Mercurial > repos > guerler > springsuite
annotate planemo/lib/python3.7/site-packages/boto/cloudsearch/search.py @ 0:d30785e31577 draft
"planemo upload commit 6eee67778febed82ddd413c3ca40b3183a3898f1"
author | guerler |
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date | Fri, 31 Jul 2020 00:18:57 -0400 |
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1 # Copyright (c) 2012 Mitch Garnaat http://garnaat.org/ |
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2 # Copyright (c) 2012 Amazon.com, Inc. or its affiliates. |
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3 # All Rights Reserved |
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4 # |
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5 # Permission is hereby granted, free of charge, to any person obtaining a |
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6 # copy of this software and associated documentation files (the |
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7 # "Software"), to deal in the Software without restriction, including |
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8 # without limitation the rights to use, copy, modify, merge, publish, dis- |
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9 # tribute, sublicense, and/or sell copies of the Software, and to permit |
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10 # persons to whom the Software is furnished to do so, subject to the fol- |
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11 # lowing conditions: |
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12 # |
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13 # The above copyright notice and this permission notice shall be included |
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14 # in all copies or substantial portions of the Software. |
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15 # |
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16 # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS |
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17 # OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABIL- |
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18 # ITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT |
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19 # SHALL THE AUTHOR BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, |
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20 # WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
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21 # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS |
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22 # IN THE SOFTWARE. |
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23 # |
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24 from math import ceil |
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25 from boto.compat import json, map, six |
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26 import requests |
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27 |
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28 |
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29 class SearchServiceException(Exception): |
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30 pass |
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31 |
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32 |
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33 class CommitMismatchError(Exception): |
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34 pass |
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35 |
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36 |
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37 class SearchResults(object): |
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38 def __init__(self, **attrs): |
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39 self.rid = attrs['info']['rid'] |
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40 # self.doc_coverage_pct = attrs['info']['doc-coverage-pct'] |
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41 self.cpu_time_ms = attrs['info']['cpu-time-ms'] |
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42 self.time_ms = attrs['info']['time-ms'] |
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43 self.hits = attrs['hits']['found'] |
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44 self.docs = attrs['hits']['hit'] |
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45 self.start = attrs['hits']['start'] |
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46 self.rank = attrs['rank'] |
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47 self.match_expression = attrs['match-expr'] |
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48 self.query = attrs['query'] |
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49 self.search_service = attrs['search_service'] |
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50 |
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51 self.facets = {} |
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52 if 'facets' in attrs: |
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53 for (facet, values) in attrs['facets'].items(): |
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54 if 'constraints' in values: |
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55 self.facets[facet] = dict((k, v) for (k, v) in map(lambda x: (x['value'], x['count']), values['constraints'])) |
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56 |
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57 self.num_pages_needed = ceil(self.hits / self.query.real_size) |
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58 |
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59 def __len__(self): |
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60 return len(self.docs) |
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61 |
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62 def __iter__(self): |
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63 return iter(self.docs) |
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64 |
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65 def next_page(self): |
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66 """Call Cloudsearch to get the next page of search results |
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67 |
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68 :rtype: :class:`boto.cloudsearch.search.SearchResults` |
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69 :return: the following page of search results |
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70 """ |
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71 if self.query.page <= self.num_pages_needed: |
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72 self.query.start += self.query.real_size |
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73 self.query.page += 1 |
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74 return self.search_service(self.query) |
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75 else: |
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76 raise StopIteration |
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77 |
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78 |
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79 class Query(object): |
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80 |
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81 RESULTS_PER_PAGE = 500 |
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82 |
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83 def __init__(self, q=None, bq=None, rank=None, |
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84 return_fields=None, size=10, |
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85 start=0, facet=None, facet_constraints=None, |
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86 facet_sort=None, facet_top_n=None, t=None): |
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87 |
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88 self.q = q |
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89 self.bq = bq |
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90 self.rank = rank or [] |
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91 self.return_fields = return_fields or [] |
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92 self.start = start |
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93 self.facet = facet or [] |
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94 self.facet_constraints = facet_constraints or {} |
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95 self.facet_sort = facet_sort or {} |
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96 self.facet_top_n = facet_top_n or {} |
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97 self.t = t or {} |
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98 self.page = 0 |
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99 self.update_size(size) |
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100 |
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101 def update_size(self, new_size): |
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102 self.size = new_size |
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103 self.real_size = Query.RESULTS_PER_PAGE if (self.size > |
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104 Query.RESULTS_PER_PAGE or self.size == 0) else self.size |
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105 |
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106 def to_params(self): |
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107 """Transform search parameters from instance properties to a dictionary |
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108 |
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109 :rtype: dict |
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110 :return: search parameters |
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111 """ |
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112 params = {'start': self.start, 'size': self.real_size} |
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113 |
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114 if self.q: |
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115 params['q'] = self.q |
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116 |
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117 if self.bq: |
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118 params['bq'] = self.bq |
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119 |
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120 if self.rank: |
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121 params['rank'] = ','.join(self.rank) |
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122 |
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123 if self.return_fields: |
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124 params['return-fields'] = ','.join(self.return_fields) |
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125 |
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126 if self.facet: |
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127 params['facet'] = ','.join(self.facet) |
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128 |
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129 if self.facet_constraints: |
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130 for k, v in six.iteritems(self.facet_constraints): |
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131 params['facet-%s-constraints' % k] = v |
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132 |
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133 if self.facet_sort: |
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134 for k, v in six.iteritems(self.facet_sort): |
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135 params['facet-%s-sort' % k] = v |
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136 |
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137 if self.facet_top_n: |
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138 for k, v in six.iteritems(self.facet_top_n): |
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139 params['facet-%s-top-n' % k] = v |
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140 |
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141 if self.t: |
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142 for k, v in six.iteritems(self.t): |
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143 params['t-%s' % k] = v |
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144 return params |
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145 |
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146 |
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147 class SearchConnection(object): |
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148 |
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149 def __init__(self, domain=None, endpoint=None): |
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150 self.domain = domain |
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151 self.endpoint = endpoint |
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152 if not endpoint: |
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153 self.endpoint = domain.search_service_endpoint |
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154 |
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155 def build_query(self, q=None, bq=None, rank=None, return_fields=None, |
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156 size=10, start=0, facet=None, facet_constraints=None, |
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157 facet_sort=None, facet_top_n=None, t=None): |
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158 return Query(q=q, bq=bq, rank=rank, return_fields=return_fields, |
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159 size=size, start=start, facet=facet, |
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160 facet_constraints=facet_constraints, |
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161 facet_sort=facet_sort, facet_top_n=facet_top_n, t=t) |
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162 |
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163 def search(self, q=None, bq=None, rank=None, return_fields=None, |
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164 size=10, start=0, facet=None, facet_constraints=None, |
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165 facet_sort=None, facet_top_n=None, t=None): |
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166 """ |
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167 Send a query to CloudSearch |
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168 |
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169 Each search query should use at least the q or bq argument to specify |
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170 the search parameter. The other options are used to specify the |
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171 criteria of the search. |
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172 |
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173 :type q: string |
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174 :param q: A string to search the default search fields for. |
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175 |
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176 :type bq: string |
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177 :param bq: A string to perform a Boolean search. This can be used to |
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178 create advanced searches. |
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179 |
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180 :type rank: List of strings |
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181 :param rank: A list of fields or rank expressions used to order the |
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182 search results. A field can be reversed by using the - operator. |
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183 ``['-year', 'author']`` |
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184 |
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185 :type return_fields: List of strings |
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186 :param return_fields: A list of fields which should be returned by the |
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187 search. If this field is not specified, only IDs will be returned. |
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188 ``['headline']`` |
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189 |
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190 :type size: int |
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191 :param size: Number of search results to specify |
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192 |
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193 :type start: int |
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194 :param start: Offset of the first search result to return (can be used |
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195 for paging) |
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196 |
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197 :type facet: list |
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198 :param facet: List of fields for which facets should be returned |
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199 ``['colour', 'size']`` |
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200 |
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201 :type facet_constraints: dict |
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202 :param facet_constraints: Use to limit facets to specific values |
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203 specified as comma-delimited strings in a Dictionary of facets |
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204 ``{'colour': "'blue','white','red'", 'size': "big"}`` |
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205 |
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206 :type facet_sort: dict |
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207 :param facet_sort: Rules used to specify the order in which facet |
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208 values should be returned. Allowed values are *alpha*, *count*, |
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209 *max*, *sum*. Use *alpha* to sort alphabetical, and *count* to sort |
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210 the facet by number of available result. |
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211 ``{'color': 'alpha', 'size': 'count'}`` |
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212 |
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213 :type facet_top_n: dict |
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214 :param facet_top_n: Dictionary of facets and number of facets to |
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215 return. |
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216 ``{'colour': 2}`` |
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217 |
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218 :type t: dict |
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219 :param t: Specify ranges for specific fields |
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220 ``{'year': '2000..2005'}`` |
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221 |
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222 :rtype: :class:`boto.cloudsearch.search.SearchResults` |
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223 :return: Returns the results of this search |
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224 |
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225 The following examples all assume we have indexed a set of documents |
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226 with fields: *author*, *date*, *headline* |
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227 |
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228 A simple search will look for documents whose default text search |
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229 fields will contain the search word exactly: |
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230 |
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231 >>> search(q='Tim') # Return documents with the word Tim in them (but not Timothy) |
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232 |
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233 A simple search with more keywords will return documents whose default |
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234 text search fields contain the search strings together or separately. |
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235 |
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236 >>> search(q='Tim apple') # Will match "tim" and "apple" |
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237 |
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238 More complex searches require the boolean search operator. |
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239 |
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240 Wildcard searches can be used to search for any words that start with |
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241 the search string. |
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242 |
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243 >>> search(bq="'Tim*'") # Return documents with words like Tim or Timothy) |
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244 |
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245 Search terms can also be combined. Allowed operators are "and", "or", |
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246 "not", "field", "optional", "token", "phrase", or "filter" |
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247 |
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248 >>> search(bq="(and 'Tim' (field author 'John Smith'))") |
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249 |
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250 Facets allow you to show classification information about the search |
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251 results. For example, you can retrieve the authors who have written |
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252 about Tim: |
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253 |
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254 >>> search(q='Tim', facet=['Author']) |
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255 |
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256 With facet_constraints, facet_top_n and facet_sort more complicated |
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257 constraints can be specified such as returning the top author out of |
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258 John Smith and Mark Smith who have a document with the word Tim in it. |
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259 |
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260 >>> search(q='Tim', |
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261 ... facet=['Author'], |
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262 ... facet_constraints={'author': "'John Smith','Mark Smith'"}, |
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263 ... facet=['author'], |
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264 ... facet_top_n={'author': 1}, |
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265 ... facet_sort={'author': 'count'}) |
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266 """ |
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267 |
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268 query = self.build_query(q=q, bq=bq, rank=rank, |
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269 return_fields=return_fields, |
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270 size=size, start=start, facet=facet, |
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271 facet_constraints=facet_constraints, |
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272 facet_sort=facet_sort, |
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273 facet_top_n=facet_top_n, t=t) |
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274 return self(query) |
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275 |
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276 def __call__(self, query): |
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277 """Make a call to CloudSearch |
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278 |
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279 :type query: :class:`boto.cloudsearch.search.Query` |
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280 :param query: A group of search criteria |
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281 |
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282 :rtype: :class:`boto.cloudsearch.search.SearchResults` |
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283 :return: search results |
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284 """ |
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285 url = "http://%s/2011-02-01/search" % (self.endpoint) |
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286 params = query.to_params() |
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287 |
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288 r = requests.get(url, params=params) |
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289 body = r.content.decode('utf-8') |
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290 try: |
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291 data = json.loads(body) |
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292 except ValueError as e: |
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293 if r.status_code == 403: |
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294 msg = '' |
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295 import re |
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296 g = re.search('<html><body><h1>403 Forbidden</h1>([^<]+)<', body) |
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297 try: |
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298 msg = ': %s' % (g.groups()[0].strip()) |
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299 except AttributeError: |
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300 pass |
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301 raise SearchServiceException('Authentication error from Amazon%s' % msg) |
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302 raise SearchServiceException("Got non-json response from Amazon. %s" % body, query) |
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303 |
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304 if 'messages' in data and 'error' in data: |
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305 for m in data['messages']: |
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306 if m['severity'] == 'fatal': |
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307 raise SearchServiceException("Error processing search %s " |
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308 "=> %s" % (params, m['message']), query) |
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309 elif 'error' in data: |
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310 raise SearchServiceException("Unknown error processing search %s" |
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311 % json.dumps(data), query) |
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312 |
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313 data['query'] = query |
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314 data['search_service'] = self |
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315 |
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316 return SearchResults(**data) |
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317 |
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318 def get_all_paged(self, query, per_page): |
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319 """Get a generator to iterate over all pages of search results |
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320 |
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321 :type query: :class:`boto.cloudsearch.search.Query` |
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322 :param query: A group of search criteria |
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323 |
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324 :type per_page: int |
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325 :param per_page: Number of docs in each :class:`boto.cloudsearch.search.SearchResults` object. |
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326 |
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327 :rtype: generator |
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328 :return: Generator containing :class:`boto.cloudsearch.search.SearchResults` |
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329 """ |
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330 query.update_size(per_page) |
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331 page = 0 |
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332 num_pages_needed = 0 |
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333 while page <= num_pages_needed: |
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334 results = self(query) |
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335 num_pages_needed = results.num_pages_needed |
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336 yield results |
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337 query.start += query.real_size |
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338 page += 1 |
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339 |
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340 def get_all_hits(self, query): |
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341 """Get a generator to iterate over all search results |
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342 |
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343 Transparently handles the results paging from Cloudsearch |
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344 search results so even if you have many thousands of results |
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345 you can iterate over all results in a reasonably efficient |
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346 manner. |
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347 |
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348 :type query: :class:`boto.cloudsearch.search.Query` |
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349 :param query: A group of search criteria |
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350 |
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351 :rtype: generator |
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352 :return: All docs matching query |
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353 """ |
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354 page = 0 |
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355 num_pages_needed = 0 |
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356 while page <= num_pages_needed: |
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357 results = self(query) |
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358 num_pages_needed = results.num_pages_needed |
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359 for doc in results: |
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360 yield doc |
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361 query.start += query.real_size |
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362 page += 1 |
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363 |
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364 def get_num_hits(self, query): |
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365 """Return the total number of hits for query |
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366 |
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367 :type query: :class:`boto.cloudsearch.search.Query` |
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368 :param query: a group of search criteria |
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369 |
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370 :rtype: int |
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371 :return: Total number of hits for query |
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372 """ |
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373 query.update_size(1) |
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374 return self(query).hits |
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375 |
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376 |
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377 |