feat: export author spread metrics
This commit is contained in:
wxs
@@ -1,6 +1,7 @@
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import { describe, expect, test } from "vitest";
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import { buildMarketCsv } from "../src/content/market/csv-exporter";
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import { buildSpreadInfoColumns } from "../src/content/market/spread-info";
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import type { MarketRecord } from "../src/content/market/types";
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describe("csv-exporter", () => {
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@@ -21,12 +22,13 @@ describe("csv-exporter", () => {
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"秒思api-新增A3数",
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"秒思api-新增A3率",
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"秒思api-CPA3",
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"秒思api-cp_search"
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"秒思api-cp_search",
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...buildSpreadInfoColumns()
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].join(",")
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);
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});
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test("uses page export field order and appends the two plugin columns", () => {
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test("uses page export field order and appends the plugin columns", () => {
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const csv = buildMarketCsv([
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{
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authorId: "123",
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@@ -66,11 +68,16 @@ describe("csv-exporter", () => {
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"秒思api-新增A3数",
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"秒思api-新增A3率",
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"秒思api-CPA3",
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"秒思api-cp_search"
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"秒思api-cp_search",
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...buildSpreadInfoColumns()
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].join(",")
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);
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expect(rowLine).toBe(
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'Alice,100w,"¥450,000",0.5% - 1%,1% - 3%,0.36%,"9,689.96","78,366.22",3.44%,1.79,14.46'
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expect(rowLine).toMatch(
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new RegExp(
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`^${escapeRegExp(
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'Alice,100w,"¥450,000",0.5% - 1%,1% - 3%,0.36%,"9,689.96","78,366.22",3.44%,1.79,14.46'
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)}`
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)
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);
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});
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@@ -101,10 +108,13 @@ describe("csv-exporter", () => {
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"秒思api-新增A3数",
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"秒思api-新增A3率",
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"秒思api-CPA3",
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"秒思api-cp_search"
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"秒思api-cp_search",
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...buildSpreadInfoColumns()
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].join(",")
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);
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expect(rowLine).toBe("Alice,100w,,,,,,,,");
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expect(rowLine.split(",").slice(0, 10).join(",")).toBe(
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"Alice,100w,,,,,,,,"
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);
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});
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test("escapes commas and quotes", () => {
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@@ -137,7 +147,10 @@ describe("csv-exporter", () => {
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]);
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const [, rowLine] = csv.split("\n");
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expect(rowLine).toBe("123,Alice,,,,,,,,,,");
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expect(rowLine.split(",").slice(0, 12).join(",")).toBe(
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"123,Alice,,,,,,,,,,"
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);
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expect(rowLine.split(",").slice(12).every((cell) => cell === "")).toBe(true);
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});
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test("uses normalized display values in export rows", () => {
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@@ -172,6 +185,53 @@ describe("csv-exporter", () => {
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]);
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const [, rowLine] = csv.split("\n");
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expect(rowLine).toBe("123,Alice,,,0.5% - 1%,0.02% - 0.1%,,,,,,");
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expect(rowLine.split(",").slice(0, 12).join(",")).toBe(
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"123,Alice,,,0.5% - 1%,0.02% - 0.1%,,,,,,"
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);
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});
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test("appends spread info metric columns after backend metrics", () => {
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const csv = buildMarketCsv([
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{
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authorId: "123",
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authorName: "Alice",
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spreadMetrics: {
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"个人视频_近30天_完播率": "28.24%",
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"只看指派_排除营销流量_星图视频_近30天_互动率": "4.02%"
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},
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status: "success"
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} satisfies MarketRecord
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]);
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const [headerLine, rowLine] = csv.split("\n");
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expect(headerLine).toContain(
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[
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"秒思api-cp_search",
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"个人视频_近30天_完播率",
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"个人视频_近30天_播放量中位数"
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].join(",")
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);
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expect(headerLine).toContain(
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"只看指派_排除营销流量_星图视频_近30天_互动率"
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);
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expect(rowLine).toContain("28.24%");
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expect(rowLine).toContain("4.02%");
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});
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test("emits empty spread info cells when spread metrics are absent", () => {
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const csv = buildMarketCsv([
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{
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authorId: "123",
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authorName: "Alice",
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status: "success"
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} satisfies MarketRecord
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]);
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const [, rowLine] = csv.split("\n");
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expect(rowLine.split(",").slice(-70).every((cell) => cell === "")).toBe(true);
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});
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});
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function escapeRegExp(value: string): string {
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return value.replace(/[.*+?^${}()|[\]\\]/g, "\\$&");
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}
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@@ -293,7 +293,10 @@ describe("market-content-entry", () => {
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});
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test("renders the plugin action bar inside the native market action row", async () => {
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document.body.innerHTML = buildMarketFixture();
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document.body.innerHTML = buildRealMarketFixture([
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{ authorId: "a", authorName: "Alpha", price21To60s: "450000" },
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{ authorId: "b", authorName: "Beta", price21To60s: "70000" }
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]);
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const { createMarketController } = await import("../src/content/market/index");
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const controller = trackController(createMarketController({
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@@ -1217,6 +1220,71 @@ describe("market-content-entry", () => {
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expect(onCsvReady).toHaveBeenCalledWith("csv-output");
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});
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test("export hydrates spread info with attribute_datas.id before building csv", async () => {
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document.body.innerHTML = buildRealMarketFixture([
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{ authorId: "a", authorName: "Alpha", price21To60s: "450000" },
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{ authorId: "b", authorName: "Beta", price21To60s: "70000" }
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]);
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attachMarketListState([
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{
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attribute_datas: {
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id: "spread-a",
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nickname: "Alpha"
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},
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star_id: "a"
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},
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{
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attribute_datas: {
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id: "spread-b",
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nickname: "Beta"
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},
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star_id: "b"
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}
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]);
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const buildCsv = vi.fn(() => "csv-output");
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const loadSpreadMetrics = vi.fn(async (spreadAuthorId: string) => ({
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"个人视频_近30天_完播率": spreadAuthorId === "spread-a" ? "28.24%" : "18.24%"
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}));
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const { createMarketController } = await import("../src/content/market/index");
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const controller = trackController(createMarketController({
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buildCsv,
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document,
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loadAuthorMetrics: async () => ({
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success: false,
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reason: "request-failed"
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}),
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loadSpreadMetrics,
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onCsvReady: vi.fn(),
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window
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}));
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await controller.ready;
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setSelectValue('[data-plugin-export-range="select"]', "current");
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dispatchChange('[data-plugin-export-range="select"]');
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click('[data-plugin-export="button"]');
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await waitForMockCall(buildCsv, 80, 50);
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expect(loadSpreadMetrics).toHaveBeenCalledWith("spread-a");
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expect(loadSpreadMetrics).toHaveBeenCalledWith("spread-b");
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expect(buildCsv.mock.calls[0][0]).toEqual([
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expect.objectContaining({
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authorId: "a",
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spreadAuthorId: "spread-a",
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spreadMetrics: {
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"个人视频_近30天_完播率": "28.24%"
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}
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}),
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expect.objectContaining({
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authorId: "b",
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spreadAuthorId: "spread-b",
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spreadMetrics: {
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"个人视频_近30天_完播率": "18.24%"
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}
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})
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]);
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});
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test(
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"default export captures the first 5 pages and keeps non-empty fields when merging duplicates",
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async () => {
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@@ -155,6 +155,49 @@ describe("silent-export-controller", () => {
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expect(records?.map((record) => record.authorId)).toEqual(["2", "3"]);
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});
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test("keeps attribute_datas.id as the spread author id while preserving star_id as row id", async () => {
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document.documentElement.setAttribute(
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"data-sces-market-request-snapshot",
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JSON.stringify({
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body: JSON.stringify({
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page_param: {
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page: 1
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}
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}),
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method: "POST",
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url: "https://xingtu.cn/api/mock-market-search"
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})
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);
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const controller = createSilentExportController({
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document,
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fetchImpl: async () => ({
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json: async () => ({
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authors: [
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{
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attribute_datas: {
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id: "spread-1",
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nickname: "达人1"
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},
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star_id: "row-1"
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}
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]
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}),
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ok: true
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})
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});
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const records = await controller.exportRecords({
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mode: "count",
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pageCount: 1
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});
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expect(records?.[0]).toMatchObject({
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authorId: "row-1",
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spreadAuthorId: "spread-1"
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});
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});
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test("starts from page 1 when the captured request omits an explicit page number", async () => {
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document.documentElement.setAttribute(
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"data-sces-market-request-snapshot",
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@@ -0,0 +1,168 @@
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import { describe, expect, test, vi } from "vitest";
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import {
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buildSpreadInfoColumns,
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buildSpreadInfoUrl,
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createSpreadInfoClient,
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DEFAULT_SPREAD_INFO_CONFIGS,
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mapSpreadInfoResponse
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} from "../src/content/market/spread-info";
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describe("spread-info", () => {
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test("builds the spread info url with all request parameters", () => {
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expect(
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buildSpreadInfoUrl(
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"7361012802036695050",
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{
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flowType: 1,
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onlyAssign: true,
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range: 2,
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type: 2
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},
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"https://www.xingtu.cn"
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)
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).toBe(
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"https://www.xingtu.cn/gw/api/data_sp/get_author_spread_info?o_author_id=7361012802036695050&platform_source=1&platform_channel=1&type=2&flow_type=1&only_assign=true&range=2"
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);
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});
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test("defines personal video ranges with fixed non-prefix parameters", () => {
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const personalConfigs = DEFAULT_SPREAD_INFO_CONFIGS.filter(
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(config) => config.type === 1
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);
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expect(personalConfigs).toEqual([
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{
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flowType: 0,
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onlyAssign: false,
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range: 2,
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type: 1
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},
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{
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flowType: 0,
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onlyAssign: false,
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range: 3,
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type: 1
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}
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]);
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expect(buildSpreadInfoColumns(personalConfigs).slice(0, 2)).toEqual([
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"个人视频_近30天_完播率",
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"个人视频_近30天_播放量中位数"
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]);
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});
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test("defines all xingtu video assign flow and range combinations", () => {
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const xingtuConfigs = DEFAULT_SPREAD_INFO_CONFIGS.filter(
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(config) => config.type === 2
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);
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expect(xingtuConfigs).toHaveLength(8);
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expect(xingtuConfigs).toContainEqual({
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flowType: 1,
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onlyAssign: true,
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range: 2,
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type: 2
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});
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expect(xingtuConfigs).toContainEqual({
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flowType: 0,
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onlyAssign: false,
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range: 3,
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type: 2
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});
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expect(buildSpreadInfoColumns([
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{
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flowType: 1,
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onlyAssign: true,
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range: 2,
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type: 2
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}
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])).toEqual([
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"只看指派_排除营销流量_星图视频_近30天_完播率",
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"只看指派_排除营销流量_星图视频_近30天_播放量中位数",
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"只看指派_排除营销流量_星图视频_近30天_互动率",
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"只看指派_排除营销流量_星图视频_近30天_作品平均时长",
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"只看指派_排除营销流量_星图视频_近30天_作品平均评论数",
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"只看指派_排除营销流量_星图视频_近30天_作品平均点赞数",
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"只看指派_排除营销流量_星图视频_近30天_作品平均转发数"
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]);
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});
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test("maps spread info response values into display values", () => {
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expect(
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mapSpreadInfoResponse({
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avg_duration: "5600",
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comment_avg: "7502",
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interact_rate: {
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value: 402
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},
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item_rate: {
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play_mid: {
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value: 10913233
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}
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},
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like_avg: "494458",
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play_over_rate: {
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value: 2824
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},
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share_avg: "188267"
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})
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).toEqual({
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averageCommentCount: "7502",
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averageDuration: "56",
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averageLikeCount: "494458",
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averageShareCount: "188267",
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finishRate: "28.24%",
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interactionRate: "4.02%",
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playMedian: "10913233"
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});
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});
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test("loads each configured spread metric column for one author", async () => {
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const fetchImpl = vi.fn(async () => ({
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json: async () => ({
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avg_duration: "5600",
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comment_avg: "7502",
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interact_rate: {
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value: 402
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},
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like_avg: "494458",
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play_mid: "10913233",
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play_over_rate: {
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value: 2824
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},
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share_avg: "188267"
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}),
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ok: true
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}));
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const client = createSpreadInfoClient({
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configs: [
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{
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flowType: 0,
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onlyAssign: false,
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range: 2,
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type: 1
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}
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],
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fetchImpl
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});
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await expect(
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client.loadAuthorSpreadMetrics("7361012802036695050")
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).resolves.toEqual({
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"个人视频_近30天_互动率": "4.02%",
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"个人视频_近30天_作品平均点赞数": "494458",
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"个人视频_近30天_作品平均评论数": "7502",
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"个人视频_近30天_作品平均时长": "56",
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"个人视频_近30天_作品平均转发数": "188267",
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"个人视频_近30天_完播率": "28.24%",
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"个人视频_近30天_播放量中位数": "10913233"
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});
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expect(fetchImpl).toHaveBeenCalledWith(
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"https://www.xingtu.cn/gw/api/data_sp/get_author_spread_info?o_author_id=7361012802036695050&platform_source=1&platform_channel=1&type=1&flow_type=0&only_assign=false&range=2",
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expect.objectContaining({
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credentials: "include",
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method: "GET"
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})
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);
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});
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});
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