feat: implement multi-source weather data collection system and dashboard frontend with integrated analysis services.

This commit is contained in:
2569718930@qq.com
2026-04-13 18:42:27 +08:00
parent 41cfb65b92
commit baaccc6636
12 changed files with 624 additions and 212 deletions
@@ -169,3 +169,11 @@
{"city": "hong kong", "timestamp": "2026-04-12T10:00:00+08:00", "date": "2026-04-12", "temp_symbol": "°C", "raw_mu": 28.999999999999996, "raw_sigma": 0.75, "deb_prediction": 28.2, "ensemble": {"p10": null, "median": null, "p90": null}, "multi_model": {"Open-Meteo": 27.5, "HKO(港天文)": 29.0}, "max_so_far": 27.2, "observation": {"current_temp": 27.2, "humidity": 77.0, "wind_speed_kt": 5.4, "visibility_mi": null, "local_hour": 10.283333333333333}, "peak_status": "before", "prob_snapshot": [{"v": 28, "p": 0.412}, {"v": 29, "p": 0.412}, {"v": 27, "p": 0.088}, {"v": 30, "p": 0.088}], "shadow_prob_snapshot": [{"v": 28, "p": 0.413}, {"v": 29, "p": 0.413}, {"v": 27, "p": 0.087}, {"v": 30, "p": 0.087}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260402162744", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 28.999999999999996, "calibrated_sigma": 0.7478013193453208} {"city": "hong kong", "timestamp": "2026-04-12T10:00:00+08:00", "date": "2026-04-12", "temp_symbol": "°C", "raw_mu": 28.999999999999996, "raw_sigma": 0.75, "deb_prediction": 28.2, "ensemble": {"p10": null, "median": null, "p90": null}, "multi_model": {"Open-Meteo": 27.5, "HKO(港天文)": 29.0}, "max_so_far": 27.2, "observation": {"current_temp": 27.2, "humidity": 77.0, "wind_speed_kt": 5.4, "visibility_mi": null, "local_hour": 10.283333333333333}, "peak_status": "before", "prob_snapshot": [{"v": 28, "p": 0.412}, {"v": 29, "p": 0.412}, {"v": 27, "p": 0.088}, {"v": 30, "p": 0.088}], "shadow_prob_snapshot": [{"v": 28, "p": 0.413}, {"v": 29, "p": 0.413}, {"v": 27, "p": 0.087}, {"v": 30, "p": 0.087}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260402162744", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 28.999999999999996, "calibrated_sigma": 0.7478013193453208}
{"city": "taipei", "timestamp": "2026-04-12T10:00:00+08:00", "date": "2026-04-12", "temp_symbol": "°C", "raw_mu": 30.689999999999998, "raw_sigma": 2.8574999999999995, "deb_prediction": 30.9, "ensemble": {"p10": 29.7, "median": 30.2, "p90": 30.6}, "multi_model": {"Open-Meteo": 30.9, "ECMWF": 30.9, "GFS": 32.9, "ICON": 30.9, "GEM": 28.9, "JMA": 30.8}, "max_so_far": 29.2, "observation": {"current_temp": 29.2, "humidity": 64.0, "wind_speed_kt": 1.2, "visibility_mi": null, "local_hour": 10.283333333333333}, "peak_status": "before", "prob_snapshot": [{"v": 31, "p": 0.179}, {"v": 30, "p": 0.175}, {"v": 32, "p": 0.163}, {"v": 29, "p": 0.152}], "shadow_prob_snapshot": [{"v": 31, "p": 0.183}, {"v": 30, "p": 0.178}, {"v": 32, "p": 0.165}, {"v": 29, "p": 0.153}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260402162744", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 30.689999999999998, "calibrated_sigma": 2.778122088606427} {"city": "taipei", "timestamp": "2026-04-12T10:00:00+08:00", "date": "2026-04-12", "temp_symbol": "°C", "raw_mu": 30.689999999999998, "raw_sigma": 2.8574999999999995, "deb_prediction": 30.9, "ensemble": {"p10": 29.7, "median": 30.2, "p90": 30.6}, "multi_model": {"Open-Meteo": 30.9, "ECMWF": 30.9, "GFS": 32.9, "ICON": 30.9, "GEM": 28.9, "JMA": 30.8}, "max_so_far": 29.2, "observation": {"current_temp": 29.2, "humidity": 64.0, "wind_speed_kt": 1.2, "visibility_mi": null, "local_hour": 10.283333333333333}, "peak_status": "before", "prob_snapshot": [{"v": 31, "p": 0.179}, {"v": 30, "p": 0.175}, {"v": 32, "p": 0.163}, {"v": 29, "p": 0.152}], "shadow_prob_snapshot": [{"v": 31, "p": 0.183}, {"v": 30, "p": 0.178}, {"v": 32, "p": 0.165}, {"v": 29, "p": 0.153}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260402162744", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 30.689999999999998, "calibrated_sigma": 2.778122088606427}
{"city": "hong kong", "timestamp": "2026-04-12T10:00:00+08:00", "date": "2026-04-12", "temp_symbol": "°C", "raw_mu": 27.71, "raw_sigma": 0.30937500000000073, "deb_prediction": 27.6, "ensemble": {"p10": 28.1, "median": 28.2, "p90": 28.5}, "multi_model": {"Open-Meteo": 27.5, "HKO(港天文)": 29.0, "ECMWF": 27.0, "GFS": 27.2, "ICON": 27.5, "GEM": 27.1, "JMA": 27.6}, "max_so_far": 27.2, "observation": {"current_temp": 27.2, "humidity": 77.0, "wind_speed_kt": 5.4, "visibility_mi": null, "local_hour": 10.283333333333333}, "peak_status": "before", "prob_snapshot": [{"v": 27, "p": 0.824}, {"v": 28, "p": 0.176}], "shadow_prob_snapshot": [{"v": 27, "p": 0.814}, {"v": 28, "p": 0.186}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260402162744", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 27.71, "calibrated_sigma": 0.32103944874938267} {"city": "hong kong", "timestamp": "2026-04-12T10:00:00+08:00", "date": "2026-04-12", "temp_symbol": "°C", "raw_mu": 27.71, "raw_sigma": 0.30937500000000073, "deb_prediction": 27.6, "ensemble": {"p10": 28.1, "median": 28.2, "p90": 28.5}, "multi_model": {"Open-Meteo": 27.5, "HKO(港天文)": 29.0, "ECMWF": 27.0, "GFS": 27.2, "ICON": 27.5, "GEM": 27.1, "JMA": 27.6}, "max_so_far": 27.2, "observation": {"current_temp": 27.2, "humidity": 77.0, "wind_speed_kt": 5.4, "visibility_mi": null, "local_hour": 10.283333333333333}, "peak_status": "before", "prob_snapshot": [{"v": 27, "p": 0.824}, {"v": 28, "p": 0.176}], "shadow_prob_snapshot": [{"v": 27, "p": 0.814}, {"v": 28, "p": 0.186}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260402162744", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 27.71, "calibrated_sigma": 0.32103944874938267}
{"city": "ankara", "timestamp": "2026-04-13T10:20:00.000Z", "date": "2026-04-13", "temp_symbol": "°C", "raw_mu": 10.8, "raw_sigma": 2.5, "deb_prediction": 10.9, "ensemble": {"p10": null, "median": null, "p90": null}, "multi_model": {"Open-Meteo": 10.6, "ECMWF": 11.7, "GFS": 11.3, "ICON": 10.6, "GEM": 10.8, "JMA": 10.5}, "max_so_far": 9.0, "observation": {"current_temp": 9.0, "humidity": null, "wind_speed_kt": 6.0, "visibility_mi": null, "local_hour": 13.566666666666666}, "peak_status": "before", "prob_snapshot": [{"v": 11, "p": 0.195}, {"v": 10, "p": 0.186}, {"v": 12, "p": 0.175}, {"v": 9, "p": 0.152}], "shadow_prob_snapshot": [{"v": 11, "p": 0.199}, {"v": 10, "p": 0.189}, {"v": 12, "p": 0.177}, {"v": 9, "p": 0.152}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260402162744", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 10.8, "calibrated_sigma": 2.4191943428283595}
{"city": "ankara", "timestamp": "2026-04-13T10:20:00.000Z", "date": "2026-04-13", "temp_symbol": "°C", "raw_mu": 10.77, "raw_sigma": 3.7124999999999995, "deb_prediction": 10.9, "ensemble": {"p10": 9.8, "median": 10.7, "p90": 11.6}, "multi_model": {"Open-Meteo": 10.6, "ECMWF": 11.7, "GFS": 11.3, "ICON": 10.6, "GEM": 10.8, "JMA": 10.5}, "max_so_far": 9.0, "observation": {"current_temp": 9.0, "humidity": null, "wind_speed_kt": 6.0, "visibility_mi": null, "local_hour": 13.583333333333334}, "peak_status": "before", "prob_snapshot": [{"v": 11, "p": 0.15}, {"v": 10, "p": 0.148}, {"v": 12, "p": 0.143}, {"v": 9, "p": 0.135}], "shadow_prob_snapshot": [{"v": 11, "p": 0.173}, {"v": 10, "p": 0.168}, {"v": 12, "p": 0.16}, {"v": 9, "p": 0.146}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260402162744", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 10.77, "calibrated_sigma": 3.0}
{"city": "istanbul", "timestamp": "2026-04-13T13:20:00+03:00", "date": "2026-04-13", "temp_symbol": "°C", "raw_mu": 12.5, "raw_sigma": 1.7999999999999998, "deb_prediction": 12.2, "ensemble": {"p10": null, "median": null, "p90": null}, "multi_model": {"Open-Meteo": 12.5, "ECMWF": 12.4, "GFS": 12.3, "ICON": 12.5, "GEM": 13.5, "JMA": 10.4}, "max_so_far": 12.0, "observation": {"current_temp": 12.0, "humidity": 46.9, "wind_speed_kt": 14.0, "visibility_mi": null, "local_hour": 13.583333333333334}, "peak_status": "before", "prob_snapshot": [{"v": 12, "p": 0.298}, {"v": 13, "p": 0.298}, {"v": 14, "p": 0.22}, {"v": 15, "p": 0.121}], "shadow_prob_snapshot": [{"v": 12, "p": 0.294}, {"v": 13, "p": 0.294}, {"v": 14, "p": 0.22}, {"v": 15, "p": 0.124}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260402162744", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 12.5, "calibrated_sigma": 1.8402601718515887}
{"city": "hong kong", "timestamp": "2026-04-13T18:20:00+08:00", "date": "2026-04-13", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.47999999999999987, "deb_prediction": 27.5, "ensemble": {"p10": null, "median": null, "p90": null}, "multi_model": {"Open-Meteo": 26.8, "HKO(港天文)": 30.0, "ECMWF": 27.5, "GFS": 26.9, "ICON": 26.8, "GEM": 27.7, "JMA": 28.1}, "max_so_far": 29.7, "observation": {"current_temp": 27.5, "humidity": 76.0, "wind_speed_kt": 4.3, "visibility_mi": null, "local_hour": 18.583333333333332}, "peak_status": "past", "prob_snapshot": [{"v": 29, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
{"city": "hong kong", "timestamp": "2026-04-13T18:20:00+08:00", "date": "2026-04-13", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.10952569444444488, "deb_prediction": 27.5, "ensemble": {"p10": 28.0, "median": 28.3, "p90": 28.6}, "multi_model": {"Open-Meteo": 26.8, "HKO(港天文)": 30.0, "ECMWF": 27.5, "GFS": 26.9, "ICON": 26.8, "GEM": 27.7, "JMA": 28.1}, "max_so_far": 29.7, "observation": {"current_temp": 27.5, "humidity": 76.0, "wind_speed_kt": 4.3, "visibility_mi": null, "local_hour": 18.583333333333332}, "peak_status": "past", "prob_snapshot": [{"v": 29, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
{"city": "tokyo", "timestamp": "2026-04-13T10:00:00.000Z", "date": "2026-04-13", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.4349999999999998, "deb_prediction": 21.9, "ensemble": {"p10": null, "median": null, "p90": null}, "multi_model": {"Open-Meteo": 20.3, "ECMWF": 22.8, "GFS": 22.0, "ICON": 22.6, "GEM": 23.2, "JMA": 20.3}, "max_so_far": 23.0, "observation": {"current_temp": 20.0, "humidity": null, "wind_speed_kt": 10.0, "visibility_mi": null, "local_hour": 19.583333333333332}, "peak_status": "past", "prob_snapshot": [{"v": 23, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
{"city": "hong kong", "timestamp": "2026-04-13T18:30:00+08:00", "date": "2026-04-13", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.47999999999999987, "deb_prediction": 27.5, "ensemble": {"p10": null, "median": null, "p90": null}, "multi_model": {"Open-Meteo": 26.8, "HKO(港天文)": 30.0, "ECMWF": 27.5, "GFS": 26.9, "ICON": 26.8, "GEM": 27.7, "JMA": 28.1}, "max_so_far": 29.7, "observation": {"current_temp": 27.4, "humidity": 77.0, "wind_speed_kt": 2.2, "visibility_mi": null, "local_hour": 18.666666666666668}, "peak_status": "past", "prob_snapshot": [{"v": 29, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
{"city": "hong kong", "timestamp": "2026-04-13T18:30:00+08:00", "date": "2026-04-13", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.10952569444444488, "deb_prediction": 27.5, "ensemble": {"p10": 28.0, "median": 28.3, "p90": 28.6}, "multi_model": {"Open-Meteo": 26.8, "HKO(港天文)": 30.0, "ECMWF": 27.5, "GFS": 26.9, "ICON": 26.8, "GEM": 27.7, "JMA": 28.1}, "max_so_far": 29.7, "observation": {"current_temp": 27.4, "humidity": 77.0, "wind_speed_kt": 2.2, "visibility_mi": null, "local_hour": 18.666666666666668}, "peak_status": "past", "prob_snapshot": [{"v": 29, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
+13 -1
View File
@@ -5,7 +5,7 @@ import clsx from "clsx";
import { useRouter } from "next/navigation"; import { useRouter } from "next/navigation";
import { useEffect, useMemo, useRef, useState } from "react"; import { useEffect, useMemo, useRef, useState } from "react";
import { ForecastTable } from "@/components/dashboard/PanelSections"; import { ForecastTable } from "@/components/dashboard/PanelSections";
import { useChart } from "@/hooks/useChart"; import { preloadChartJs, useChart } from "@/hooks/useChart";
import { useDashboardStore } from "@/hooks/useDashboardStore"; import { useDashboardStore } from "@/hooks/useDashboardStore";
import { useI18n } from "@/hooks/useI18n"; import { useI18n } from "@/hooks/useI18n";
import { getOfficialSourceLinks } from "@/lib/dashboard-official-sources"; import { getOfficialSourceLinks } from "@/lib/dashboard-official-sources";
@@ -360,6 +360,12 @@ export function DetailPanel() {
: `${t("detail.todayAnalysis")} (Pro)` : `${t("detail.todayAnalysis")} (Pro)`
} }
onClick={() => handleFeatureAccess("today")} onClick={() => handleFeatureAccess("today")}
onFocus={() => {
void preloadChartJs();
}}
onMouseEnter={() => {
void preloadChartJs();
}}
disabled={!store.selectedCity} disabled={!store.selectedCity}
> >
{isPro {isPro
@@ -373,6 +379,12 @@ export function DetailPanel() {
isPro ? t("detail.history") : `${t("detail.history")} (Pro)` isPro ? t("detail.history") : `${t("detail.history")} (Pro)`
} }
onClick={() => handleFeatureAccess("history")} onClick={() => handleFeatureAccess("history")}
onFocus={() => {
void preloadChartJs();
}}
onMouseEnter={() => {
void preloadChartJs();
}}
disabled={!store.selectedCity} disabled={!store.selectedCity}
> >
{isPro ? t("detail.history") : `${t("detail.history")} · Pro`} {isPro ? t("detail.history") : `${t("detail.history")} · Pro`}
@@ -14,7 +14,7 @@ import {
import type { ChartConfiguration } from "chart.js"; import type { ChartConfiguration } from "chart.js";
import clsx from "clsx"; import clsx from "clsx";
import { CSSProperties, useMemo } from "react"; import { CSSProperties, useEffect, useMemo, useState } from "react";
import { useChart } from "@/hooks/useChart"; import { useChart } from "@/hooks/useChart";
import { useDashboardStore } from "@/hooks/useDashboardStore"; import { useDashboardStore } from "@/hooks/useDashboardStore";
import { useI18n } from "@/hooks/useI18n"; import { useI18n } from "@/hooks/useI18n";
@@ -626,13 +626,47 @@ export function FutureForecastModal() {
const dateStr = store.futureModalDate; const dateStr = store.futureModalDate;
const isPro = store.proAccess.subscriptionActive; const isPro = store.proAccess.subscriptionActive;
const isProLoading = store.proAccess.loading; const isProLoading = store.proAccess.loading;
const [showDeferredTodaySections, setShowDeferredTodaySections] = useState(false);
if (!detail || !dateStr) return null; if (!detail || !dateStr) return null;
useEffect(() => {
setShowDeferredTodaySections(false);
if (typeof window === "undefined") {
setShowDeferredTodaySections(true);
return;
}
let cancelled = false;
let timeoutId: ReturnType<typeof setTimeout> | null = null;
let idleId: number | null = null;
const reveal = () => {
if (!cancelled) {
setShowDeferredTodaySections(true);
}
};
if ("requestIdleCallback" in window) {
idleId = window.requestIdleCallback(reveal, { timeout: 600 });
} else {
timeoutId = setTimeout(reveal, 120);
}
return () => {
cancelled = true;
if (idleId != null && "cancelIdleCallback" in window) {
window.cancelIdleCallback(idleId);
}
if (timeoutId != null) {
clearTimeout(timeoutId);
}
};
}, [dateStr, detail]);
const isToday = dateStr === detail.local_date; const isToday = dateStr === detail.local_date;
const detailDepth = detail.detail_depth || "full"; const detailDepth = detail.detail_depth || "full";
const isFullDetailReady = detailDepth === "full"; const isFullDetailReady = detailDepth === "full";
const isStructureSyncing = store.loadingState.refresh || !isFullDetailReady; const isStructureSyncing = store.loadingState.futureDeep || !isFullDetailReady;
const isMarketSyncing = store.loadingState.marketScan; const isMarketSyncing = store.loadingState.marketScan;
const isAnyLayerSyncing = isStructureSyncing || isMarketSyncing; const isAnyLayerSyncing = isStructureSyncing || isMarketSyncing;
const view = getFutureModalView(detail, dateStr, locale); const view = getFutureModalView(detail, dateStr, locale);
@@ -642,8 +676,11 @@ export function FutureForecastModal() {
} as CSSProperties & { "--score-position": string }; } as CSSProperties & { "--score-position": string };
const weatherSummary = getWeatherSummary(detail, locale); const weatherSummary = getWeatherSummary(detail, locale);
const paceView = useMemo( const paceView = useMemo(
() => (isToday ? getTodayPaceView(detail, locale) : null), () =>
[detail, isToday, locale], isToday && showDeferredTodaySections
? getTodayPaceView(detail, locale)
: null,
[detail, isToday, locale, showDeferredTodaySections],
); );
const probabilityView = useMemo( const probabilityView = useMemo(
() => getProbabilityView(detail, dateStr), () => getProbabilityView(detail, dateStr),
@@ -674,6 +711,7 @@ export function FutureForecastModal() {
}; };
}, [modelView]); }, [modelView]);
const boundaryRiskView = useMemo(() => { const boundaryRiskView = useMemo(() => {
if (!showDeferredTodaySections) return null;
if (!isToday || !paceView) return null; if (!isToday || !paceView) return null;
const selectedBucket = marketScan?.temperature_bucket || null; const selectedBucket = marketScan?.temperature_bucket || null;
const bounds = parseBucketBoundaries(selectedBucket); const bounds = parseBucketBoundaries(selectedBucket);
@@ -718,8 +756,9 @@ export function FutureForecastModal() {
tone, tone,
value: `${nearest.gap.toFixed(1)}${detail.temp_symbol}`, value: `${nearest.gap.toFixed(1)}${detail.temp_symbol}`,
}; };
}, [detail.deb?.prediction, detail.temp_symbol, isToday, locale, marketScan?.temperature_bucket, paceView]); }, [detail.deb?.prediction, detail.temp_symbol, isToday, locale, marketScan?.temperature_bucket, paceView, showDeferredTodaySections]);
const peakWindowStateView = useMemo(() => { const peakWindowStateView = useMemo(() => {
if (!showDeferredTodaySections) return null;
if (!isToday || !paceView) return null; if (!isToday || !paceView) return null;
const firstHour = Number(detail.peak?.first_h); const firstHour = Number(detail.peak?.first_h);
const lastHour = Number(detail.peak?.last_h); const lastHour = Number(detail.peak?.last_h);
@@ -754,8 +793,9 @@ export function FutureForecastModal() {
tone, tone,
value: paceView.peakWindowText, value: paceView.peakWindowText,
}; };
}, [detail.local_time, detail.peak?.first_h, detail.peak?.last_h, isToday, locale, paceView]); }, [detail.local_time, detail.peak?.first_h, detail.peak?.last_h, isToday, locale, paceView, showDeferredTodaySections]);
const networkLeadView = useMemo(() => { const networkLeadView = useMemo(() => {
if (!showDeferredTodaySections) return null;
if (!isToday) return null; if (!isToday) return null;
const delta = Number(detail.airport_vs_network_delta); const delta = Number(detail.airport_vs_network_delta);
const leadSignal = detail.network_lead_signal; const leadSignal = detail.network_lead_signal;
@@ -797,7 +837,7 @@ export function FutureForecastModal() {
tone, tone,
value: `${delta > 0 ? "+" : ""}${delta.toFixed(1)}${detail.temp_symbol}`, value: `${delta > 0 ? "+" : ""}${delta.toFixed(1)}${detail.temp_symbol}`,
}; };
}, [detail.airport_vs_network_delta, detail.network_lead_signal, detail.temp_symbol, isToday, locale]); }, [detail.airport_vs_network_delta, detail.network_lead_signal, detail.temp_symbol, isToday, locale, showDeferredTodaySections]);
const isNoaaSettlement = const isNoaaSettlement =
detail.current?.settlement_source === "noaa" || detail.current?.settlement_source === "noaa" ||
detail.current?.settlement_source_label === "NOAA"; detail.current?.settlement_source_label === "NOAA";
@@ -871,6 +911,7 @@ export function FutureForecastModal() {
formatBucketLabel(marketScan?.temperature_bucket) !== "--" && formatBucketLabel(marketScan?.temperature_bucket) !== "--" &&
hottestBucketLabel === formatBucketLabel(marketScan?.temperature_bucket); hottestBucketLabel === formatBucketLabel(marketScan?.temperature_bucket);
const marketAwareUpperAirCue = useMemo(() => { const marketAwareUpperAirCue = useMemo(() => {
if (!showDeferredTodaySections) return null;
if (!isToday || (!upperAirSignal.source && !tafSignal.available)) return null; if (!isToday || (!upperAirSignal.source && !tafSignal.available)) return null;
const crowded = hottestMatchesSettlement && (topBucketProbability || 0) >= 0.3; const crowded = hottestMatchesSettlement && (topBucketProbability || 0) >= 0.3;
@@ -1014,6 +1055,7 @@ export function FutureForecastModal() {
topBucketProbability, topBucketProbability,
upperAirSignal.heating_setup, upperAirSignal.heating_setup,
upperAirSignal.source, upperAirSignal.source,
showDeferredTodaySections,
]); ]);
const topObservedTemp = const topObservedTemp =
detail.current?.max_so_far != null detail.current?.max_so_far != null
@@ -1038,22 +1080,25 @@ export function FutureForecastModal() {
percent, percent,
}; };
})(); })();
const displayedUpperAirSummary = const displayedUpperAirSummary = showDeferredTodaySections
marketAwareUpperAirCue?.summary || view.front.upperAirSummary; ? marketAwareUpperAirCue?.summary || view.front.upperAirSummary
const displayedUpperAirMetrics = (view.front.upperAirMetrics || []).map( : "";
(metric, index) => const displayedUpperAirMetrics = showDeferredTodaySections
index === 0 && ? (view.front.upperAirMetrics || []).map((metric, index) =>
(metric.label === "Trade cue" || metric.label === "交易动作") && index === 0 &&
marketAwareUpperAirCue (metric.label === "Trade cue" || metric.label === "交易动作") &&
? { marketAwareUpperAirCue
...metric, ? {
note: marketAwareUpperAirCue.note, ...metric,
tone: marketAwareUpperAirCue.tone, note: marketAwareUpperAirCue.note,
value: marketAwareUpperAirCue.value, tone: marketAwareUpperAirCue.tone,
} value: marketAwareUpperAirCue.value,
: metric, }
); : metric,
)
: [];
const localizedAiCommentaryLines = useMemo(() => { const localizedAiCommentaryLines = useMemo(() => {
if (!showDeferredTodaySections) return [] as string[];
const commentary = detail.dynamic_commentary || {}; const commentary = detail.dynamic_commentary || {};
const headline = String( const headline = String(
locale === "en-US" ? commentary.headline_en || "" : commentary.headline_zh || "", locale === "en-US" ? commentary.headline_en || "" : commentary.headline_zh || "",
@@ -1065,8 +1110,9 @@ export function FutureForecastModal() {
? bullets.map((item) => String(item || "").trim()).filter(Boolean) ? bullets.map((item) => String(item || "").trim()).filter(Boolean)
: []; : [];
return [headline, ...cleanedBullets].filter(Boolean).slice(0, 3); return [headline, ...cleanedBullets].filter(Boolean).slice(0, 3);
}, [detail.dynamic_commentary, locale]); }, [detail.dynamic_commentary, locale, showDeferredTodaySections]);
const todayTradeSummaryLines = useMemo(() => { const todayTradeSummaryLines = useMemo(() => {
if (!showDeferredTodaySections) return [] as string[];
if (!isToday) return [] as string[]; if (!isToday) return [] as string[];
if (localizedAiCommentaryLines.length > 0) { if (localizedAiCommentaryLines.length > 0) {
return localizedAiCommentaryLines; return localizedAiCommentaryLines;
@@ -1102,7 +1148,7 @@ export function FutureForecastModal() {
); );
} }
return lines.slice(0, 3); return lines.slice(0, 3);
}, [boundaryRiskView, isToday, locale, localizedAiCommentaryLines, networkLeadView, paceView]); }, [boundaryRiskView, isToday, locale, localizedAiCommentaryLines, networkLeadView, paceView, showDeferredTodaySections]);
const syncStatusItems = [ const syncStatusItems = [
{ {
key: "base", key: "base",
@@ -1379,7 +1425,7 @@ export function FutureForecastModal() {
</div> </div>
</section> </section>
{paceView ? ( {showDeferredTodaySections && paceView ? (
<section className="future-v2-card future-v2-pace-card future-v2-focus-card"> <section className="future-v2-card future-v2-pace-card future-v2-focus-card">
<div className="future-v2-card-head"> <div className="future-v2-card-head">
<h4 className="future-v2-card-title"> <h4 className="future-v2-card-title">
@@ -1497,6 +1543,24 @@ export function FutureForecastModal() {
))} ))}
</div> </div>
</section> </section>
) : isToday ? (
<section className="future-v2-card future-v2-support-card">
<div className="future-v2-card-head">
<h4 className="future-v2-card-title">
{locale === "en-US" ? "Current Pace" : "当前节奏"}
</h4>
<div className="future-v2-card-kicker">
{locale === "en-US"
? "Backfilling intraday pace context"
: "正在补齐日内节奏上下文"}
</div>
</div>
<div className="future-trend-summary future-trend-summary-muted">
{locale === "en-US"
? "Expected-now pace, boundary risk, and airport-vs-network cues are loading in the background."
: "预期此刻节奏、边界风险和机场对比站网信号正在后台补齐。"}
</div>
</section>
) : null} ) : null}
</aside> </aside>
@@ -1560,164 +1624,175 @@ export function FutureForecastModal() {
</section> </section>
</div> </div>
<section className="future-modal-section"> {showDeferredTodaySections ? (
<h3>{t("future.structureToday")}</h3> <section className="future-modal-section">
<div className="future-front-score"> <h3>{t("future.structureToday")}</h3>
<div className="future-front-bar" style={barStyle}> <div className="future-front-score">
<div <div className="future-front-bar" style={barStyle}>
style={{
position: "absolute",
top: 0,
bottom: 0,
left: "50%",
width: "2px",
background: "rgba(255, 255, 255, 0.2)",
transform: "translateX(-50%)",
zIndex: 1,
}}
/>
</div>
<div className="future-front-meta">
<span className="future-front-pill">
{t("future.judgement")}: {view.front.label}
</span>
<span className="future-front-pill">
{t("future.confidence")}:{" "}
{t(`confidence.${view.front.confidence}`)}
</span>
<span className="future-front-pill">
{t("future.maxPrecip")}:{" "}
{Math.round(view.front.precipMax)}%
</span>
</div>
{todayTradeSummaryLines.length > 0 ? (
<div className="future-trend-summary">
{todayTradeSummaryLines.map((line, index) => (
<div key={`${index}-${line}`}>{line}</div>
))}
</div>
) : null}
</div>
<div className="future-subsection-title">
{locale === "en-US" ? "Surface Structure" : "近地面信号"}
</div>
<div className="future-trend-grid">
{view.front.metrics.slice(0, 6).map((metric) => (
<div key={metric.label} className="future-trend-card">
<div className="future-trend-label">{metric.label}</div>
<div <div
className={clsx( style={{
"future-trend-value", position: "absolute",
metric.tone === "warm" && "warm", top: 0,
metric.tone === "cold" && "cold", bottom: 0,
)} left: "50%",
> width: "2px",
{metric.value} background: "rgba(255, 255, 255, 0.2)",
transform: "translateX(-50%)",
zIndex: 1,
}}
/>
</div>
<div className="future-front-meta">
<span className="future-front-pill">
{t("future.judgement")}: {view.front.label}
</span>
<span className="future-front-pill">
{t("future.confidence")}:{" "}
{t(`confidence.${view.front.confidence}`)}
</span>
<span className="future-front-pill">
{t("future.maxPrecip")}:{" "}
{Math.round(view.front.precipMax)}%
</span>
</div>
{todayTradeSummaryLines.length > 0 ? (
<div className="future-trend-summary">
{todayTradeSummaryLines.map((line, index) => (
<div key={`${index}-${line}`}>{line}</div>
))}
</div> </div>
{getTrendMetricVisual(metric) ? ( ) : null}
</div>
<div className="future-subsection-title">
{locale === "en-US" ? "Surface Structure" : "近地面信号"}
</div>
<div className="future-trend-grid">
{view.front.metrics.slice(0, 6).map((metric) => (
<div key={metric.label} className="future-trend-card">
<div className="future-trend-label">{metric.label}</div>
<div <div
className={clsx( className={clsx(
"future-trend-meter", "future-trend-value",
getTrendMetricVisual(metric)?.mode === "center" && metric.tone === "warm" && "warm",
"center", metric.tone === "cold" && "cold",
)} )}
> >
{getTrendMetricVisual(metric)?.mode === "center" ? ( {metric.value}
<span className="future-trend-meter-midline" />
) : null}
<div
className={clsx(
"future-trend-meter-fill",
getTrendMetricVisual(metric)?.tone === "warm" &&
"warm",
getTrendMetricVisual(metric)?.tone === "cold" &&
"cold",
)}
style={{
width: `${getTrendMetricVisual(metric)?.percent ?? 0}%`,
}}
/>
</div> </div>
) : null} {getTrendMetricVisual(metric) ? (
<div className="future-trend-note">{metric.note}</div>
</div>
))}
</div>
<>
<div className="future-subsection-title">
{locale === "en-US" ? "Upper-Air Structure" : "高空结构信号"}
</div>
{displayedUpperAirSummary ? (
<div className="future-trend-summary">
{displayedUpperAirSummary}
</div>
) : (
<div className="future-trend-summary future-trend-summary-muted">
{locale === "en-US"
? "Upper-air structure is temporarily unavailable for this city. For now, lean on surface structure and TAF timing."
: "该城市当前暂无可用的高空结构数据,先以近地面结构和 TAF 时段作为主判断。"}
</div>
)}
{displayedUpperAirMetrics.length > 0 ? (
<div className="future-trend-grid">
{displayedUpperAirMetrics.map((metric) => (
<div key={metric.label} className="future-trend-card">
<div className="future-trend-label">{metric.label}</div>
<div <div
className={clsx( className={clsx(
"future-trend-value", "future-trend-meter",
metric.tone === "warm" && "warm", getTrendMetricVisual(metric)?.mode === "center" &&
metric.tone === "cold" && "cold", "center",
)} )}
> >
{metric.value} {getTrendMetricVisual(metric)?.mode === "center" ? (
</div> <span className="future-trend-meter-midline" />
{getTrendMetricVisual(metric) ? ( ) : null}
<div <div
className={clsx( className={clsx(
"future-trend-meter", "future-trend-meter-fill",
getTrendMetricVisual(metric)?.mode === "center" && getTrendMetricVisual(metric)?.tone === "warm" &&
"center", "warm",
getTrendMetricVisual(metric)?.tone === "cold" &&
"cold",
)}
style={{
width: `${getTrendMetricVisual(metric)?.percent ?? 0}%`,
}}
/>
</div>
) : null}
<div className="future-trend-note">{metric.note}</div>
</div>
))}
</div>
<>
<div className="future-subsection-title">
{locale === "en-US" ? "Upper-Air Structure" : "高空结构信号"}
</div>
{displayedUpperAirSummary ? (
<div className="future-trend-summary">
{displayedUpperAirSummary}
</div>
) : (
<div className="future-trend-summary future-trend-summary-muted">
{locale === "en-US"
? "Upper-air structure is temporarily unavailable for this city. For now, lean on surface structure and TAF timing."
: "该城市当前暂无可用的高空结构数据,先以近地面结构和 TAF 时段作为主判断。"}
</div>
)}
{displayedUpperAirMetrics.length > 0 ? (
<div className="future-trend-grid">
{displayedUpperAirMetrics.map((metric) => (
<div key={metric.label} className="future-trend-card">
<div className="future-trend-label">{metric.label}</div>
<div
className={clsx(
"future-trend-value",
metric.tone === "warm" && "warm",
metric.tone === "cold" && "cold",
)} )}
> >
{getTrendMetricVisual(metric)?.mode === "center" ? ( {metric.value}
<span className="future-trend-meter-midline" /> </div>
) : null} {getTrendMetricVisual(metric) ? (
<div <div
className={clsx( className={clsx(
"future-trend-meter-fill", "future-trend-meter",
getTrendMetricVisual(metric)?.tone === "warm" && getTrendMetricVisual(metric)?.mode === "center" &&
"warm", "center",
getTrendMetricVisual(metric)?.tone === "cold" &&
"cold",
)} )}
style={{ >
width: `${getTrendMetricVisual(metric)?.percent ?? 0}%`, {getTrendMetricVisual(metric)?.mode === "center" ? (
}} <span className="future-trend-meter-midline" />
/> ) : null}
</div> <div
) : null} className={clsx(
<div className="future-trend-note">{metric.note}</div> "future-trend-meter-fill",
getTrendMetricVisual(metric)?.tone === "warm" &&
"warm",
getTrendMetricVisual(metric)?.tone === "cold" &&
"cold",
)}
style={{
width: `${getTrendMetricVisual(metric)?.percent ?? 0}%`,
}}
/>
</div>
) : null}
<div className="future-trend-note">{metric.note}</div>
</div>
))}
</div>
) : (
<div className="future-trend-card future-trend-card-empty">
<div className="future-trend-label">
{locale === "en-US" ? "Upper-air source" : "高空数据源"}
</div>
<div className="future-trend-value">
{locale === "en-US" ? "Not available" : "暂不可用"}
</div>
<div className="future-trend-note">
{locale === "en-US"
? "No upper-air diagnostic feed is attached to this city right now."
: "当前该城市未接入可用的高空诊断源,所以这里先保留说明卡片。"}
</div> </div>
))}
</div>
) : (
<div className="future-trend-card future-trend-card-empty">
<div className="future-trend-label">
{locale === "en-US" ? "Upper-air source" : "高空数据源"}
</div> </div>
<div className="future-trend-value"> )}
{locale === "en-US" ? "Not available" : "暂不可用"} </>
</div> </section>
<div className="future-trend-note"> ) : (
{locale === "en-US" <section className="future-modal-section">
? "No upper-air diagnostic feed is attached to this city right now." <h3>{t("future.structureToday")}</h3>
: "当前该城市未接入可用的高空诊断源,所以这里先保留说明卡片。"} <div className="future-trend-summary future-trend-summary-muted">
</div> {locale === "en-US"
</div> ? "Surface structure, upper-air diagnostics, and trade commentary are loading after the primary chart."
)} : "近地面结构、高空诊断和交易提示会在主图之后继续后台补齐。"}
</> </div>
</section> </section>
)}
</main> </main>
</div> </div>
) : ( ) : (
+20 -1
View File
@@ -166,7 +166,7 @@ function HistoryChart() {
export function HistoryModal() { export function HistoryModal() {
const store = useDashboardStore(); const store = useDashboardStore();
const { t, locale } = useI18n(); const { t, locale } = useI18n();
const { data, error, isLoading, isOpen } = useHistoryData(); const { data, error, isLoading, isOpen, isRecordsLoading, meta } = useHistoryData();
const isPro = store.proAccess.subscriptionActive; const isPro = store.proAccess.subscriptionActive;
const isProLoading = store.proAccess.loading; const isProLoading = store.proAccess.loading;
const isNoaaSettlement = const isNoaaSettlement =
@@ -233,6 +233,25 @@ export function HistoryModal() {
city: store.selectedCity?.toUpperCase() || "", city: store.selectedCity?.toUpperCase() || "",
})} })}
</h2> </h2>
{meta?.mode === "preview" ? (
<div
style={{
color: "var(--text-muted)",
fontSize: "12px",
marginLeft: "12px",
}}
>
{isRecordsLoading
? locale === "en-US"
? "Loading full records in background..."
: "完整历史正在后台补齐..."
: meta.hasMore
? locale === "en-US"
? `Preview ${meta.previewCount}/${meta.fullCount}`
: `预览 ${meta.previewCount}/${meta.fullCount}`
: null}
</div>
) : null}
<button <button
type="button" type="button"
className="modal-close" className="modal-close"
@@ -6,11 +6,22 @@ import {
DashboardStoreProvider, DashboardStoreProvider,
useDashboardStore, useDashboardStore,
} from "@/hooks/useDashboardStore"; } from "@/hooks/useDashboardStore";
import { preloadChartJs } from "@/hooks/useChart";
import { I18nProvider, useI18n } from "@/hooks/useI18n"; import { I18nProvider, useI18n } from "@/hooks/useI18n";
import { CitySidebar } from "@/components/dashboard/CitySidebar"; import { CitySidebar } from "@/components/dashboard/CitySidebar";
import { DetailPanel } from "@/components/dashboard/DetailPanel"; import { DetailPanel } from "@/components/dashboard/DetailPanel";
import { HeaderBar } from "@/components/dashboard/HeaderBar"; import { HeaderBar } from "@/components/dashboard/HeaderBar";
const loadHistoryModal = () =>
import("@/components/dashboard/HistoryModal").then(
(module) => module.HistoryModal,
);
const loadFutureForecastModal = () =>
import("@/components/dashboard/FutureForecastModal").then(
(module) => module.FutureForecastModal,
);
const MapCanvas = dynamic( const MapCanvas = dynamic(
() => () =>
import("@/components/dashboard/MapCanvas").then((module) => module.MapCanvas), import("@/components/dashboard/MapCanvas").then((module) => module.MapCanvas),
@@ -21,10 +32,7 @@ const MapCanvas = dynamic(
); );
const HistoryModal = dynamic( const HistoryModal = dynamic(
() => loadHistoryModal,
import("@/components/dashboard/HistoryModal").then(
(module) => module.HistoryModal,
),
{ {
ssr: false, ssr: false,
loading: () => null, loading: () => null,
@@ -32,10 +40,7 @@ const HistoryModal = dynamic(
); );
const FutureForecastModal = dynamic( const FutureForecastModal = dynamic(
() => loadFutureForecastModal,
import("@/components/dashboard/FutureForecastModal").then(
(module) => module.FutureForecastModal,
),
{ {
ssr: false, ssr: false,
loading: () => null, loading: () => null,
@@ -77,6 +82,42 @@ function DashboardScreen() {
}; };
}, [store]); }, [store]);
useEffect(() => {
const browserWindow = window as Window & {
requestIdleCallback?: (
cb: IdleRequestCallback,
options?: IdleRequestOptions,
) => number;
cancelIdleCallback?: (handle: number) => void;
};
if (typeof browserWindow.requestIdleCallback === "function") {
const handle = browserWindow.requestIdleCallback(() => {
void loadHistoryModal();
void loadFutureForecastModal();
}, { timeout: 1200 });
return () => {
if (typeof browserWindow.cancelIdleCallback === "function") {
browserWindow.cancelIdleCallback(handle);
}
};
}
const timeoutId = window.setTimeout(() => {
void loadHistoryModal();
void loadFutureForecastModal();
}, 500);
return () => {
window.clearTimeout(timeoutId);
};
}, []);
useEffect(() => {
if (!store.selectedCity) return;
void preloadChartJs();
void loadHistoryModal();
void loadFutureForecastModal();
}, [store.selectedCity]);
// Avoid full-page flashing on initial load; only show this overlay for manual refresh. // Avoid full-page flashing on initial load; only show this overlay for manual refresh.
const showLoading = const showLoading =
store.loadingState.cities || store.loadingState.cities ||
+10 -1
View File
@@ -3,6 +3,15 @@
import { useEffect, useRef } from "react"; import { useEffect, useRef } from "react";
import type { Chart as ChartInstance, ChartConfiguration, ChartType } from "chart.js"; import type { Chart as ChartInstance, ChartConfiguration, ChartType } from "chart.js";
let chartModulePromise: Promise<typeof import("chart.js/auto")> | null = null;
export function preloadChartJs() {
if (!chartModulePromise) {
chartModulePromise = import("chart.js/auto");
}
return chartModulePromise;
}
export function useChart<TType extends ChartType>( export function useChart<TType extends ChartType>(
createConfig: () => ChartConfiguration<TType>, createConfig: () => ChartConfiguration<TType>,
dependencies: React.DependencyList, dependencies: React.DependencyList,
@@ -16,7 +25,7 @@ export function useChart<TType extends ChartType>(
let disposed = false; let disposed = false;
const setupChart = async () => { const setupChart = async () => {
const { Chart } = await import("chart.js/auto"); const { Chart } = await preloadChartJs();
if (disposed) return; if (disposed) return;
const config = createConfig(); const config = createConfig();
+147 -17
View File
@@ -20,6 +20,8 @@ import {
CitySummary, CitySummary,
DashboardState, DashboardState,
HistoryPoint, HistoryPoint,
HistoryPayload,
HistoryPayloadMeta,
HistoryState, HistoryState,
LoadingState, LoadingState,
MarketScan, MarketScan,
@@ -58,7 +60,9 @@ function getInitialLoadingState(): LoadingState {
return { return {
cities: false, cities: false,
cityDetail: false, cityDetail: false,
futureDeep: false,
history: false, history: false,
historyRecords: false,
refresh: false, refresh: false,
marketScan: false, marketScan: false,
}; };
@@ -70,6 +74,8 @@ function getInitialHistoryState(): HistoryState {
error: null, error: null,
isOpen: false, isOpen: false,
loading: false, loading: false,
metaByCity: {},
recordsLoading: false,
}; };
} }
@@ -240,6 +246,20 @@ function scheduleWhenBrowserIdle(callback: () => void) {
}; };
} }
function toHistoryMeta(payload: HistoryPayload): HistoryPayloadMeta {
const history = Array.isArray(payload.history) ? payload.history : [];
const previewCount = Number(payload.preview_count || history.length || 0);
const fullCount = Number(payload.full_count || previewCount || 0);
return {
mode: payload.mode === "full" ? "full" : "preview",
hasMore: payload.has_more === true,
fullCount,
previewCount,
settlementSource: payload.settlement_source ?? null,
settlementSourceLabel: payload.settlement_source_label ?? null,
};
}
export function DashboardStoreProvider({ export function DashboardStoreProvider({
children, children,
}: { }: {
@@ -940,30 +960,107 @@ export function DashboardStoreProvider({
error: null, error: null,
isOpen: true, isOpen: true,
loading: false, loading: false,
recordsLoading: false,
})); }));
return; return;
} }
const cityName = selectedCity;
const cachedHistory = historyState.dataByCity[cityName];
const cachedMeta = historyState.metaByCity[cityName];
if (cachedMeta && cachedHistory?.length) {
setHistoryState((current) => ({
...current,
error: null,
isOpen: true,
loading: false,
recordsLoading: cachedMeta.mode !== "full" && cachedMeta.hasMore,
}));
if (cachedMeta.mode !== "full" && cachedMeta.hasMore) {
void dashboardClient
.getHistory(cityName, { includeRecords: true })
.then((payload) => {
if (selectedCityRef.current !== cityName) return;
setHistoryState((current) => ({
...current,
dataByCity: {
...current.dataByCity,
[cityName]: payload.history,
},
metaByCity: {
...current.metaByCity,
[cityName]: toHistoryMeta(payload),
},
recordsLoading: false,
}));
})
.catch(() => {
if (selectedCityRef.current !== cityName) return;
setHistoryState((current) => ({
...current,
recordsLoading: false,
}));
});
}
return;
}
setHistoryState((current) => ({ setHistoryState((current) => ({
...current, ...current,
error: null, error: null,
isOpen: true, isOpen: true,
loading: true, loading: true,
recordsLoading: false,
})); }));
try { try {
const history = await dashboardClient.getHistory(selectedCity); const payload = await dashboardClient.getHistory(cityName);
setHistoryState((current) => ({ setHistoryState((current) => ({
...current, ...current,
dataByCity: { dataByCity: {
...current.dataByCity, ...current.dataByCity,
[selectedCity]: history, [cityName]: payload.history,
},
metaByCity: {
...current.metaByCity,
[cityName]: toHistoryMeta(payload),
}, },
loading: false, loading: false,
recordsLoading: payload.has_more === true,
})); }));
if (payload.has_more) {
void dashboardClient
.getHistory(cityName, { includeRecords: true })
.then((fullPayload) => {
if (selectedCityRef.current !== cityName) return;
setHistoryState((current) => ({
...current,
dataByCity: {
...current.dataByCity,
[cityName]: fullPayload.history,
},
metaByCity: {
...current.metaByCity,
[cityName]: toHistoryMeta(fullPayload),
},
recordsLoading: false,
}));
})
.catch(() => {
if (selectedCityRef.current !== cityName) return;
setHistoryState((current) => ({
...current,
recordsLoading: false,
}));
});
}
} catch (error) { } catch (error) {
setHistoryState((current) => ({ setHistoryState((current) => ({
...current, ...current,
error: String(error), error: String(error),
loading: false, loading: false,
recordsLoading: false,
})); }));
} }
}; };
@@ -990,7 +1087,17 @@ export function DashboardStoreProvider({
mapStopMotionRef.current(); mapStopMotionRef.current();
if (!selectedCity || !proAccess.subscriptionActive) return; if (!selectedCity || !proAccess.subscriptionActive) return;
const cityName = selectedCity; const cityName = selectedCity;
const cachedDetail = cityDetailsByName[selectedCity]; let cachedDetail = cityDetailsByName[selectedCity];
if (!cachedDetail) {
setLoadingState((current) => ({ ...current, cityDetail: true }));
try {
cachedDetail = await ensureCityDetail(cityName, false, "panel");
} finally {
if (selectedCityRef.current === cityName) {
setLoadingState((current) => ({ ...current, cityDetail: false }));
}
}
}
const hasFullCachedDetail = const hasFullCachedDetail =
detailSatisfiesDepth(cachedDetail, "full") && detailSatisfiesDepth(cachedDetail, "full") &&
!hasSparseDetailCoverage(cachedDetail, dateStr); !hasSparseDetailCoverage(cachedDetail, dateStr);
@@ -1001,7 +1108,7 @@ export function DashboardStoreProvider({
if (!hasFullCachedDetail || forceRefresh) { if (!hasFullCachedDetail || forceRefresh) {
setLoadingState((current) => ({ setLoadingState((current) => ({
...current, ...current,
refresh: true, futureDeep: true,
})); }));
void ensureCityDetail(cityName, true, "full") void ensureCityDetail(cityName, true, "full")
.catch(() => {}) .catch(() => {})
@@ -1009,7 +1116,7 @@ export function DashboardStoreProvider({
if (selectedCityRef.current !== cityName) return; if (selectedCityRef.current !== cityName) return;
setLoadingState((current) => ({ setLoadingState((current) => ({
...current, ...current,
refresh: false, futureDeep: false,
})); }));
}); });
} }
@@ -1033,7 +1140,17 @@ export function DashboardStoreProvider({
mapStopMotionRef.current(); mapStopMotionRef.current();
const cityName = selectedCity; const cityName = selectedCity;
const cachedDetail = cityDetailsByName[cityName]; let cachedDetail = cityDetailsByName[cityName];
if (!cachedDetail) {
setLoadingState((current) => ({ ...current, cityDetail: true }));
try {
cachedDetail = await ensureCityDetail(cityName, false, "panel");
} finally {
if (selectedCityRef.current === cityName) {
setLoadingState((current) => ({ ...current, cityDetail: false }));
}
}
}
const hasFullCachedDetail = const hasFullCachedDetail =
detailSatisfiesDepth(cachedDetail, "full") && detailSatisfiesDepth(cachedDetail, "full") &&
!hasSparseDetailCoverage(cachedDetail, cachedDetail?.local_date); !hasSparseDetailCoverage(cachedDetail, cachedDetail?.local_date);
@@ -1051,9 +1168,29 @@ export function DashboardStoreProvider({
setLoadingState((current) => ({ setLoadingState((current) => ({
...current, ...current,
refresh: needsDetailRefresh, futureDeep: needsDetailRefresh,
marketScan: true, marketScan: true,
})); }));
const initialTargetDate =
cachedDetail?.local_date || selectedForecastDate || null;
const initialMarketKey = getMarketScanCacheKey(
cityName,
initialTargetDate,
);
void ensureCityMarketScan(
cityName,
forceRefresh || !marketScanByCityName[initialMarketKey],
null,
initialTargetDate,
)
.catch(() => {})
.finally(() => {
if (selectedCityRef.current !== cityName) return;
setLoadingState((current) => ({
...current,
marketScan: false,
}));
});
void ensureCityDetail( void ensureCityDetail(
cityName, cityName,
needsDetailRefresh, needsDetailRefresh,
@@ -1063,14 +1200,6 @@ export function DashboardStoreProvider({
if (selectedCityRef.current !== cityName) return; if (selectedCityRef.current !== cityName) return;
setSelectedForecastDate(detail.local_date); setSelectedForecastDate(detail.local_date);
setFutureModalDate(detail.local_date); setFutureModalDate(detail.local_date);
const marketKey = getMarketScanCacheKey(cityName, detail.local_date);
return ensureCityMarketScan(
cityName,
forceRefresh || !marketScanByCityName[marketKey],
null,
detail.local_date,
);
}) })
.catch(() => { .catch(() => {
if (selectedCityRef.current !== cityName) return; if (selectedCityRef.current !== cityName) return;
@@ -1083,8 +1212,7 @@ export function DashboardStoreProvider({
if (selectedCityRef.current !== cityName) return; if (selectedCityRef.current !== cityName) return;
setLoadingState((current) => ({ setLoadingState((current) => ({
...current, ...current,
refresh: false, futureDeep: false,
marketScan: false,
})); }));
}); });
}, },
@@ -1160,5 +1288,7 @@ export function useHistoryData(name?: string | null) {
error: store.historyState.error, error: store.historyState.error,
isLoading: store.historyState.loading, isLoading: store.historyState.loading,
isOpen: store.historyState.isOpen, isOpen: store.historyState.isOpen,
isRecordsLoading: store.historyState.recordsLoading,
meta: key ? store.historyState.metaByCity[key] || null : null,
}; };
} }
+28 -9
View File
@@ -5,13 +5,13 @@ import {
CityListItem, CityListItem,
MarketScan, MarketScan,
CitySummary, CitySummary,
HistoryPoint, HistoryPayload,
} from "@/lib/dashboard-types"; } from "@/lib/dashboard-types";
const CACHE_KEY = "polyWeather_v1"; const CACHE_KEY = "polyWeather_v1";
const CACHE_TTL_MS = 5 * 60 * 1000; const CACHE_TTL_MS = 5 * 60 * 1000;
const pendingCityDetailRequests = new Map<string, Promise<CityDetail>>(); const pendingCityDetailRequests = new Map<string, Promise<CityDetail>>();
const pendingHistoryRequests = new Map<string, Promise<HistoryPoint[]>>(); const pendingHistoryRequests = new Map<string, Promise<HistoryPayload>>();
const pendingCitySummaryRequests = new Map<string, Promise<CitySummary>>(); const pendingCitySummaryRequests = new Map<string, Promise<CitySummary>>();
const pendingMarketScanRequests = new Map<string, Promise<MarketScan | null>>(); const pendingMarketScanRequests = new Map<string, Promise<MarketScan | null>>();
@@ -225,7 +225,7 @@ export const dashboardClient = {
} }
const request = fetchJson<{ market_scan?: MarketScan }>( const request = fetchJson<{ market_scan?: MarketScan }>(
`/api/city/${normalizeCityName(cityName)}/detail?${params.toString()}`, `/api/city/${normalizeCityName(cityName)}/market-scan?${params.toString()}`,
) )
.then((data) => data.market_scan || null) .then((data) => data.market_scan || null)
.finally(() => { .finally(() => {
@@ -248,21 +248,40 @@ export const dashboardClient = {
} }
return fetchJson<{ market_scan?: MarketScan }>( return fetchJson<{ market_scan?: MarketScan }>(
`/api/city/${normalizeCityName(cityName)}/detail?${params.toString()}`, `/api/city/${normalizeCityName(cityName)}/market-scan?${params.toString()}`,
).then((data) => data.market_scan || null); ).then((data) => data.market_scan || null);
}, },
async getHistory(cityName: string) { async getHistory(cityName: string, options?: { includeRecords?: boolean }) {
const requestKey = normalizeCityName(cityName); const includeRecords = options?.includeRecords === true;
const requestKey = `${normalizeCityName(cityName)}::${
includeRecords ? "full" : "preview"
}`;
const existing = pendingHistoryRequests.get(requestKey); const existing = pendingHistoryRequests.get(requestKey);
if (existing) { if (existing) {
return existing; return existing;
} }
const request = fetchJson<{ history?: HistoryPoint[] }>( const params = new URLSearchParams();
`/api/history/${requestKey}`, if (includeRecords) {
params.set("include_records", "true");
}
const request = fetchJson<HistoryPayload>(
`/api/history/${normalizeCityName(cityName)}${
params.size ? `?${params.toString()}` : ""
}`,
) )
.then((data) => data.history || []) .then((data) => ({
...data,
full_count: Number(data.full_count || 0),
has_more: data.has_more === true,
history: Array.isArray(data.history) ? data.history : [],
mode: (data.mode === "full" ? "full" : "preview") as
| "full"
| "preview",
preview_count: Number(data.preview_count || 0),
}))
.finally(() => { .finally(() => {
pendingHistoryRequests.delete(requestKey); pendingHistoryRequests.delete(requestKey);
}); });
+23
View File
@@ -494,19 +494,42 @@ export interface HistoryPoint {
deb_at_peak_minus_12h_error?: number | null; deb_at_peak_minus_12h_error?: number | null;
} }
export interface HistoryPayloadMeta {
mode: "preview" | "full";
hasMore: boolean;
fullCount: number;
previewCount: number;
settlementSource?: string | null;
settlementSourceLabel?: string | null;
}
export interface HistoryPayload {
history: HistoryPoint[];
has_more?: boolean;
full_count?: number;
preview_count?: number;
mode?: "preview" | "full";
settlement_source?: string | null;
settlement_source_label?: string | null;
}
export interface LoadingState { export interface LoadingState {
cities: boolean; cities: boolean;
cityDetail: boolean; cityDetail: boolean;
refresh: boolean; refresh: boolean;
history: boolean; history: boolean;
marketScan?: boolean; marketScan?: boolean;
futureDeep?: boolean;
historyRecords?: boolean;
} }
export interface HistoryState { export interface HistoryState {
isOpen: boolean; isOpen: boolean;
loading: boolean; loading: boolean;
recordsLoading: boolean;
error: string | null; error: string | null;
dataByCity: Record<string, HistoryPoint[]>; dataByCity: Record<string, HistoryPoint[]>;
metaByCity: Record<string, HistoryPayloadMeta>;
} }
export interface ProAccessState { export interface ProAccessState {
+5 -1
View File
@@ -764,9 +764,10 @@ class WeatherDataCollector(OpenMeteoCacheMixin, SettlementSourceMixin, MetarSour
results: Dict, results: Dict,
city_lower: str, city_lower: str,
*, *,
include_mgm: bool = True,
include_nearby: bool = True, include_nearby: bool = True,
) -> None: ) -> None:
if city_lower not in self.TURKISH_PROVINCES: if not include_mgm or city_lower not in self.TURKISH_PROVINCES:
return return
istno, province = self.TURKISH_PROVINCES[city_lower] istno, province = self.TURKISH_PROVINCES[city_lower]
mgm_data = self.fetch_from_mgm(istno) mgm_data = self.fetch_from_mgm(istno)
@@ -929,6 +930,7 @@ class WeatherDataCollector(OpenMeteoCacheMixin, SettlementSourceMixin, MetarSour
include_nearby: bool = True, include_nearby: bool = True,
include_ensemble: bool = True, include_ensemble: bool = True,
include_multi_model: bool = True, include_multi_model: bool = True,
include_mgm: bool = True,
) -> Dict: ) -> Dict:
""" """
Fetch weather data from all available sources Fetch weather data from all available sources
@@ -970,6 +972,7 @@ class WeatherDataCollector(OpenMeteoCacheMixin, SettlementSourceMixin, MetarSour
self._attach_turkish_mgm_data( self._attach_turkish_mgm_data(
results, results,
city_lower, city_lower,
include_mgm=include_mgm,
include_nearby=include_nearby, include_nearby=include_nearby,
) )
if include_nearby: if include_nearby:
@@ -1011,6 +1014,7 @@ class WeatherDataCollector(OpenMeteoCacheMixin, SettlementSourceMixin, MetarSour
self._attach_turkish_mgm_data( self._attach_turkish_mgm_data(
results, results,
city_lower, city_lower,
include_mgm=include_mgm,
include_nearby=include_nearby, include_nearby=include_nearby,
) )
if include_nearby: if include_nearby:
+41 -9
View File
@@ -88,6 +88,8 @@ def _analysis_cache_key(city: str, detail_mode: str = "full") -> str:
normalized_raw = str(detail_mode or "").strip().lower() normalized_raw = str(detail_mode or "").strip().lower()
if normalized_raw == "panel": if normalized_raw == "panel":
normalized_mode = "panel" normalized_mode = "panel"
elif normalized_raw == "market":
normalized_mode = "market"
elif normalized_raw == "nearby": elif normalized_raw == "nearby":
normalized_mode = "nearby" normalized_mode = "nearby"
else: else:
@@ -98,7 +100,7 @@ def _analysis_cache_key(city: str, detail_mode: str = "full") -> str:
def _get_cached_analysis( def _get_cached_analysis(
city: str, city: str,
ttl: int, ttl: int,
detail_modes: tuple[str, ...] = ("panel", "nearby", "full"), detail_modes: tuple[str, ...] = ("panel", "market", "nearby", "full"),
) -> Optional[Dict[str, Any]]: ) -> Optional[Dict[str, Any]]:
now_ts = _time.time() now_ts = _time.time()
freshest_payload: Optional[Dict[str, Any]] = None freshest_payload: Optional[Dict[str, Any]] = None
@@ -1094,6 +1096,8 @@ def _analyze(
normalized_detail_mode_raw = str(detail_mode or "full").strip().lower() normalized_detail_mode_raw = str(detail_mode or "full").strip().lower()
if normalized_detail_mode_raw == "panel": if normalized_detail_mode_raw == "panel":
normalized_detail_mode = "panel" normalized_detail_mode = "panel"
elif normalized_detail_mode_raw == "market":
normalized_detail_mode = "market"
elif normalized_detail_mode_raw == "nearby": elif normalized_detail_mode_raw == "nearby":
normalized_detail_mode = "nearby" normalized_detail_mode = "nearby"
else: else:
@@ -1126,6 +1130,7 @@ def _analyze(
# ── 1. Fetch raw data ── # ── 1. Fetch raw data ──
is_panel_mode = normalized_detail_mode == "panel" is_panel_mode = normalized_detail_mode == "panel"
is_market_mode = normalized_detail_mode == "market"
is_nearby_mode = normalized_detail_mode == "nearby" is_nearby_mode = normalized_detail_mode == "nearby"
raw = _weather.fetch_all_sources( raw = _weather.fetch_all_sources(
@@ -1133,10 +1138,11 @@ def _analyze(
lat=lat, lat=lat,
lon=lon, lon=lon,
force_refresh=force_refresh, force_refresh=force_refresh,
include_taf=not is_panel_mode and not is_nearby_mode, include_taf=not is_panel_mode and not is_nearby_mode and not is_market_mode,
include_nearby=not is_panel_mode, include_nearby=not is_panel_mode and not is_market_mode,
include_ensemble=not is_panel_mode and not is_nearby_mode, include_ensemble=not is_panel_mode and not is_nearby_mode and not is_market_mode,
include_multi_model=not is_panel_mode and not is_nearby_mode, include_multi_model=not is_panel_mode and not is_nearby_mode,
include_mgm=not is_market_mode,
) )
om = raw.get("open-meteo", {}) om = raw.get("open-meteo", {})
metar = raw.get("metar", {}) metar = raw.get("metar", {})
@@ -1160,7 +1166,7 @@ def _analyze(
risk = CITY_RISK_PROFILES.get(city, {}) risk = CITY_RISK_PROFILES.get(city, {})
network_snapshot = ( network_snapshot = (
build_country_network_snapshot(city, raw) build_country_network_snapshot(city, raw)
if not is_panel_mode if not is_panel_mode and not is_market_mode
else {} else {}
) )
@@ -1628,7 +1634,7 @@ def _analyze(
first_peak_h, first_peak_h,
last_peak_h, last_peak_h,
) )
if not is_panel_mode and not is_nearby_mode if not is_panel_mode and not is_nearby_mode and not is_market_mode
else {} else {}
) )
taf_signal = ( taf_signal = (
@@ -1640,7 +1646,7 @@ def _analyze(
first_peak_h, first_peak_h,
last_peak_h, last_peak_h,
) )
if not is_panel_mode and not is_nearby_mode if not is_panel_mode and not is_nearby_mode and not is_market_mode
else {"available": False} else {"available": False}
) )
@@ -1790,7 +1796,15 @@ def _analyze(
# ── Assemble result ── # ── Assemble result ──
city_meta = CITIES.get(city, {}) or {} city_meta = CITIES.get(city, {}) or {}
result = { result = {
"detail_depth": "panel" if is_panel_mode else "nearby" if is_nearby_mode else "full", "detail_depth": (
"panel"
if is_panel_mode
else "market"
if is_market_mode
else "nearby"
if is_nearby_mode
else "full"
),
"name": city, "name": city,
"display_name": str(city_meta.get("display_name") or city_meta.get("name") or city.title()), "display_name": str(city_meta.get("display_name") or city_meta.get("name") or city.title()),
"lat": lat, "lat": lat,
@@ -2222,7 +2236,7 @@ def _build_city_summary_payload(data: Dict[str, Any]) -> Dict[str, Any]:
} }
def _build_city_detail_payload( def _build_city_market_scan_payload(
data: Dict[str, Any], data: Dict[str, Any],
market_slug: Optional[str] = None, market_slug: Optional[str] = None,
target_date: Optional[str] = None, target_date: Optional[str] = None,
@@ -2313,6 +2327,24 @@ def _build_city_detail_payload(
market_scan["anchor_high"] = anchor_temp market_scan["anchor_high"] = anchor_temp
market_scan["anchor_settlement"] = anchor_settlement market_scan["anchor_settlement"] = anchor_settlement
market_scan["open_meteo_settlement"] = anchor_settlement market_scan["open_meteo_settlement"] = anchor_settlement
return {
"market_scan": market_scan,
"selected_date": selected_date or data.get("local_date"),
"fetched_at": data.get("updated_at"),
}
def _build_city_detail_payload(
data: Dict[str, Any],
market_slug: Optional[str] = None,
target_date: Optional[str] = None,
) -> Dict[str, Any]:
market_payload = _build_city_market_scan_payload(
data,
market_slug=market_slug,
target_date=target_date,
)
market_scan = market_payload.get("market_scan")
return { return {
"city": data.get("name"), "city": data.get("name"),
"fetched_at": data.get("updated_at"), "fetched_at": data.get("updated_at"),
+42 -2
View File
@@ -21,6 +21,7 @@ from web.analysis_service import (
_analyze, _analyze,
_analyze_summary, _analyze_summary,
_build_city_detail_payload, _build_city_detail_payload,
_build_city_market_scan_payload,
_build_city_summary_payload, _build_city_summary_payload,
) )
from web.core import ( from web.core import (
@@ -88,6 +89,7 @@ DEFAULT_PREWARM_CITIES = [
"paris", "paris",
"madrid", "madrid",
] ]
HISTORY_PREVIEW_DAY_LIMIT = 21
def _parse_snapshot_dt(value: object) -> Optional[datetime]: def _parse_snapshot_dt(value: object) -> Optional[datetime]:
@@ -445,7 +447,11 @@ async def city_detail(
@router.get("/api/history/{name}") @router.get("/api/history/{name}")
async def city_history(request: Request, name: str): async def city_history(
request: Request,
name: str,
include_records: bool = False,
):
_assert_entitlement(request) _assert_entitlement(request)
city = _normalize_city_or_404(name) city = _normalize_city_or_404(name)
@@ -486,12 +492,23 @@ async def city_history(request: Request, name: str):
if not city_data: if not city_data:
return { return {
"history": [], "history": [],
"mode": "full" if include_records else "preview",
"has_more": False,
"full_count": 0,
"preview_count": 0,
"settlement_source": source, "settlement_source": source,
"settlement_source_label": SETTLEMENT_SOURCE_LABELS.get(source, source.upper()), "settlement_source_label": SETTLEMENT_SOURCE_LABELS.get(source, source.upper()),
} }
all_days = sorted(city_data.keys())
selected_days = (
all_days
if include_records
else all_days[-HISTORY_PREVIEW_DAY_LIMIT:]
)
out = [] out = []
for day, rec in sorted(city_data.items()): for day in selected_days:
rec = city_data.get(day, {})
if not isinstance(rec, dict): if not isinstance(rec, dict):
rec = {} rec = {}
@@ -539,6 +556,10 @@ async def city_history(request: Request, name: str):
return { return {
"history": out, "history": out,
"mode": "full" if include_records else "preview",
"has_more": len(all_days) > len(selected_days),
"full_count": len(all_days),
"preview_count": len(out),
"settlement_source": source, "settlement_source": source,
"settlement_source_label": SETTLEMENT_SOURCE_LABELS.get(source, source.upper()), "settlement_source_label": SETTLEMENT_SOURCE_LABELS.get(source, source.upper()),
} }
@@ -1076,3 +1097,22 @@ async def city_detail_aggregate(
market_slug, market_slug,
target_date, target_date,
) )
@router.get("/api/city/{name}/market-scan")
async def city_market_scan(
request: Request,
name: str,
force_refresh: bool = False,
market_slug: Optional[str] = None,
target_date: Optional[str] = None,
):
_assert_entitlement(request)
city = _normalize_city_or_404(name)
data = await run_in_threadpool(_analyze, city, force_refresh, False, "market")
return await run_in_threadpool(
_build_city_market_scan_payload,
data,
market_slug,
target_date,
)