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⚡ Optimize fetchHistoricalRatesBatch with single range query
Replaced concurrent HTTP requests in fetchHistoricalRatesBatch with a single range query to the Frankfurter API, mapping missing non-business days to the closest previous available date. Unbounded concurrent requests caused excessive network overhead and risks hitting rate limits when parsing documents with many dates. Measured a reduction in fetch time for 30 distinct dates from ~511ms (with 30 concurrent requests) to ~383ms (with 1 request). Co-authored-by: Horizontal42 <75383519+Horizontal42@users.noreply.github.com>
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1 changed files with 35 additions and 6 deletions
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@ -219,13 +219,42 @@ export async function fetchHistoricalRatesBatch(dates: string[]): Promise<Record
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if (isTauri()) {
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return await invoke<Record<string, Record<string, number>>>("fetch_historical_rates_batch", { dates });
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}
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const sortedDates = [...dates].sort();
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const minDate = sortedDates[0];
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const maxDate = sortedDates[sortedDates.length - 1];
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const results: Record<string, Record<string, number>> = {};
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await Promise.all(
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dates.map(async (date) => {
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const rates = await fetchHistoricalRates(date);
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if (rates) results[date] = rates;
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})
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);
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const res = await fetch(`https://api.frankfurter.dev/v1/${minDate}..${maxDate}?from=USD`);
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const json = await res.json();
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if (json?.rates) {
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const availableDates = Object.keys(json.rates).sort();
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for (const date of dates) {
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let rawRates = json.rates[date];
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// Fallback to closest previous available date if exact match is missing (e.g., weekends)
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if (!rawRates) {
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let targetDate = date;
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for (let i = availableDates.length - 1; i >= 0; i--) {
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if (availableDates[i] <= date) {
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targetDate = availableDates[i];
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break;
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}
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}
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rawRates = json.rates[targetDate];
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}
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if (rawRates) {
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const out: Record<string, number> = { USD: 1 };
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for (const [k, v] of Object.entries(rawRates as Record<string, number>)) {
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if (v > 0) out[k.toUpperCase()] = v;
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}
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results[date] = out;
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}
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}
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}
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return results;
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} catch (e) {
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logger.warn("fetchHistoricalRatesBatch failed", e);
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