{"id":4864,"date":"2018-03-22T06:37:43","date_gmt":"2018-03-22T13:37:43","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/?p=4864"},"modified":"2025-06-13T23:43:11","modified_gmt":"2025-06-14T06:43:11","slug":"geospatial-queries-using-python-search-cities","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/ko\/geospatial-queries-using-python-search-cities\/","title":{"rendered":"\uc9c0\ub9ac\uacf5\uac04 \ucffc\ub9ac: Python\uc744 \uc0ac\uc6a9\ud558\uc5ec \ub3c4\uc2dc \uac80\uc0c9\ud558\uae30"},"content":{"rendered":"

\"16665891<\/h3>\n

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\uc9c0\ub9ac\uacf5\uac04 \ucffc\ub9ac: Python\uc744 \uc0ac\uc6a9\ud558\uc5ec \ub3c4\uc2dc \uac80\uc0c9\ud558\uae30<\/strong><\/h2>\n

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\uc624\ub298 \uc18c\uac1c\ud574\ub4dc\ub9b4 \ub0b4\uc6a9\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4. \uc9c0\ub9ac\uacf5\uac04 \ucffc\ub9ac<\/a><\/u>\u00a0\ub97c \uc0ac\uc6a9\ud569\ub2c8\ub2e4. \uc9c0\ub9ac\uacf5\uac04 \ucffc\ub9ac<\/a><\/u>\u00a0\ub97c \uc0ac\uc6a9\ud558\uba74 \uc9c0\ub9ac\uc801 \uc704\uce58\ub97c \uae30\uc900\uc73c\ub85c \ubb38\uc11c\ub97c \uac80\uc0c9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n

\ud568\uaed8 \ud30c\uc774\uc36c\uc5d0\uc11c \ub2e4\uc74c\uc744 \uc0ac\uc6a9\ud558\ub294 \ub3c4\uad6c\ub97c \uc791\uc131\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4. \uc9c0\ub9ac\uacf5\uac04 \ucffc\ub9ac<\/a><\/u>\u00a0\uc640 \ud568\uaed8 Couchbase REST API<\/a><\/u>\u00a0\uadf8\ub9ac\uace0 \uce74\uc6b0\uce58\ubca0\uc774\uc2a4 \uc804\uccb4 \ud14d\uc2a4\ud2b8 \uac80\uc0c9<\/a><\/u>\ub97c \ud074\ub9ad\ud558\uba74 \ub3c4\uc2dc \ub370\uc774\ud130\ubca0\uc774\uc2a4\ub97c \uac80\uc0c9\ud558\ub294 \ub370 \ub3c4\uc6c0\uc774 \ub429\ub2c8\ub2e4.<\/p>\n

\uc804\uc81c \uc870\uac74<\/strong><\/h2>\n

\uc885\uc18d\uc131<\/strong><\/h3>\n

\uc774 \ubb38\uc11c\uc5d0\uc11c\ub294 \ub2e4\uc74c\uc744 \uc0ac\uc6a9\ud588\uc2b5\ub2c8\ub2e4. \uce74\uc6b0\uce58\ubca0\uc774\uc2a4 \uc5d4\ud130\ud504\ub77c\uc774\uc988 \uc5d0\ub514\uc158<\/a> 5.1.0 \ube4c\ub4dc 5552 \ubc0f Python<\/a> 3.6.4.<\/p>\n

\uc774 \ubb38\uc11c\uc758 \uc2a4\ub2c8\ud3ab\uc744 \uc2e4\ud589\ud558\ub824\uba74 pip\ub97c \ud1b5\ud574 Couchbase 2.3(\uc800\ub294 2.3.4\ub97c \uc0ac\uc6a9 \uc911\uc785\ub2c8\ub2e4)\uc744 \uc124\uce58\ud574\uc57c \ud569\ub2c8\ub2e4.<\/p>\n

\uce74\uc6b0\uce58\ubca0\uc774\uc2a4<\/strong><\/h3>\n
    \n
  1. \ub3c4\uc2dc \ubc84\ud0b7 \ub9cc\ub4e4\uae30<\/li>\n
  2. \uc9c0\uc624\ud3ec\uc778\ud2b8 \uc720\ud615\uc758 \uc9c0\ub9ac\uc801 \ud544\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub3c4\uc2dc \uac80\uc0c9\uc744 \ub9cc\ub4ed\ub2c8\ub2e4. \uc774\uc5d0 \ub300\ud55c \uc790\uc138\ud55c \ub0b4\uc6a9\uc740 \ud558\uc704 \ud544\ub4dc \uc0bd\uc785<\/a><\/u>\u00a0\ubb38\uc11c\uc758 \uc77c\ubd80\uc785\ub2c8\ub2e4.<\/li>\n<\/ol>\n

    \uc544\ub798 \uc774\ubbf8\uc9c0\uc640 \uac19\uc774 \ud45c\uc2dc\ub418\uc5b4\uc57c \ud569\ub2c8\ub2e4:<\/p>\n

    \"image<\/p>\n

    Couchbase\uc5d0 \ub370\uc774\ud130 \ucc44\uc6b0\uae30<\/strong><\/h2>\n

    \uc6b0\uc120, \uc6b4\ub3d9\uc5d0 \ud544\uc694\ud55c \ub370\uc774\ud130\uac00 \ud544\uc694\ud569\ub2c8\ub2e4. \uc774\ub97c \uc704\ud574 \ub2e4\uc74c\uc758 \ub3c4\uc2dc \ub370\uc774\ud130\ubca0\uc774\uc2a4\ub97c \uc0ac\uc6a9\ud560 \uac83\uc785\ub2c8\ub2e4. geonames.org<\/a><\/u>.<\/p>\n

    \uc9c0\uc624\ub124\uc784\uc5d0\ub294 \ub3c4\uc2dc \ubaa9\ub85d\uacfc \uc6b0\ud3b8\ubc88\ud638 \ubaa9\ub85d\uc774\ub77c\ub294 \ub450 \uac00\uc9c0 \uc8fc\uc694 \ub370\uc774\ud130\ubca0\uc774\uc2a4\uac00 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n

    \ubaa8\ub450 \uad6d\uac00\ubcc4\ub85c \uc774\ub984, \uc88c\ud45c, \uc778\uad6c, \uc2dc\uac04\ub300, \uad6d\uac00 \ucf54\ub4dc \ub4f1\uc758 \ud574\ub2f9 \uc815\ubcf4\uac00 \ud3ec\ud568\ub41c \uad6d\uac00\ubcc4\ub85c \uadf8\ub8f9\ud654\ub418\uc5b4 \uc788\uc2b5\ub2c8\ub2e4. \ub458 \ub2e4 CSV \ud615\uc2dd\uc785\ub2c8\ub2e4.<\/p>\n

    \uc774 \uc5f0\uc2b5\uc5d0\uc11c\ub294 \ub3c4\uc2dc \ubaa9\ub85d\uc744 \uc0ac\uc6a9\ud558\uaca0\uc2b5\ub2c8\ub2e4. \uc800\ub294 PL.zip<\/a><\/u>\u00a0\uc5d0\uc11c \uc6d0\ud558\ub294 \uac83\uc744 \uc790\uc720\ub86d\uac8c \uc120\ud0dd\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub3c4\uc2dc \ubaa9\ub85d<\/a><\/u>.<\/p>\n

    \ub370\uc774\ud130 \ubaa8\ub378<\/strong><\/h3>\n

    \ub3c4\uc2dc \ud074\ub798\uc2a4\ub294 \uc804\uccb4 \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc5d0\uc11c \uc0ac\uc6a9\ud560 \ub2e8\uc77c \ub3c4\uc2dc\uc758 \ud45c\ud604\uc774 \ub420 \uac83\uc785\ub2c8\ub2e4. \uc774\ub97c \ubaa8\ub378\ub85c \ucea1\uc290\ud654\ud568\uc73c\ub85c\uc368 API\ub97c \ud1b5\ud569\ud558\uace0 \ubcc0\uacbd\ub420 \uc218 \uc788\ub294 \ud0c0\uc0ac \ub370\uc774\ud130 \uc18c\uc2a4(\uc608: CSV \ud30c\uc77c)\uc5d0 \uc758\uc874\ud560 \ud544\uc694\uac00 \uc5c6\uc2b5\ub2c8\ub2e4.<\/p>\n

    \ub300\ubd80\ubd84\uc758 \uc2a4\ub2c8\ud3ab\uc740 (\ub2ec\ub9ac \uba85\uc2dc\ub418\uc9c0 \uc54a\ub294 \ud55c) core.py \ud30c\uc77c\uc5d0 \uc788\uc2b5\ub2c8\ub2e4. \ub530\ub77c\uc11c \uc804\uccb4 \ub0b4\uc6a9\uc744 \ub36e\uc5b4\uc4f0\uc9c0 \ub9d0\uace0 \uc5c5\ub370\uc774\ud2b8(\ud2b9\ud788 \uc0c8 \uac00\uc838\uc624\uae30\ub97c \ucd94\uac00\ud560 \ub54c)\ud558\ub294 \uac83\uc744 \uc78a\uc9c0 \ub9c8\uc138\uc694.<\/p>\n

    # core.py\r\nclass City:\r\n   def __init__(self, geonameid, feature_class, name, population, lat, lon):\r\n       self.geonameid = geonameid\r\n       self.feature_class = feature_class\r\n       self.name = name\r\n       self.population = population\r\n       self.lat = lat\r\n       self.lon = lon\r\n\r\n   @classmethod\r\n   def from_csv_row(cls, row):\r\n       return cls(row[0], row[7], row[1], row[12], row[4], row[5])<\/pre>\n
     <\/p>\n
    \ub3c4\uc2dc\ub97c \ucc98\ub9ac\ud558\ub294 CSV \ubc18\ubcf5\uae30<\/strong><\/h3>\n
    \ubaa8\ub378 \ud074\ub798\uc2a4\uac00 \uc788\uc73c\ubbc0\ub85c \uc774\uc81c CSV \ud30c\uc77c\uc5d0\uc11c \ub3c4\uc2dc\ub97c \uc77d\ub294 \ub370 \ub3c4\uc6c0\uc774 \ub418\ub294 \uc774\ud130\ub808\uc774\ud130\ub97c \uc900\ube44\ud560 \ucc28\ub840\uc785\ub2c8\ub2e4.<\/p>\n
    # core.py\r\nimport csv\r\nfrom collections import Iterator\r\n\r\nclass CitiesCsvIterator(Iterator):\r\n   def __init__(self, path):\r\n       self._path = path\r\n       self._fp = None\r\n       self._csv_reader = None\r\n\r\n   def __enter__(self):\r\n       self._fp = open(self._path, 'r')\r\n       self._csv_reader = csv.reader(self._fp, delimiter='\\t')\r\n\r\n       return self\r\n\r\n   def __exit__(self, exc_type, exc_val, exc_tb):\r\n       self._fp.close()\r\n\r\n   def __next__(self):\r\n       return City.from_csv_row(next(self._csv_reader))\r\n<\/pre>\n
    \uce74\uc6b0\uce58\ubca0\uc774\uc2a4 \ubc84\ud0b7\uc5d0 \ub3c4\uc2dc \uc0bd\uc785\ud558\uae30<\/strong><\/h3>\n
    \ub3c4\uc2dc\ub97c \ud45c\ud604\ud558\ub294 \ubc29\uc2dd\uc744 \ud1b5\ud569\ud588\uc73c\uba70, csv \ud30c\uc77c\uc5d0\uc11c \ub3c4\uc2dc\ub97c \uc77d\ub294 \uc774\ud130\ub808\uc774\ud130\uac00 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
    \uc774\uc81c \uc774 \ub370\uc774\ud130\ub97c \uae30\ubcf8 \ub370\uc774\ud130 \uc18c\uc2a4\uc5d0 \ub123\uc744 \ucc28\ub840\uc785\ub2c8\ub2e4, \uce74\uc6b0\uce58\ubca0\uc774\uc2a4<\/a><\/u>.<\/p>\n
    # core.py\r\nimport logging\r\nimport sys\r\nfrom couchbase.cluster import Cluster, PasswordAuthenticator\r\n\r\n\r\nlogger = logging.getLogger()\r\nlogger.setLevel(logging.DEBUG)\r\nlogger.addHandler(logging.StreamHandler(sys.stdout))\r\n\r\n\r\ndef get_bucket(username, password, connection_string='couchbase:\/\/localhost'):\r\n   cluster = Cluster(connection_string)\r\n   authenticator = PasswordAuthenticator(username, password)\r\n   cluster.authenticate(authenticator)\r\n\r\n   return cluster.open_bucket('cities')\r\n\r\n\r\nclass CitiesService:\r\n   def __init__(self, bucket):\r\n       self._bucket = bucket\r\n\r\n   def load_from_csv(self, path):\r\n       with CitiesCsvIterator(path) as cities_iterator:\r\n           for city in cities_iterator:\r\n               if city.feature_class not in ('PPL', 'PPLA', 'PPLA2', 'PPLA3',\r\n                                             'PPLA4', 'PPLC'):\r\n                   continue\r\n\r\n               logger.info(f'Inserting {city.geonameid}')\r\n               self._bucket.upsert(\r\n                   city.geonameid,\r\n                   {\r\n                       'name': city.name,\r\n                       'feature_class': city.feature_class,\r\n                       'population': city.population,\r\n                       'geo': {'lat': float(city.lat),\r\n                               'lon': float(city.lon)}\r\n                   }\r\n               )\r\n\r\n<\/pre>\n
     <\/p>\n
    \uc9c0\uae08\uae4c\uc9c0 \uc791\uc131\ud55c \ubaa8\ub4e0 \ub0b4\uc6a9\uc774 \uc81c\ub300\ub85c \uc791\ub3d9\ud558\ub294\uc9c0 \ud655\uc778\ud558\uae30 \uc704\ud574 CSV \ucf58\ud150\uce20\ub97c Couchbase\uc5d0 \ub85c\ub4dc\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n
    # core.py\r\n\r\nbucket = get_bucket('admin', 'test123456')\r\ncities_service = CitiesService(bucket)\r\ncities_service.load_from_csv('~\/directory-with-cities\/PL\/PL.txt', bucket)<\/pre>\n
     <\/p>\n
    \uc774 \uc2dc\uc810\uc5d0\uc11c Couchbase \ubc84\ud0b7\uc5d0 \ub3c4\uc2dc\uac00 \ub85c\ub4dc\ub418\uc5b4 \uc788\uc5b4\uc57c \ud569\ub2c8\ub2e4. \uc18c\uc694 \uc2dc\uac04\uc740 \uc120\ud0dd\ud55c \uad6d\uac00\uc5d0 \ub530\ub77c \ub2e4\ub985\ub2c8\ub2e4.<\/p>\n
    \ub3c4\uc2dc \uac80\uc0c9<\/strong><\/h2>\n
    \ub370\uc774\ud130\ub85c \ubc84\ud0b7\uc744 \uc900\ube44\ud588\uc73c\ub2c8 \uc774\uc81c CitiesService\ub85c \ub3cc\uc544\uc640\uc11c \ub3c4\uc2dc \uac80\uc0c9\uc5d0 \ub3c4\uc6c0\uc774 \ub420 \uba87 \uac00\uc9c0 \ubc29\ubc95\uc744 \uc900\ube44\ud560 \ucc28\ub840\uc785\ub2c8\ub2e4.<\/p>\n
    \ud558\uc9c0\ub9cc \uc2dc\uc791\ud558\uae30 \uc804\uc5d0 \ub2e4\uc74c \uba54\uc11c\ub4dc\ub97c \ucd94\uac00\ud558\uc5ec City \ud074\ub798\uc2a4\ub97c \uc57d\uac04 \uc218\uc815\ud574\uc57c \ud569\ub2c8\ub2e4:<\/p>\n
    # core.py\r\n\r\n@classmethod\r\ndef\u00a0from_couchbase_dict(cls, row):\r\nfields =\u00a0row['fields']\r\n\r\nreturn\u00a0cls(row['id'],\r\nfields['feature_class'],\r\nfields['name'],\r\nfields['population'],\r\nfields['geo'][1],\r\nfields['geo'][0])\r\n\r\n<\/pre>\n
    \uc774\uac83\uc774 CitiesService\uc5d0\uc11c \uad6c\ud604\ud560 \ubc29\ubc95\uc758 \ubaa9\ub85d\uc785\ub2c8\ub2e4:<\/p>\n