +# BASE defaults to /thermograph in tests (THERMOGRAPH_BASE unset). +B = "/thermograph" +SLUG = "london-england-gb" # present in cities.json + + +@pytest.fixture +def client(monkeypatch, history, recent): + monkeypatch.setattr(climate, "load_cached_history", lambda cell: history.clone()) + monkeypatch.setattr(climate, "get_recent_forecast", lambda cell: recent.clone()) + monkeypatch.setattr(climate, "get_history", lambda cell: (history.clone(), {"cached": True})) + return TestClient(appmod.app) + + +def test_city_set_slugs_unique_and_lookup(): + slugs = cities.all_slugs() + assert len(slugs) == len(set(slugs)) >= 100 + assert cities.get(SLUG) is not None + assert cities.get("does-not-exist") is None + + +def test_robots_txt(client): + r = client.get(f"{B}/robots.txt") + assert r.status_code == 200 + assert "Sitemap:" in r.text and "/sitemap.xml" in r.text + assert "Disallow: /thermograph/api/" in r.text + + +def test_sitemap_lists_city_urls(client): + r = client.get(f"{B}/sitemap.xml") + assert r.status_code == 200 + assert "" in r.text + assert f"/climate/{SLUG}/july" in r.text + assert f"/climate/{SLUG}/records" in r.text + + +def test_city_page_renders_stats_in_html(client): + r = client.get(f"{B}/climate/{SLUG}") + assert r.status_code == 200 + b = r.text + assert "London" in b and "climate" in b.lower() + assert 'rel="canonical"' in b and f"/climate/{SLUG}" in b + assert '"@type":"Dataset"' in b + assert "average temperatures by month" in b.lower() + # a real number rendered (°F appears in the normals/today text) + assert "°F" in b + + +def test_city_404(client): + assert client.get(f"{B}/climate/nope-not-a-city").status_code == 404 + + +def test_month_and_records(client): + assert client.get(f"{B}/climate/{SLUG}/july").status_code == 200 + assert client.get(f"{B}/climate/{SLUG}/records").status_code == 200 + assert client.get(f"{B}/climate/{SLUG}/notamonth").status_code == 404 + + +def test_hub_glossary_about(client): + assert client.get(f"{B}/climate").status_code == 200 + assert client.get(f"{B}/glossary").status_code == 200 + assert client.get(f"{B}/glossary/percentile").status_code == 200 + assert client.get(f"{B}/glossary/not-a-term").status_code == 404 + assert client.get(f"{B}/about").status_code == 200 diff --git a/warm_cities.py b/warm_cities.py new file mode 100644 index 0000000..3813f1c --- /dev/null +++ b/warm_cities.py @@ -0,0 +1,48 @@ +"""Pre-warm the archives for the curated city set (backend/cities.json) so the +crawlable /climate pages render from cache and a search-engine crawl never bursts +the archive API quota. Run at/after deploy: + + python warm_cities.py [--limit N] [--pace SECONDS] + +Idempotent: a cell whose archive is already cached is skipped. Fetches are paced +(default 2s) to stay well under the archive API's rate limit. A cell that still +has no cached archive when its page is first requested self-heals via get_history, +so this is an optimization, not a hard dependency. +""" +import sys +import time + +import cities +import climate +import grid + + +def main(limit: int | None = None, pace: float = 2.0) -> None: + todo = cities.all_cities() + if limit: + todo = todo[:limit] + fetched = skipped = failed = 0 + for i, c in enumerate(todo, 1): + cell = grid.snap(c["lat"], c["lon"]) + cached = climate.load_cached_history(cell) + if cached is not None and not cached.is_empty(): + skipped += 1 + continue + try: + climate.get_history(cell) # fetch + cache the ~45-yr archive + climate.get_recent_forecast(cell) # + the recent/forecast bundle (today block) + fetched += 1 + print(f"[{i}/{len(todo)}] warmed {c['slug']} ({cell['id']})") + time.sleep(pace) + except Exception as e: # noqa: BLE001 - keep going; the page self-heals later + failed += 1 + print(f"[{i}/{len(todo)}] FAILED {c['slug']}: {e}") + time.sleep(pace) + print(f"done: fetched={fetched} skipped(cached)={skipped} failed={failed}") + + +if __name__ == "__main__": + args = sys.argv[1:] + lim = int(args[args.index("--limit") + 1]) if "--limit" in args else None + pc = float(args[args.index("--pace") + 1]) if "--pace" in args else 2.0 + main(limit=lim, pace=pc)