'commit'
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@@ -1,6 +1,5 @@
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from fastapi import APIRouter
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from fastapi import APIRouter
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import json
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from Model.RenkouModel import RenkouModel
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from Model.RuYuanZaiYuanCountModel import RuYuanZaiYuanModel
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from Model.RuYuanZaiYuanCountModel import RuYuanZaiYuanModel
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# 创建APIRouter实例
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# 创建APIRouter实例
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@@ -11,14 +10,6 @@ router = APIRouter(prefix="/bigscreen", tags=["大屏展示"])
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async def root():
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async def root():
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return {"message": "Welcome to YunNan Education World!"}
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return {"message": "Welcome to YunNan Education World!"}
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@router.get("/population/chart/{year}")
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async def get_population_chart_config(year: str = "2024"):
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return RenkouModel.generate_population_chart_config(year)
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@router.get("/population/urbanization")
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async def get_urbanization_rate_chart_config():
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return RenkouModel.generate_urbanization_rate_chart_config()
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@router.get("/school/preschool/chart")
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@router.get("/school/preschool/chart")
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async def get_preschool_education_chart_config():
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async def get_preschool_education_chart_config():
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return RuYuanZaiYuanModel.generate_preschool_education_config()
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return RuYuanZaiYuanModel.generate_preschool_education_config()
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import json
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from pyecharts import options as opts
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from pyecharts.charts import Bar, Line
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from pyecharts.globals import CurrentConfig
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from Config.Config import ONLINE_HOST
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CurrentConfig.ONLINE_HOST = ONLINE_HOST
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class RenkouModel:
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@staticmethod
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def load_population_data():
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try:
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# 获取当前文件所在目录的父目录，然后找到Data文件夹
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data_path = "./Data/RenKou.json"
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with open(data_path, "r", encoding="utf-8") as f:
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data = json.load(f)
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return data
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except Exception as e:
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print(f"读取人口数据出错: {e}")
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return []
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@staticmethod
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def generate_population_chart_config(year="2024"):
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# 加载人口数据
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population_data = RenkouModel.load_population_data()
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# 筛选出州市级数据
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cities = [item for item in population_data if len(item["area_code"]) == 9 and item["area_code"].endswith("000") and item["area_code"][4:6] == "00" and item["area_code"][2:8] != "000000"]
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# 提取城市名称和人口数据
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city_names = [city["area_name"] for city in cities]
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total_populations = [city["total_population"].get(year, 0) for city in cities]
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urban_populations = [city["urban_population"].get(year, 0) for city in cities]
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rural_populations = [city["rural_population"].get(year, 0) for city in cities]
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# 创建柱状图
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c = (
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Bar()
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.add_xaxis(city_names)
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.add_yaxis("总人口", total_populations, stack="stack1")
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.add_yaxis("城镇人口", urban_populations, stack="stack1")
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.add_yaxis("农村人口", rural_populations, stack="stack1")
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.set_global_opts(
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title_opts=opts.TitleOpts(
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title=f"云南省各州市人口分布图（{year}年）",
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pos_top="1%",
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pos_left="center"
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),
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tooltip_opts=opts.TooltipOpts(
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trigger="axis",
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axis_pointer_type="shadow"
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),
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legend_opts=opts.LegendOpts(
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pos_top="8%",
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pos_right="5%"
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),
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datazoom_opts=[opts.DataZoomOpts()],
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xaxis_opts=opts.AxisOpts(
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axislabel_opts=opts.LabelOpts(rotate=45)
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),
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yaxis_opts=opts.AxisOpts(
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name="人口数量（万人）",
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name_location="middle",
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name_gap=40
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)
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)
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.set_series_opts(
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label_opts=opts.LabelOpts(is_show=False),
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markline_opts=opts.MarkLineOpts(
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data=[opts.MarkLineItem(type_="average", name="平均值")]
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)
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)
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)
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# 获取图表的选项配置
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options_str = c.dump_options_with_quotes()
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return json.loads(options_str)
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@staticmethod
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def generate_urbanization_rate_chart_config():
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# 加载人口数据
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population_data = RenkouModel.load_population_data()
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# 筛选出州市级数据
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cities = [item for item in population_data if len(item["area_code"]) == 9 and item["area_code"].endswith("000") and item["area_code"][4:6] == "00" and item["area_code"][2:8] != "000000"]
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# 提取城市名称
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city_names = [city["area_name"] for city in cities]
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# 创建折线图
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line = (
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Line()
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.add_xaxis(city_names)
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)
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# 添加各年份的城镇化率数据
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years = ["2020", "2021", "2022", "2023", "2024"]
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for year in years:
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urbanization_rates = [city["urbanization_rate"].get(year, 0) for city in cities]
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line.add_yaxis(f"{year}年", urbanization_rates,
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markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_="max")]))
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line.set_global_opts(
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title_opts=opts.TitleOpts(
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title="云南省各州市城镇化率变化趋势",
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pos_top="1%",
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pos_left="center"
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),
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tooltip_opts=opts.TooltipOpts(trigger="axis"),
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legend_opts=opts.LegendOpts(
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pos_top="8%",
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pos_right="5%"
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),
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datazoom_opts=[opts.DataZoomOpts()],
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xaxis_opts=opts.AxisOpts(
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axislabel_opts=opts.LabelOpts(rotate=45)
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),
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yaxis_opts=opts.AxisOpts(
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name="城镇化率（%）",
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name_location="middle",
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name_gap=40,
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min_=0,
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max_=100
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)
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)
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# 获取图表的选项配置
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options_str = line.dump_options_with_quotes()
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return json.loads(options_str)
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Model/__pycache__/RuYuanZaiYuanCountModel.cpython-310.pyc
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Model/__pycache__/RuYuanZaiYuanCountModel.cpython-310.pyc
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<!DOCTYPE html>
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<html lang="zh-CN">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>云南教育决策研究服务系统</title>
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<!-- 引入外部资源 -->
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<script src="https://gcore.jsdelivr.net/npm/echarts@6.0.0/dist/echarts.min.js"></script>
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<link rel="stylesheet" href="css/style.css">
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</head>
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<body>
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<div class="header">
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<h1>云南教育决策研究服务系统</h1>
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<p>数据可视化展示平台</p>
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</div>
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<div class="chart-container">
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<div class="tabs">
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<div class="tab active" data-tab="population">人口数据图表</div>
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<div class="tab" data-tab="urbanization">城镇化率图表</div>
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</div>
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<div class="tab-content active" id="population-tab">
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<h2>云南省各州市人口分布</h2>
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<div class="controls">
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<select id="yearSelect">
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<option value="2020">2020年</option>
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<option value="2021">2021年</option>
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<option value="2022">2022年</option>
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<option value="2023">2023年</option>
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<option value="2024" selected>2024年</option>
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</select>
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</div>
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<div id="populationChart" class="chart"></div>
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</div>
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<div class="tab-content" id="urbanization-tab">
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<h2>云南省各州市城镇化率变化趋势</h2>
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<div class="controls">
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</div>
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<div id="urbanizationChart" class="chart"></div>
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</div>
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</div>
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<!-- 引入外部JS -->
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<script src="js/jquery-3.7.1.min.js"></script>
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<script src="js/script.js"></script>
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</body>
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</html>
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