import { describe, expect, test } from "vitest";

import { buildMarketCsv } from "../src/content/market/csv-exporter";
import { buildSpreadInfoColumns } from "../src/content/market/spread-info";
import type { MarketRecord } from "../src/content/market/types";

describe("csv-exporter", () => {
  test("uses fallback header order when no page export fields are available", () => {
    const csv = buildMarketCsv([]);
    const [headerLine] = csv.split("\n");

    expect(headerLine).toBe(
      [
        "达人ID",
        "达人名称",
        "地区",
        "21-60s报价",
        "商单视频看后搜率",
        "个人视频看后搜率",
        "秒思api-看后搜率",
        "秒思api-看后搜数",
        "秒思api-新增A3数",
        "秒思api-新增A3率",
        "秒思api-CPA3",
        "秒思api-cp_search",
        ...buildSpreadInfoColumns()
      ].join(",")
    );
  });

  test("uses page export field order and appends the plugin columns", () => {
    const csv = buildMarketCsv([
      {
        authorId: "123",
        authorName: "Alice",
        exportFields: {
          达人信息: "Alice",
          代表视频: "示例视频",
          粉丝数: "100w",
          "21-60s报价": "¥450,000"
        },
        status: "success",
        backendMetrics: {
          a3IncreaseCount: "78,366.22",
          afterViewSearchCount: "9,689.96",
          afterViewSearchRate: "0.36%",
          cpSearch: "14.46",
          cpa3: "1.79",
          newA3Rate: "3.44%"
        },
        rates: {
          singleVideoAfterSearchRate: "0.5%-1%",
          personalVideoAfterSearchRate: "1% - 3%"
        }
      } satisfies MarketRecord
    ]);

    const [headerLine, rowLine] = csv.split("\n");
    expect(headerLine).toBe(
      [
        "达人信息",
        "粉丝数",
        "21-60s报价",
        "商单视频看后搜率",
        "个人视频看后搜率",
        "秒思api-看后搜率",
        "秒思api-看后搜数",
        "秒思api-新增A3数",
        "秒思api-新增A3率",
        "秒思api-CPA3",
        "秒思api-cp_search",
        ...buildSpreadInfoColumns()
      ].join(",")
    );
    expect(rowLine).toMatch(
      new RegExp(
        `^${escapeRegExp(
          'Alice,100w,"¥450,000",0.5% - 1%,1% - 3%,0.36%,"9,689.96","78,366.22",3.44%,1.79,14.46'
        )}`
      )
    );
  });

  test("omits the representative video column from exported page fields", () => {
    const csv = buildMarketCsv([
      {
        authorId: "123",
        authorName: "Alice",
        exportFields: {
          达人信息: "Alice",
          代表视频: "示例视频",
          粉丝数: "100w"
        },
        status: "success"
      } satisfies MarketRecord
    ]);

    const [headerLine, rowLine] = csv.split("\n");

    expect(headerLine).toBe(
      [
        "达人信息",
        "粉丝数",
        "商单视频看后搜率",
        "个人视频看后搜率",
        "秒思api-看后搜率",
        "秒思api-看后搜数",
        "秒思api-新增A3数",
        "秒思api-新增A3率",
        "秒思api-CPA3",
        "秒思api-cp_search",
        ...buildSpreadInfoColumns()
      ].join(",")
    );
    expect(rowLine.split(",").slice(0, 10).join(",")).toBe(
      "Alice,100w,,,,,,,,"
    );
  });

  test("escapes commas and quotes", () => {
    const csv = buildMarketCsv([
      {
        authorId: "123",
        authorName: "Alice, \"A\"",
        location: "Hangzhou",
        price21To60s: "450000",
        status: "success",
        rates: {
          singleVideoAfterSearchRate: "0.5%-1%",
          personalVideoAfterSearchRate: "1% - 3%"
        }
      }
    ]);

    const [, rowLine] = csv.split("\n");
    expect(rowLine).toContain("\"Alice, \"\"A\"\"\"");
  });

  test("emits empty rate fields plus failed status for failed rows", () => {
    const csv = buildMarketCsv([
      {
        authorId: "123",
        authorName: "Alice",
        status: "failed",
        failureReason: "request-failed"
      }
    ]);

    const [, rowLine] = csv.split("\n");
    expect(rowLine.split(",").slice(0, 12).join(",")).toBe(
      "123,Alice,,,,,,,,,,"
    );
    expect(rowLine.split(",").slice(12).every((cell) => cell === "")).toBe(true);
  });

  test("uses normalized display values in export rows", () => {
    const csv = buildMarketCsv([
      {
        authorId: "123",
        authorName: "Alice",
        status: "success",
        rates: {
          singleVideoAfterSearchRate: "0.5%-1%",
          personalVideoAfterSearchRate: "0.02 - 0.1%"
        }
      } satisfies MarketRecord
    ]);

    const [, rowLine] = csv.split("\n");
    expect(rowLine).toContain("0.5% - 1%");
    expect(rowLine).toContain("0.02% - 0.1%");
  });

  test("emits empty backend metric cells when backend metrics are absent", () => {
    const csv = buildMarketCsv([
      {
        authorId: "123",
        authorName: "Alice",
        status: "success",
        rates: {
          singleVideoAfterSearchRate: "0.5%-1%",
          personalVideoAfterSearchRate: "0.02 - 0.1%"
        }
      } satisfies MarketRecord
    ]);

    const [, rowLine] = csv.split("\n");
    expect(rowLine.split(",").slice(0, 12).join(",")).toBe(
      "123,Alice,,,0.5% - 1%,0.02% - 0.1%,,,,,,"
    );
  });

  test("appends spread info metric columns after backend metrics", () => {
    const csv = buildMarketCsv([
      {
        authorId: "123",
        authorName: "Alice",
        spreadMetrics: {
          "个人视频_近30天_完播率": "28.24%",
          "只看指派_排除营销流量_星图视频_近30天_互动率": "4.02%"
        },
        status: "success"
      } satisfies MarketRecord
    ]);

    const [headerLine, rowLine] = csv.split("\n");
    expect(headerLine).toContain(
      [
        "秒思api-cp_search",
        "个人视频_近30天_完播率",
        "个人视频_近30天_播放量中位数"
      ].join(",")
    );
    expect(headerLine).toContain(
      "只看指派_排除营销流量_星图视频_近30天_互动率"
    );
    expect(rowLine).toContain("28.24%");
    expect(rowLine).toContain("4.02%");
  });

  test("emits empty spread info cells when spread metrics are absent", () => {
    const csv = buildMarketCsv([
      {
        authorId: "123",
        authorName: "Alice",
        status: "success"
      } satisfies MarketRecord
    ]);

    const [, rowLine] = csv.split("\n");
    expect(rowLine.split(",").slice(-70).every((cell) => cell === "")).toBe(true);
  });
});

function escapeRegExp(value: string): string {
  return value.replace(/[.*+?^${}()|[\]\\]/g, "\\$&");
}