{"id":1014535,"date":"2024-12-27T11:57:01","date_gmt":"2024-12-27T03:57:01","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1014535.html"},"modified":"2024-12-27T11:57:03","modified_gmt":"2024-12-27T03:57:03","slug":"python%e5%a6%82%e4%bd%95%e7%94%9f%e6%88%90shp%e6%96%87%e4%bb%b6","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1014535.html","title":{"rendered":"python\u5982\u4f55\u751f\u6210shp\u6587\u4ef6"},"content":{"rendered":"

\"python\u5982\u4f55\u751f\u6210shp\u6587\u4ef6\"<\/p>\n

Python\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528\u5e93\u5982geopandas<\/code>\u3001pyshp<\/code>\u548cfiona<\/code>\u7b49\u6765\u751f\u6210SHP\u6587\u4ef6\u3001\u5176\u4e2dgeopandas<\/code>\u662f\u6700\u4e3a\u65b9\u4fbf\u548c\u5f3a\u5927\u7684\u9009\u62e9\u3001\u5b83\u63d0\u4f9b\u4e86\u7b80\u5355\u7684\u63a5\u53e3\u6765\u521b\u5efa\u548c\u64cd\u4f5c\u5730\u7406\u6570\u636e<\/strong>\u3002\u5728geopandas<\/code>\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u521b\u5efaGeoDataFrame\u5bf9\u8c61\u5e76\u8bbe\u7f6e\u51e0\u4f55\u5217\u6765\u751f\u6210SHP\u6587\u4ef6\u3002GeoDataFrame\u7c7b\u4f3c\u4e8epandas DataFrame\uff0c\u4f46\u5b83\u5177\u6709\u51e0\u4f55\u6570\u636e\u7684\u652f\u6301\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u89e3\u91ca\u5982\u4f55\u4f7f\u7528geopandas<\/code>\u751f\u6210SHP\u6587\u4ef6\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u5b89\u88c5\u4e0e\u51c6\u5907<\/p>\n<\/p>\n

\u5728\u5f00\u59cb\u4e4b\u524d\uff0c\u786e\u4fdd\u5df2\u7ecf\u5b89\u88c5\u4e86geopandas<\/code>\u5e93\u3002\u5982\u679c\u6ca1\u6709\u5b89\u88c5\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u901a\u8fc7pip\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install geopandas<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u6b64\u5916\uff0cgeopandas<\/code>\u4f9d\u8d56\u4e8e\u5176\u4ed6\u51e0\u4e2a\u5e93\uff0c\u4f8b\u5982shapely<\/code>\u3001fiona<\/code>\u7b49\uff0c\u8fd9\u4e9b\u901a\u5e38\u4f1a\u81ea\u52a8\u5b89\u88c5\uff0c\u4f46\u5728\u67d0\u4e9b\u73af\u5883\u4e2d\u53ef\u80fd\u9700\u8981\u624b\u52a8\u5b89\u88c5\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u521b\u5efaGeoDataFrame<\/p>\n<\/p>\n
GeoDataFrame\u662fgeopandas<\/code>\u7684\u6838\u5fc3\u6570\u636e\u7ed3\u6784\uff0c\u7528\u4e8e\u5b58\u50a8\u5730\u7406\u6570\u636e\u3002\u8981\u521b\u5efa\u4e00\u4e2aGeoDataFrame\uff0c\u6211\u4eec\u9700\u8981\u63d0\u4f9b\u51e0\u4f55\u6570\u636e\uff08\u5982\u70b9\u3001\u7ebf\u3001\u9762\uff09\u548c\u5bf9\u5e94\u7684\u5c5e\u6027\u6570\u636e\u3002<\/p>\n<\/p>\n
    \n
  1. \n
    \u5b9a\u4e49\u51e0\u4f55\u6570\u636e\uff1a<\/strong><\/p>\n<\/p>\n
    \u5728geopandas<\/code>\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528shapely<\/code>\u5e93\u6765\u5b9a\u4e49\u51e0\u4f55\u5bf9\u8c61\uff0c\u4f8b\u5982\u70b9\u3001\u7ebf\u548c\u9762\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u521b\u5efa\u4e00\u4e9b\u7b80\u5355\u7684\u51e0\u4f55\u5bf9\u8c61\uff1a<\/p>\n<\/p>\n
    from shapely.geometry import Point, LineString, Polygon<\/p>\n
    \u521b\u5efa\u70b9<\/strong><\/h2>\n
    point = Point(1, 2)<\/p>\n
    \u521b\u5efa\u7ebf<\/strong><\/h2>\n
    line = LineString([(0, 0), (1, 1), (2, 2)])<\/p>\n
    \u521b\u5efa\u9762<\/strong><\/h2>\n
    polygon = Polygon([(0, 0), (1, 0), (1, 1), (0, 1)])<\/p>\n
    <\/code><\/pre>\n<\/p>\n<\/li>\n
  2. \n
    \u521b\u5efaGeoDataFrame\uff1a<\/strong><\/p>\n<\/p>\n
    \u6211\u4eec\u53ef\u4ee5\u4f7f\u7528geopandas.GeoDataFrame<\/code>\u6765\u521b\u5efa\u4e00\u4e2aGeoDataFrame\u5bf9\u8c61\u3002\u5728\u521b\u5efa\u65f6\uff0c\u6211\u4eec\u9700\u8981\u6307\u5b9a\u51e0\u4f55\u6570\u636e\u548c\u5176\u4ed6\u5c5e\u6027\u6570\u636e\u3002<\/p>\n<\/p>\n
    import geopandas as gpd<\/p>\n
    import pandas as pd<\/p>\n
    \u521b\u5efa\u5c5e\u6027\u6570\u636e<\/strong><\/h2>\n
    data = {'Name': ['Point A', 'Line B', 'Polygon C'],<\/p>\n
            'Value': [10, 20, 30]}<\/p>\n
    \u521b\u5efaGeoDataFrame<\/strong><\/h2>\n
    gdf = gpd.GeoDataFrame(data, geometry=[point, line, polygon])<\/p>\n
    <\/code><\/pre>\n<\/p>\n<\/li>\n<\/ol>\n
    \u4e09\u3001\u4fdd\u5b58\u4e3aSHP\u6587\u4ef6<\/p>\n<\/p>\n
    \u4e00\u65e6\u6211\u4eec\u6709\u4e86GeoDataFrame\u5bf9\u8c61\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u8f7b\u677e\u5730\u5c06\u5176\u4fdd\u5b58\u4e3aSHP\u6587\u4ef6\u3002\u4f7f\u7528to_file<\/code>\u65b9\u6cd5\u6307\u5b9a\u6587\u4ef6\u8def\u5f84\u548c\u683c\u5f0f\u5373\u53ef\u3002<\/p>\n<\/p>\n
    # \u4fdd\u5b58\u4e3aSHP\u6587\u4ef6<\/p>\n
    gdf.to_file('output.shp')<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u56db\u3001\u66f4\u591a\u9ad8\u7ea7\u64cd\u4f5c<\/p>\n<\/p>\n
    \u5728\u751f\u6210SHP\u6587\u4ef6\u7684\u8fc7\u7a0b\u4e2d\uff0c\u53ef\u80fd\u4f1a\u9047\u5230\u9700\u8981\u6267\u884c\u66f4\u590d\u6742\u7684\u64cd\u4f5c\uff0c\u6bd4\u5982\u8bbe\u7f6e\u5750\u6807\u7cfb\u3001\u5904\u7406\u591a\u79cd\u51e0\u4f55\u7c7b\u578b\u7b49\u3002\u4e0b\u9762\u4ecb\u7ecd\u4e00\u4e9b\u5e38\u89c1\u7684\u9ad8\u7ea7\u64cd\u4f5c\u3002<\/p>\n<\/p>\n
      \n
    1. \n
      \u8bbe\u7f6e\u5750\u6807\u7cfb\uff08CRS\uff09\uff1a<\/strong><\/p>\n<\/p>\n
      \u5750\u6807\u53c2\u8003\u7cfb\uff08CRS\uff09\u662f\u5730\u7406\u6570\u636e\u7684\u91cd\u8981\u7ec4\u6210\u90e8\u5206\uff0c\u5b9a\u4e49\u4e86\u6570\u636e\u7684\u6295\u5f71\u65b9\u5f0f\u3002\u6211\u4eec\u53ef\u4ee5\u5728\u521b\u5efaGeoDataFrame\u65f6\u8bbe\u7f6eCRS\uff0c\u4e5f\u53ef\u4ee5\u5728\u4e4b\u540e\u66f4\u6539\u3002<\/p>\n<\/p>\n
      # \u8bbe\u7f6eCRS\u4e3aWGS84<\/p>\n
      gdf.crs = 'EPSG:4326'<\/p>\n
      <\/code><\/pre>\n<\/p>\n<\/li>\n
    2. \n
      \u5904\u7406\u591a\u79cd\u51e0\u4f55\u7c7b\u578b\uff1a<\/strong><\/p>\n<\/p>\n
      \u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u6211\u4eec\u53ef\u80fd\u4f1a\u9047\u5230\u9700\u8981\u5904\u7406\u591a\u79cd\u51e0\u4f55\u7c7b\u578b\u7684\u6570\u636e\u3002geopandas<\/code>\u652f\u6301\u6df7\u5408\u51e0\u4f55\u7c7b\u578b\uff0c\u8fd9\u610f\u5473\u7740\u4f60\u53ef\u4ee5\u5728\u540c\u4e00\u4e2aGeoDataFrame\u4e2d\u5b58\u50a8\u70b9\u3001\u7ebf\u548c\u9762\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n
      # \u521b\u5efa\u6df7\u5408\u51e0\u4f55\u7c7b\u578b\u7684\u6570\u636e<\/p>\n
      mixed_geometries = [Point(1, 2), LineString([(2, 3), (3, 4)]), Polygon([(4, 5), (5, 6), (6, 5)])]<\/p>\n
      gdf_mixed = gpd.GeoDataFrame({'Name': ['A', 'B', 'C']}, geometry=mixed_geometries)<\/p>\n
      <\/code><\/pre>\n<\/p>\n<\/li>\n
    3. \n
      \u8bfb\u53d6\u73b0\u6709\u7684SHP\u6587\u4ef6\uff1a<\/strong><\/p>\n<\/p>\n
      \u5728\u8bb8\u591a\u60c5\u51b5\u4e0b\uff0c\u6211\u4eec\u53ef\u80fd\u9700\u8981\u8bfb\u53d6\u73b0\u6709\u7684SHP\u6587\u4ef6\u8fdb\u884c\u5904\u7406\u3002geopandas<\/code>\u63d0\u4f9b\u4e86\u65b9\u4fbf\u7684\u65b9\u6cd5\u6765\u8bfb\u53d6SHP\u6587\u4ef6\u3002<\/p>\n<\/p>\n
      # \u8bfb\u53d6SHP\u6587\u4ef6<\/p>\n
      gdf_existing = gpd.read_file('existing_file.shp')<\/p>\n
      <\/code><\/pre>\n<\/p>\n<\/li>\n<\/ol>\n
      \u4e94\u3001\u4f18\u5316\u4e0e\u6ce8\u610f\u4e8b\u9879<\/p>\n<\/p>\n
      \u5728\u5904\u7406\u548c\u751f\u6210SHP\u6587\u4ef6\u65f6\uff0c\u6709\u4e00\u4e9b\u4f18\u5316\u5efa\u8bae\u548c\u6ce8\u610f\u4e8b\u9879\u53ef\u4ee5\u5e2e\u52a9\u63d0\u9ad8\u6548\u7387\u548c\u6570\u636e\u7684\u5b8c\u6574\u6027\u3002<\/p>\n<\/p>\n
        \n
      1. \n
        \u6570\u636e\u9a8c\u8bc1\uff1a<\/strong><\/p>\n<\/p>\n
        \u5728\u5904\u7406\u5730\u7406\u6570\u636e\u65f6\uff0c\u786e\u4fdd\u6570\u636e\u7684\u5b8c\u6574\u6027\u548c\u51c6\u786e\u6027\u975e\u5e38\u91cd\u8981\u3002\u53ef\u4ee5\u4f7f\u7528geopandas<\/code>\u7684\u4e00\u4e9b\u5185\u7f6e\u65b9\u6cd5\u6765\u9a8c\u8bc1\u51e0\u4f55\u6570\u636e\u3002<\/p>\n<\/p>\n
        # \u68c0\u67e5\u51e0\u4f55\u662f\u5426\u6709\u6548<\/p>\n
        gdf['is_valid'] = gdf.is_valid<\/p>\n
        <\/code><\/pre>\n<\/p>\n<\/li>\n
      2. \n
        \u6027\u80fd\u4f18\u5316\uff1a<\/strong><\/p>\n<\/p>\n
        \u5728\u5904\u7406\u5927\u89c4\u6a21\u5730\u7406\u6570\u636e\u65f6\uff0c\u53ef\u80fd\u4f1a\u9047\u5230\u6027\u80fd\u74f6\u9888\u3002\u53ef\u4ee5\u901a\u8fc7\u51cf\u5c11\u4e0d\u5fc5\u8981\u7684\u8ba1\u7b97\u3001\u4f7f\u7528\u66f4\u9ad8\u6548\u7684\u6570\u636e\u7ed3\u6784\u7b49\u65b9\u5f0f\u8fdb\u884c\u4f18\u5316\u3002<\/p>\n<\/p>\n
        \u4f8b\u5982\uff0c\u4f7f\u7528\u5206\u5757\u8bfb\u53d6SHP\u6587\u4ef6\u4ee5\u964d\u4f4e\u5185\u5b58\u6d88\u8017\uff1a<\/p>\n<\/p>\n
        for chunk in pd.read_csv('large_file.shp', chunksize=10000):<\/p>\n
            # \u5904\u7406\u6bcf\u4e2a\u6570\u636e\u5757<\/p>\n
            pass<\/p>\n
        <\/code><\/pre>\n<\/p>\n<\/li>\n
      3. \n
        \u6587\u4ef6\u683c\u5f0f\u8f6c\u6362\uff1a<\/strong><\/p>\n<\/p>\n
        \u867d\u7136SHP\u6587\u4ef6\u662f\u5730\u7406\u6570\u636e\u7684\u5e38\u7528\u683c\u5f0f\uff0c\u4f46\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff0c\u5176\u4ed6\u683c\u5f0f\u53ef\u80fd\u66f4\u9002\u5408\uff0c\u5982GeoJSON\u3001KML\u7b49\u3002geopandas<\/code>\u652f\u6301\u591a\u79cd\u683c\u5f0f\u7684\u8f6c\u6362\u3002<\/p>\n<\/p>\n
        # \u4fdd\u5b58\u4e3aGeoJSON\u6587\u4ef6<\/p>\n
        gdf.to_file('output.geojson', driver='GeoJSON')<\/p>\n
        <\/code><\/pre>\n<\/p>\n<\/li>\n<\/ol>\n
        \u516d\u3001\u603b\u7ed3<\/p>\n<\/p>\n
        Python\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u5de5\u5177\u6765\u5904\u7406\u548c\u751f\u6210\u5730\u7406\u6570\u636e\uff0c\u5176\u4e2dgeopandas<\/code>\u662f\u6700\u4e3a\u4fbf\u6377\u548c\u529f\u80fd\u4e30\u5bcc\u7684\u5e93\u4e4b\u4e00\u3002\u901a\u8fc7\u672c\u6587\u7684\u4ecb\u7ecd\uff0c\u6211\u4eec\u4e86\u89e3\u4e86\u5982\u4f55\u4f7f\u7528geopandas<\/code>\u521b\u5efa\u548c\u4fdd\u5b58SHP\u6587\u4ef6\u7684\u57fa\u672c\u65b9\u6cd5\u548c\u4e00\u4e9b\u9ad8\u7ea7\u6280\u5de7\u3002\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u7ed3\u5408\u5177\u4f53\u9700\u6c42\u548c\u6570\u636e\u7279\u70b9\uff0c\u53ef\u4ee5\u8fdb\u4e00\u6b65\u63a2\u7d22\u548c\u4f18\u5316\u5730\u7406\u6570\u636e\u5904\u7406\u7684\u5de5\u4f5c\u6d41\u7a0b\u3002\u5e0c\u671b\u8fd9\u4e9b\u4fe1\u606f\u80fd\u5e2e\u52a9\u4f60\u66f4\u597d\u5730\u5904\u7406\u5730\u7406\u6570\u636e\u5e76\u751f\u6210SHP\u6587\u4ef6\u3002<\/p>\n<\/p>\n
        \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
         \u5982\u4f55\u5728Python\u4e2d\u751f\u6210shp\u6587\u4ef6\uff1f<\/strong>
        \u5728Python\u4e2d\u751f\u6210shp\u6587\u4ef6\u901a\u5e38\u9700\u8981\u4f7f\u7528\u4e00\u4e9b\u4e13\u95e8\u7684\u5e93\uff0c\u4f8b\u5982Geopandas\u6216Fiona\u3002\u8fd9\u4e9b\u5e93\u63d0\u4f9b\u4e86\u7b80\u5355\u7684\u63a5\u53e3\u6765\u521b\u5efa\u548c\u5199\u5165shp\u6587\u4ef6\u3002\u4f60\u53ef\u4ee5\u901a\u8fc7\u5b89\u88c5\u8fd9\u4e9b\u5e93\u6765\u5f00\u59cb\uff0c\u4f8b\u5982\u4f7f\u7528pip install geopandas<\/code>\u3002\u521b\u5efashp\u6587\u4ef6\u7684\u57fa\u672c\u6b65\u9aa4\u5305\u62ec\u5b9a\u4e49\u51e0\u4f55\u5f62\u72b6\u548c\u5c5e\u6027\uff0c\u7136\u540e\u4f7f\u7528GeoDataFrame<\/code>\u6765\u5b58\u50a8\u8fd9\u4e9b\u6570\u636e\uff0c\u5e76\u6700\u7ec8\u5c06\u5176\u5bfc\u51fa\u4e3ashp\u6587\u4ef6\u3002<\/p>\n
        \u4f7f\u7528Python\u751f\u6210shp\u6587\u4ef6\u9700\u8981\u54ea\u4e9b\u5e93\uff1f<\/strong>
        \u751f\u6210shp\u6587\u4ef6\u5e38\u7528\u7684\u5e93\u6709Geopandas\u548cFiona\u3002Geopandas\u662f\u4e00\u4e2a\u65b9\u4fbf\u7684\u5de5\u5177\uff0c\u53ef\u4ee5\u5904\u7406\u5730\u7406\u6570\u636e\uff0c\u652f\u6301\u591a\u79cd\u6587\u4ef6\u683c\u5f0f\uff1b\u800cFiona\u5219\u66f4\u5e95\u5c42\uff0c\u4e13\u6ce8\u4e8e\u6587\u4ef6\u7684\u8bfb\u5199\u3002\u5982\u679c\u4f60\u53ea\u9700\u8981\u7b80\u5355\u7684\u5730\u7406\u6570\u636e\u5904\u7406\uff0cGeopandas\u53ef\u80fd\u662f\u66f4\u597d\u7684\u9009\u62e9\uff0c\u4f46\u5982\u679c\u9700\u8981\u66f4\u7075\u6d3b\u7684\u63a7\u5236\uff0cFiona\u4f1a\u66f4\u5408\u9002\u3002<\/p>\n
        \u751f\u6210shp\u6587\u4ef6\u65f6\uff0c\u5982\u4f55\u5904\u7406\u5730\u7406\u6570\u636e\u7684\u5750\u6807\u7cfb\uff1f<\/strong>
        \u5728\u751f\u6210shp\u6587\u4ef6\u65f6\uff0c\u5750\u6807\u7cfb\u7684\u5b9a\u4e49\u975e\u5e38\u91cd\u8981\u3002Geopandas\u5141\u8bb8\u4f60\u5728\u521b\u5efaGeoDataFrame<\/code>\u65f6\u6307\u5b9a\u5750\u6807\u53c2\u8003\u7cfb\u7edf\uff08CRS\uff09\u3002\u901a\u5e38\uff0c\u4f60\u9700\u8981\u786e\u4fdd\u6570\u636e\u7684\u5750\u6807\u7cfb\u4e0e\u76ee\u6807shp\u6587\u4ef6\u7684\u4e00\u81f4\u3002\u53ef\u4ee5\u4f7f\u7528to_crs()<\/code>\u65b9\u6cd5\u6765\u8f6c\u6362\u5750\u6807\u7cfb\uff0c\u786e\u4fdd\u5728\u5bfc\u51fa\u65f6\u6570\u636e\u7684\u7a7a\u95f4\u4fe1\u606f\u662f\u51c6\u786e\u7684\u3002<\/p>\n
        \u751f\u6210\u7684shp\u6587\u4ef6\u5982\u4f55\u8fdb\u884c\u53ef\u89c6\u5316\uff1f<\/strong>
        \u751f\u6210\u7684shp\u6587\u4ef6\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u5de5\u5177\u8fdb\u884c\u53ef\u89c6\u5316\u3002\u4f8b\u5982\uff0c\u4f7f\u7528Geopandas\u672c\u8eab\u53ef\u4ee5\u8f7b\u677e\u5730\u7ed8\u5236\u5730\u56fe\uff0c\u53ea\u9700\u8c03\u7528plot()<\/code>\u65b9\u6cd5\u3002\u6b64\u5916\uff0c\u50cfQGIS\u8fd9\u6837\u7684GIS\u8f6f\u4ef6\u4e5f\u53ef\u4ee5\u6253\u5f00\u548c\u7f16\u8f91shp\u6587\u4ef6\uff0c\u4ece\u800c\u4f7f\u5f97\u6570\u636e\u7684\u53ef\u89c6\u5316\u548c\u5206\u6790\u53d8\u5f97\u66f4\u52a0\u76f4\u89c2\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528\u5e93\u5982geopandas\u3001pyshp\u548cfiona\u7b49\u6765\u751f\u6210SHP\u6587\u4ef6\u3001\u5176\u4e2dgeopanda […]","protected":false},"author":3,"featured_media":1014540,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1014535"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1014535"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1014535\/revisions"}],"predecessor-version":[{"id":1014543,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1014535\/revisions\/1014543"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1014540"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1014535"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1014535"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1014535"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}