lll = {'database': "test",
'user': 'postgres', 'password': 'postgis',
'host': '127.0.0.1', 'port': '5432'}
engine = create_engine(
f"postgresql+psycopg2://{lll['user']}:{lll['password']}@{lll['host']}:{lll['port']}/{lll['database']}")
# print(engine)
map_data = cq
spatial_ref = int(map_data.crs.srs.split(':')[-1]) # 读取shp的空间参考
print(spatial_ref, type(spatial_ref))
map_data['geometry'] = map_data['geometry'].apply(lambda x: WKTElement(x.wkt, spatial_ref))
# geopandas 的to_sql()方法继承自pandas, 将GeoDataFrame中的数据写入数据库
print(map_data)
map_data.to_sql(
name='tbl_name1',
con=engine,
index=False,
if_exists='replace', # 如果表存在，则替换原有表
chunksize=1000, # 设置一次入库大小，防止数据量太大卡顿
# 指定geometry的类型,这里直接指定geometry_type='GEOMETRY'，防止MultiPolygon无法写入
dtype={'geometry': Geometry(geometry_type='GEOMETRY', srid=spatial_ref)},
method='multi'
)
标签：shp,map,ref,geometry,geopandas,spatial,postgis,lll,data From： https://www.cnblogs.com/luochunxi/p/16627488.html