#!/usr/bin/env python3 """ 用 pyecharts 生成专业期货图表 """ import akshare as ak from pyecharts.charts import Kline, Line, Bar, Grid, Page from pyecharts import options as opts from pyecharts.globals import ThemeType import pandas as pd import os # 创建输出目录 output_dir = '/root/.openclaw/workspace/ppt_charts_pyecharts' os.makedirs(output_dir, exist_ok=True) # 获取历史日线数据 - 玉米期货主力合约 # 玉米期货在大连商品交易所(DCE) hist = ak.futures_zh_daily_sina(symbol="C0") hist = hist.tail(60).reset_index(drop=True) # 准备K线数据 [open, close, low, high] kline_data = [] for _, row in hist.iterrows(): kline_data.append([ float(row['open']), float(row['close']), float(row['low']), float(row['high']) ]) dates = hist['date'].tolist() # 1. K线图 + MA均线 kline = ( Kline(init_opts=opts.InitOpts( width="1200px", height="600px", theme=ThemeType.DARK, bg_color="#1a1a2e" )) .add_xaxis(dates) .add_yaxis( "K线", kline_data, itemstyle_opts=opts.ItemStyleOpts( color="#ef4444", # 涨 红色 color0="#22c55e", # 跌 绿色 border_color="#ef4444", border_color0="#22c55e" ) ) .set_global_opts( title_opts=opts.TitleOpts( title="玉米期货主力合约(C0) 走势", subtitle="数据来源: AKShare", title_textstyle_opts=opts.TextStyleOpts(color="#fff", font_size=20), subtitle_textstyle_opts=opts.TextStyleOpts(color="#aaa", font_size=12), pos_left="center" ), tooltip_opts=opts.TooltipOpts( trigger="axis", axis_pointer_type="cross", background_color="rgba(50,50,50,0.8)", border_color="#666", textstyle_opts=opts.TextStyleOpts(color="#fff") ), legend_opts=opts.LegendOpts( pos_top="10%", textstyle_opts=opts.TextStyleOpts(color="#fff") ), xaxis_opts=opts.AxisOpts( type_="category", axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(color="#666")), axislabel_opts=opts.LabelOpts(color="#aaa", rotate=45), splitline_opts=opts.SplitLineOpts(is_show=False) ), yaxis_opts=opts.AxisOpts( type_="value", axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(color="#666")), axislabel_opts=opts.LabelOpts(color="#aaa"), splitline_opts=opts.SplitLineOpts( linestyle_opts=opts.LineStyleOpts(color="#333", type_="dashed") ) ), datazoom_opts=[ opts.DataZoomOpts(type_="inside", range_start=0, range_end=100), opts.DataZoomOpts(type_="slider", range_start=0, range_end=100, pos_bottom="5%") ] ) ) # 计算并添加均线 ma5 = hist['close'].rolling(window=5).mean().bfill().tolist() ma10 = hist['close'].rolling(window=10).mean().bfill().tolist() ma20 = hist['close'].rolling(window=20).mean().bfill().tolist() line_ma5 = ( Line() .add_xaxis(dates) .add_yaxis("MA5", ma5, is_smooth=True, linestyle_opts=opts.LineStyleOpts(width=2, color="#fbbf24"), label_opts=opts.LabelOpts(is_show=False)) ) line_ma10 = ( Line() .add_xaxis(dates) .add_yaxis("MA10", ma10, is_smooth=True, linestyle_opts=opts.LineStyleOpts(width=2, color="#60a5fa"), label_opts=opts.LabelOpts(is_show=False)) ) line_ma20 = ( Line() .add_xaxis(dates) .add_yaxis("MA20", ma20, is_smooth=True, linestyle_opts=opts.LineStyleOpts(width=2, color="#a78bfa"), label_opts=opts.LabelOpts(is_show=False)) ) kline.overlap(line_ma5) kline.overlap(line_ma10) kline.overlap(line_ma20) # 保存K线图 kline.render(f"{output_dir}/kline_chart.html") kline.render(f"{output_dir}/kline_chart.png") # 2. 成交量图 volumes = hist['volume'].astype(float).tolist() colors = ["#ef4444" if hist['close'].iloc[i] >= hist['open'].iloc[i] else "#22c55e" for i in range(len(hist))] bar = ( Bar(init_opts=opts.InitOpts(width="1200px", height="300px", theme=ThemeType.DARK, bg_color="#1a1a2e")) .add_xaxis(dates) .add_yaxis("成交量", volumes, itemstyle_opts=opts.ItemStyleOpts(color=colors)) .set_global_opts( title_opts=opts.TitleOpts(title="成交量", title_textstyle_opts=opts.TextStyleOpts(color="#fff")), xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=45, color="#aaa")), yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(color="#aaa")) ) ) bar.render(f"{output_dir}/volume_chart.html") bar.render(f"{output_dir}/volume_chart.png") # 3. 相关品种对比图 symbols = {'C0': '玉米', 'M0': '豆粕', 'CS0': '淀粉', 'LH0': '生猪'} colors_map = {'C0': '#fbbf24', 'M0': '#60a5fa', 'CS0': '#a78bfa', 'LH0': '#f472b6'} line_chart = ( Line(init_opts=opts.InitOpts( width="1200px", height="600px", theme=ThemeType.DARK, bg_color="#1a1a2e" )) .set_global_opts( title_opts=opts.TitleOpts( title="相关品种价格走势对比", subtitle="归一化处理（基准=100）", title_textstyle_opts=opts.TextStyleOpts(color="#fff", font_size=20), pos_left="center" ), legend_opts=opts.LegendOpts( pos_top="10%", textstyle_opts=opts.TextStyleOpts(color="#fff", font_size=14) ), tooltip_opts=opts.TooltipOpts(trigger="axis"), xaxis_opts=opts.AxisOpts( type_="category", axislabel_opts=opts.LabelOpts(color="#aaa", rotate=45) ), yaxis_opts=opts.AxisOpts( type_="value", name="涨跌幅(%)", name_textstyle_opts=opts.TextStyleOpts(color="#aaa"), axislabel_opts=opts.LabelOpts(color="#aaa", formatter="{value}%"), splitline_opts=opts.SplitLineOpts( linestyle_opts=opts.LineStyleOpts(color="#333", type_="dashed") ) ) ) ) line_chart.add_xaxis(dates) for code, name in symbols.items(): try: df_sym = ak.futures_zh_daily_sina(symbol=code) df_sym = df_sym.tail(60).reset_index(drop=True) if len(df_sym) > 0: base_price = float(df_sym['close'].iloc[0]) normalized = [(float(p) / base_price - 1) * 100 for p in df_sym['close']] line_chart.add_yaxis( name, normalized, is_smooth=True, symbol_size=0, linestyle_opts=opts.LineStyleOpts(width=3, color=colors_map[code]), label_opts=opts.LabelOpts(is_show=False) ) except Exception as e: print(f"获取 {code} 数据失败: {e}") line_chart.render(f"{output_dir}/correlation_chart.html") line_chart.render(f"{output_dir}/correlation_chart.png") print(f"✅ 图表生成完成！保存在: {output_dir}") print(f" - K线图: {output_dir}/kline_chart.html") print(f" - 成交量: {output_dir}/volume_chart.html") print(f" - 相关品种对比: {output_dir}/correlation_chart.html")