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karrmagadgeteer2karrmagadgeteer2
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added scripts to compare vs python package
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‎package.json‎

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@@ -32,7 +32,8 @@
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"plot": "tsx scripts/plot.ts",
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"plot:iris": "tsx scripts/plot.ts --iris",
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"plot:captor": "tsx scripts/plot.ts",
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"efficient-frontier": "tsx scripts/efficient-frontier.ts"
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"efficient-frontier": "tsx scripts/efficient-frontier.ts",
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"compare-metrics": "tsx scripts/compare-metrics.ts"
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},
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"keywords": [
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"finance",

‎scripts/compare-metrics.ts‎

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#!/usr/bin/env node
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/**
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* Compare TypeScript openseries-ts metrics vs Python metrics (from data.json).
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*
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* Loads iris.json into OpenTimeSeries, computes metrics with the TS implementation,
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* and displays them side-by-side with Python-calculated metrics from data.json.
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*
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* Run: npx tsx scripts/compare-metrics.ts [--decimals=N]
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* npm run compare-metrics -- --decimals=6
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*
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* Options:
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* --decimals=N Number of decimal places for comparison (default: 4)
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* --decimals N Same, space-separated
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* COMPARE_DECIMALS Env var (avoids npm -- when using npm run)
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*
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* Requires iris.json and data.json in ~/Documents (from the Python fetch snippet).
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*/
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import { existsSync, readFileSync } from "node:fs";
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import { homedir } from "node:os";
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import { join } from "node:path";
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import { OpenTimeSeries } from "../src/series";
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const DOCUMENTS = join(homedir(), "Documents");
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const IRIS_PATH = join(DOCUMENTS, "iris.json");
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const DATA_PATH = join(DOCUMENTS, "data.json");
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interface IrisJsonItem {
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dates: string[];
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values: number[];
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name?: string;
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timeseries_id?: string;
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}
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function loadSeriesFromIrisJson(path: string): OpenTimeSeries {
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const raw = JSON.parse(readFileSync(path, "utf-8"));
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const item: IrisJsonItem = Array.isArray(raw) ? raw[0] : raw;
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return OpenTimeSeries.fromArrays(
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item.name ?? "Series",
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item.dates,
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item.values,
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{ timeseriesId: item.timeseries_id ?? "", countries: "SE" },
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);
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}
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function loadPythonMetrics(path: string): Record<string, unknown> {
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const raw = JSON.parse(readFileSync(path, "utf-8"));
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// data.json: {"Captor Iris Bond": {"value_ret": 0.025, "geo_ret": ..., ...}}
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const col = typeof raw === "object" && raw !== null ? Object.values(raw)[0] : raw;
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return (col as Record<string, unknown>) ?? {};
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}
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function tsDateStr(v: unknown): string {
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if (typeof v === "string") return v.slice(0, 10);
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return String(v);
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}
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function roundToStr(n: number, decimals: number): string {
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if (Number.isNaN(n)) return "NaN";
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if (!Number.isFinite(n)) return String(n);
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if (decimals <= 0) return String(Math.round(n));
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const rounded = Number(n.toFixed(decimals));
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return Number.isInteger(rounded) ? String(rounded) : n.toFixed(decimals);
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}
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function formatForDisplay(v: unknown, decimals: number): string {
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if (v === undefined) return "—";
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if (typeof v === "number") return roundToStr(v, decimals);
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return tsDateStr(v);
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}
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function parseDecimals(args: string[]): number {
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const def = 4;
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// --decimals=N
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const eqArg = args.find((a) => a.startsWith("--decimals="));
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if (eqArg) {
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const n = parseInt(eqArg.slice(11), 10);
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if (Number.isInteger(n) && n >= 0) return n;
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}
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// --decimals N
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const idx = args.indexOf("--decimals");
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if (idx >= 0 && args[idx + 1] != null) {
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const n = parseInt(args[idx + 1]!, 10);
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if (Number.isInteger(n) && n >= 0) return n;
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}
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// env COMPARE_DECIMALS (works with npm run even without --)
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const env = process.env.COMPARE_DECIMALS;
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if (env) {
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const n = parseInt(env, 10);
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if (Number.isInteger(n) && n >= 0) return n;
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}
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return def;
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}
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function main(): void {
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const decimals = parseDecimals(process.argv.slice(2));
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if (!existsSync(IRIS_PATH)) {
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console.error(`iris.json not found at ${IRIS_PATH}`);
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process.exit(1);
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}
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if (!existsSync(DATA_PATH)) {
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console.error(`data.json not found at ${DATA_PATH}`);
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process.exit(1);
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}
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console.log("Loading timeseries from iris.json...");
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const series = loadSeriesFromIrisJson(IRIS_PATH);
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console.log("Loading Python metrics from data.json...");
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const pythonMetrics = loadPythonMetrics(DATA_PATH);
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// Compute TS metrics; map Python property names to TS getters/methods
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const tsMetrics: Record<string, string | number> = {};
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const metrics: { pyKey: string; getTs: () => number | string }[] = [
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{ pyKey: "value_ret", getTs: () => series.valueRet() },
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{ pyKey: "geo_ret", getTs: () => series.geoRet() },
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{ pyKey: "arithmetic_ret", getTs: () => series.arithmeticRet() },
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{ pyKey: "vol", getTs: () => series.vol() },
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{ pyKey: "downside_deviation", getTs: () => series.downsideDeviation() },
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{ pyKey: "ret_vol_ratio", getTs: () => series.retVolRatio(0) },
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{ pyKey: "sortino_ratio", getTs: () => series.sortinoRatio(0, 0) },
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{ pyKey: "z_score", getTs: () => series.zScore() },
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{ pyKey: "skew", getTs: () => series.skew() },
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{ pyKey: "kurtosis", getTs: () => series.kurtosis() },
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{ pyKey: "positive_share", getTs: () => series.positiveShare() },
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{ pyKey: "var_down", getTs: () => series.varDown(0.95) },
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{ pyKey: "cvar_down", getTs: () => series.cvarDown(0.95) },
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{ pyKey: "vol_from_var", getTs: () => series.volFromVar(0.95) },
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{ pyKey: "worst", getTs: () => series.worst(1) },
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{ pyKey: "worst_month", getTs: () => series.worstMonth() },
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{ pyKey: "max_drawdown", getTs: () => series.maxDrawdown() },
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{ pyKey: "first_idx", getTs: () => series.firstIdx },
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{ pyKey: "last_idx", getTs: () => series.lastIdx },
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{ pyKey: "length", getTs: () => series.length },
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{ pyKey: "span_of_days", getTs: () => series.spanOfDays },
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{ pyKey: "yearfrac", getTs: () => series.yearfrac },
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{ pyKey: "periods_in_a_year", getTs: () => series.periodsInAYear },
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];
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for (const { pyKey, getTs } of metrics) {
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try {
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const v = getTs();
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tsMetrics[pyKey] = typeof v === "number" ? v : v;
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} catch {
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tsMetrics[pyKey] = NaN;
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}
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}
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// Build comparison table
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const allKeys = new Set([
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...Object.keys(pythonMetrics),
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...Object.keys(tsMetrics),
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]);
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const sortedKeys = [...allKeys].sort();
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const rows: string[] = [];
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let matches = 0;
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const col1 = 35;
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const col2 = 28;
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const col3 = 28;
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const col4 = 6;
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const header =
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"Metric".padEnd(col1) +
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"Python (data.json)".padEnd(col2) +
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"TypeScript (openseries-ts)".padEnd(col3) +
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"Match".padEnd(col4);
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rows.push(header);
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rows.push("=".repeat(col1 + col2 + col3 + col4));
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for (const key of sortedKeys) {
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const pyVal = pythonMetrics[key];
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const tsVal = tsMetrics[key];
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const pyStr = formatForDisplay(pyVal, decimals);
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const tsStr = formatForDisplay(tsVal, decimals);
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let match = "";
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if (pyVal !== undefined && tsVal !== undefined) {
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let matchStr = false;
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if (typeof pyVal === "number" && typeof tsVal === "number") {
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matchStr = roundToStr(pyVal, decimals) === roundToStr(tsVal, decimals);
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} else {
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matchStr = tsDateStr(pyVal) === String(tsVal).slice(0, 10);
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}
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if (matchStr) {
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match = "✓";
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matches++;
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}
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}
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rows.push(
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key.padEnd(col1) +
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pyStr.padEnd(col2) +
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tsStr.padEnd(col3) +
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match.padEnd(col4),
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);
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}
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console.log("\n" + rows.join("\n"));
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console.log("=".repeat(col1 + col2 + col3 + col4));
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const compared = sortedKeys.filter((k) => pythonMetrics[k] !== undefined && tsMetrics[k] !== undefined);
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console.log(`\nMatched: ${matches}/${compared.length} (rounded to ${decimals} decimals or same date)`);
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}
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main();

‎scripts/load_py_openseries_data.py‎

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"""Module to create metrics from the openseries Python package."""
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from requests import get as requests_get
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from pathlib import Path
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from openseries import OpenTimeSeries
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if __name__ == "__main__":
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tid = "5b72a10c23d27735104e0576"
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urliris = f"https://api.captor.se/public/api/opentimeseries/{tid}"
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resp_iris = requests_get(urliris, timeout=10)
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resp_iris.raise_for_status()
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idata = resp_iris.json()
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iris = OpenTimeSeries.from_arrays(
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name="Captor Iris Bond",
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dates=idata["dates"],
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values=idata["values"],
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timeseries_id=tid
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)
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_ = iris.to_json(what_output="values", filename="iris.json")
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data = iris.all_properties()
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data.columns = data.columns.droplevel(level=1)
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data_path = Path.home() / "Documents" / "data.json"
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data.to_json(data_path, date_format="iso")

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