Source code for malleefowl.processes.wps_esgsearch

import json
from datetime import datetime
from dateutil import parser as date_parser

from pywps import Process
from pywps import LiteralInput
from pywps import ComplexInput
from pywps import LiteralOutput
from pywps import ComplexOutput
from pywps import Format, FORMATS
from import Metadata

from import ESGSearch

import logging
LOGGER = logging.getLogger(__name__)

[docs]class ESGSearchProcess(Process): """ wps wrapper for esg search. TODO: bbox constraint for datasets """ def __init__(self): inputs = [ LiteralInput('url', 'URL', data_type='string', abstract="URL of ESGF Search Index. Example:", min_occurs=1, max_occurs=1, default="", ), LiteralInput('distrib', 'Distributed', data_type='boolean', abstract="If flag is set then a distributed search will be run.", min_occurs=0, max_occurs=1, default='0', ), LiteralInput('replica', 'Replica', data_type='boolean', abstract="If flag is set then search will include replicated datasets.", min_occurs=0, max_occurs=1, default='False', ), LiteralInput('latest', 'Latest', data_type='boolean', abstract="If flag is set then search will include only latest datasets.", min_occurs=0, max_occurs=1, default='True', ), LiteralInput('temporal', 'Temporal', data_type='boolean', abstract="If flag is set then search will use temporal filter.", min_occurs=0, max_occurs=1, default='1', ), LiteralInput('search_type', 'Search Type', data_type='string', abstract="Search on Datasets, Files or Aggregations.", min_occurs=0, max_occurs=1, default='Dataset', allowed_values=['Dataset', 'File', 'Aggregation'] ), LiteralInput('constraints', 'Constraints', data_type='string', abstract="Constraints as list of key/value pairs." "Example: project:CORDEX, time_frequency:mon, variable:tas", min_occurs=1, max_occurs=1, default="project:CORDEX, time_frequency:mon, variable:tas", ), LiteralInput('query', 'Query', data_type='string', abstract="Freetext query. For Example: temperatue", min_occurs=0, max_occurs=1, default='*', ), LiteralInput('start', 'Start', data_type='dateTime', abstract="Startime: 2000-01-11T12:00:00Z", min_occurs=0, max_occurs=1, ), LiteralInput('end', 'End', data_type='dateTime', abstract="Endtime: 2005-12-31T12:00:00Z", min_occurs=0, max_occurs=1, ), LiteralInput('limit', 'Limit', data_type='integer', abstract="Maximum number of datasets in search result", min_occurs=0, max_occurs=1, default='10', allowed_values=[0, 1, 2, 5, 10, 20, 50, 100, 200] ), LiteralInput('offset', 'Offset', data_type='integer', abstract="Start search of datasets at offset.", min_occurs=0, max_occurs=1, default='0', ), ] outputs = [ ComplexOutput('output', 'Search Result', abstract="JSON document with search result", as_reference=True, supported_formats=[Format('application/json')]), ComplexOutput('summary', 'Search Result Summary', abstract="JSON document with search result summary", as_reference=True, supported_formats=[Format('application/json')]), ComplexOutput('facet_counts', 'Facet Counts', abstract="JSON document with facet counts for constraints.", as_reference=True, supported_formats=[Format('application/json')]), ] super(ESGSearchProcess, self).__init__( self._handler, identifier="esgsearch", title="ESGF Search", version="0.6", abstract="Search ESGF datasets, files and aggreations.", metadata=[ Metadata('Birdhouse', ''), Metadata('User Guide', ''), ], inputs=inputs, outputs=outputs, status_supported=True, store_supported=True, ) def _handler(self, request, response): distrib = False if 'distrib' in request.inputs: distrib = request.inputs['distrib'][0].data replica = False if 'replica' in request.inputs: replica = request.inputs['replica'][0].data latest = True if 'latest' in request.inputs: latest = request.inputs['latest'][0].data esgsearch = ESGSearch( url=request.inputs['url'][0].data, distrib=distrib, replica=replica, latest=latest, ) constrains_str = request.inputs['constraints'][0].data.strip() constraints = [] for constrain in constrains_str.split(','): key, value = constrain.split(':') constraints.append((key.strip(), value.strip())) if 'start' in request.inputs: start = request.inputs['start'][0].data else: start = None if 'end' in request.inputs: end = request.inputs['end'][0].data else: end = None if 'offset' in request.inputs: offset = request.inputs['offset'][0].data else: offset = 0 if 'limit' in request.inputs: limit = request.inputs['limit'][0].data else: limit = 10 if 'query' in request.inputs: query = request.inputs['query'][0].data else: query = '*' if 'search_type' in request.inputs: search_type = request.inputs['search_type'][0].data else: search_type = 'Dataset' temporal = True if 'temporal' in request.inputs: temporal = request.inputs['temporal'][0].data (result, summary, facet_counts) = constraints=constraints, query=query, start=start, end=end, search_type=search_type, limit=limit, offset=offset, temporal=temporal) with open('out.json', 'w') as fp: json.dump(obj=result, fp=fp, indent=4, sort_keys=True) response.outputs['output'].file = with open('summary.json', 'w') as fp: json.dump(obj=summary, fp=fp, indent=4, sort_keys=True) response.outputs['summary'].file = with open('counts.json', 'w') as fp: json.dump(obj=facet_counts, fp=fp, indent=4, sort_keys=True) response.outputs['facet_counts'].file = return response