1 | :mod:`waeup.kofa.catalog` -- Cataloging support Kofa |
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2 | **************************************************** |
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3 | |
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4 | .. module:: waeup.kofa.catalog |
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5 | |
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6 | Components that support cataloging and searching objects inside a |
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7 | Kofa site. |
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8 | |
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9 | .. :doctest: |
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10 | .. :layer: waeup.kofa.testing.KofaUnitTestLayer |
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11 | |
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12 | .. contents:: |
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13 | |
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14 | Classes |
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15 | ======= |
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16 | |
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17 | :class:`KofaQuery` |
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18 | ------------------ |
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19 | |
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20 | .. class:: KofaQuery() |
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21 | |
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22 | .. attribute:: grok.implements(hurry.query.interfaces.IQuery) |
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23 | |
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24 | A `hurry.query.query.Query` compatible query that also supports |
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25 | retrival of plain ``Bree`` result sets as used inside a catalog. |
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26 | |
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27 | Like `hurry.query.query.Query` objects, `KofaQuery` is some kind |
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28 | of a meta query or 'compound query' that can give the cataloged |
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29 | objects (or their int ids) matching one or more 'subqueries'. |
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30 | |
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31 | This way you can search for objects (or their int ids) that match |
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32 | several criteria at the same time. See ``examples`` section below. |
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33 | |
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34 | A singleton instance of this class is also available as global |
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35 | utility. |
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36 | |
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37 | .. method:: searchResults(query) |
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38 | |
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39 | Get the cataloged objects determined by ``query``. |
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40 | |
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41 | .. method:: apply(query) |
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42 | |
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43 | Get the list of int ids (a `BTree` result set) for objects |
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44 | determined by ``query``. |
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45 | |
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46 | The list of int ids is less expensive to compute than the |
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47 | complete search results and sufficient, for instance, when you |
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48 | only need the number of objects that match a query and not the |
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49 | objects themselves. |
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50 | |
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51 | Examples |
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52 | ======== |
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53 | |
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54 | Getting a general query object |
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55 | ------------------------------ |
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56 | |
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57 | We can get a KofaQuery object by asking for an unnamed global utility |
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58 | implementing `hurry.query.interfaces.IQuery`: |
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59 | |
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60 | >>> from hurry.query.interfaces import IQuery |
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61 | >>> from zope.component import getUtility |
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62 | >>> q = getUtility(IQuery) |
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63 | >>> q |
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64 | <waeup.kofa.catalog.KofaQuery object at 0x...> |
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65 | |
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66 | This query can get 'subqueries' and delivers the objects found or |
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67 | their ids. To show this we have to setup a catalog with some entries. |
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68 | |
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69 | |
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70 | Setting up a catalog and feeding it |
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71 | ----------------------------------- |
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72 | |
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73 | >>> from zope.catalog.interfaces import ICatalog |
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74 | >>> from zope.catalog.catalog import Catalog |
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75 | >>> mycat = Catalog() |
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76 | |
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77 | We register this catalog with the component architechture as a utility |
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78 | named 'mycatalog': |
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79 | |
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80 | >>> from zope.component import provideUtility |
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81 | >>> provideUtility(mycat, ICatalog, 'mycatalog') |
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82 | |
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83 | We setup a special content type whose instances we will catalog later: |
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84 | |
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85 | >>> from zope.interface import Interface, Attribute, implements |
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86 | >>> from zope.container.contained import Contained |
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87 | >>> class IMammoth(Interface): |
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88 | ... name = Attribute('name') |
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89 | ... age = Attribute('age') |
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90 | |
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91 | >>> class Mammoth(Contained): |
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92 | ... implements(IMammoth) |
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93 | ... def __init__(self, name, age): |
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94 | ... self.name = name |
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95 | ... self.age = age |
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96 | ... def __cmp__(self, other): |
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97 | ... return cmp(self.name, other.name) |
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98 | |
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99 | By including the __cmp__ method we make sure search results can be |
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100 | stably sorted. |
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101 | |
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102 | We also setup a `zope.intid.interfaces.IIntIds` utility. This is not |
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103 | necessary for plain catalogs, but when we want to use KofaQuery (or |
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104 | `hurry.query.query.Query` objects), as to get a unique mapping from |
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105 | objects (stored in ZODB) to integer numbers (stored in catalogs), |
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106 | these query objects lookup a global IIntIds utiliy: |
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107 | |
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108 | >>> from zope import interface |
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109 | >>> import zope.intid.interfaces |
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110 | >>> class DummyIntId(object): |
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111 | ... interface.implements(zope.intid.interfaces.IIntIds) |
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112 | ... MARKER = '__dummy_int_id__' |
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113 | ... def __init__(self): |
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114 | ... self.counter = 0 |
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115 | ... self.data = {} |
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116 | ... def register(self, obj): |
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117 | ... intid = getattr(obj, self.MARKER, None) |
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118 | ... if intid is None: |
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119 | ... setattr(obj, self.MARKER, self.counter) |
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120 | ... self.data[self.counter] = obj |
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121 | ... intid = self.counter |
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122 | ... self.counter += 1 |
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123 | ... return intid |
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124 | ... def getObject(self, intid): |
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125 | ... return self.data[intid] |
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126 | ... def __iter__(self): |
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127 | ... return iter(self.data) |
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128 | >>> intid = DummyIntId() |
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129 | >>> from zope.component import provideUtility |
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130 | >>> provideUtility(intid, zope.intid.interfaces.IIntIds) |
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131 | |
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132 | Now we can catalog some mammoths. Here we create a herd and catalog |
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133 | each item of it: |
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134 | |
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135 | >>> from zope.catalog.field import FieldIndex |
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136 | >>> mycat['mammoth_name'] = FieldIndex('name', IMammoth) |
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137 | >>> mycat['mammoth_age'] = FieldIndex('age', IMammoth) |
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138 | |
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139 | >>> herd = [ |
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140 | ... Mammoth(name='Fred', age=33), |
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141 | ... Mammoth(name='Hank', age=30), |
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142 | ... Mammoth(name='Wilma', age=28), |
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143 | ... ] |
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144 | |
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145 | >>> for mammoth in herd: |
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146 | ... mycat.index_doc(intid.register(mammoth), mammoth) |
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147 | |
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148 | |
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149 | Searching for result sets |
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150 | ------------------------- |
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151 | |
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152 | Finally we can perform queries: |
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153 | |
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154 | >>> from hurry.query import Eq |
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155 | >>> from zope.component import getUtility |
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156 | >>> subquery1 = Eq(('mycatalog', 'mammoth_name'), 'Fred') |
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157 | |
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158 | The latter means: search for objects whose name is ``'Fred'`` in the |
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159 | ``mammoth_name`` index of a catalog registered as a utility named |
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160 | ``mycatalog``. |
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161 | |
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162 | >>> from hurry.query import Between |
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163 | >>> subquery2 = Between(('mycatalog', 'mammoth_age'), 30, 33) |
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164 | |
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165 | This means: ask for objects cataloged in an index named 'mammoth_age', |
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166 | whose cataloged value is between 30 and 33 (including this values). |
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167 | |
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168 | >>> r1 = q.apply(subquery2) |
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169 | >>> r1 |
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170 | IFSet([0, 1]) |
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171 | |
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172 | Using ``apply()`` above, we get a set of values stored in an |
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173 | ``IFBTree``: |
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174 | |
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175 | >>> type(r1) |
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176 | <type 'BTrees.IFBTree.IFSet'> |
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177 | |
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178 | ``IFBTree`` objects implement a rather efficient integer to float |
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179 | mapping where also integers are allowed as values. For each object |
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180 | found (i.e. mammoths whose age is between 30 and 33), we get the |
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181 | number of its entry. |
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182 | |
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183 | To get the real object, we can use intids here, because we setup an |
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184 | appropriate IIntIds utility before: |
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185 | |
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186 | >>> [intid.getObject(x).name for x in r1] |
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187 | ['Fred', 'Hank'] |
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188 | |
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189 | We can (and should) also use the `searchResults()` method explained |
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190 | below to do that. |
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191 | |
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192 | Retrieving BTree sets can, however, make sense, if you want to know |
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193 | only the number of results for a particular query or whether there are |
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194 | results at all in a more efficient way: |
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195 | |
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196 | >>> len(r1) |
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197 | 2 |
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198 | |
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199 | Searching for objects |
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200 | --------------------- |
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201 | |
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202 | Very often we don't want to know the catalog-internal 'ids' of |
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203 | searched objects but the objects themselves. |
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204 | |
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205 | This can be done by using the ``searchResults`` method of |
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206 | ``KofaQuery``: |
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207 | |
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208 | >>> r2 = q.searchResults(subquery1) |
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209 | >>> r2 |
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210 | <zope.catalog.catalog.ResultSet instance at 0x...> |
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211 | |
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212 | >>> list(r2) |
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213 | [<Mammoth object at 0x...>] |
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214 | |
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215 | We got one result item, we can immediately ask for further infos. To |
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216 | access a result item by its index number, we have to turn the |
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217 | ResultSet into an ordinary list before: |
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218 | |
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219 | >>> entry = list(r2)[0] |
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220 | >>> entry.name, entry.age |
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221 | ('Fred', 33) |
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222 | |
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223 | We can also use ``subquery2`` as above: |
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224 | |
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225 | >>> r3 = q.searchResults(subquery2) |
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226 | >>> [(x.name, x.age) for x in r3] |
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227 | [('Fred', 33), ('Hank', 30)] |
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228 | |
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229 | or use both queries at once: |
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230 | |
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231 | >>> r4 = q.searchResults(subquery1 & subquery2) |
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232 | >>> [(x.name, x.age) for x in r4] |
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233 | [('Fred', 33)] |
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234 | |
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235 | which will give us, of course, the same result set as with subquery1. |
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