feat: 添加 Linux/Windows 双平台测试套件（云南省界叠加分析）
- test-linux: platform=linux, docker + python3 - test-windows: platform=windows, arcpy + python3 - 附示例 GeoJSON: 云南/昆明/大理/百色 Ref: SuiteHub/agent-profiles#22
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#!/usr/bin/env python3
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"""
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Step 1: GeoJSON → SHP
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将省界和城市 GeoJSON 文件转换为 Shapefile
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"""
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import sys
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import json
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import os
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import geopandas as gpd
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def main():
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province_path = os.environ.get("PARAM_PROVINCE", "")
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cities_param = os.environ.get("PARAM_CITIES", "")
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output_dir = os.environ.get("PARAM_OUTPUT_DIR", "/tmp/output/shp")
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if not province_path:
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print(json.dumps({"error": "缺少 province 参数", "success": False}))
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sys.exit(1)
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if not cities_param:
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print(json.dumps({"error": "缺少 cities 参数", "success": False}))
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sys.exit(1)
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os.makedirs(output_dir, exist_ok=True)
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# 读取并转换省界
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print(json.dumps({"msg": f"读取省界: {province_path}"}))
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province_gdf = gpd.read_file(province_path)
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province_shp = os.path.join(output_dir, "province.shp")
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province_gdf.to_file(province_shp, driver="ESRI Shapefile")
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print(json.dumps({"msg": f"省界已转为 SHP: {province_shp}", "count": len(province_gdf)}))
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# 读取并转换每个城市 GeoJSON
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city_files = [c.strip() for c in cities_param.split(",") if c.strip()]
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converted = []
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for cf in city_files:
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if not os.path.isfile(cf):
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print(json.dumps({"warn": f"文件不存在，跳过: {cf}"}))
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continue
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print(json.dumps({"msg": f"读取城市: {cf}"}))
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gdf = gpd.read_file(cf)
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base = os.path.splitext(os.path.basename(cf))[0]
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shp_path = os.path.join(output_dir, f"{base}.shp")
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gdf.to_file(shp_path, driver="ESRI Shapefile")
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converted.append(base)
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print(json.dumps({"msg": f"已转换: {cf} → {shp_path}", "count": len(gdf)}))
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result = {
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"success": True,
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"province_shp": province_shp,
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"city_count": len(converted),
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"cities": converted
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}
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print(json.dumps(result))
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if __name__ == "__main__":
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main()
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#!/usr/bin/env python3
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"""
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Step 3: 输出 Excel
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将叠加分析结果写入 Excel 文件
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"""
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import sys
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import json
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import os
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from openpyxl import Workbook
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from openpyxl.styles import Font, Alignment, PatternFill
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def main():
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result_dir = os.environ.get("PARAM_RESULT_DIR", "/tmp/output/result")
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output_path = os.environ.get("PARAM_OUTPUT_PATH", "")
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if not output_path:
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print(json.dumps({"error": "缺少 output_path 参数", "success": False}))
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sys.exit(1)
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# 读取分析结果
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result_json = os.path.join(result_dir, "overlay_results.json")
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if not os.path.isfile(result_json):
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print(json.dumps({"error": f"结果文件不存在: {result_json}", "success": False}))
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sys.exit(1)
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with open(result_json, "r", encoding="utf-8") as f:
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results = json.load(f)
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# 创建工作簿
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wb = Workbook()
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ws = wb.active
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ws.title = "叠加分析结果"
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# 标题样式
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header_font = Font(bold=True, size=12, color="FFFFFF")
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header_fill = PatternFill(start_color="4472C4", end_color="4472C4", fill_type="solid")
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header_align = Alignment(horizontal="center", vertical="center")
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# 表头
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headers = ["城市", "城市代码", "城市名称", "人口", "在省内", "相交", "状态"]
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for col, h in enumerate(headers, 1):
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cell = ws.cell(row=1, column=col, value=h)
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cell.font = header_font
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cell.fill = header_fill
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cell.alignment = header_align
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# 数据行
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pass_fill = PatternFill(start_color="E2EFDA", end_color="E2EFDA", fill_type="solid")
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fail_fill = PatternFill(start_color="FCE4EC", end_color="FCE4EC", fill_type="solid")
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for row_idx, r in enumerate(results, 2):
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ws.cell(row=row_idx, column=1, value=r.get("city", ""))
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ws.cell(row=row_idx, column=2, value=r.get("city_code", ""))
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ws.cell(row=row_idx, column=3, value=r.get("city_name", ""))
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ws.cell(row=row_idx, column=4, value=r.get("population", 0))
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ws.cell(row=row_idx, column=5, value="是" if r.get("in_province") else "否")
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ws.cell(row=row_idx, column=6, value="是" if r.get("intersects") else "否")
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ws.cell(row=row_idx, column=7, value=r.get("status", ""))
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# 条件高亮
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fill = pass_fill if r.get("in_province") else fail_fill
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for col in range(1, 8):
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ws.cell(row=row_idx, column=col).fill = fill
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# 调整列宽
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ws.column_dimensions["A"].width = 15
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ws.column_dimensions["B"].width = 12
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ws.column_dimensions["C"].width = 15
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ws.column_dimensions["D"].width = 12
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ws.column_dimensions["E"].width = 10
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ws.column_dimensions["F"].width = 10
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ws.column_dimensions["G"].width = 15
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# 确保输出目录存在
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out_dir = os.path.dirname(output_path)
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if out_dir:
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os.makedirs(out_dir, exist_ok=True)
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wb.save(output_path)
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print(json.dumps({
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"success": True,
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"output_path": output_path,
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"total": len(results),
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"msg": f"Excel 已输出到: {output_path}"
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}))
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if __name__ == "__main__":
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main()
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#!/usr/bin/env python3
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"""
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Step 2: 叠加分析
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判断各城市是否在省界内（spatial join），输出分析结果
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"""
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import sys
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import json
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import os
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import glob
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import geopandas as gpd
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def main():
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province_shp = os.environ.get("PARAM_PROVINCE_SHP", "")
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cities_dir = os.environ.get("PARAM_CITIES_DIR", "/tmp/output/shp")
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output_dir = os.environ.get("PARAM_OUTPUT_DIR", "/tmp/output/result")
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if not province_shp or not os.path.isfile(province_shp):
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print(json.dumps({"error": f"省界 SHP 文件不存在: {province_shp}", "success": False}))
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sys.exit(1)
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os.makedirs(output_dir, exist_ok=True)
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# 读取省界
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print(json.dumps({"msg": f"读取省界 SHP: {province_shp}"}))
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province = gpd.read_file(province_shp)
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if province.empty:
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print(json.dumps({"error": "省界数据为空", "success": False}))
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sys.exit(1)
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# 确保坐标系一致
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target_crs = province.crs or "EPSG:4326"
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province = province.to_crs(target_crs)
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# 查找所有城市 SHP
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city_shp_files = glob.glob(os.path.join(cities_dir, "*.shp"))
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city_shp_files = [f for f in city_shp_files
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if os.path.basename(f) != "province.shp"]
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if not city_shp_files:
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print(json.dumps({"error": "未找到城市 SHP 文件", "success": False}))
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sys.exit(1)
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results = []
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for shp in city_shp_files:
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city_name = os.path.splitext(os.path.basename(shp))[0]
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print(json.dumps({"msg": f"分析城市: {city_name}"}))
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city = gpd.read_file(shp)
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if city.empty:
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results.append({"city": city_name, "in_province": False,
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"reason": "数据为空", "status": "跳过"})
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continue
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city = city.to_crs(target_crs)
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# 空间判断：城市中心点是否在省界内
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city_centroid = city.geometry.centroid.iloc[0]
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in_province = province.geometry.contains(city_centroid).any()
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# 也检查 intersect 作为辅助判断
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intersects = province.geometry.intersects(city.geometry).any()
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status = "通过 ✅" if in_province else "不通过 ❌"
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city_name_prop = city.iloc[0].get("name", city_name)
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city_code = city.iloc[0].get("code", "")
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city_pop = city.iloc[0].get("population", 0)
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results.append({
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"city": city_name,
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"city_code": str(city_code),
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"city_name": str(city_name_prop),
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"population": int(city_pop) if city_pop else 0,
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"in_province": bool(in_province),
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"intersects": bool(intersects),
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"status": status
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})
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print(json.dumps({"msg": f"{city_name}: {status}"}))
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# 输出分析结果 JSON
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result_path = os.path.join(output_dir, "overlay_results.json")
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with open(result_path, "w", encoding="utf-8") as f:
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json.dump(results, f, ensure_ascii=False, indent=2)
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summary = {
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"success": True,
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"total_cities": len(results),
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"in_province": sum(1 for r in results if r["in_province"]),
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"not_in_province": sum(1 for r in results if not r["in_province"]),
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"results": results,
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"result_json": result_path
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}
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print(json.dumps(summary))
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if __name__ == "__main__":
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main()
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