'commit'

Routes/BigScreen.py

@@ -1,10 +1,11 @@
 from fastapi import APIRouter
 import pyecharts
 from pyecharts import options as opts
-from pyecharts.charts import Bar
+from pyecharts.charts import Bar, Line
 from pyecharts.faker import Faker
 from pyecharts.globals import CurrentConfig
 import json
+import os
 
 # 创建 APIRouter 实例
 router = APIRouter(prefix="/bigscreen", tags=["大屏展示"])
@@ -13,9 +14,9 @@ router = APIRouter(prefix="/bigscreen", tags=["大屏展示"])
 CurrentConfig.ONLINE_HOST = "https://gcore.jsdelivr.net/npm/echarts@6.0.0/dist/"
 
 # 定义一个 helloWorld 路由
-@router.get("/hello")
-async def hello_world():
-    return {"message": "helloWorld"}
+@router.get("/")
+async def root():
+    return {"message": "Welcome to YunNan Education World!"}
 
 # 生成图表配置的函数
 def generate_bar_chart_config():
@@ -50,23 +51,65 @@ async def get_bar_chart_config():
     chart_config = generate_bar_chart_config()
     return chart_config
 
-# 定义一个带有参数的路由，可以自定义图表标题
-@router.get("/chart/bar/{title}")
-async def get_custom_bar_chart_config(title: str):
-    """
-    获取自定义标题的柱状图配置
-    """
+# 读取人口数据
+def load_population_data():
+    try:
+        # 获取当前文件所在目录的父目录，然后找到Data文件夹
+        current_dir = os.path.dirname(os.path.abspath(__file__))
+        project_root = os.path.dirname(current_dir)
+        data_path = os.path.join(project_root, "Data", "RenKou.json")
+        
+        with open(data_path, "r", encoding="utf-8") as f:
+            data = json.load(f)
+        return data
+    except Exception as e:
+        print(f"读取人口数据出错: {e}")
+        return []
+
+# 生成人口数据图表配置
+def generate_population_chart_config(year="2024"):
+    # 加载人口数据
+    population_data = load_population_data()
+    
+    # 筛选出州市级数据（排除县级数据）
+    # 正确的格式是 9 位数字，且以 000 结尾但不以 000000 结尾
+    cities = [item for item in population_data if len(item["area_code"]) == 9 and item["area_code"].endswith("000") and not item["area_code"].endswith("000000")]
+    
+    # 提取城市名称和人口数据
+    city_names = [city["area_name"] for city in cities]
+    total_populations = [city["total_population"].get(year, 0) for city in cities]
+    urban_populations = [city["urban_population"].get(year, 0) for city in cities]
+    rural_populations = [city["rural_population"].get(year, 0) for city in cities]
+    
+    # 创建柱状图
     c = (
         Bar()
-        .add_xaxis(Faker.choose())
-        .add_yaxis("商家A", Faker.values())
-        .add_yaxis("商家B", Faker.values())
-        .set_global_opts(title_opts=opts.TitleOpts(title=title))
+        .add_xaxis(city_names)
+        .add_yaxis("总人口", total_populations, stack="stack1")
+        .add_yaxis("城镇人口", urban_populations, stack="stack1")
+        .add_yaxis("农村人口", rural_populations, stack="stack1")
+        .set_global_opts(
+            title_opts=opts.TitleOpts(title=f"云南省各州市人口分布图（{year}年）"),
+            tooltip_opts=opts.TooltipOpts(
+                trigger="axis",
+                axis_pointer_type="shadow"
+            ),
+            legend_opts=opts.LegendOpts(pos_top="5%"),
+            datazoom_opts=[opts.DataZoomOpts()],
+            xaxis_opts=opts.AxisOpts(
+                axislabel_opts=opts.LabelOpts(rotate=45)
+            ),
+            yaxis_opts=opts.AxisOpts(
+                name="人口数量（万人）",
+                name_location="middle",
+                name_gap=40
+            )
+        )
         .set_series_opts(
             label_opts=opts.LabelOpts(is_show=False),
             markline_opts=opts.MarkLineOpts(
-                data=[opts.MarkLineItem(y=50, name="yAxis=50")]
-            ),
+                data=[opts.MarkLineItem(type_="average", name="平均值")]
+            )
         )
     )
     
@@ -77,3 +120,80 @@ async def get_custom_bar_chart_config(title: str):
     options_json = json.loads(options_str)
     
     return options_json
+
+# 生成城镇化率图表配置
+def generate_urbanization_rate_chart_config():
+    # 加载人口数据
+    population_data = load_population_data()
+    
+    # 筛选出州市级数据（排除县级数据）
+    # 正确的格式是 9 位数字，且以 000 结尾但不以 000000 结尾
+    cities = [item for item in population_data if len(item["area_code"]) == 9 and item["area_code"].endswith("000") and not item["area_code"].endswith("000000")]
+    
+    # 提取城市名称和城镇化率数据
+    city_names = [city["area_name"] for city in cities]
+    
+    # 创建折线图
+    line = (
+        Line()
+        .add_xaxis(city_names)
+    )
+    
+    # 添加各年份的城镇化率数据
+    years = ["2020", "2021", "2022", "2023", "2024"]
+    for year in years:
+        urbanization_rates = [city["urbanization_rate"].get(year, 0) for city in cities]
+        line.add_yaxis(f"{year}年", urbanization_rates, 
+                      markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_="max")]))
+    
+    line.set_global_opts(
+        title_opts=opts.TitleOpts(title="云南省各州市城镇化率变化趋势"),
+        tooltip_opts=opts.TooltipOpts(trigger="axis"),
+        legend_opts=opts.LegendOpts(pos_top="5%"),
+        datazoom_opts=[opts.DataZoomOpts()],
+        xaxis_opts=opts.AxisOpts(
+            axislabel_opts=opts.LabelOpts(rotate=45)
+        ),
+        yaxis_opts=opts.AxisOpts(
+            name="城镇化率（%）",
+            name_location="middle",
+            name_gap=40,
+            min_=0,
+            max_=100
+        )
+    )
+    
+    # 获取图表的选项配置
+    options_str = line.dump_options_with_quotes()
+    
+    # 将字符串转换为 JSON 对象
+    options_json = json.loads(options_str)
+    
+    return options_json
+
+# 定义一个返回人口数据图表配置的路由
+@router.get("/population/chart/{year}")
+async def get_population_chart_config(year: str = "2024"):
+    """
+    获取人口数据图表配置
+    """
+    chart_config = generate_population_chart_config(year)
+    return chart_config
+
+# 定义一个返回城镇化率图表配置的路由
+@router.get("/population/urbanization")
+async def get_urbanization_rate_chart_config():
+    """
+    获取城镇化率图表配置
+    """
+    chart_config = generate_urbanization_rate_chart_config()
+    return chart_config
+
+# 定义一个返回人口数据原始数据的路由
+@router.get("/population/data")
+async def get_population_data():
+    """
+    获取人口数据原始数据
+    """
+    population_data = load_population_data()
+    return {"data": population_data}