'commit'

Controller/EducationDataController.py

@@ -0,0 +1,67 @@
+from fastapi import APIRouter, Query
+from Model.EducationDataModel import EducationDataModel
+
+
+# 创建APIRouter实例
+router = APIRouter(prefix="/EducationData", tags=["教育统计数据"])
+
+
+@router.get("/byYear")
+async def get_education_data_by_year(
+    year: int = Query(default=2023, ge=2015, le=2028,
+                      description="年份: 2015-2028范围内的年份")
+):
+    """获取指定年份所有学段的教育数据"""
+    try:
+        # 调用EducationDataModel的方法获取数据
+        data = EducationDataModel.get_education_data_by_year(year)
+        
+        # 返回包含状态和数据的响应
+        return {
+            "code": 200,
+            "message": "success",
+            "data": data
+        }
+    except Exception as e:
+        # 异常处理
+        return {
+            "code": 500,
+            "message": f"获取数据失败: {str(e)}",
+            "data": []
+        }
+
+
+@router.get("/populationByYear")
+async def get_population_data_by_year(
+    year: int = Query(default=2023, ge=2015, le=2028,
+                      description="年份: 2015-2028范围内的年份")
+):
+    """获取指定年份的云南省人口数据"""
+    try:
+        # 调用EducationDataModel的方法获取人口数据
+        data = EducationDataModel.get_population_data_by_year(year)
+        
+        if data:
+            # 返回包含状态和数据的响应
+            return {
+                "code": 200,
+                "message": "success",
+                "data": data
+            }
+        else:
+            # 未找到数据的情况
+            return {
+                "code": 404,
+                "message": f"未找到{year}年的云南省人口数据",
+                "data": None
+            }
+    except Exception as e:
+        # 异常处理
+        return {
+            "code": 500,
+            "message": f"获取数据失败: {str(e)}",
+            "data": None
+        }
+
+
+

Controller/RuYuanZaiYuanCountController.py

@@ -1,21 +1,24 @@
-from fastapi import APIRouter
+from fastapi import APIRouter, Query
 
 from Model.RuYuanZaiYuanCountModel import RuYuanZaiYuanModel
 
 # 创建APIRouter实例
-router = APIRouter(prefix="/RuYuanZaiYuan", tags=["大屏展示"])
-
-# 默认的根路由
-@router.get("/")
-async def root():
-    return {"message": "Welcome to YunNan Education World!"}
-
-@router.get("/school/preschool/chart")
-async def get_preschool_education_chart_config():
-    return RuYuanZaiYuanModel.generate_preschool_education_config()
-
-@router.get("/school/preschool/inschool/chart")
-async def get_preschool_in_school_chart_config():
-    return RuYuanZaiYuanModel.generate_in_school_education_config()
+router = APIRouter(prefix="/RuYuanZaiYuan", tags=["入校、在校人数统计"])
+
+
+@router.get("/school/chart")
+async def get_education_chart_config(
+    education_stage: str = Query(default="preschool", pattern="^(preschool|primary|junior|senior)$", 
+                              description="教育阶段: preschool(学前), primary(小学), junior(初中), senior(高中)")
+):
+    return RuYuanZaiYuanModel.generate_preschool_education_config(education_stage)
+
+@router.get("/school/inschool/chart")
+async def get_in_school_chart_config(
+    education_stage: str = Query(default="preschool", pattern="^(preschool|primary|junior|senior)$", 
+                              description="教育阶段: preschool(学前), primary(小学), junior(初中), senior(高中)")
+):
+    return RuYuanZaiYuanModel.generate_in_school_education_config(education_stage)
+
 
 

Model/EducationDataModel.py

@@ -0,0 +1,350 @@
+import os
+import json
+
+
+class EducationDataModel:
+    # 定义支持的教育阶段映射
+    EDUCATION_STAGES = {
+        'preschool': '学前',
+        'primary': '小学',
+        'junior': '初中',
+        'senior': '高中',
+        'vocational': '中职'
+    }
+
+    # 获取脚本所在目录的绝对路径
+    BASE_DIR = os.path.dirname(os.path.abspath(__file__))
+    # 使用绝对路径定义数据目录和文件
+    DATA_DIR = os.path.join(BASE_DIR, '../Data')
+    SCHOOL_COUNT_FILE = os.path.join(DATA_DIR, 'SchoolCount.json')
+    TEACHER_COUNT_FILE = os.path.join(DATA_DIR, 'TeacherCount.json')
+    ENROLLMENT_COUNT_FILE = os.path.join(DATA_DIR, 'ZaiXiaoShengCount.json')
+    ADMISSION_COUNT_FILE = os.path.join(DATA_DIR, 'ZhaoShengCount.json')
+    POPULATION_FILE = os.path.join(DATA_DIR, 'RenKou.json')  # 新增：人口数据文件路径
+
+    @staticmethod
+    def load_json_file(file_path):
+        """加载JSON文件数据"""
+        try:
+            with open(file_path, 'r', encoding='utf-8') as f:
+                return json.load(f)
+        except Exception as e:
+            print(f"加载文件 {file_path} 失败: {e}")
+            return None
+
+    @staticmethod
+    def get_province_data(data):
+        """从数据中提取云南省的数据"""
+        if not data or not isinstance(data, list):
+            return None
+        
+        # 查找云南省的数据
+        for item in data:
+            if item.get('area_name') == '云南省':
+                return item
+        
+        print("未找到云南省的数据")
+        return None
+
+    @staticmethod
+    def get_school_count_by_year_and_stage(year, stage):
+        """获取指定年份和学段的学校总数"""
+        school_data = EducationDataModel.load_json_file(EducationDataModel.SCHOOL_COUNT_FILE)
+        province_data = EducationDataModel.get_province_data(school_data)
+        
+        if not province_data:
+            return 0
+        
+        # 根据学段获取对应的学校数据字段名
+        stage_field_mapping = {
+            'preschool': 'preschool_schools',
+            'primary': 'primary_schools',
+            'junior': 'junior_schools',
+            'senior': 'senior_schools',
+            'vocational': 'vocational_schools'
+        }
+        
+        field_name = stage_field_mapping.get(stage)
+        if not field_name or field_name not in province_data:
+            print(f"学段 {stage} 对应的学校数据字段不存在")
+            return 0
+        
+        year_data = province_data[field_name].get(str(year))
+        if not year_data:
+            print(f"年份 {year} 的学校数据不存在")
+            return 0
+        
+        # 计算学校总数 - 处理vocational_schools的特殊格式
+        try:
+            # 对于vocational学段，数据可能是直接的数值而不是字典
+            if stage == 'vocational' and isinstance(year_data, int):
+                return year_data
+            # 对于其他学段或正常字典格式
+            elif isinstance(year_data, dict):
+                if 'urban' in year_data and 'town' in year_data and 'rural' in year_data:
+                    total_schools = year_data.get('urban', 0) + year_data.get('town', 0) + year_data.get('rural', 0)
+                    return total_schools
+                elif 'total' in year_data:
+                    # 如果没有分区数据但有total字段，使用total
+                    return year_data.get('total', 0)
+                else:
+                    print(f"年份 {year} 的学校数据缺少必要的字段")
+                    return 0
+            else:
+                print(f"年份 {year} 的学校数据格式不正确")
+                return 0
+        except Exception as e:
+            print(f"计算学校总数时出错: {e}")
+            return 0
+
+    @staticmethod
+    def get_teacher_count_by_year_and_stage(year, stage):
+        """获取指定年份和学段的教职工总数"""
+        teacher_data = EducationDataModel.load_json_file(EducationDataModel.TEACHER_COUNT_FILE)
+        province_data = EducationDataModel.get_province_data(teacher_data)
+        
+        if not province_data:
+            return 0
+        
+        # 根据学段获取对应的教职工数据字段名
+        stage_field_mapping = {
+            'preschool': 'preschool_teachers',
+            'primary': 'primary_teachers',
+            'junior': 'junior_teachers',
+            'senior': 'senior_teachers',
+            'vocational': 'vocational_teachers'
+        }
+        
+        field_name = stage_field_mapping.get(stage)
+        if not field_name or field_name not in province_data:
+            print(f"学段 {stage} 对应的教职工数据字段不存在")
+            return 0
+        
+        year_data = province_data[field_name].get(str(year))
+        if not year_data or not isinstance(year_data, dict):
+            print(f"年份 {year} 的教职工数据不存在或格式不正确")
+            return 0
+        
+        # 优先使用total_staff，如果为0或不存在，则返回教师总数
+        try:
+            total_staff = year_data.get('total_staff', 0)
+            if total_staff == 0:
+                total_staff = year_data.get('total_teacher', 0)
+            return total_staff
+        except Exception as e:
+            print(f"获取教职工总数时出错: {e}")
+            return 0
+
+    @staticmethod
+    def get_enrollment_count_by_year_and_stage(year, stage):
+        """获取指定年份和学段的在校生总数"""
+        enrollment_data = EducationDataModel.load_json_file(EducationDataModel.ENROLLMENT_COUNT_FILE)
+        province_data = EducationDataModel.get_province_data(enrollment_data)
+        
+        if not province_data or 'student_data' not in province_data:
+            print("未找到学生数据")
+            return 0
+        
+        stage_data = province_data['student_data'].get(stage)
+        if not stage_data:
+            print(f"学段 {stage} 的学生数据不存在")
+            return 0
+        
+        year_data = stage_data.get(str(year))
+        if not year_data or not isinstance(year_data, dict):
+            print(f"年份 {year} 的学生数据不存在或格式不正确")
+            return 0
+        
+        # 返回在校生总数 - 处理vocational数据只有total字段的情况
+        try:
+            if 'urban' in year_data and 'town' in year_data and 'rural' in year_data:
+                # 通过累加城区、镇区、乡村数据计算总数
+                total_enrollment = year_data.get('urban', 0) + year_data.get('town', 0) + year_data.get('rural', 0)
+                return total_enrollment
+            elif 'total' in year_data and stage == 'vocational':
+                # 对于vocational学段，如果只有total字段，使用total
+                return year_data.get('total', 0)
+            else:
+                # 对于其他学段，如果没有分区数据，直接报错
+                print(f"年份 {year} 的学生数据缺少城区、镇区或乡村字段")
+                return 0
+        except Exception as e:
+            print(f"获取在校生总数时出错: {e}")
+            return 0
+
+    @staticmethod
+    def get_admission_count_by_year_and_stage(year, stage):
+        """获取指定年份和学段的招生总数"""
+        admission_data = EducationDataModel.load_json_file(EducationDataModel.ADMISSION_COUNT_FILE)
+        province_data = EducationDataModel.get_province_data(admission_data)
+        
+        if not province_data or 'education_data' not in province_data:
+            print("未找到教育数据")
+            return 0
+        
+        stage_data = province_data['education_data'].get(stage)
+        if not stage_data:
+            print(f"学段 {stage} 的教育数据不存在")
+            return 0
+        
+        year_data = stage_data.get(str(year))
+        if not year_data or not isinstance(year_data, dict):
+            print(f"年份 {year} 的教育数据不存在或格式不正确")
+            return 0
+        
+        # 返回招生总数 - 处理vocational数据只有total字段的情况
+        try:
+            if 'urban' in year_data and 'town' in year_data and 'rural' in year_data:
+                # 通过累加城区、镇区、乡村数据计算总数
+                total_admission = year_data.get('urban', 0) + year_data.get('town', 0) + year_data.get('rural', 0)
+                return total_admission
+            elif 'total' in year_data and stage == 'vocational':
+                # 对于vocational学段，如果只有total字段，使用total
+                return year_data.get('total', 0)
+            else:
+                # 对于其他学段，如果没有分区数据，直接报错
+                print(f"年份 {year} 的教育数据缺少城区、镇区或乡村字段")
+                return 0
+        except Exception as e:
+            print(f"获取招生总数时出错: {e}")
+            return 0
+
+    @staticmethod
+    def get_education_data_by_year(year):
+        """获取指定年份所有学段的教育数据"""
+        result = []
+        
+        for stage_code, stage_name in EducationDataModel.EDUCATION_STAGES.items():
+            # 获取各类数据（增加异常处理）
+            try:
+                school_count = EducationDataModel.get_school_count_by_year_and_stage(year, stage_code)
+                teacher_count = EducationDataModel.get_teacher_count_by_year_and_stage(year, stage_code)
+                enrollment_count = EducationDataModel.get_enrollment_count_by_year_and_stage(year, stage_code)
+                admission_count = EducationDataModel.get_admission_count_by_year_and_stage(year, stage_code)
+                
+                # 转换为万人单位
+                teacher_count_10k = round(teacher_count / 10000, 2) if teacher_count else 0
+                enrollment_count_10k = round(enrollment_count / 10000, 2) if enrollment_count else 0
+                admission_count_10k = round(admission_count / 10000, 2) if admission_count else 0
+                
+                # 添加到结果列表
+                result.append({
+                    'education_stage': stage_name,
+                    'school_count': school_count,
+                    'teacher_count_10k': teacher_count_10k,
+                    'enrollment_count_10k': enrollment_count_10k,
+                    'admission_count_10k': admission_count_10k
+                })
+            except Exception as e:
+                print(f"处理学段 {stage_name} 时出错: {e}")
+                # 出错时添加一个默认的空数据条目
+                result.append({
+                    'education_stage': stage_name,
+                    'school_count': 0,
+                    'teacher_count_10k': 0,
+                    'enrollment_count_10k': 0,
+                    'admission_count_10k': 0
+                })
+        
+        return result
+
+    # 新增：人口数据相关方法
+    @staticmethod
+    def get_population_data_by_year(year):
+        """获取指定年份的云南省人口数据"""
+        # 加载人口数据文件
+        population_data = EducationDataModel.load_json_file(EducationDataModel.POPULATION_FILE)
+        # 获取云南省数据
+        yunnan_data = EducationDataModel.get_province_data(population_data)
+        
+        if not yunnan_data:
+            print(f"未获取到云南省{year}年的人口数据")
+            return None
+        
+        year_str = str(year)
+        result = {
+            'year': year,
+            'total_population': yunnan_data.get('total_population', {}).get(year_str, 0),  # 万人
+            'birth_population': yunnan_data.get('birth_population', {}).get(year_str, 0),  # 原数据单位为个
+            'urban_population': yunnan_data.get('urban_population', {}).get(year_str, 0),  # 万人
+            'rural_population': yunnan_data.get('rural_population', {}).get(year_str, 0),  # 万人
+            'urbanization_rate': yunnan_data.get('urbanization_rate', {}).get(year_str, 0)  # %
+        }
+        
+        # 将新生人口转换为万人（如果是整数）
+        if isinstance(result['birth_population'], int):
+            result['birth_population'] = round(result['birth_population'] / 10000, 1)
+        
+        return result
+
+    @staticmethod
+    def print_population_data(population_data):
+        """打印人口数据"""
+        if not population_data:
+            print("没有可打印的人口数据")
+            return
+        
+        year = population_data.get('year', '未知')
+        print(f"云南省 {year}年人口概览")
+        print("-------------------")
+        print(f"总人口 {population_data.get('total_population', 0):,} 万人")
+        print(f"新生人口 {population_data.get('birth_population', 0)} 万人")
+        print(f"城镇人口 {population_data.get('urban_population', 0):,} 万人")
+        print(f"乡村人口 {population_data.get('rural_population', 0):,} 万人")
+        print(f"城镇化率 {population_data.get('urbanization_rate', 0):.2f} %")
+        
+        # 验证数据一致性
+        total = population_data.get('total_population', 0)
+        urban_rural_sum = population_data.get('urban_population', 0) + population_data.get('rural_population', 0)
+        if abs(total - urban_rural_sum) > 0.01:
+            print("\n注意：总人口与城镇人口+乡村人口存在差异")
+            print(f"差异值: {abs(total - urban_rural_sum):.2f} 万人")
+
+    @staticmethod
+    def print_education_data(data, year):
+        """打印教育数据"""
+        print(f"\n===== {year}年云南省各学段教育数据统计（单位：学校总数-个，其余-万人）=====")
+        print(f"{'学段':<8}{'学校总数':<10}{'教职工总数':<12}{'在校生总数':<12}{'招生总数':<12}")
+        print("=" * 60)
+        
+        for item in data:
+            print(f"{item['education_stage']:<8}{item['school_count']:<10}{item['teacher_count_10k']:<12.2f}{item['enrollment_count_10k']:<12.2f}{item['admission_count_10k']:<12.2f}")
+
+    @staticmethod
+    def main(year=2023):
+        """主函数"""
+        try:
+            print(f"正在获取 {year} 年数据...")
+            print(f"数据目录: {EducationDataModel.DATA_DIR}")
+            
+            # 检查数据文件是否存在
+            for file_path in [EducationDataModel.SCHOOL_COUNT_FILE, 
+                             EducationDataModel.TEACHER_COUNT_FILE, 
+                             EducationDataModel.ENROLLMENT_COUNT_FILE, 
+                             EducationDataModel.ADMISSION_COUNT_FILE, 
+                             EducationDataModel.POPULATION_FILE]:  # 新增：检查人口数据文件
+                if os.path.exists(file_path):
+                    print(f"找到数据文件: {file_path}")
+                else:
+                    print(f"警告：数据文件不存在: {file_path}")
+            
+            # 获取并打印教育数据
+            education_data = EducationDataModel.get_education_data_by_year(year)
+            if education_data:
+                EducationDataModel.print_education_data(education_data, year)
+            else:
+                print("未获取到任何教育数据")
+                
+            # 新增：获取并打印人口数据
+            print("\n" + "=" * 50)
+            population_data = EducationDataModel.get_population_data_by_year(year)
+            EducationDataModel.print_population_data(population_data)
+                
+        except Exception as e:
+            print(f"获取数据时发生错误: {e}")
+            import traceback
+            traceback.print_exc()
+
+
+if __name__ == "__main__":
+    EducationDataModel.main()

Model/RuYuanZaiYuanCountModel.py

@@ -1,14 +1,15 @@
 import json
-from pyecharts import options as opts
-from pyecharts.charts import Bar, Line
-from pyecharts.globals import CurrentConfig
-
-from Config.Config import ONLINE_HOST
-
-CurrentConfig.ONLINE_HOST = ONLINE_HOST
 
 
 class RuYuanZaiYuanModel:
+    # 定义支持的教育阶段映射
+    EDUCATION_STAGES = {
+        'preschool': '学前',
+        'primary': '小学',
+        'junior': '初中',
+        'senior': '高中'
+    }
+
     @staticmethod
     def load_student_data():
         try:
@@ -26,52 +27,70 @@ class RuYuanZaiYuanModel:
             return [], []
 
     @staticmethod
-    def generate_preschool_education_config():
-        # 获取学前教育相关数据
-        # enrollment_data, in_school_data = RuYuanZaiYuanModel.load_student_data()
-        #
-        # # 提取云南省级数据
-        # yunnan_enroll = next((item for item in enrollment_data if item["area_name"] == "云南省"), None)
-        #
-        # if not yunnan_enroll:
-        #     return {}
-        #
-        # # 提取年份数据(2015-2024)
-        # years = [str(year) for year in range(2015, 2025)]
-        #
-        # # 构建学前教育数据
-        # urban_data = []  # 城区数据
-        # town_data = []  # 镇区数据
-        # rural_data = []  # 乡村数据
-        # total_enroll = []  # 总入园数
-        #
-        # for year in years:
-        #     enroll_data = yunnan_enroll["education_data"]["preschool"].get(year, {})
-        #     urban_data.append(enroll_data.get("urban", 0) / 10000)  # 转换为万人
-        #     town_data.append(enroll_data.get("town", 0) / 10000)  # 转换为万人
-        #     rural_data.append(enroll_data.get("rural", 0) / 10000)  # 转换为万人
-        #     # 计算总和作为总入园数，而非使用文件中的total字段
-        #     calculated_total = enroll_data.get("urban", 0) + enroll_data.get("town", 0) + enroll_data.get("rural", 0)
-        #     total_enroll.append(calculated_total / 10000)  # 转换为万人
+    def generate_preschool_education_config(education_stage='preschool'):
+        # 验证教育阶段参数
+        if education_stage not in RuYuanZaiYuanModel.EDUCATION_STAGES:
+            education_stage = 'preschool'  # 默认使用学前
 
-        xAxis = ["2019", "2020", "2021", "2022", "2023", "2024", "2025", "2026"]
-        series_data_1 = [2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6]
-        series_data_2 = [2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6]
-        series_data_3 = [2.4, 5.2, 8.0, 25.4, 27.7, 73.7, 155.6]
-        series_data_4 = [2.0, 2.2, 3.3, 4.5, 6.3, 10.2, 20.3]
-        line_data = [2.0, 2.2, 3.3, 4.5, 6.3, 10.2, 20.3]
-        data = {"xAxis_data": xAxis,
-                "series_data_1": series_data_1,
-                "series_data_2": series_data_2,
-                "series_data_3": series_data_3,
-                "series_data_4": series_data_4,
-                "line_data": line_data
-                }
+        # 获取学前教育相关数据
+        enrollment_data, in_school_data = RuYuanZaiYuanModel.load_student_data()
+        # 提取云南省级数据
+        yunnan_enroll = next((item for item in enrollment_data if item["area_name"] == "云南省"), None)
+
+        if not yunnan_enroll:
+            return {}
+
+        # # 构建学前教育数据
+        urban_data = []  # 城区数据
+        town_data = []  # 镇区数据
+        rural_data = []  # 乡村数据
+        total_enroll = []  # 总人数
+
+        # 提取年份数据(2015-2024)
+        years = [str(year) for year in range(2015, 2025)]
+
+        for year in years:
+            # 使用传入的教育阶段参数
+            enroll_data = yunnan_enroll["education_data"].get(education_stage, {}).get(year, {})
+            urban_data.append(enroll_data.get("urban", 0) / 10000)  # 转换为万人
+            town_data.append(enroll_data.get("town", 0) / 10000)  # 转换为万人
+            rural_data.append(enroll_data.get("rural", 0) / 10000)  # 转换为万人
+            # 计算总和作为总人数
+            calculated_total = enroll_data.get("urban", 0) + enroll_data.get("town", 0) + enroll_data.get("rural", 0)
+            total_enroll.append(calculated_total / 10000)  # 转换为万人
+
+        # 添加2022年基数的粉色折线
+        base_year = "2022"
+        # 找到2022年在years中的索引位置
+        base_index = years.index(base_year) if base_year in years else 0
+        # 获取2022年的总人数作为基数
+        base_value = total_enroll[base_index] if base_index < len(total_enroll) else 0
+        # 创建2022年基数折线数据（2022-2024年）
+        base_2022_line = []
+        for i, year in enumerate(years):
+            # 只在2022年及之后显示基数线
+            if i >= base_index:
+                base_2022_line.append(base_value)
+            else:
+                base_2022_line.append(None)  # 2022年之前不显示
+        data = {
+            "xAxis_data": years,
+            "series_data_0": urban_data,  # 城区
+            "series_data_1": town_data,  # 镇区
+            "series_data_2": rural_data,  # 乡村
+            "series_data_3": total_enroll,  # 总人数
+            "series_data_4": base_2022_line,  # 2022年基数
+            "education_stage": RuYuanZaiYuanModel.EDUCATION_STAGES.get(education_stage, '学前')  # 添加教育阶段名称
+        }
         return data
 
     @staticmethod
-    def generate_in_school_education_config():
-        # 获取学前教育相关数据
+    def generate_in_school_education_config(education_stage='preschool'):
+        # 验证教育阶段参数
+        if education_stage not in RuYuanZaiYuanModel.EDUCATION_STAGES:
+            education_stage = 'preschool'  # 默认使用学前
+
+        # 获取在校生相关数据
         enrollment_data, in_school_data = RuYuanZaiYuanModel.load_student_data()
 
         # 提取云南省级数据
@@ -83,15 +102,15 @@ class RuYuanZaiYuanModel:
         # 提取年份数据(2015-2024)
         years = [str(year) for year in range(2015, 2025)]
 
-        # 构建学前教育数据
+        # 构建数据
         urban_data = []  # 城区数据
         town_data = []  # 镇区数据
         rural_data = []  # 乡村数据
-        total_in_school = []  # 总在园数
+        total_in_school = []  # 总人数
 
         for year in years:
-            # 将education_data改为student_data
-            in_school_year_data = yunnan_in_school["student_data"]["preschool"].get(year, {})
+            # 使用传入的教育阶段参数
+            in_school_year_data = yunnan_in_school["student_data"].get(education_stage, {}).get(year, {})
 
             # 先获取原始数据
             urban_val = in_school_year_data.get("urban", 0)
@@ -111,7 +130,7 @@ class RuYuanZaiYuanModel:
         base_year = "2022"
         # 找到2022年在years中的索引位置
         base_index = years.index(base_year) if base_year in years else 0
-        # 获取2022年的总在园数作为基数
+        # 获取2022年的总人数作为基数
         base_value = total_in_school[base_index] if base_index < len(total_in_school) else 0
         # 创建2022年基数折线数据（2022-2024年）
         base_2022_line = []
@@ -122,137 +141,14 @@ class RuYuanZaiYuanModel:
             else:
                 base_2022_line.append(None)  # 2022年之前不显示
 
-        # 构建ECharts配置
-        option = {
-            "tooltip": {
-                "trigger": "axis",
-                "axisPointer": {
-                    "type": "cross",
-                    "crossStyle": {"color": "#999"}
-                },
-                "textStyle": {"color": "#333"},
-                "backgroundColor": "rgba(255, 255, 255, 0.8)",
-                "borderColor": "rgba(0, 0, 0, 0.2)",
-                "borderWidth": 1
-            },
-            "legend": {
-                "data": ["城区", "镇区", "乡村", "总在园数", "2022年基数(万人)"],
-                "top": 30,
-                "textStyle": {"color": "#333"},
-                "icon": "roundRect",
-                "itemWidth": 12,
-                "itemHeight": 12
-            },
-            "xAxis": [
-                {
-                    "type": "category",
-                    "data": years,
-                    "axisPointer": {"type": "shadow"},
-                    "axisLabel": {"color": "#333"},
-                    "axisLine": {"lineStyle": {"color": "#333"}}
-                }
-            ],
-            "yAxis": [
-                {
-                    "type": "value",
-                    "name": "人数",
-                    "min": 0,
-                    "max": 200,  # 将左侧Y轴最大值从100修改为200万
-                    "interval": 40,  # 调整间隔为40万，确保坐标轴上有5个主要刻度(0,40,80,120,160,200)
-                    "axisLabel": {
-                        "formatter": "{value} 万人",
-                        "color": "#333"
-                    },
-                    "axisLine": {"lineStyle": {"color": "#333"}},
-                    "splitLine": {"lineStyle": {"color": "rgba(0,0,0,0.1)"}}
-                },
-                {
-                    "type": "value",
-                    "name": "总在园数",
-                    "min": 0,
-                    "max": 320,  # 将右侧Y轴最大值从160扩大一倍到320万
-                    "interval": 60,  # 调整间隔为60万
-                    "position": "right",
-                    "nameLocation": "end",
-                    "nameGap": 30,
-                    "axisLabel": {
-                        "formatter": "{value} 万人",
-                        "color": "#00a859"  # 改为绿色
-                    },
-                    "axisLine": {"show": True, "lineStyle": {"color": "#00a859"}},  # 改为绿色
-                    "axisTick": {"show": True},
-                    "splitLine": {"show": False}
-                }
-            ],
-            "series": [
-                {
-                    "name": "城区",
-                    "type": "bar",
-                    "data": urban_data,
-                    "itemStyle": {
-                        "color": "#5470c6",
-                        "borderRadius": [6, 6, 0, 0]
-                    },
-                    "barWidth": "25%",
-                    "barGap": "-10%"
-                },
-                {
-                    "name": "镇区",
-                    "type": "bar",
-                    "data": town_data,
-                    "itemStyle": {
-                        "color": "#91cc75",
-                        "borderRadius": [6, 6, 0, 0]
-                    },
-                    "barWidth": "25%",
-                    "barGap": "-10%"
-                },
-                {
-                    "name": "乡村",
-                    "type": "bar",
-                    "data": rural_data,
-                    "itemStyle": {
-                        "color": "#fac858",
-                        "borderRadius": [6, 6, 0, 0]
-                    },
-                    "barWidth": "25%",
-                    "barGap": "-10%"
-                },
-                {
-                    "name": "总在园数",
-                    "type": "line",
-                    "yAxisIndex": 1,
-                    "data": total_in_school,
-                    "lineStyle": {"color": "#00a859", "width": 3},  # 改为绿色
-                    "symbol": "circle",
-                    "symbolSize": 8,
-                    "itemStyle": {"color": "#00a859"},  # 改为绿色
-                    "emphasis": {
-                        "focus": "series"
-                    },
-                    "z": 10  # 确保折线图显示在最上层
-                },
-                # 添加2022年基数的粉色折线
-                {
-                    "name": "2022年基数(万人)",
-                    "type": "line",
-                    "yAxisIndex": 1,
-                    "data": base_2022_line,
-                    "lineStyle": {"color": "#ff9e9e", "width": 2, "type": "solid"},
-                    "symbol": "circle",
-                    "symbolSize": 6,
-                    "itemStyle": {"color": "#ff9e9e"},
-                    "emphasis": {
-                        "focus": "series"
-                    },
-                    "z": 5  # 确保折线图显示在柱状图之上，但在总在园数折线之下
-                }
-            ],
-            "grid": {
-                "left": "3%",
-                "right": "15%",  # 稍微增加右侧边距，确保Y轴标签不被截断
-                "bottom": "3%",
-                "containLabel": True
-            }
+        data = {
+            "xAxis_data": years,
+            "series_data_0": urban_data,
+            "series_data_1": town_data,
+            "series_data_2": rural_data,
+            "series_data_3": total_in_school,
+            "series_data_4": base_2022_line,
+            "education_stage": RuYuanZaiYuanModel.EDUCATION_STAGES.get(education_stage, '学前')  # 添加教育阶段名称
         }
-        return option
+
+        return data

Start.py

@@ -4,7 +4,7 @@ from fastapi import FastAPI
 from fastapi.staticfiles import StaticFiles
 import uvicorn
 from Controller.RuYuanZaiYuanCountController import router as ruyuanZaiYuan_router
-
+from Controller.EducationDataController import router as educationData_router
 # 创建 FastAPI 应用实例
 app = FastAPI(title="云南教育决策研究服务系统", description="云南省教育数据分析和可视化平台")
 
@@ -14,6 +14,7 @@ app.mount("/static", StaticFiles(directory="static"), name="static")
 # 包含大屏展示路由
 app.include_router(ruyuanZaiYuan_router)
 
+app.include_router(educationData_router)
 # 主程序入口
 if __name__ == "__main__":
     # 启动 FastAPI 应用，监听 8100 端口

Test/population_statistics.py

@@ -0,0 +1,274 @@
+import json
+import os
+from datetime import datetime
+
+class PopulationStatistics:
+    def __init__(self, data_file):
+        """初始化人口统计类，加载数据文件"""
+        self.data_file = data_file
+        self.data = self.load_data()
+        self.years = list(range(2015, 2025))  # 2015-2024年
+        
+    def load_data(self):
+        """加载人口数据JSON文件"""
+        try:
+            with open(self.data_file, 'r', encoding='utf-8') as f:
+                return json.load(f)
+        except FileNotFoundError:
+            print(f"错误：找不到数据文件 {self.data_file}")
+            return []
+        except json.JSONDecodeError:
+            print(f"错误：数据文件 {self.data_file} 格式不正确")
+            return []
+    
+    def get_province_data(self):
+        """获取云南省全省数据"""
+        for item in self.data:
+            if item['area_name'] == '云南省' and item['area_code'] == '530000000':
+                return item
+        return None
+    
+    def get_city_data(self, city_name):
+        """获取指定城市的数据"""
+        for item in self.data:
+            if item['area_name'] == city_name:
+                return item
+        return None
+    
+    def get_all_cities(self):
+        """获取所有地市级城市列表"""
+        cities = []
+        # 地市级城市的area_code格式为53XX00000
+        for item in self.data:
+            if len(item['area_code']) == 9 and item['area_code'][-5:] == '00000' and item['area_code'] != '530000000':
+                cities.append(item)
+        return cities
+    
+    def calculate_total_population_by_year(self, level='province'):
+        """按年份计算总人口
+        level: 'province'(全省), 'city'(昆明市), 'all_cities'(所有地级市)
+        """
+        result = {}
+        
+        if level == 'province':
+            province_data = self.get_province_data()
+            if province_data:
+                result = province_data['total_population']
+        
+        elif level == 'city':
+            city_data = self.get_city_data('昆明市')
+            if city_data:
+                result = city_data['total_population']
+        
+        elif level == 'all_cities':
+            cities = self.get_all_cities()
+            for year in self.years:
+                total = 0
+                for city in cities:
+                    if str(year) in city['total_population']:
+                        total += city['total_population'][str(year)]
+                result[str(year)] = total
+        
+        return result
+    
+    def calculate_urbanization_trend(self, area_name='云南省'):
+        """计算指定地区的城镇化率趋势"""
+        area_data = None
+        if area_name == '云南省':
+            area_data = self.get_province_data()
+        else:
+            area_data = self.get_city_data(area_name)
+            
+        if area_data and 'urbanization_rate' in area_data:
+            return area_data['urbanization_rate']
+        return {}
+    
+    def compare_city_populations(self, year=2023):
+        """比较指定年份各城市的人口数量"""
+        cities = self.get_all_cities()
+        result = {}
+        
+        for city in cities:
+            if str(year) in city['total_population']:
+                result[city['area_name']] = city['total_population'][str(year)]
+        
+        # 按人口数量排序
+        return dict(sorted(result.items(), key=lambda x: x[1], reverse=True))
+    
+    def calculate_population_growth(self, area_name='云南省', start_year=2020, end_year=2023):
+        """计算指定地区在指定时间段内的人口增长率"""
+        area_data = None
+        if area_name == '云南省':
+            area_data = self.get_province_data()
+        else:
+            area_data = self.get_city_data(area_name)
+        
+        if not area_data:
+            return None
+        
+        start_pop = area_data['total_population'].get(str(start_year), 0)
+        end_pop = area_data['total_population'].get(str(end_year), 0)
+        
+        if start_pop == 0:
+            return None
+        
+        growth_rate = ((end_pop - start_pop) / start_pop) * 100
+        return growth_rate
+    
+    def analyze_birth_rate(self, area_name='云南省'):
+        """分析指定地区的出生率趋势"""
+        area_data = None
+        if area_name == '云南省':
+            area_data = self.get_province_data()
+        else:
+            area_data = self.get_city_data(area_name)
+        
+        if not area_data or 'birth_population' not in area_data or 'total_population' not in area_data:
+            return {}
+        
+        birth_rates = {}
+        for year in self.years:
+            year_str = str(year)
+            if year_str in area_data['birth_population'] and year_str in area_data['total_population']:
+                birth_pop = area_data['birth_population'][year_str]
+                total_pop = area_data['total_population'][year_str]
+                
+                # 注意：总人口单位是万人，出生人口单位是个，需要统一单位
+                if total_pop > 0 and birth_pop > 0:
+                    birth_rate = (birth_pop / (total_pop * 10000)) * 1000  # 千分比
+                    birth_rates[year] = birth_rate
+        
+        return birth_rates
+    
+    def save_results_to_file(self, results, filename):
+        """将统计结果保存到文件"""
+        # 创建结果目录
+        result_dir = os.path.join(os.path.dirname(self.data_file), '../Results')
+        os.makedirs(result_dir, exist_ok=True)
+        
+        # 生成带时间戳的文件名
+        timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
+        full_filename = f"{filename}_{timestamp}.txt"
+        full_path = os.path.join(result_dir, full_filename)
+        
+        # 保存结果
+        with open(full_path, 'w', encoding='utf-8') as f:
+            f.write(f"人口统计结果 - 生成时间：{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n")
+            for key, value in results.items():
+                if isinstance(value, dict):
+                    f.write(f"{key}:\n")
+                    for k, v in value.items():
+                        f.write(f"  {k}: {v}\n")
+                else:
+                    f.write(f"{key}: {value}\n")
+        
+        print(f"统计结果已保存至：{full_path}")
+        return full_path
+
+# 主函数演示如何使用这个类
+if __name__ == "__main__":
+    # 数据文件路径
+    data_file = os.path.join(os.path.dirname(__file__), '../Data/RenKou.json')
+    
+    # 创建统计类实例
+    stats = PopulationStatistics(data_file)
+    
+    # 检查数据是否成功加载
+    if not stats.data:
+        print("无法加载数据，程序退出。")
+        exit(1)
+    
+    # 主菜单
+    print("云南省人口数据统计分析工具")
+    print("========================")
+    
+    while True:
+        print("\n请选择要执行的统计分析：")
+        print("1. 查看云南省历年总人口统计")
+        print("2. 查看昆明市历年总人口统计")
+        print("3. 分析云南省城镇化率趋势")
+        print("4. 分析昆明市城镇化率趋势")
+        print("5. 比较2023年各城市人口数量")
+        print("6. 计算云南省2020-2023年人口增长率")
+        print("7. 分析云南省出生率趋势")
+        print("8. 分析昆明市出生率趋势")
+        print("9. 导出所有统计结果")
+        print("0. 退出程序")
+        
+        choice = input("请输入您的选择（0-9）：")
+        
+        if choice == '0':
+            print("感谢使用，再见！")
+            break
+        
+        elif choice == '1':
+            result = stats.calculate_total_population_by_year('province')
+            print("\n云南省历年总人口统计（单位：万人）：")
+            for year, population in result.items():
+                print(f"{year}年: {population}")
+        
+        elif choice == '2':
+            result = stats.calculate_total_population_by_year('city')
+            print("\n昆明市历年总人口统计（单位：万人）：")
+            for year, population in result.items():
+                print(f"{year}年: {population}")
+        
+        elif choice == '3':
+            result = stats.calculate_urbanization_trend('云南省')
+            print("\n云南省历年城镇化率（单位：%）：")
+            for year, rate in result.items():
+                print(f"{year}年: {rate}")
+        
+        elif choice == '4':
+            result = stats.calculate_urbanization_trend('昆明市')
+            print("\n昆明市历年城镇化率（单位：%）：")
+            for year, rate in result.items():
+                print(f"{year}年: {rate}")
+        
+        elif choice == '5':
+            result = stats.compare_city_populations(2023)
+            print("\n2023年各城市人口数量排名（单位：万人）：")
+            for i, (city, population) in enumerate(result.items(), 1):
+                print(f"{i}. {city}: {population}")
+        
+        elif choice == '6':
+            rate = stats.calculate_population_growth('云南省', 2020, 2023)
+            if rate is not None:
+                print(f"\n云南省2020-2023年人口增长率: {rate:.2f}%")
+            else:
+                print("\n无法计算人口增长率")
+        
+        elif choice == '7':
+            result = stats.analyze_birth_rate('云南省')
+            print("\n云南省历年出生率（单位：‰）：")
+            for year, rate in result.items():
+                print(f"{year}年: {rate:.2f}")
+        
+        elif choice == '8':
+            result = stats.analyze_birth_rate('昆明市')
+            print("\n昆明市历年出生率（单位：‰）：")
+            for year, rate in result.items():
+                print(f"{year}年: {rate:.2f}")
+        
+        elif choice == '9':
+            # 收集所有统计结果
+            all_results = {
+                "云南省历年总人口统计（万人）": stats.calculate_total_population_by_year('province'),
+                "昆明市历年总人口统计（万人）": stats.calculate_total_population_by_year('city'),
+                "云南省历年城镇化率（%）": stats.calculate_urbanization_trend('云南省'),
+                "昆明市历年城镇化率（%）": stats.calculate_urbanization_trend('昆明市'),
+                "2023年各城市人口数量排名（万人）": stats.compare_city_populations(2023),
+                "云南省2020-2023年人口增长率（%）": stats.calculate_population_growth('云南省', 2020, 2023),
+                "云南省历年出生率（‰）": stats.analyze_birth_rate('云南省'),
+                "昆明市历年出生率（‰）": stats.analyze_birth_rate('昆明市')
+            }
+            
+            # 保存结果到文件
+            file_path = stats.save_results_to_file(all_results, "population_statistics")
+            print(f"\n所有统计结果已保存至文件：{file_path}")
+        
+        else:
+            print("\n无效的选择，请重新输入。")
+
+        # 等待用户按Enter键继续
+        input("\n按Enter键继续...")

Test/read_population_data.py

@@ -0,0 +1,52 @@
+import json
+import os
+
+# 获取脚本所在目录
+script_dir = os.path.dirname(os.path.abspath(__file__))
+# 构建数据文件的绝对路径
+file_path = os.path.join(script_dir, '../Data/RenKou.json')
+
+# 读取JSON数据
+with open(file_path, 'r', encoding='utf-8') as f:
+    population_data = json.load(f)
+
+# 查找云南省的数据
+for area in population_data:
+    if area.get('area_name') == '云南省':
+        yunnan_data = area
+        break
+
+# 提取2023年的人口数据
+year = '2023'
+
+# 总人口（万人）
+total_population = yunnan_data.get('total_population', {}).get(year, 0)
+
+# 新生人口（万人，注意原数据是整数，需要转换为万人）
+birth_population = yunnan_data.get('birth_population', {}).get(year, 0)
+# 转换为万人（如果是整数）
+if isinstance(birth_population, int):
+    birth_population = round(birth_population / 10000, 1)
+
+# 城镇人口（万人）
+urban_population = yunnan_data.get('urban_population', {}).get(year, 0)
+
+# 乡村人口（万人）
+rural_population = yunnan_data.get('rural_population', {}).get(year, 0)
+
+# 城镇化率（%）
+urbanization_rate = yunnan_data.get('urbanization_rate', {}).get(year, 0)
+
+# 打印结果
+print("云南省 2023年人口概览")
+print("-------------------")
+print(f"总人口 {total_population:,} 万人")
+print(f"新生人口 {birth_population} 万人")
+print(f"城镇人口 {urban_population:,} 万人")
+print(f"乡村人口 {rural_population:,} 万人")
+print(f"城镇化率 {urbanization_rate:.2f} %")
+
+# 验证数据一致性
+if abs(total_population - (urban_population + rural_population)) > 0.01:
+    print("\n注意：总人口与城镇人口+乡村人口存在差异")
+    print(f"差异值: {abs(total_population - (urban_population + rural_population)):.2f} 万人")

Test/test_education_interfaces.py

@@ -0,0 +1,166 @@
+import requests
+import json
+import time
+
+# API基础URL
+BASE_URL = "http://localhost:8100/RuYuanZaiYuan"
+EDUCATION_DATA_BASE_URL = "http://localhost:8100/EducationData"
+
+# 支持的教育阶段
+test_education_stages = [
+    ("preschool", "学前"),
+    ("primary", "小学"),
+    ("junior", "初中"),
+    ("senior", "高中")
+]
+
+# 测试年份
+test_years = [2023, 2022, 2024]
+
+
+def test_school_chart_interface():
+    """测试获取教育阶段图表数据接口"""
+    print("\n===== 测试 /school/chart 接口 =====")
+    
+    for stage_code, stage_name in test_education_stages:
+        url = f"{BASE_URL}/school/chart?education_stage={stage_code}"
+        print(f"\n测试 {stage_name}({stage_code}) 数据:")
+        
+        try:
+            response = requests.get(url)
+            response.raise_for_status()  # 如果状态码不是200，抛出异常
+            
+            data = response.json()
+            print(f"响应状态码: {response.status_code}")
+            print(f"响应数据: {json.dumps(data, ensure_ascii=False, indent=2)}")
+            
+            # 验证返回数据的基本结构
+            assert "xAxis_data" in data, "返回数据缺少xAxis_data字段"
+            assert "series_data_0" in data, "返回数据缺少series_data_0字段(城区数据)"
+            assert "series_data_1" in data, "返回数据缺少series_data_1字段(镇区数据)"
+            assert "series_data_2" in data, "返回数据缺少series_data_2字段(乡村数据)"
+            assert "series_data_3" in data, "返回数据缺少series_data_3字段(总人数数据)"
+            assert "series_data_4" in data, "返回数据缺少series_data_4字段(2022年基数数据)"
+            assert "education_stage" in data, "返回数据缺少education_stage字段"
+            assert data["education_stage"] == stage_name, f"教育阶段名称不匹配，期望: {stage_name}，实际: {data['education_stage']}"
+            
+            print(f"✅ {stage_name} 数据验证通过")
+            
+        except requests.exceptions.RequestException as e:
+            print(f"❌ 请求失败: {e}")
+        except AssertionError as e:
+            print(f"❌ 数据验证失败: {e}")
+        
+        # 添加短暂延迟，避免请求过于频繁
+        time.sleep(0.5)
+
+
+# @router.get("/school/inschool/chart")
+# async def get_in_school_chart_config(
+#     education_stage: str = Query(default="preschool", pattern="^(preschool|primary|junior|senior)$",
+#                               description="教育阶段: preschool(学前), primary(小学), junior(初中), senior(高中)")
+# ):
+#     return RuYuanZaiYuanModel.generate_in_school_education_config(education_stage)
+#
+
+
+def test_education_data_by_year():
+    """测试获取指定年份教育数据接口"""
+    print("\n===== 测试 /EducationData/byYear 接口 =====")
+    
+    # 测试不同年份的数据
+    for year in test_years:
+        url = f"{EDUCATION_DATA_BASE_URL}/byYear?year={year}"
+        print(f"\n测试 {year} 年数据:")
+        
+        try:
+            response = requests.get(url)
+            response.raise_for_status()  # 如果状态码不是200，抛出异常
+            
+            data = response.json()
+            print(f"响应状态码: {response.status_code}")
+            print(f"响应数据: {json.dumps(data, ensure_ascii=False, indent=2)}")
+            
+            # 验证返回数据的基本结构
+            assert "code" in data, "返回数据缺少code字段"
+            assert "message" in data, "返回数据缺少message字段"
+            assert "data" in data, "返回数据缺少data字段"
+            assert data["code"] == 200, f"状态码不匹配，期望: 200，实际: {data['code']}"
+            assert isinstance(data["data"], list), "data字段应为列表类型"
+            
+            # 验证数据内容
+            if data["data"]:
+                # 检查每个数据项的结构
+                for item in data["data"]:
+                    assert "education_stage" in item, "数据项缺少education_stage字段"
+                    assert "school_count" in item, "数据项缺少school_count字段"
+                    assert "teacher_count_10k" in item, "数据项缺少teacher_count_10k字段"
+                    assert "enrollment_count_10k" in item, "数据项缺少enrollment_count_10k字段"
+                    assert "admission_count_10k" in item, "数据项缺少admission_count_10k字段"
+                    
+                    # 检查数值类型
+                    assert isinstance(item["school_count"], (int, float)), "school_count应为数值类型"
+                    assert isinstance(item["teacher_count_10k"], (int, float)), "teacher_count_10k应为数值类型"
+                    assert isinstance(item["enrollment_count_10k"], (int, float)), "enrollment_count_10k应为数值类型"
+                    assert isinstance(item["admission_count_10k"], (int, float)), "admission_count_10k应为数值类型"
+                
+                print(f"✅ {year} 年数据验证通过，共包含 {len(data['data'])} 个教育阶段的数据")
+            else:
+                print(f"⚠️ {year} 年未返回数据")
+                
+        except requests.exceptions.RequestException as e:
+            print(f"❌ 请求失败: {e}")
+        except AssertionError as e:
+            print(f"❌ 数据验证失败: {e}")
+        
+        # 添加短暂延迟，避免请求过于频繁
+        time.sleep(0.5)
+
+    # 测试边界值
+    print("\n===== 测试边界值 =====")
+    
+    # 测试最小值年份
+    min_year = 2015
+    url = f"{EDUCATION_DATA_BASE_URL}/byYear?year={min_year}"
+    print(f"\n测试最小值年份 {min_year}:")
+    try:
+        response = requests.get(url)
+        response.raise_for_status()
+        print(f"响应状态码: {response.status_code}")
+        print(f"✅ 最小值年份测试通过")
+    except requests.exceptions.RequestException as e:
+        print(f"❌ 请求失败: {e}")
+    
+    # 测试最大值年份
+    max_year = 2028
+    url = f"{EDUCATION_DATA_BASE_URL}/byYear?year={max_year}"
+    print(f"\n测试最大值年份 {max_year}:")
+    try:
+        response = requests.get(url)
+        response.raise_for_status()
+        print(f"响应状态码: {response.status_code}")
+        print(f"✅ 最大值年份测试通过")
+    except requests.exceptions.RequestException as e:
+        print(f"❌ 请求失败: {e}")
+    
+    # 测试超出范围的年份
+    invalid_year = 2030
+    url = f"{EDUCATION_DATA_BASE_URL}/byYear?year={invalid_year}"
+    print(f"\n测试超出范围的年份 {invalid_year}:")
+    try:
+        response = requests.get(url)
+        if response.status_code == 422:  # FastAPI的验证错误状态码
+            print(f"响应状态码: {response.status_code}")
+            print(f"✅ 超出范围年份正确返回验证错误")
+        else:
+            print(f"❌ 期望状态码422，实际: {response.status_code}")
+    except requests.exceptions.RequestException as e:
+        print(f"❌ 请求失败: {e}")
+
+
+if __name__ == "__main__":
+    # 测试原有接口
+    # test_school_chart_interface()
+    
+    # 测试新添加的教育数据接口
+    test_education_data_by_year()

Test/test_population_data_interface.py

@@ -0,0 +1,124 @@
+import requests
+import json
+import time
+
+# API基础URL
+EDUCATION_DATA_BASE_URL = "http://localhost:8100/EducationData"
+
+# 测试年份
+test_years = [2023, 2022, 2024]
+
+
+def test_population_data_by_year():
+    """测试获取指定年份人口数据接口"""
+    print("\n===== 测试 /EducationData/populationByYear 接口 =====")
+    
+    # 测试不同年份的数据
+    for year in test_years:
+        url = f"{EDUCATION_DATA_BASE_URL}/populationByYear?year={year}"
+        print(f"\n测试 {year} 年人口数据:")
+        
+        try:
+            response = requests.get(url)
+            response.raise_for_status()  # 如果状态码不是200，抛出异常
+            
+            data = response.json()
+            print(f"响应状态码: {response.status_code}")
+            print(f"响应数据: {json.dumps(data, ensure_ascii=False, indent=2)}")
+            
+            # 验证返回数据的基本结构
+            assert "code" in data, "返回数据缺少code字段"
+            assert "message" in data, "返回数据缺少message字段"
+            assert "data" in data, "返回数据缺少data字段"
+            assert data["code"] == 200, f"状态码不匹配，期望: 200，实际: {data['code']}"
+            
+            # 验证数据内容
+            if data["data"]:
+                # 检查数据项的结构
+                population_data = data["data"]
+                assert "year" in population_data, "数据缺少year字段"
+                assert "total_population" in population_data, "数据缺少total_population字段"
+                assert "birth_population" in population_data, "数据缺少birth_population字段"
+                assert "urban_population" in population_data, "数据缺少urban_population字段"
+                assert "rural_population" in population_data, "数据缺少rural_population字段"
+                assert "urbanization_rate" in population_data, "数据缺少urbanization_rate字段"
+                
+                # 检查数值类型
+                assert isinstance(population_data["year"], int), "year应为整数类型"
+                assert isinstance(population_data["total_population"], (int, float)), "total_population应为数值类型"
+                assert isinstance(population_data["birth_population"], (int, float)), "birth_population应为数值类型"
+                assert isinstance(population_data["urban_population"], (int, float)), "urban_population应为数值类型"
+                assert isinstance(population_data["rural_population"], (int, float)), "rural_population应为数值类型"
+                assert isinstance(population_data["urbanization_rate"], (int, float)), "urbanization_rate应为数值类型"
+                
+                # 检查年份是否匹配
+                assert population_data["year"] == year, f"年份不匹配，期望: {year}，实际: {population_data['year']}"
+                
+                print(f"✅ {year} 年人口数据验证通过")
+            else:
+                print(f"⚠️ {year} 年未返回人口数据")
+                
+        except requests.exceptions.RequestException as e:
+            print(f"❌ 请求失败: {e}")
+        except AssertionError as e:
+            print(f"❌ 数据验证失败: {e}")
+        
+        # 添加短暂延迟，避免请求过于频繁
+        time.sleep(0.5)
+    
+    # 测试边界值
+    print("\n===== 测试边界值 =====")
+    
+    # 测试最小值年份
+    min_year = 2015
+    url = f"{EDUCATION_DATA_BASE_URL}/populationByYear?year={min_year}"
+    print(f"\n测试最小值年份 {min_year}:")
+    try:
+        response = requests.get(url)
+        response.raise_for_status()
+        data = response.json()
+        print(f"响应状态码: {response.status_code}")
+        if data["code"] == 200 or data["code"] == 404:
+            print(f"✅ 最小值年份测试通过")
+        else:
+            print(f"❌ 状态码异常: {data['code']}")
+    except requests.exceptions.RequestException as e:
+        print(f"❌ 请求失败: {e}")
+    
+    # 测试最大值年份
+    max_year = 2028
+    url = f"{EDUCATION_DATA_BASE_URL}/populationByYear?year={max_year}"
+    print(f"\n测试最大值年份 {max_year}:")
+    try:
+        response = requests.get(url)
+        response.raise_for_status()
+        data = response.json()
+        print(f"响应状态码: {response.status_code}")
+        if data["code"] == 200 or data["code"] == 404:
+            print(f"✅ 最大值年份测试通过")
+        else:
+            print(f"❌ 状态码异常: {data['code']}")
+    except requests.exceptions.RequestException as e:
+        print(f"❌ 请求失败: {e}")
+    
+    # 测试超出范围的年份
+    invalid_year = 2030
+    url = f"{EDUCATION_DATA_BASE_URL}/populationByYear?year={invalid_year}"
+    print(f"\n测试超出范围的年份 {invalid_year}:")
+    try:
+        response = requests.get(url)
+        if response.status_code == 422:  # FastAPI的验证错误状态码
+            print(f"响应状态码: {response.status_code}")
+            print(f"✅ 超出范围年份正确返回验证错误")
+        else:
+            data = response.json()
+            print(f"响应状态码: {response.status_code}")
+            print(f"响应数据: {json.dumps(data, ensure_ascii=False, indent=2)}")
+            print(f"❌ 期望状态码422，实际: {response.status_code}")
+    except requests.exceptions.RequestException as e:
+        print(f"❌ 请求失败: {e}")
+
+
+if __name__ == "__main__":
+    # 测试新添加的人口数据接口
+    test_population_data_by_year()

Tools/T3_SchoolCount.py

@@ -74,7 +74,7 @@ def main():
             },
 
             # 初中教育
-            'junior_high_schools': {
+            'junior_schools': {
                 'years': [2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024],
                 'columns': [
                     {'year': 2015, 'urban': 'CF', 'town': 'CG', 'rural': 'CH'},
@@ -92,7 +92,7 @@ def main():
             },
 
             # 普通高中教育
-            'senior_high_schools': {
+            'senior_schools': {
                 'years': [2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024],
                 'columns': [
                     {'year': 2015, 'urban': 'DT', 'town': 'DU', 'rural': 'DV'},

Tools/T7_TeacherCount.py

@@ -53,7 +53,7 @@ EDUCATION_STAGES = {
             {'year': 2024, 'total_staff': 'EZ', 'urban_staff': 'FA', 'town_staff': 'FB', 'rural_staff': 'FC', 'total_teacher': 'FD', 'urban_teacher': 'FE', 'town_teacher': 'FF', 'rural_teacher': 'FG'}
         ]
     },
-    'junior_high_teachers': {
+    'junior_teachers': {
         'years': [2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024],
         'columns': [
             {'year': 2015, 'total_staff': 'FH', 'urban_staff': 'FI', 'town_staff': 'FJ', 'rural_staff': 'FK', 'total_teacher': 'FL', 'urban_teacher': 'FM', 'town_teacher': 'FN', 'rural_teacher': 'FO'},
@@ -68,7 +68,7 @@ EDUCATION_STAGES = {
             {'year': 2024, 'total_staff': 'IB', 'urban_staff': 'IC', 'town_staff': 'ID', 'rural_staff': 'IE', 'total_teacher': 'IF', 'urban_teacher': 'IG', 'town_teacher': 'IH', 'rural_teacher': 'II'}
         ]
     },
-    'senior_high_teachers': {
+    'senior_teachers': {
         'years': [2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024],
         'columns': [
             {'year': 2015, 'total_staff': 'IJ', 'urban_staff': 'IK', 'town_staff': 'IL', 'rural_staff': 'IM', 'total_teacher': 'IN', 'urban_teacher': 'IO', 'town_teacher': 'IP', 'rural_teacher': 'IQ'},

static/RuYuanZaiYuanCount.html

@@ -1,135 +0,0 @@
-<!DOCTYPE html>
-<html lang="zh-CN">
-<head>
-    <meta charset="UTF-8">
-    <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>云南省学前教育数据</title>
-    <link rel="stylesheet" href="css/style.css">
-    <script src="https://cdn.jsdelivr.net/npm/echarts@5.4.3/dist/echarts.min.js"></script>
-    <script src="js/jquery-3.7.1.min.js"></script>
-    <style>
-        .chart-controls {
-            margin: 20px 0;
-            text-align: center;
-        }
-        .btn-group {
-            display: inline-flex;
-            border-radius: 4px;
-            overflow: hidden;
-            box-shadow: 0 2px 4px rgba(0,0,0,0.1);
-        }
-        .btn {
-            padding: 10px 20px;
-            border: none;
-            background: #f0f0f0;
-            cursor: pointer;
-            font-size: 14px;
-            transition: all 0.3s;
-        }
-        .btn.active {
-            background: #409eff;
-            color: white;
-        }
-        .btn:hover:not(.active) {
-            background: #e0e0e0;
-        }
-        .container {
-            max-width: 1200px;
-            margin: 0 auto;
-            padding: 20px;
-        }
-        h1 {
-            text-align: center;
-            color: #333;
-            margin-bottom: 30px;
-        }
-    </style>
-</head>
-<body>
-    <div class="container">
-        <h1>学前教育发展规模预测</h1>
-        
-        <div class="chart-controls">
-            <div class="btn-group">
-                <button class="btn active" data-type="enroll">入园数总量</button>
-                <button class="btn" data-type="inschool">在园数总量</button>
-            </div>
-        </div>
-        
-        <div id="preschoolChart" style="width: 100%; height: 500px;"></div>
-        <div id="message" class="message"></div>
-    </div>
-
-    <script>
-        // 初始化图表
-        var preschoolChart = echarts.init(document.getElementById('preschoolChart'));
-        var chartData = null;
-        var currentType = 'enroll';
-
-        // 显示加载状态
-        function showLoading() {
-            preschoolChart.showLoading();
-        }
-
-        // 隐藏加载状态
-        function hideLoading() {
-            preschoolChart.hideLoading();
-        }
-
-        // 显示错误信息
-        function showError(message) {
-            $('#message').text('错误: ' + message);
-            console.error(message);
-        }
-
-        // 渲染图表
-        function renderChart() {
-            if (!chartData) return;
-
-            var option = JSON.parse(JSON.stringify(chartData));
-            
-            // 根据用户要求，现在显示所有系列数据，不需要过滤
-            preschoolChart.setOption(option);
-        }
-
-        // 加载学前教育数据
-        function loadPreschoolData() {
-            showLoading();
-            
-            // 根据当前类型加载不同数据
-            var url = currentType === 'enroll' ? 
-                      '/RuYuanZaiYuan/school/preschool/chart' :
-                      '/RuYuanZaiYuan/school/preschool/inschool/chart';
-                       
-            $.getJSON(url)
-                .done(function(data) {
-                    chartData = data;
-                    renderChart();
-                })
-                .fail(function(jqXHR, textStatus, errorThrown) {
-                    showError(errorThrown || '获取数据失败，请检查接口是否正常');
-                })
-                .always(function() {
-                    hideLoading();
-                });
-        }
-
-        // 按钮点击事件
-        $(document).ready(function() {
-            loadPreschoolData();
-
-            $('.btn').click(function() {
-                $('.btn').removeClass('active');
-                $(this).addClass('active');
-                currentType = $(this).data('type');
-                loadPreschoolData(); // 点击按钮后重新加载数据，而不是只渲染
-            });
-
-            // 窗口大小变化时调整图表
-            $(window).resize(function() {
-                preschoolChart.resize();
-            });
-        });
-    </script>
-</body>
-</html>

static/index.html

@@ -166,8 +166,8 @@
             </li>
         </ul>
     </div>
-    <script type="text/javascript" src="js/jquery.js"></script>
-    <script type="text/javascript" src="https://gcore.jsdelivr.net/npm/echarts@6.0.0/dist/echarts.min.js"></script>
+    <script type="text/javascript" src="js/jquery-3.7.1.min.js"></script>
+    <script type="text/javascript" src="js/echarts.min.js"></script>
     <script language="JavaScript" src="js/index.js"></script>
     <script language="JavaScript" src="js/data/index.js"></script>
 </body>

static/js/data/index.js

@@ -36,43 +36,108 @@ option_1_1 = {
       name: "城区",
       type: "bar",
       data: [],
+      tooltip: { valueFormatter: (v) => v + " 万人" },
       itemStyle: { borderRadius: [6, 6, 0, 0] },
     },
     {
       name: "镇区",
       type: "bar",
-      data: [      ],
+      data: [],
+      tooltip: { valueFormatter: (v) => v + " 万人" },
       itemStyle: { borderRadius: [6, 6, 0, 0] },
     },
     {
       name: "乡村",
       type: "bar",
-      data: [      ],
+      data: [],
+      tooltip: { valueFormatter: (v) => v + " 万人" },
       itemStyle: { borderRadius: [6, 6, 0, 0] },
     },
     {
       name: "总入园数",
       type: "line",
       yAxisIndex: 1,
-      data: [
-      ],
+      data: [],
+      tooltip: { valueFormatter: (v) => v + " 万人" },
     },
     {
       name: "2022年基数",
       type: "line",
       yAxisIndex: 1,
-      data: [
-        null,
-        null,
-        null,
-        null,
-        null,
-        null,
-        null,
-        105.6714,
-        105.6714,
-        105.6714,
-      ],
+      data: [],
+      tooltip: { valueFormatter: (v) => typeof v === "number" ? v + " 万人" : v },
+    },
+  ],
+};
+
+option_1_2 = {
+  grid: { left: 0, right: 0, top: 40, bottom: 10, containLabel: true },
+  textStyle: { color: "#fff" },
+  tooltip: {
+    trigger: "axis",
+    axisPointer: { type: "cross", crossStyle: { color: "#999" } },
+    textStyle: { color: "#fff" },
+    backgroundColor: "rgba(96,98,102,0.8)",
+    borderColor: "rgba(255,255,255,0.3)",
+    borderWidth: 1,
+  },
+  legend: {
+    data: ["城区", "镇区", "乡村", "总在园数", "2022年基数"],
+    top: 0,
+    textStyle: { color: "#fff" },
+    icon: "roundRect",
+    itemWidth: 12,
+    itemHeight: 12,
+  },
+  xAxis: [
+    {
+      type: "category",
+      data: [],
+      axisPointer: { type: "shadow" },
+      axisLine: { lineStyle: { color: "#fff" } },
+      axisLabel: { color: "#fff" },
+      nameTextStyle: { color: "#fff" },
+    },
+  ],
+  yAxis: [
+    { type: "value", axisLabel: { formatter: "{value}", color: "#fff" } },
+    { type: "value", axisLabel: { formatter: "{value}", color: "#fff" } },
+  ],
+  series: [
+    {
+      name: "城区",
+      type: "bar",
+      data: [],
+      tooltip: { valueFormatter: (v) => v + " 万人" },
+      itemStyle: { borderRadius: [6, 6, 0, 0] },
+    },
+    {
+      name: "镇区",
+      type: "bar",
+      data: [],
+      tooltip: { valueFormatter: (v) => v + " 万人" },
+      itemStyle: { borderRadius: [6, 6, 0, 0] },
+    },
+    {
+      name: "乡村",
+      type: "bar",
+      data: [],
+      tooltip: { valueFormatter: (v) => v + " 万人" },
+      itemStyle: { borderRadius: [6, 6, 0, 0] },
+    },
+    {
+      name: "总在园数",
+      type: "line",
+      yAxisIndex: 1,
+      data: [],
+      tooltip: { valueFormatter: (v) => v + " 万人" },
+    },
+    {
+      name: "2022年基数",
+      type: "line",
+      yAxisIndex: 1,
+      data: [],
+      tooltip: { valueFormatter: (v) => typeof v === "number" ? v + " 万人" : v },
     },
   ],
 };

static/js/index.js

@@ -16,11 +16,11 @@ $(window).load(function () {
 });
 
 $(function () {
-  echarts_1();
+  echarts_1_1();
   echarts_2();
   // echarts_3();
 
-  function echarts_1() {
+  function echarts_1_1() {
     var myChart = echarts.init(document.getElementById("echarts01"));
 
     $.ajax({
@@ -29,14 +29,12 @@ $(function () {
       dataType: "json",
       url: "/RuYuanZaiYuan/school/preschool/chart",
       success: function (res) {
-        option_1_1.series.forEach((seriesItem, index) => {
-          seriesItem.tooltip = { valueFormatter: (v) => v + " 万人" };
-        });
         option_1_1.xAxis[0].data = res.xAxis_data;
-        option_1_1.series[0].data = res.series_data_1;
-        option_1_1.series[1].data = res.series_data_2;
-        option_1_1.series[2].data = res.series_data_3;
-        option_1_1.series[3].data = res.series_data_4;
+        option_1_1.series[0].data = res.series_data_0;
+        option_1_1.series[1].data = res.series_data_1;
+        option_1_1.series[2].data = res.series_data_2;
+        option_1_1.series[3].data = res.series_data_3;
+        option_1_1.series[4].data = res.series_data_4;        
         myChart.setOption(option_1_1);
         window.addEventListener("resize", function () {
           myChart.resize();
@@ -282,18 +280,12 @@ $(function () {
     $(this).siblings().removeClass("active");
     // 添加active类到当前点击的元素
     $(this).addClass("active");
-
     // 获取当前选中的标签数据
     var selectedTab = $(this).data("tab");    
-
-    // 这里可以添加根据标签切换内容的逻辑
-    console.log("切换到: " + selectedTab);
-
-    // 示例：根据标签切换图表数据
     switch (selectedTab) {
       case "入园数":
         // 加载入园数数据
-        echarts_1();
+        echarts_1_1();
         break;
       case "在园数":
         echarts_3();