/csw_unidata.ipynb

## csw_unidata.ipynb
{
  "cells": [
    {
      "metadata": {
        "collapsed": false
      },
      "cell_type": "markdown",
      "source": "# How to search the IOOS CSW catalog with Python tools\n\n\nThis notebook demonstrates a how to query a [Catalog Service for the Web (CSW)](https://en.wikipedia.org/wiki/Catalog_Service_for_the_Web), like the IOOS Catalog, and to parse its results into endpoints that can be used to access the data."
    },
    {
      "metadata": {
        "collapsed": true,
        "trusted": true,
        "ExecuteTime": {
          "start_time": "2017-03-18T12:54:45.379944",
          "end_time": "2017-03-18T12:54:45.392957"
        }
      },
      "cell_type": "code",
      "source": "import os\nimport sys\n\nioos_tools = os.path.join(os.path.pardir)\nsys.path.append(ioos_tools)",
      "execution_count": 1,
      "outputs": []
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "Let's start by creating the search filters.\nThe filter used here constraints the search on a certain geographical region (bounding box), a time span (last week), and some [CF](http://cfconventions.org/Data/cf-standard-names/37/build/cf-standard-name-table.html) variable standard names that represent sea surface temperature."
    },
    {
      "metadata": {
        "collapsed": false,
        "trusted": true,
        "ExecuteTime": {
          "start_time": "2017-03-18T12:54:45.413978",
          "end_time": "2017-03-18T12:54:45.487051"
        }
      },
      "cell_type": "code",
      "source": "from datetime import datetime, timedelta\nimport dateutil.parser\n\nservice_type = 'WMS'\n\nmin_lon, min_lat = -90.0, 30.0 \nmax_lon, max_lat = -80.0, 40.0 \n\nbbox = [min_lon, min_lat, max_lon, max_lat]\ncrs = 'urn:ogc:def:crs:OGC:1.3:CRS84'\n\n# Temporal range: Last week.\nnow = datetime.utcnow()\nstart, stop = now - timedelta(days=(7)), now\n\nstart = dateutil.parser.parse('2017-03-01T00:00:00Z')\nstop  = dateutil.parser.parse('2017-04-01T00:00:00Z')\n\n\n# Ocean Model Names\nmodel_names = ['NAM', 'GFS']",
      "execution_count": 2,
      "outputs": []
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "With these 3 elements it is possible to assemble a [OGC Filter Encoding (FE)](http://www.opengeospatial.org/standards/filter) using the `owslib.fes`\\* module.\n\n\\* OWSLib is a Python package for client programming with Open Geospatial Consortium (OGC) web service (hence OWS) interface standards, and their related content models."
    },
    {
      "metadata": {
        "collapsed": false,
        "trusted": true,
        "ExecuteTime": {
          "start_time": "2017-03-18T12:54:45.493057",
          "end_time": "2017-03-18T12:54:50.660219"
        }
      },
      "cell_type": "code",
      "source": "from owslib import fes\nfrom ioos_tools.ioos import fes_date_filter\n\nkw = dict(wildCard='*', escapeChar='\\\\',\n          singleChar='?', propertyname='apiso:AnyText')\n\nor_filt = fes.Or([fes.PropertyIsLike(literal=('*%s*' % val), **kw)\n                  for val in model_names])\n\nkw = dict(wildCard='*', escapeChar='\\\\',\n          singleChar='?', propertyname='apiso:ServiceType')\n\nserviceType = fes.PropertyIsLike(literal=('*%s*' % service_type), **kw)\n\n\nbegin, end = fes_date_filter(start, stop)\nbbox_crs = fes.BBox(bbox, crs=crs)\n\nfilter_list = [\n    fes.And(\n        [\n            bbox_crs,  # bounding box\n            begin, end,  # start and end date\n            or_filt,  # or conditions (CF variable names)\n            serviceType  # search only for datasets that have WMS services\n        ]\n    )\n]",
      "execution_count": 3,
      "outputs": []
    },
    {
      "metadata": {
        "collapsed": false,
        "trusted": true,
        "ExecuteTime": {
          "start_time": "2017-03-18T12:54:50.668227",
          "end_time": "2017-03-18T12:54:51.159718"
        }
      },
      "cell_type": "code",
      "source": "from owslib.csw import CatalogueServiceWeb\n\n\nendpoint = 'https://data.ioos.us/csw'\n\ncsw = CatalogueServiceWeb(endpoint, timeout=60)",
      "execution_count": 4,
      "outputs": []
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "The `csw` object created from `CatalogueServiceWeb` did not fetched anything yet.\nIt is the method `getrecords2` that uses the filter for the search. However, even though there is a `maxrecords` option, the search is always limited by the server side and there is the need to iterate over multiple calls of `getrecords2` to actually retrieve all records.\nThe `get_csw_records` does exactly that."
    },
    {
      "metadata": {
        "collapsed": true,
        "trusted": true,
        "ExecuteTime": {
          "start_time": "2017-03-18T12:54:51.166725",
          "end_time": "2017-03-18T12:54:51.207766"
        }
      },
      "cell_type": "code",
      "source": "def get_csw_records(csw, filter_list, pagesize=10, maxrecords=1000):\n    \"\"\"Iterate `maxrecords`/`pagesize` times until the requested value in\n    `maxrecords` is reached.\n    \"\"\"\n    from owslib.fes import SortBy, SortProperty\n    # Iterate over sorted results.\n    sortby = SortBy([SortProperty('dc:title', 'ASC')])\n    csw_records = {}\n    startposition = 0\n    nextrecord = getattr(csw, 'results', 1)\n    while nextrecord != 0:\n        csw.getrecords2(constraints=filter_list, startposition=startposition,\n                        maxrecords=pagesize, sortby=sortby)\n        csw_records.update(csw.records)\n        if csw.results['nextrecord'] == 0:\n            break\n        startposition += pagesize + 1  # Last one is included.\n        if startposition >= maxrecords:\n            break\n    csw.records.update(csw_records)",
      "execution_count": 5,
      "outputs": []
    },
    {
      "metadata": {
        "collapsed": false,
        "scrolled": true,
        "trusted": true,
        "ExecuteTime": {
          "start_time": "2017-03-18T12:54:51.216775",
          "end_time": "2017-03-18T12:54:53.838394"
        }
      },
      "cell_type": "code",
      "source": "get_csw_records(csw, filter_list, pagesize=10, maxrecords=1000)\n\nrecords = '\\n'.join(csw.records.keys())\nprint('Found {} records.\\n'.format(len(csw.records.keys())))\nfor key, value in list(csw.records.items()):\n    print('[{}]\\n{}\\n'.format(value.title, key))",
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Found 17 records.\n\n[NAM CONUS 40km/Best NAM CONUS 40km Time Series]\nedu.ucar.unidata:grib/NCEP/NAM/CONUS_40km/conduit/Best\n\n[NAM CONUS 80km/Best NAM CONUS 80km Time Series]\nedu.ucar.unidata:grib/NCEP/NAM/CONUS_80km/Best\n\n[NAM Fireweather Nested/Best NAM Fireweather Nested Time Series/LambertConformal_622X510 (Center 38.53N 78.03W)]\nedu.ucar.unidata:grib/NCEP/NAM/Firewxnest/Best/LambertConformal_622X510-38p53N-78p03W\n\n[NAM Polar 90km/Best NAM Polar 90km Time Series]\nedu.ucar.unidata:grib/NCEP/NAM/Polar_90km/Best\n\n[NOAA/NCEP Global Forecast System (GFS) Atmospheric Model]\nncep_global\n\n[NOAA/NCEP Global Forecast System (GFS) Atmospheric Model: Pacific]\nncep_pac\n\n[WaveWatch III (WW3) Global Wave Model]\nww3_global\n\n[NAM CONUS 12km from NOAAPORT/Best NAM CONUS 12km from NOAAPORT Time Series]\nedu.ucar.unidata:grib/NCEP/NAM/CONUS_12km/Best\n\n[NAM CONUS 12km from CONDUIT/Best NAM CONUS 12km from CONDUIT Time Series]\nedu.ucar.unidata:grib/NCEP/NAM/CONUS_12km/conduit/Best\n\n[NAM Alaska 45km from CONDUIT/Best NAM Alaska 45km from CONDUIT Time Series]\nedu.ucar.unidata:grib/NCEP/NAM/Alaska_45km/conduit/Best\n\n[GFS CONUS 20km/Best GFS CONUS 20km Time Series]\nedu.ucar.unidata:grib/NCEP/GFS/CONUS_20km/Best\n\n[NAM Alaska 11km/Best NAM Alaska 11km Time Series]\nedu.ucar.unidata:grib/NCEP/NAM/Alaska_11km/Best\n\n[GFS CONUS 80km/Best GFS CONUS 80km Time Series]\nedu.ucar.unidata:grib/NCEP/GFS/CONUS_80km/Best\n\n[NAM CONUS 20km/Best NAM CONUS 20km Time Series]\nedu.ucar.unidata:grib/NCEP/NAM/CONUS_20km/noaaport/Best\n\n[NAM Alaska 22km/Best NAM Alaska 22km Time Series]\nedu.ucar.unidata:grib/NCEP/NAM/Alaska_22km/Best\n\n[NAM Alaska 45km from NOAAPORT/Best NAM Alaska 45km from NOAAPORT Time Series]\nedu.ucar.unidata:grib/NCEP/NAM/Alaska_45km/noaaport/Best\n\n[GFS CONUS 95km/Best GFS CONUS 95km Time Series]\nedu.ucar.unidata:grib/NCEP/GFS/CONUS_95km/Best\n\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "collapsed": false,
        "trusted": true,
        "ExecuteTime": {
          "start_time": "2017-03-18T12:54:53.845401",
          "end_time": "2017-03-18T12:54:53.894450"
        }
      },
      "cell_type": "code",
      "source": "csw.request",
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": "b'<csw:GetRecords xmlns:csw=\"http://www.opengis.net/cat/csw/2.0.2\" xmlns:gml=\"http://www.opengis.net/gml\" xmlns:ogc=\"http://www.opengis.net/ogc\" xmlns:xsi=\"http://www.w3.org/2001/XMLSchema-instance\" outputSchema=\"http://www.opengis.net/cat/csw/2.0.2\" outputFormat=\"application/xml\" version=\"2.0.2\" service=\"CSW\" resultType=\"results\" startPosition=\"11\" maxRecords=\"10\" xsi:schemaLocation=\"http://www.opengis.net/cat/csw/2.0.2 http://schemas.opengis.net/csw/2.0.2/CSW-discovery.xsd\"><csw:Query typeNames=\"csw:Record\"><csw:ElementSetName>summary</csw:ElementSetName><csw:Constraint version=\"1.1.0\"><ogc:Filter><ogc:And><ogc:BBOX><ogc:PropertyName>ows:BoundingBox</ogc:PropertyName><gml:Envelope srsName=\"urn:ogc:def:crs:OGC:1.3:CRS84\"><gml:lowerCorner>-90.0 30.0</gml:lowerCorner><gml:upperCorner>-80.0 40.0</gml:upperCorner></gml:Envelope></ogc:BBOX><ogc:PropertyIsLessThanOrEqualTo><ogc:PropertyName>apiso:TempExtent_begin</ogc:PropertyName><ogc:Literal>2017-04-01 00:00</ogc:Literal></ogc:PropertyIsLessThanOrEqualTo><ogc:PropertyIsGreaterThanOrEqualTo><ogc:PropertyName>apiso:TempExtent_end</ogc:PropertyName><ogc:Literal>2017-03-01 00:00</ogc:Literal></ogc:PropertyIsGreaterThanOrEqualTo><ogc:Or><ogc:PropertyIsLike wildCard=\"*\" singleChar=\"?\" escapeChar=\"\\\\\"><ogc:PropertyName>apiso:AnyText</ogc:PropertyName><ogc:Literal>*NAM*</ogc:Literal></ogc:PropertyIsLike><ogc:PropertyIsLike wildCard=\"*\" singleChar=\"?\" escapeChar=\"\\\\\"><ogc:PropertyName>apiso:AnyText</ogc:PropertyName><ogc:Literal>*GFS*</ogc:Literal></ogc:PropertyIsLike></ogc:Or><ogc:PropertyIsLike wildCard=\"*\" singleChar=\"?\" escapeChar=\"\\\\\"><ogc:PropertyName>apiso:ServiceType</ogc:PropertyName><ogc:Literal>*WMS*</ogc:Literal></ogc:PropertyIsLike></ogc:And></ogc:Filter></csw:Constraint><ogc:SortBy><ogc:SortProperty><ogc:PropertyName>dc:title</ogc:PropertyName><ogc:SortOrder>ASC</ogc:SortOrder></ogc:SortProperty></ogc:SortBy></csw:Query></csw:GetRecords>'"
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "metadata": {
        "collapsed": false,
        "trusted": true,
        "ExecuteTime": {
          "start_time": "2017-03-18T12:54:53.902458",
          "end_time": "2017-03-18T12:54:53.916472"
        }
      },
      "cell_type": "code",
      "source": "#write to JSON for use in TerriaJS\ncsw_request = '\"{}\": {}\"'.format('getRecordsTemplate',str(csw.request,'utf-8'))\n\nimport io\nimport json\nwith io.open('query.json', 'a', encoding='utf-8') as f:\n            f.write(json.dumps(csw_request, ensure_ascii=False))\n            f.write('\\n')",
      "execution_count": 8,
      "outputs": []
    }
  ],
  "metadata": {
    "_draft": {
      "nbviewer_url": "https://gist.github.com/8ca00c0386618a87062f9b8b490b3161"
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      "language": "python"
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    "gist": {
      "id": "8ca00c0386618a87062f9b8b490b3161",
      "data": {
        "description": "notebooks_demos/notebooks/csw_unidata.ipynb",
        "public": true
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	{
	"cells": [
	{
	"metadata": {
	"collapsed": false
	},
	"cell_type": "markdown",
	"source": "# How to search the IOOS CSW catalog with Python tools\n\n\nThis notebook demonstrates a how to query a [Catalog Service for the Web (CSW)](https://en.wikipedia.org/wiki/Catalog_Service_for_the_Web), like the IOOS Catalog, and to parse its results into endpoints that can be used to access the data."
	},
	{
	"metadata": {
	"collapsed": true,
	"trusted": true,
	"ExecuteTime": {
	"start_time": "2017-03-18T12:54:45.379944",
	"end_time": "2017-03-18T12:54:45.392957"
	}
	},
	"cell_type": "code",
	"source": "import os\nimport sys\n\nioos_tools = os.path.join(os.path.pardir)\nsys.path.append(ioos_tools)",
	"execution_count": 1,
	"outputs": []
	},
	{
	"metadata": {},
	"cell_type": "markdown",
	"source": "Let's start by creating the search filters.\nThe filter used here constraints the search on a certain geographical region (bounding box), a time span (last week), and some [CF](http://cfconventions.org/Data/cf-standard-names/37/build/cf-standard-name-table.html) variable standard names that represent sea surface temperature."
	},
	{
	"metadata": {
	"collapsed": false,
	"trusted": true,
	"ExecuteTime": {
	"start_time": "2017-03-18T12:54:45.413978",
	"end_time": "2017-03-18T12:54:45.487051"
	}
	},
	"cell_type": "code",
	"source": "from datetime import datetime, timedelta\nimport dateutil.parser\n\nservice_type = 'WMS'\n\nmin_lon, min_lat = -90.0, 30.0 \nmax_lon, max_lat = -80.0, 40.0 \n\nbbox = [min_lon, min_lat, max_lon, max_lat]\ncrs = 'urn:ogc:def:crs:OGC:1.3:CRS84'\n\n# Temporal range: Last week.\nnow = datetime.utcnow()\nstart, stop = now - timedelta(days=(7)), now\n\nstart = dateutil.parser.parse('2017-03-01T00:00:00Z')\nstop = dateutil.parser.parse('2017-04-01T00:00:00Z')\n\n\n# Ocean Model Names\nmodel_names = ['NAM', 'GFS']",
	"execution_count": 2,
	"outputs": []
	},
	{
	"metadata": {},
	"cell_type": "markdown",
	"source": "With these 3 elements it is possible to assemble a [OGC Filter Encoding (FE)](http://www.opengeospatial.org/standards/filter) using the `owslib.fes`\\* module.\n\n\\* OWSLib is a Python package for client programming with Open Geospatial Consortium (OGC) web service (hence OWS) interface standards, and their related content models."
	},
	{
	"metadata": {
	"collapsed": false,
	"trusted": true,
	"ExecuteTime": {
	"start_time": "2017-03-18T12:54:45.493057",
	"end_time": "2017-03-18T12:54:50.660219"
	}
	},
	"cell_type": "code",
	"source": "from owslib import fes\nfrom ioos_tools.ioos import fes_date_filter\n\nkw = dict(wildCard='', escapeChar='\\\\',\n singleChar='?', propertyname='apiso:AnyText')\n\nor_filt = fes.Or([fes.PropertyIsLike(literal=('%s' % val), kw)\n for val in model_names])\n\nkw = dict(wildCard='', escapeChar='\\\\',\n singleChar='?', propertyname='apiso:ServiceType')\n\nserviceType = fes.PropertyIsLike(literal=('%s' % service_type), **kw)\n\n\nbegin, end = fes_date_filter(start, stop)\nbbox_crs = fes.BBox(bbox, crs=crs)\n\nfilter_list = [\n fes.And(\n [\n bbox_crs, # bounding box\n begin, end, # start and end date\n or_filt, # or conditions (CF variable names)\n serviceType # search only for datasets that have WMS services\n ]\n )\n]",
	"execution_count": 3,
	"outputs": []
	},
	{
	"metadata": {
	"collapsed": false,
	"trusted": true,
	"ExecuteTime": {
	"start_time": "2017-03-18T12:54:50.668227",
	"end_time": "2017-03-18T12:54:51.159718"
	}
	},
	"cell_type": "code",
	"source": "from owslib.csw import CatalogueServiceWeb\n\n\nendpoint = 'https://data.ioos.us/csw'\n\ncsw = CatalogueServiceWeb(endpoint, timeout=60)",
	"execution_count": 4,
	"outputs": []
	},
	{
	"metadata": {},
	"cell_type": "markdown",
	"source": "The `csw` object created from `CatalogueServiceWeb` did not fetched anything yet.\nIt is the method `getrecords2` that uses the filter for the search. However, even though there is a `maxrecords` option, the search is always limited by the server side and there is the need to iterate over multiple calls of `getrecords2` to actually retrieve all records.\nThe `get_csw_records` does exactly that."
	},
	{
	"metadata": {
	"collapsed": true,
	"trusted": true,
	"ExecuteTime": {
	"start_time": "2017-03-18T12:54:51.166725",
	"end_time": "2017-03-18T12:54:51.207766"
	}
	},
	"cell_type": "code",
	"source": "def get_csw_records(csw, filter_list, pagesize=10, maxrecords=1000):\n \"\"\"Iterate `maxrecords`/`pagesize` times until the requested value in\n `maxrecords` is reached.\n \"\"\"\n from owslib.fes import SortBy, SortProperty\n # Iterate over sorted results.\n sortby = SortBy([SortProperty('dc:title', 'ASC')])\n csw_records = {}\n startposition = 0\n nextrecord = getattr(csw, 'results', 1)\n while nextrecord != 0:\n csw.getrecords2(constraints=filter_list, startposition=startposition,\n maxrecords=pagesize, sortby=sortby)\n csw_records.update(csw.records)\n if csw.results['nextrecord'] == 0:\n break\n startposition += pagesize + 1 # Last one is included.\n if startposition >= maxrecords:\n break\n csw.records.update(csw_records)",
	"execution_count": 5,
	"outputs": []
	},
	{
	"metadata": {
	"collapsed": false,
	"scrolled": true,
	"trusted": true,
	"ExecuteTime": {
	"start_time": "2017-03-18T12:54:51.216775",
	"end_time": "2017-03-18T12:54:53.838394"
	}
	},
	"cell_type": "code",
	"source": "get_csw_records(csw, filter_list, pagesize=10, maxrecords=1000)\n\nrecords = '\\n'.join(csw.records.keys())\nprint('Found {} records.\\n'.format(len(csw.records.keys())))\nfor key, value in list(csw.records.items()):\n print('[{}]\\n{}\\n'.format(value.title, key))",
	"execution_count": 6,
	"outputs": [
	{
	"output_type": "stream",
	"text": "Found 17 records.\n\n[NAM CONUS 40km/Best NAM CONUS 40km Time Series]\nedu.ucar.unidata:grib/NCEP/NAM/CONUS_40km/conduit/Best\n\n[NAM CONUS 80km/Best NAM CONUS 80km Time Series]\nedu.ucar.unidata:grib/NCEP/NAM/CONUS_80km/Best\n\n[NAM Fireweather Nested/Best NAM Fireweather Nested Time Series/LambertConformal_622X510 (Center 38.53N 78.03W)]\nedu.ucar.unidata:grib/NCEP/NAM/Firewxnest/Best/LambertConformal_622X510-38p53N-78p03W\n\n[NAM Polar 90km/Best NAM Polar 90km Time Series]\nedu.ucar.unidata:grib/NCEP/NAM/Polar_90km/Best\n\n[NOAA/NCEP Global Forecast System (GFS) Atmospheric Model]\nncep_global\n\n[NOAA/NCEP Global Forecast System (GFS) Atmospheric Model: Pacific]\nncep_pac\n\n[WaveWatch III (WW3) Global Wave Model]\nww3_global\n\n[NAM CONUS 12km from NOAAPORT/Best NAM CONUS 12km from NOAAPORT Time Series]\nedu.ucar.unidata:grib/NCEP/NAM/CONUS_12km/Best\n\n[NAM CONUS 12km from CONDUIT/Best NAM CONUS 12km from CONDUIT Time Series]\nedu.ucar.unidata:grib/NCEP/NAM/CONUS_12km/conduit/Best\n\n[NAM Alaska 45km from CONDUIT/Best NAM Alaska 45km from CONDUIT Time Series]\nedu.ucar.unidata:grib/NCEP/NAM/Alaska_45km/conduit/Best\n\n[GFS CONUS 20km/Best GFS CONUS 20km Time Series]\nedu.ucar.unidata:grib/NCEP/GFS/CONUS_20km/Best\n\n[NAM Alaska 11km/Best NAM Alaska 11km Time Series]\nedu.ucar.unidata:grib/NCEP/NAM/Alaska_11km/Best\n\n[GFS CONUS 80km/Best GFS CONUS 80km Time Series]\nedu.ucar.unidata:grib/NCEP/GFS/CONUS_80km/Best\n\n[NAM CONUS 20km/Best NAM CONUS 20km Time Series]\nedu.ucar.unidata:grib/NCEP/NAM/CONUS_20km/noaaport/Best\n\n[NAM Alaska 22km/Best NAM Alaska 22km Time Series]\nedu.ucar.unidata:grib/NCEP/NAM/Alaska_22km/Best\n\n[NAM Alaska 45km from NOAAPORT/Best NAM Alaska 45km from NOAAPORT Time Series]\nedu.ucar.unidata:grib/NCEP/NAM/Alaska_45km/noaaport/Best\n\n[GFS CONUS 95km/Best GFS CONUS 95km Time Series]\nedu.ucar.unidata:grib/NCEP/GFS/CONUS_95km/Best\n\n",
	"name": "stdout"
	}
	]
	},
	{
	"metadata": {
	"collapsed": false,
	"trusted": true,
	"ExecuteTime": {
	"start_time": "2017-03-18T12:54:53.845401",
	"end_time": "2017-03-18T12:54:53.894450"
	}
	},
	"cell_type": "code",
	"source": "csw.request",
	"execution_count": 7,
	"outputs": [
	{
	"output_type": "execute_result",
	"data": {
	"text/plain": "b'<csw:GetRecords xmlns:csw=\"http://www.opengis.net/cat/csw/2.0.2\" xmlns:gml=\"http://www.opengis.net/gml\" xmlns:ogc=\"http://www.opengis.net/ogc\" xmlns:xsi=\"http://www.w3.org/2001/XMLSchema-instance\" outputSchema=\"http://www.opengis.net/cat/csw/2.0.2\" outputFormat=\"application/xml\" version=\"2.0.2\" service=\"CSW\" resultType=\"results\" startPosition=\"11\" maxRecords=\"10\" xsi:schemaLocation=\"http://www.opengis.net/cat/csw/2.0.2 http://schemas.opengis.net/csw/2.0.2/CSW-discovery.xsd\"><csw:Query typeNames=\"csw:Record\"><csw:ElementSetName>summary</csw:ElementSetName><csw:Constraint version=\"1.1.0\"><ogc:Filter><ogc:And><ogc:BBOX><ogc:PropertyName>ows:BoundingBox</ogc:PropertyName><gml:Envelope srsName=\"urn:ogc:def:crs:OGC:1.3:CRS84\"><gml:lowerCorner>-90.0 30.0</gml:lowerCorner><gml:upperCorner>-80.0 40.0</gml:upperCorner></gml:Envelope></ogc:BBOX><ogc:PropertyIsLessThanOrEqualTo><ogc:PropertyName>apiso:TempExtent_begin</ogc:PropertyName><ogc:Literal>2017-04-01 00:00</ogc:Literal></ogc:PropertyIsLessThanOrEqualTo><ogc:PropertyIsGreaterThanOrEqualTo><ogc:PropertyName>apiso:TempExtent_end</ogc:PropertyName><ogc:Literal>2017-03-01 00:00</ogc:Literal></ogc:PropertyIsGreaterThanOrEqualTo><ogc:Or><ogc:PropertyIsLike wildCard=\"\" singleChar=\"?\" escapeChar=\"\\\\\"><ogc:PropertyName>apiso:AnyText</ogc:PropertyName><ogc:Literal>NAM</ogc:Literal></ogc:PropertyIsLike><ogc:PropertyIsLike wildCard=\"\" singleChar=\"?\" escapeChar=\"\\\\\"><ogc:PropertyName>apiso:AnyText</ogc:PropertyName><ogc:Literal>GFS</ogc:Literal></ogc:PropertyIsLike></ogc:Or><ogc:PropertyIsLike wildCard=\"\" singleChar=\"?\" escapeChar=\"\\\\\"><ogc:PropertyName>apiso:ServiceType</ogc:PropertyName><ogc:Literal>WMS*</ogc:Literal></ogc:PropertyIsLike></ogc:And></ogc:Filter></csw:Constraint><ogc:SortBy><ogc:SortProperty><ogc:PropertyName>dc:title</ogc:PropertyName><ogc:SortOrder>ASC</ogc:SortOrder></ogc:SortProperty></ogc:SortBy></csw:Query></csw:GetRecords>'"
	},
	"metadata": {},
	"execution_count": 7
	}
	]
	},
	{
	"metadata": {
	"collapsed": false,
	"trusted": true,
	"ExecuteTime": {
	"start_time": "2017-03-18T12:54:53.902458",
	"end_time": "2017-03-18T12:54:53.916472"
	}
	},
	"cell_type": "code",
	"source": "#write to JSON for use in TerriaJS\ncsw_request = '\"{}\": {}\"'.format('getRecordsTemplate',str(csw.request,'utf-8'))\n\nimport io\nimport json\nwith io.open('query.json', 'a', encoding='utf-8') as f:\n f.write(json.dumps(csw_request, ensure_ascii=False))\n f.write('\\n')",
	"execution_count": 8,
	"outputs": []
	}
	],
	"metadata": {
	"_draft": {
	"nbviewer_url": "https://gist.github.com/8ca00c0386618a87062f9b8b490b3161"
	},
	"kernelspec": {
	"name": "python3",
	"display_name": "Python 3",
	"language": "python"
	},
	"gist": {
	"id": "8ca00c0386618a87062f9b8b490b3161",
	"data": {
	"description": "notebooks_demos/notebooks/csw_unidata.ipynb",
	"public": true
	}
	},
	"language_info": {
	"version": "3.5.3",
	"file_extension": ".py",
	"name": "python",
	"pygments_lexer": "ipython3",
	"nbconvert_exporter": "python",
	"codemirror_mode": {
	"version": 3,
	"name": "ipython"
	},
	"mimetype": "text/x-python"
	}
	},
	"nbformat": 4,
	"nbformat_minor": 0
	}