339 lines
12 KiB
Python
339 lines
12 KiB
Python
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#!/usr/bin/env python3
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"""贵州茅台年度分析报告生成器
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独立示例脚本，演示如何使用 tushare + ppt_station 生成完整投资分析报告。
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新报告请优先使用 run_job.py + Job JSON 声明式编排。
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使用 tushare 获取数据，生成包含复杂双轴图表的 PPT。
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"""
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import sys
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import json
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from pathlib import Path
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from datetime import datetime
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sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
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import tushare as ts
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import pandas as pd
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import numpy as np
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from ppt_station.config import settings
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# ============================================================================
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# 配置
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# ============================================================================
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STOCK_CODE = "600519.SH"
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STOCK_NAME = "贵州茅台"
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INDEX_CODE = "000300.SH"
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INDEX_NAME = "沪深300"
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YEAR = 2025
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OUTPUT_DIR = Path(__file__).resolve().parent.parent.parent / "output" / "moutai_report"
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TEMPLATE_PATH = Path(__file__).resolve().parent.parent.parent / "aim" / "aim03.pptx"
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def fetch_data():
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"""从 tushare 获取所有需要的数据"""
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pro = ts.pro_api(settings.tushare_token)
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print("📊 获取贵州茅台日线数据...", file=sys.stderr)
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# 当年日线数据
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df_stock = ts.pro_bar(
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ts_code=STOCK_CODE,
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start_date=f"{YEAR}0101",
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end_date=f"{YEAR}1231",
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adj="qfq",
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)
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df_stock = df_stock.sort_values("trade_date").reset_index(drop=True)
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df_stock["trade_date"] = pd.to_datetime(df_stock["trade_date"], format="%Y%m%d")
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print("📊 获取沪深300指数数据...", file=sys.stderr)
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# 对应的沪深300指数（使用 pro_bar + asset='I' 替代 index_daily）
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df_index = ts.pro_bar(
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ts_code=INDEX_CODE,
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start_date=f"{YEAR}0101",
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end_date=f"{YEAR}1231",
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asset="I",
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)
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df_index = df_index.sort_values("trade_date").reset_index(drop=True)
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df_index["trade_date"] = pd.to_datetime(df_index["trade_date"], format="%Y%m%d")
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print("📊 获取近5年日线数据...", file=sys.stderr)
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# 近5年数据（成立以来走势）
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df_stock_5y = ts.pro_bar(
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ts_code=STOCK_CODE,
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start_date=f"{YEAR - 4}0101",
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end_date=f"{YEAR}1231",
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adj="qfq",
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)
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df_stock_5y = df_stock_5y.sort_values("trade_date").reset_index(drop=True)
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df_stock_5y["trade_date"] = pd.to_datetime(df_stock_5y["trade_date"], format="%Y%m%d")
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df_index_5y = ts.pro_bar(
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ts_code=INDEX_CODE,
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start_date=f"{YEAR - 4}0101",
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end_date=f"{YEAR}1231",
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asset="I",
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)
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df_index_5y = df_index_5y.sort_values("trade_date").reset_index(drop=True)
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df_index_5y["trade_date"] = pd.to_datetime(df_index_5y["trade_date"], format="%Y%m%d")
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return df_stock, df_index, df_stock_5y, df_index_5y
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def compute_ytd_chart(df_stock, df_index):
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"""计算当年收益率走势图数据：茅台收益率 vs 沪深300收盘价"""
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# 合并数据
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df = pd.merge(
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df_stock[["trade_date", "close", "vol"]],
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df_index[["trade_date", "close"]],
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on="trade_date",
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how="inner",
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suffixes=("_stock", "_index"),
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)
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# 计算累计收益率
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base_stock = df["close_stock"].iloc[0]
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base_index = df["close_index"].iloc[0]
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df["茅台累计收益率"] = (df["close_stock"] / base_stock - 1)
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df["沪深300指数"] = df["close_index"]
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# 日期列
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df = df.rename(columns={"trade_date": "日期"})
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return df[["日期", "沪深300指数", "茅台累计收益率"]]
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def compute_5y_chart(df_stock_5y, df_index_5y):
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"""计算近5年走势数据：茅台累计收益率 + 成交额"""
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stock = df_stock_5y[["trade_date", "close", "amount"]].copy()
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stock.columns = ["trade_date", "close_stock", "amount_stock"]
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index = df_index_5y[["trade_date", "close"]].copy()
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index.columns = ["trade_date", "close_index"]
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df = pd.merge(stock, index, on="trade_date", how="inner")
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# 累计收益率
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base_stock = df["close_stock"].iloc[0]
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df["茅台累计收益率"] = (df["close_stock"] / base_stock - 1)
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# 成交额（万元）
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df["成交额(万元)"] = df["amount_stock"] / 10 # tushare amount 单位是千元
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df = df.rename(columns={"trade_date": "日期"})
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return df[["日期", "茅台累计收益率", "成交额(万元)"]]
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def compute_stats(df_stock, df_stock_5y):
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"""计算关键统计指标"""
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# 当年收益率
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ytd_return = df_stock["close"].iloc[-1] / df_stock["close"].iloc[0] - 1
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# 5年累计收益率
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total_return = df_stock_5y["close"].iloc[-1] / df_stock_5y["close"].iloc[0] - 1
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# 年化收益率
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n_years = len(df_stock_5y) / 245 # 大约交易日数
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annualized = (1 + total_return) ** (1 / n_years) - 1 if n_years > 0 else 0
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# 最新价
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latest_price = df_stock["close"].iloc[-1]
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# 最新市值（假设总股本约12.56亿股）
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total_shares = 12.56 # 亿股
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market_cap = latest_price * total_shares # 亿元
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return {
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"ytd_return": ytd_return,
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"total_return": total_return,
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"annualized": annualized,
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"latest_price": latest_price,
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"market_cap": market_cap,
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"report_date": df_stock["trade_date"].iloc[-1].strftime("%Y-%m-%d"),
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"start_date": df_stock_5y["trade_date"].iloc[0].strftime("%Y-%m-%d"),
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}
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def main():
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OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
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# 获取数据
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df_stock, df_index, df_stock_5y, df_index_5y = fetch_data()
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print(f"✅ 获取到 {len(df_stock)} 条当年数据, {len(df_stock_5y)} 条5年数据", file=sys.stderr)
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# 计算图表数据
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ytd_df = compute_ytd_chart(df_stock, df_index)
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fivey_df = compute_5y_chart(df_stock_5y, df_index_5y)
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stats = compute_stats(df_stock, df_stock_5y)
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print(f"📈 当年收益率: {stats['ytd_return']:.2%}", file=sys.stderr)
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print(f"📈 5年累计收益率: {stats['total_return']:.2%}", file=sys.stderr)
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print(f"📈 年化收益率: {stats['annualized']:.2%}", file=sys.stderr)
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print(f"📈 最新价: {stats['latest_price']:.2f}", file=sys.stderr)
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# 保存 CSV
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ytd_csv = OUTPUT_DIR / "ytd_chart.csv"
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fivey_csv = OUTPUT_DIR / "fivey_chart.csv"
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ytd_df.to_csv(ytd_csv, index=False)
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fivey_df.to_csv(fivey_csv, index=False)
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print(f"💾 已保存 CSV: {ytd_csv}, {fivey_csv}", file=sys.stderr)
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# 构建 config.json
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config = {
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"text_data": {
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"标题": f"{STOCK_NAME}{YEAR}年度投资分析报告",
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"作者": "PPT-Station 自动生成",
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"日期": stats["report_date"],
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"标题1": f"{STOCK_NAME}股价与估值分析",
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"标题2": f"{STOCK_NAME}财务与经营分析",
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"标题3": f"{STOCK_NAME}投资价值总结",
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"组合名称": f"{STOCK_NAME}（{STOCK_CODE}）",
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"报告日期": stats["report_date"],
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"成立日期": stats["start_date"],
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"资产规模": f"{stats['market_cap']:.0f}亿元",
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"本年收益": f"{stats['ytd_return']:.2%}",
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"本年收益金额": f"{stats['latest_price']:.2f}元/股",
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"累计收益率": f"{stats['total_return']:.2%}",
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"累计收益金额": f"近5年({YEAR-4}-{YEAR})",
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"平均年化": f"{stats['annualized']:.2%}",
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},
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"chart_configs": {
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"当年收益率走势图": {
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"csv_path": "ytd_chart.csv",
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"categories_col": "日期",
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"series_config": [
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{
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"key": "沪深300指数",
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"name": f"{INDEX_NAME}指数(收盘价)",
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"type": "bar",
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"axis": "secondary",
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},
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{
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"key": "茅台累计收益率",
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"name": f"{STOCK_NAME}累计收益率（左轴）",
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"type": "line",
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"axis": "primary",
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},
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],
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"style": {
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"color_scheme": "aim00",
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"line_width_pt": 2.0,
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"marker_style": "none",
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},
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"layout": {
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"title": f"{STOCK_NAME}{YEAR}年累计收益率走势图",
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"legend": {
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"position": "top",
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"font_size_pt": 9,
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"font_name": "黑体",
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},
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"value_axis": {
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"number_format": "0%",
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"font_size_pt": 9,
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"font_name": "黑体",
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"has_major_gridlines": False,
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},
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"secondary_value_axis": {
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"number_format": "#,##0",
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"font_size_pt": 9,
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"font_name": "黑体",
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"has_major_gridlines": False,
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},
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"date_axis": {
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"base_unit": "days",
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"number_format": "yyyy/mm",
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},
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},
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},
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"组合成立以来收益率走势": {
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"csv_path": "fivey_chart.csv",
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"categories_col": "日期",
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"series_config": [
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{
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"key": "茅台累计收益率",
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"name": f"{STOCK_NAME}累计收益率",
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"type": "line",
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"axis": "primary",
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},
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{
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"key": "成交额(万元)",
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"name": "成交额(万元)",
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"type": "area",
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"axis": "secondary",
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},
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],
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"style": {
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"color_scheme": "aim00",
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"line_width_pt": 2.0,
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"marker_style": "none",
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},
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"layout": {
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"title": f"{STOCK_NAME}近5年走势（{YEAR-4}-{YEAR}）",
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"legend": {
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"position": "bottom",
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"font_size_pt": 9,
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"font_name": "黑体",
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},
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"value_axis": {
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"number_format": "0%",
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"font_size_pt": 9,
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"font_name": "黑体",
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"has_major_gridlines": False,
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},
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"secondary_value_axis": {
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"number_format": "#,##0",
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"font_size_pt": 9,
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"font_name": "黑体",
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"has_major_gridlines": False,
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},
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"date_axis": {
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"base_unit": "days",
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"number_format": "yyyy/mm",
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},
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},
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},
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},
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}
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config_path = OUTPUT_DIR / "config.json"
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with open(config_path, "w", encoding="utf-8") as f:
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json.dump(config, f, ensure_ascii=False, indent=2)
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print(f"💾 已保存配置: {config_path}", file=sys.stderr)
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# 调用 generate_ppt
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output_pptx = OUTPUT_DIR / f"moutai_{YEAR}_report.pptx"
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print(f"\n🔧 生成 PPT...", file=sys.stderr)
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from ppt_station.template.replacer import TemplateReplacer
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from ppt_station.chart_builder.styles import StyleConfig
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from ppt_station.chart_builder.layout import (
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ChartLayoutConfig,
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LegendConfig,
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ValueAxisConfig,
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)
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from ppt_station.chart_builder.date_axis import DateAxisConfig
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from pptx.enum.chart import XL_LEGEND_POSITION
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# 导入 generate_ppt 的 build_chart_config
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sys.path.insert(0, str(Path(__file__).resolve().parent))
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from generate_ppt import build_chart_config
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|
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chart_configs = {}
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for chart_name, chart_def in config["chart_configs"].items():
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print(f" 构建图表: {chart_name}", file=sys.stderr)
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chart_configs[chart_name] = build_chart_config(chart_name, chart_def, OUTPUT_DIR)
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replacer = TemplateReplacer(TEMPLATE_PATH)
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replacer.replace(data=config["text_data"], chart_configs=chart_configs)
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|
replacer.save(output_pptx)
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|
|
|
|||
|
|
print(f"\n✅ 报告已生成: {output_pptx}", file=sys.stderr)
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|
|
print(json.dumps({"status": "ok", "output": str(output_pptx)}))
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|
|
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|
|
|
|||
|
|
if __name__ == "__main__":
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|
main()
|