377 lines
14 KiB
Python
377 lines
14 KiB
Python
# Copyright (c) 2012 Mitch Garnaat http://garnaat.org/
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# Copyright (c) 2012 Amazon.com, Inc. or its affiliates.
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# All Rights Reserved
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#
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# Permission is hereby granted, free of charge, to any person obtaining a
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# copy of this software and associated documentation files (the
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# "Software"), to deal in the Software without restriction, including
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# without limitation the rights to use, copy, modify, merge, publish, dis-
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# tribute, sublicense, and/or sell copies of the Software, and to permit
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# persons to whom the Software is furnished to do so, subject to the fol-
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# lowing conditions:
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#
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# The above copyright notice and this permission notice shall be included
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# in all copies or substantial portions of the Software.
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#
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
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# OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABIL-
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# ITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT
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# SHALL THE AUTHOR BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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# WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
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# IN THE SOFTWARE.
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#
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from math import ceil
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from boto.compat import json, map, six
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import requests
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class SearchServiceException(Exception):
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pass
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class CommitMismatchError(Exception):
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pass
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class SearchResults(object):
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def __init__(self, **attrs):
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self.rid = attrs['info']['rid']
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# self.doc_coverage_pct = attrs['info']['doc-coverage-pct']
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self.cpu_time_ms = attrs['info']['cpu-time-ms']
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self.time_ms = attrs['info']['time-ms']
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self.hits = attrs['hits']['found']
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self.docs = attrs['hits']['hit']
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self.start = attrs['hits']['start']
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self.rank = attrs['rank']
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self.match_expression = attrs['match-expr']
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self.query = attrs['query']
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self.search_service = attrs['search_service']
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self.facets = {}
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if 'facets' in attrs:
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for (facet, values) in attrs['facets'].items():
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if 'constraints' in values:
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self.facets[facet] = dict((k, v) for (k, v) in map(lambda x: (x['value'], x['count']), values['constraints']))
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self.num_pages_needed = ceil(self.hits / self.query.real_size)
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def __len__(self):
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return len(self.docs)
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def __iter__(self):
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return iter(self.docs)
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def next_page(self):
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"""Call Cloudsearch to get the next page of search results
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:rtype: :class:`boto.cloudsearch.search.SearchResults`
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:return: the following page of search results
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"""
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if self.query.page <= self.num_pages_needed:
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self.query.start += self.query.real_size
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self.query.page += 1
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return self.search_service(self.query)
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else:
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raise StopIteration
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class Query(object):
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RESULTS_PER_PAGE = 500
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def __init__(self, q=None, bq=None, rank=None,
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return_fields=None, size=10,
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start=0, facet=None, facet_constraints=None,
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facet_sort=None, facet_top_n=None, t=None):
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self.q = q
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self.bq = bq
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self.rank = rank or []
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self.return_fields = return_fields or []
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self.start = start
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self.facet = facet or []
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self.facet_constraints = facet_constraints or {}
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self.facet_sort = facet_sort or {}
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self.facet_top_n = facet_top_n or {}
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self.t = t or {}
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self.page = 0
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self.update_size(size)
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def update_size(self, new_size):
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self.size = new_size
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self.real_size = Query.RESULTS_PER_PAGE if (self.size >
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Query.RESULTS_PER_PAGE or self.size == 0) else self.size
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def to_params(self):
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"""Transform search parameters from instance properties to a dictionary
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:rtype: dict
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:return: search parameters
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"""
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params = {'start': self.start, 'size': self.real_size}
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if self.q:
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params['q'] = self.q
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if self.bq:
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params['bq'] = self.bq
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if self.rank:
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params['rank'] = ','.join(self.rank)
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if self.return_fields:
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params['return-fields'] = ','.join(self.return_fields)
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if self.facet:
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params['facet'] = ','.join(self.facet)
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if self.facet_constraints:
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for k, v in six.iteritems(self.facet_constraints):
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params['facet-%s-constraints' % k] = v
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if self.facet_sort:
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for k, v in six.iteritems(self.facet_sort):
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params['facet-%s-sort' % k] = v
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if self.facet_top_n:
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for k, v in six.iteritems(self.facet_top_n):
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params['facet-%s-top-n' % k] = v
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if self.t:
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for k, v in six.iteritems(self.t):
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params['t-%s' % k] = v
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return params
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class SearchConnection(object):
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def __init__(self, domain=None, endpoint=None):
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self.domain = domain
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self.endpoint = endpoint
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if not endpoint:
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self.endpoint = domain.search_service_endpoint
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def build_query(self, q=None, bq=None, rank=None, return_fields=None,
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size=10, start=0, facet=None, facet_constraints=None,
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facet_sort=None, facet_top_n=None, t=None):
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return Query(q=q, bq=bq, rank=rank, return_fields=return_fields,
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size=size, start=start, facet=facet,
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facet_constraints=facet_constraints,
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facet_sort=facet_sort, facet_top_n=facet_top_n, t=t)
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def search(self, q=None, bq=None, rank=None, return_fields=None,
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size=10, start=0, facet=None, facet_constraints=None,
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facet_sort=None, facet_top_n=None, t=None):
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"""
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Send a query to CloudSearch
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Each search query should use at least the q or bq argument to specify
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the search parameter. The other options are used to specify the
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criteria of the search.
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:type q: string
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:param q: A string to search the default search fields for.
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:type bq: string
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:param bq: A string to perform a Boolean search. This can be used to
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create advanced searches.
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:type rank: List of strings
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:param rank: A list of fields or rank expressions used to order the
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search results. A field can be reversed by using the - operator.
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``['-year', 'author']``
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:type return_fields: List of strings
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:param return_fields: A list of fields which should be returned by the
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search. If this field is not specified, only IDs will be returned.
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``['headline']``
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:type size: int
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:param size: Number of search results to specify
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:type start: int
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:param start: Offset of the first search result to return (can be used
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for paging)
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:type facet: list
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:param facet: List of fields for which facets should be returned
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``['colour', 'size']``
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:type facet_constraints: dict
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:param facet_constraints: Use to limit facets to specific values
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specified as comma-delimited strings in a Dictionary of facets
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``{'colour': "'blue','white','red'", 'size': "big"}``
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:type facet_sort: dict
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:param facet_sort: Rules used to specify the order in which facet
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values should be returned. Allowed values are *alpha*, *count*,
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*max*, *sum*. Use *alpha* to sort alphabetical, and *count* to sort
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the facet by number of available result.
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``{'color': 'alpha', 'size': 'count'}``
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:type facet_top_n: dict
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:param facet_top_n: Dictionary of facets and number of facets to
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return.
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``{'colour': 2}``
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:type t: dict
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:param t: Specify ranges for specific fields
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``{'year': '2000..2005'}``
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:rtype: :class:`boto.cloudsearch.search.SearchResults`
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:return: Returns the results of this search
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The following examples all assume we have indexed a set of documents
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with fields: *author*, *date*, *headline*
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A simple search will look for documents whose default text search
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fields will contain the search word exactly:
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>>> search(q='Tim') # Return documents with the word Tim in them (but not Timothy)
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A simple search with more keywords will return documents whose default
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text search fields contain the search strings together or separately.
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>>> search(q='Tim apple') # Will match "tim" and "apple"
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More complex searches require the boolean search operator.
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Wildcard searches can be used to search for any words that start with
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the search string.
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>>> search(bq="'Tim*'") # Return documents with words like Tim or Timothy)
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Search terms can also be combined. Allowed operators are "and", "or",
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"not", "field", "optional", "token", "phrase", or "filter"
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>>> search(bq="(and 'Tim' (field author 'John Smith'))")
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Facets allow you to show classification information about the search
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results. For example, you can retrieve the authors who have written
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about Tim:
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>>> search(q='Tim', facet=['Author'])
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With facet_constraints, facet_top_n and facet_sort more complicated
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constraints can be specified such as returning the top author out of
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John Smith and Mark Smith who have a document with the word Tim in it.
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>>> search(q='Tim',
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... facet=['Author'],
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... facet_constraints={'author': "'John Smith','Mark Smith'"},
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... facet=['author'],
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... facet_top_n={'author': 1},
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... facet_sort={'author': 'count'})
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"""
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query = self.build_query(q=q, bq=bq, rank=rank,
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return_fields=return_fields,
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size=size, start=start, facet=facet,
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facet_constraints=facet_constraints,
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facet_sort=facet_sort,
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facet_top_n=facet_top_n, t=t)
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return self(query)
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def __call__(self, query):
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"""Make a call to CloudSearch
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:type query: :class:`boto.cloudsearch.search.Query`
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:param query: A group of search criteria
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:rtype: :class:`boto.cloudsearch.search.SearchResults`
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:return: search results
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"""
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url = "http://%s/2011-02-01/search" % (self.endpoint)
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params = query.to_params()
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r = requests.get(url, params=params)
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body = r.content.decode('utf-8')
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try:
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data = json.loads(body)
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except ValueError as e:
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if r.status_code == 403:
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msg = ''
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import re
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g = re.search('<html><body><h1>403 Forbidden</h1>([^<]+)<', body)
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try:
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msg = ': %s' % (g.groups()[0].strip())
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except AttributeError:
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pass
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raise SearchServiceException('Authentication error from Amazon%s' % msg)
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raise SearchServiceException("Got non-json response from Amazon. %s" % body, query)
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if 'messages' in data and 'error' in data:
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for m in data['messages']:
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if m['severity'] == 'fatal':
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raise SearchServiceException("Error processing search %s "
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"=> %s" % (params, m['message']), query)
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elif 'error' in data:
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raise SearchServiceException("Unknown error processing search %s"
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% json.dumps(data), query)
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data['query'] = query
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data['search_service'] = self
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return SearchResults(**data)
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def get_all_paged(self, query, per_page):
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"""Get a generator to iterate over all pages of search results
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:type query: :class:`boto.cloudsearch.search.Query`
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:param query: A group of search criteria
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:type per_page: int
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:param per_page: Number of docs in each :class:`boto.cloudsearch.search.SearchResults` object.
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:rtype: generator
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:return: Generator containing :class:`boto.cloudsearch.search.SearchResults`
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"""
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query.update_size(per_page)
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page = 0
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num_pages_needed = 0
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while page <= num_pages_needed:
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results = self(query)
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num_pages_needed = results.num_pages_needed
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yield results
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query.start += query.real_size
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page += 1
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def get_all_hits(self, query):
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"""Get a generator to iterate over all search results
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Transparently handles the results paging from Cloudsearch
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search results so even if you have many thousands of results
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you can iterate over all results in a reasonably efficient
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manner.
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:type query: :class:`boto.cloudsearch.search.Query`
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:param query: A group of search criteria
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:rtype: generator
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:return: All docs matching query
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"""
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page = 0
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num_pages_needed = 0
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while page <= num_pages_needed:
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results = self(query)
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num_pages_needed = results.num_pages_needed
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for doc in results:
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yield doc
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query.start += query.real_size
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page += 1
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def get_num_hits(self, query):
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"""Return the total number of hits for query
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:type query: :class:`boto.cloudsearch.search.Query`
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:param query: a group of search criteria
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:rtype: int
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:return: Total number of hits for query
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"""
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query.update_size(1)
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return self(query).hits
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