# -*- coding: utf-8 -*-
"""build_studio_urls.py CLI 端到端测试。

以子进程运行脚本（与真实使用方式一致：uv run python build_studio_urls.py -i ... -o ...），
覆盖输入格式（CSV UTF-8-BOM / GBK / XLSX）、成功输出、失败行与退出码约定：

  退出码 0 ：全部行生成成功
  退出码 1 ：输入文件不存在 / 格式不支持 / 缺必要列
  退出码 2 ：存在失败行（成功行仍写入输出，失败行逐行打印在 stderr）
"""

import pandas as pd
import pytest

from conftest import ROOT, URL_BUILDER_SCRIPT, run_script

ASSET_XLSX = ROOT / "assets" / "需求输入示例.xlsx"

HEADERS = ["所有者名称", "所有者ID", "实体类型", "实体名称", "实体ID", "数据周期", "国家"]

OUTPUT_COLUMNS = ["所有者名称", "所有者ID", "实体类型", "实体名称", "实体ID",
                  "数据周期", "国家", "国家代码", "指标", "指标代码", "维度", "维度代码",
                  "开始时间戳", "结束时间戳", "URL"]


def run_builder(args):
    return run_script(URL_BUILDER_SCRIPT, args)


def read_output(path):
    return pd.read_csv(path, encoding="utf-8-sig")


# ---------------------------------------------------------------------------
# 输入格式
# ---------------------------------------------------------------------------
class TestInputFormats:
    def test_csv_utf8_bom(self, tmp_path):
        src = tmp_path / "需求.csv"
        src.write_text(
            ",".join(HEADERS) + "\n"
            "示例所有者,MC123,群组,示例群组,G001,2026.07.01-2026.08.01,美国\n",
            encoding="utf-8-sig",
        )
        out = tmp_path / "out.csv"
        r = run_builder(["-i", str(src), "-o", str(out)])
        assert r.returncode == 0, r.stderr
        assert "已生成 1 条 URL" in r.stdout
        df = read_output(out)
        assert list(df.columns) == OUTPUT_COLUMNS
        assert len(df) == 1
        assert df.loc[0, "国家代码"] == "US"
        assert df.loc[0, "URL"].startswith("https://studio.youtube.com/owner/MC123/")

    def test_csv_gbk_fallback(self, tmp_path):
        """Excel 另存 ANSI/GBK 编码 CSV 也能读。"""
        src = tmp_path / "需求_gbk.csv"
        src.write_text(
            ",".join(HEADERS) + "\n"
            "示例所有者,MC123,群组,示例群组,G001,2026.07.01-2026.08.01,美国\n",
            encoding="gbk",
        )
        out = tmp_path / "out.csv"
        r = run_builder(["-i", str(src), "-o", str(out)])
        assert r.returncode == 0, r.stderr
        df = read_output(out)
        assert len(df) == 1
        assert df.loc[0, "国家代码"] == "US"

    def test_xlsx_input(self, tmp_path):
        src = tmp_path / "需求.xlsx"
        pd.DataFrame([
            {"所有者名称": "示例所有者", "所有者ID": "MC123", "实体类型": "群组",
             "实体名称": "示例群组", "实体ID": "G001",
             "数据周期": "2026.07.01-2026.08.01", "国家": "US"},
        ]).to_excel(src, index=False)
        out = tmp_path / "out.csv"
        r = run_builder(["-i", str(src), "-o", str(out)])
        assert r.returncode == 0, r.stderr
        df = read_output(out)
        assert len(df) == 1
        assert "ur_values=%27US%27" in df.loc[0, "URL"]

    def test_unsupported_extension_exits_1(self, tmp_path):
        src = tmp_path / "需求.txt"
        src.write_text("所有者ID,数据周期\nMC123,2026.07.01-2026.08.01", encoding="utf-8")
        r = run_builder(["-i", str(src), "-o", str(tmp_path / "out.csv")])
        assert r.returncode == 1
        assert "不支持的输入格式" in r.stderr

    def test_missing_file_exits_1(self, tmp_path):
        r = run_builder(["-i", str(tmp_path / "不存在.csv"), "-o", str(tmp_path / "out.csv")])
        assert r.returncode == 1
        assert "输入文件不存在" in r.stderr


# ---------------------------------------------------------------------------
# 成功路径与输出内容
# ---------------------------------------------------------------------------
class TestHappyPath:
    def test_output_content(self, tmp_path):
        src = tmp_path / "需求.csv"
        pd.DataFrame([
            {"所有者名称": "所有者A", "所有者ID": "MC123", "实体类型": "群组",
             "实体名称": "群组1", "实体ID": "G001",
             "数据周期": "2026.07.01-2026.08.01", "国家": "美国,日本"},
            {"所有者名称": "所有者B", "所有者ID": "MC456", "实体类型": "频道",
             "实体名称": "频道1", "实体ID": "UCxyz",
             "数据周期": "2026.8.1-2026.8.31", "国家": ""},
        ]).to_csv(src, index=False, encoding="utf-8-sig")
        out = tmp_path / "out.csv"
        r = run_builder(["-i", str(src), "-o", str(out)])
        assert r.returncode == 0, r.stderr
        df = read_output(out)
        assert len(df) == 2

        row0, row1 = df.iloc[0], df.iloc[1]
        assert row0["国家代码"] == "US,JP"
        assert "ur_values=%27US%27%7C%27JP%27" in row0["URL"]
        # 时间戳 = 日界线毫秒（独立于模块重算：锚点 2026-06-15 + 整日偏移）
        anchor = 1781506800000
        assert row0["开始时间戳"] == anchor + 16 * 86400000            # 2026-07-01
        assert row0["结束时间戳"] == anchor + 48 * 86400000            # 2026-08-01 次日
        # 无国家行：不含国家筛选参数，实体类型为频道
        assert "ur_values" not in row1["URL"]
        assert "entity_type=CHANNEL" in row1["URL"]
        assert "entity_id=UCxyz" in row1["URL"]
        assert row1["国家代码"] == "" or pd.isna(row1["国家代码"])

    def test_default_output_next_to_input(self, tmp_path):
        """不传 -o 时输出到输入同目录 studio_urls_output.csv。"""
        src = tmp_path / "sub"
        src.mkdir()
        inp = src / "需求.csv"
        inp.write_text(
            "所有者ID,实体ID,数据周期\nMC123,G001,2026.07.01-2026.08.01",
            encoding="utf-8-sig",
        )
        r = run_builder(["-i", str(inp)])
        assert r.returncode == 0, r.stderr
        assert (src / "studio_urls_output.csv").exists()
        assert "已生成 1 条 URL" in r.stdout

    def test_blank_rows_dropped(self, tmp_path):
        """全空行不产出 URL、不算失败。"""
        src = tmp_path / "需求.csv"
        src.write_text(
            "所有者ID,实体ID,数据周期\n"
            "MC123,G001,2026.07.01-2026.08.01\n"
            ",,\n"
            "MC456,G002,2026.07.01-2026.08.01\n",
            encoding="utf-8-sig",
        )
        out = tmp_path / "out.csv"
        r = run_builder(["-i", str(src), "-o", str(out)])
        assert r.returncode == 0, r.stderr
        assert "已生成 2 条 URL" in r.stdout

    def test_custom_countries_json(self, tmp_path):
        cj = tmp_path / "my_countries.json"
        cj.write_text('{"梦幻国": "ZZ"}', encoding="utf-8")
        src = tmp_path / "需求.csv"
        src.write_text(
            "所有者ID,实体ID,数据周期,国家\nMC123,G001,2026.07.01-2026.08.01,梦幻国",
            encoding="utf-8-sig",
        )
        out = tmp_path / "out.csv"
        r = run_builder(["-i", str(src), "-o", str(out), "--countries", str(cj)])
        assert r.returncode == 0, r.stderr
        df = read_output(out)
        assert df.loc[0, "国家代码"] == "ZZ"
        assert "ur_values=%27ZZ%27" in df.loc[0, "URL"]

    def test_unknown_columns_warned_but_ok(self, tmp_path):
        src = tmp_path / "需求.csv"
        src.write_text(
            "所有者ID,实体ID,数据周期,备注\nMC123,G001,2026.07.01-2026.08.01,随便写",
            encoding="utf-8-sig",
        )
        out = tmp_path / "out.csv"
        r = run_builder(["-i", str(src), "-o", str(out)])
        assert r.returncode == 0, r.stderr
        assert "未识别的列" in r.stderr and "备注" in r.stderr
        assert len(read_output(out)) == 1


# ---------------------------------------------------------------------------
# 指标（每行可选）
# ---------------------------------------------------------------------------
class TestMetricColumn:
    def test_metric_selected_and_default(self, tmp_path):
        """指标列：一行选"观看时长"，一行留空走 CONFIG 默认。"""
        src = tmp_path / "需求.csv"
        pd.DataFrame([
            {"所有者ID": "MC123", "实体ID": "G001", "数据周期": "2026.07.01-2026.08.01",
             "指标": "观看时长"},
            {"所有者ID": "MC123", "实体ID": "G002", "数据周期": "2026.07.01-2026.08.01",
             "指标": ""},
        ]).to_csv(src, index=False, encoding="utf-8-sig")
        out = tmp_path / "out.csv"
        r = run_builder(["-i", str(src), "-o", str(out)])
        assert r.returncode == 0, r.stderr
        df = read_output(out)
        assert list(df.columns) == OUTPUT_COLUMNS
        assert df.loc[0, "指标"] == "观看时长"
        assert df.loc[0, "指标代码"] == "EXTERNAL_WATCH_TIME"
        assert "metric=EXTERNAL_WATCH_TIME" in df.loc[0, "URL"]
        assert "o_column=EXTERNAL_WATCH_TIME" in df.loc[0, "URL"]
        # 空白行：回退 CONFIG 默认
        assert df.loc[1, "指标代码"] == "SUBSCRIBERS_NET_CHANGE"
        assert "metric=SUBSCRIBERS_NET_CHANGE" in df.loc[1, "URL"]

    def test_unknown_metric_exits_2(self, tmp_path):
        src = tmp_path / "需求.csv"
        src.write_text(
            "所有者ID,实体ID,数据周期,指标\nMC123,G001,2026.07.01-2026.08.01,神秘指标\n",
            encoding="utf-8-sig",
        )
        out = tmp_path / "out.csv"
        r = run_builder(["-i", str(src), "-o", str(out)])
        assert r.returncode == 2
        assert "未识别的指标" in r.stderr
        assert "第2行" in r.stderr

    def test_metric_code_passthrough(self, tmp_path):
        src = tmp_path / "需求.csv"
        src.write_text(
            "所有者ID,实体ID,数据周期,指标\nMC123,G001,2026.07.01-2026.08.01,external_views\n",
            encoding="utf-8-sig",
        )
        out = tmp_path / "out.csv"
        r = run_builder(["-i", str(src), "-o", str(out)])
        assert r.returncode == 0, r.stderr
        df = read_output(out)
        assert df.loc[0, "指标代码"] == "EXTERNAL_VIEWS"
        assert "metric=EXTERNAL_VIEWS" in df.loc[0, "URL"]

    def test_metric_alias_tax_revenue(self, tmp_path):
        """「税前收益/税前收入」别名 -> TOTAL_ESTIMATED_EARNINGS。"""
        src = tmp_path / "需求.csv"
        src.write_text(
            "所有者ID,实体ID,数据周期,指标\nMC123,G001,2026.07.01-2026.08.01,税前收益\n",
            encoding="utf-8-sig",
        )
        out = tmp_path / "out.csv"
        r = run_builder(["-i", str(src), "-o", str(out)])
        assert r.returncode == 0, r.stderr
        df = read_output(out)
        assert df.loc[0, "指标代码"] == "TOTAL_ESTIMATED_EARNINGS"
        assert "metric=TOTAL_ESTIMATED_EARNINGS" in df.loc[0, "URL"]


# ---------------------------------------------------------------------------
# 维度（每行可选）
# ---------------------------------------------------------------------------
class TestDimensionColumn:
    def test_dimension_selected_and_default(self, tmp_path):
        """维度列：一行选"地理位置"，一行留空走 CONFIG 默认。"""
        src = tmp_path / "需求.csv"
        pd.DataFrame([
            {"所有者ID": "MC123", "实体ID": "G001", "数据周期": "2026.07.01-2026.08.01",
             "维度": "地理位置"},
            {"所有者ID": "MC123", "实体ID": "G002", "数据周期": "2026.07.01-2026.08.01",
             "维度": ""},
        ]).to_csv(src, index=False, encoding="utf-8-sig")
        out = tmp_path / "out.csv"
        r = run_builder(["-i", str(src), "-o", str(out)])
        assert r.returncode == 0, r.stderr
        df = read_output(out)
        assert list(df.columns) == OUTPUT_COLUMNS
        assert df.loc[0, "维度"] == "地理位置"
        assert df.loc[0, "维度代码"] == "COUNTRY"
        assert "dimension=COUNTRY" in df.loc[0, "URL"]
        # 空白行：回退 CONFIG 默认
        assert df.loc[1, "维度代码"] == "USER"
        assert "dimension=USER" in df.loc[1, "URL"]

    def test_unknown_dimension_exits_2(self, tmp_path):
        src = tmp_path / "需求.csv"
        src.write_text(
            "所有者ID,实体ID,数据周期,维度\nMC123,G001,2026.07.01-2026.08.01,神秘维度\n",
            encoding="utf-8-sig",
        )
        out = tmp_path / "out.csv"
        r = run_builder(["-i", str(src), "-o", str(out)])
        assert r.returncode == 2
        assert "未识别的维度" in r.stderr
        assert "第2行" in r.stderr

    def test_dimension_code_passthrough(self, tmp_path):
        src = tmp_path / "需求.csv"
        src.write_text(
            "所有者ID,实体ID,数据周期,维度\nMC123,G001,2026.07.01-2026.08.01,video\n",
            encoding="utf-8-sig",
        )
        out = tmp_path / "out.csv"
        r = run_builder(["-i", str(src), "-o", str(out)])
        assert r.returncode == 0, r.stderr
        df = read_output(out)
        assert df.loc[0, "维度代码"] == "VIDEO"
        assert "dimension=VIDEO" in df.loc[0, "URL"]


# ---------------------------------------------------------------------------
# 失败行与退出码
# ---------------------------------------------------------------------------
class TestErrorRows:
    def test_error_row_exits_2_and_reports_line(self, tmp_path):
        """失败行：退出码 2，stderr 报「第N行」（N 按文件行号，含表头）；成功行照常输出。"""
        src = tmp_path / "需求.csv"
        src.write_text(
            "所有者ID,实体ID,数据周期\n"
            "MC123,G001,2026.07.01-2026.08.01\n"     # 第2行 成功
            "MC123,,2026.07.01-2026.08.01\n"          # 第3行 缺实体ID -> 失败
            "MC456,G002,2026.07.01-2026.08.01\n",     # 第4行 成功
            encoding="utf-8-sig",
        )
        out = tmp_path / "out.csv"
        r = run_builder(["-i", str(src), "-o", str(out)])
        assert r.returncode == 2
        assert "已生成 2 条 URL" in r.stdout
        assert "以下 1 行生成失败" in r.stderr
        assert "第3行" in r.stderr
        assert "缺少实体ID" in r.stderr
        assert len(read_output(out)) == 2

    def test_missing_required_column_exits_1(self, tmp_path):
        src = tmp_path / "需求.csv"
        src.write_text("所有者名称,实体名称\nA,B\n", encoding="utf-8-sig")
        r = run_builder(["-i", str(src), "-o", str(tmp_path / "out.csv")])
        assert r.returncode == 1
        # 提示缺失的规范字段名（owner_id 与 period 同时缺失时都列出）
        assert "缺少必要列" in r.stderr
        assert "owner_id" in r.stderr
        assert "period" in r.stderr

    def test_all_rows_fail_still_writes_empty_output(self, tmp_path):
        src = tmp_path / "需求.csv"
        src.write_text(
            "所有者ID,实体ID,数据周期\nMC123,,2026.07.01-2026.08.01\n",
            encoding="utf-8-sig",
        )
        out = tmp_path / "out.csv"
        r = run_builder(["-i", str(src), "-o", str(out)])
        assert r.returncode == 2
        assert "已生成 0 条 URL" in r.stdout
        assert out.exists()  # 空结果也落盘（仅表头）


# ---------------------------------------------------------------------------
# 集成：真实资产文件
# ---------------------------------------------------------------------------
class TestRealAsset:
    def test_example_asset_generates_all_urls(self, tmp_path):
        """assets/需求输入示例.xlsx：6 条示例（群组/所有者/频道/节目）全部成功。"""
        out = tmp_path / "out.csv"
        r = run_builder(["-i", str(ASSET_XLSX), "-o", str(out)])
        assert r.returncode == 0, r.stderr
        df = read_output(out)
        assert len(df) == 6
        # 所有者整体行：实体ID 为空时回退用所有者ID
        owner_row = df[df["实体类型"] == "所有者"].iloc[0]
        assert "entity_type=CONTENT_OWNER" in owner_row["URL"]
        assert "entity_id=bqSUnNpU67xJ51TxH4PKpQ" in owner_row["URL"]
        # 实体类型枚举全覆盖
        assert set(df["实体类型"]) == {"群组", "所有者", "频道", "节目"}
        # 每行 URL 均含 owner 路径与 time_period
        for url in df["URL"]:
            assert url.startswith(
                "https://studio.youtube.com/owner/bqSUnNpU67xJ51TxH4PKpQ/analytics/")
            assert "time_period=" in url


# ---------------------------------------------------------------------------
# CLI 参数
# ---------------------------------------------------------------------------
class TestCliArgs:
    def test_help(self):
        r = run_builder(["--help"])
        assert r.returncode == 0
        assert "批量拼接 YouTube Studio explore URL" in r.stdout

    def test_input_required(self):
        r = run_builder([])
        assert r.returncode != 0  # argparse 缺 -i 报错退出码 2
        assert "required" in r.stderr or "-i" in r.stderr