1 | ''' |
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2 | BSD Licence |
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3 | Copyright (c) 2012, Science & Technology Facilities Council (STFC) |
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4 | All rights reserved. |
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5 | |
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6 | Redistribution and use in source and binary forms, with or without modification, |
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7 | are permitted provided that the following conditions are met: |
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8 | |
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9 | * Redistributions of source code must retain the above copyright notice, |
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10 | this list of conditions and the following disclaimer. |
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11 | * Redistributions in binary form must reproduce the above copyright notice, |
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12 | this list of conditions and the following disclaimer in the documentation |
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13 | and/or other materials provided with the distribution. |
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14 | * Neither the name of the Science & Technology Facilities Council (STFC) |
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15 | nor the names of its contributors may be used to endorse or promote |
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16 | products derived from this software without specific prior written permission. |
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17 | |
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18 | THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" |
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19 | AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, |
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20 | THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR |
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21 | PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS |
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22 | BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, |
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23 | OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF |
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24 | SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) |
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25 | HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, |
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26 | OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE |
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27 | OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
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28 | |
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29 | Created on 10 Jan 2012 |
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30 | |
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31 | @author: mnagni |
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32 | ''' |
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33 | from libs.epb import EPB |
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34 | from ea_model.moles3_4.observationcollection.mo_observationcollection import MO_ObservationCollection |
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35 | from ea_model.moles3_4.observation.mo_observation import MO_Observation |
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36 | from sqlalchemy import Table, Column, ForeignKey, Integer, String |
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37 | from sqlalchemy.orm import mapper |
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38 | from MolesManager.ceda_guid import CedaGUID |
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39 | from sqlalchemy.orm.collections import InstrumentedList |
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40 | from ea_model.iso_19115_2006_metadata_corrigendum.reference_system_information.md_identifier import MD_Identifier |
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41 | from ea_model.iso_19115_2006_metadata_corrigendum.citation_and_responsible_party_information.ci_citation import CI_Citation |
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42 | from ea_model.iso_19115_2006_metadata_corrigendum.extent_information.ex_geographicboundingbox import EX_GeographicBoundingBox |
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43 | from libs.postgisutil import unifyGeometries, create_st_setSRID |
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44 | from ea_model.ceda_metadatamodel.ceda_observationcollection.ceda_observationcollection import CEDA_ObservationCollection |
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45 | from ea_model.ceda_metadatamodel.ceda_observation.ceda_observation import CEDA_Observation |
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46 | from ea_model.ceda_metadatamodel.ceda_project.ceda_project import CEDA_Project |
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47 | |
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48 | class Moles3EPBFactory(EPB): |
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49 | |
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50 | def __init__(self, dbManager): |
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51 | self._dbManager = dbManager |
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52 | self._initCEDA_Customization() |
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53 | |
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54 | |
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55 | def _initCEDA_Customization(self): |
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56 | self._associateCEDA_GUID() |
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57 | self._initSearchIndexes() |
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58 | |
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59 | def _associateCEDA_GUID(self): |
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60 | guid_table = Table('ceda_guid', self._dbManager.metadata, \ |
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61 | Column('id', String, primary_key=True), \ |
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62 | Column('ceda_observationcollection', Integer, ForeignKey('ceda_observationcollection.id')), |
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63 | Column('ceda_observation', Integer, ForeignKey('ceda_observation.id'))) |
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64 | mapper(CedaGUID, guid_table) |
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65 | self._dbManager.metadata.create_all() |
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66 | |
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67 | def _initSearchIndexes(self): |
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68 | #To Be Done - CHECK IF THE COLUMN ALREADY EXISTS! |
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69 | # We don't want sqlalchemy to know about this column so we add it externally. |
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70 | try: |
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71 | self._dbManager.engine.execute("alter table md_identifier add column code_search_vector tsvector") |
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72 | |
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73 | # This indexes the tsvector column |
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74 | |
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75 | self._dbManager.engine.execute("create index md_identifier_code_search_index on md_identifier using gin(code_search_vector)") |
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76 | |
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77 | # This sets up the trigger that keeps the tsvector column up to date. |
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78 | self._dbManager.engine.execute("create trigger md_identifier_code_search_update before update or insert on md_identifier \ |
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79 | for each row execute procedure tsvector_update_trigger('code_search_vector', 'pg_catalog.english', code)") |
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80 | except Exception as e: |
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81 | pass |
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82 | |
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83 | def _getSession(self): |
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84 | if self._dbManager is not None: |
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85 | return self._dbManager.createDbSession() |
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86 | return None |
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87 | |
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88 | def createEPB(self): |
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89 | return Moles3EPB(self._getSession()) |
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90 | |
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91 | class Moles3EPB(object): |
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92 | |
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93 | def __init__(self, session): |
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94 | self._session = session |
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95 | |
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96 | def close(self): |
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97 | return self._session.close() |
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98 | |
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99 | def searchEager(self, clazz, inst_id): |
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100 | return EPB.searchEager(clazz, inst_id, self._session) |
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101 | |
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102 | def persistInstance(self, instance): |
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103 | """ |
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104 | Adds a new migration object. |
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105 | @param migrationObj: the migration object to add |
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106 | @param session: an SQLAlchemy Session object. If not None the session IS NOT closed at the exit, |
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107 | If None (default) a new Session is created from the underlying EPB and closed at the exit. |
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108 | @return an updated, session independent, object instance reflecting the new persisted object |
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109 | """ |
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110 | EPB.persistInstance(instance, self._session) |
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111 | |
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112 | |
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113 | def updateCedaObject(self, ceda_object, cols_to_update): |
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114 | """ |
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115 | Update and eventually commit a CEDA Object in MOLES3 db. |
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116 | @param ceda_object: the CEDA object to update |
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117 | @param cols_to_update: a dictionary containing the columns to update for the given ceda_object and the desired value. |
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118 | If the attribute is a list of objects the new instances are appended only if do not exist in the actual list |
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119 | @return: the given instance with the updated attributes. |
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120 | """ |
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121 | coll = None |
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122 | try: |
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123 | coll = self._session.merge(ceda_object) |
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124 | except Exception as e: |
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125 | print e |
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126 | if coll != None: |
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127 | for k,v in cols_to_update.items(): |
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128 | if hasattr(coll, k): |
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129 | val = None |
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130 | try: |
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131 | val = self._session.merge(v) |
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132 | except Exception: |
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133 | val = v |
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134 | coll_k = getattr(coll, k) |
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135 | if type(coll_k) == list or type(coll_k) == InstrumentedList: |
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136 | tmp_coll = [] |
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137 | if type(val) == list or type(val) == InstrumentedList: |
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138 | tmp_coll.extend(val) |
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139 | else: |
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140 | tmp_coll.append(val) |
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141 | for item in tmp_coll: |
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142 | if item not in coll_k: |
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143 | coll_k.append(item) |
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144 | else: |
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145 | setattr(coll, k, val) |
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146 | self._session.commit() |
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147 | return coll |
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148 | |
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149 | def getGeograpicExtentGeometry(self, ge): |
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150 | ''' |
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151 | Creates the appropriate postgis geometry from a EX_GeographicExtent |
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152 | @param ge: an EX_GeographicExtent instance |
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153 | @return: a postgix text geometry |
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154 | ''' |
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155 | if isinstance(ge, EX_GeographicBoundingBox): |
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156 | return create_st_setSRID(ge.westBoundLongitude, ge.southBoundLatitude, \ |
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157 | ge.eastBoundLongitude, ge.northBoundLatitude) |
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158 | return None |
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159 | |
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160 | |
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161 | |
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162 | def getUnifyObservationCollectionGE(self, collection): |
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163 | """ |
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164 | Returns the union of the collections.member'a GeographicExtension(s) |
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165 | @param collection: an CEDA_ObservationColleciton instance |
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166 | """ |
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167 | bboxes = [] |
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168 | for member in collection.member: |
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169 | for ge in member.geographicExtent: |
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170 | bboxes.append(self.getGeograpicExtentGeometry(ge)) |
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171 | |
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172 | return unifyGeometries(bboxes, self) |
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173 | |
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174 | def retrieveGUIDFromInstance(self, instance): |
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175 | """ |
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176 | Returns the CedaGUID object associated with the given instance. |
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177 | @param instance: an instance of CEDA_Observation os CEDA_ObservationCollection |
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178 | """ |
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179 | if instance is None or not hasattr(instance, 'id'): |
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180 | return None |
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181 | if type(instance) == CEDA_ObservationCollection: |
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182 | return self._session.query(CedaGUID).filter(CedaGUID.ceda_observationcollection==instance.id).first() |
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183 | elif type(instance) == CEDA_Observation: |
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184 | return self._session.query(CedaGUID).filter(CedaGUID.ceda_observation==instance.id).first() |
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185 | |
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186 | def observationCollectionHasObservation(self, obs_coll_id, obs_id): |
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187 | """ |
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188 | Checks if a CEDA_Collection contains a given CEDA_Observation. |
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189 | @param obs_coll_id: the CEDA_ObservationColleciton id |
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190 | @param obs_id: the CEDA_Observation id |
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191 | @return: True if the collection contains the given observation, False otherwise |
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192 | """ |
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193 | coll = self._session.query(CEDA_ObservationCollection).filter(CEDA_ObservationCollection.id==obs_coll_id).first() |
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194 | obs = self._session.query(CEDA_Observation).filter(CEDA_Observation.id==obs_id).first() |
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195 | return obs in coll.member |
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196 | |
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197 | def observationAuthor(self, obs_id): |
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198 | """ |
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199 | Lists the CEDA_Observation author. |
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200 | @param obs_id: the CEDA_Observation id |
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201 | @return: True if the collection contains the given observation, False otherwise |
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202 | """ |
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203 | |
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204 | # TO FIX!!! |
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205 | |
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206 | ''' |
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207 | ret = self._session.query(MO_ResponsiblePartyInfo).join(MO_Observation). \ |
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208 | filter(MO_ResponsiblePartyInfo.role == CEDA_RoleValue.cl_author). \ |
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209 | filter(MO_Observation.id == obs_id) |
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210 | return ret |
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211 | ''' |
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212 | |
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213 | |
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214 | def extractObservationByTitleKeywords(self, keywords): |
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215 | """ |
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216 | Loooks for CEDA_Observation containing a specific title (observation.identifier.code) |
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217 | @param keywords: a space separated terms string |
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218 | @return: a tuple containing a CEDA_Observation satisfying the queryllection.idenfitier element having the title |
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219 | """ |
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220 | # search_vector is a ts_vector column. To search for terms, you use the |
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221 | # @@ operator. plainto_tsquery turns a string into a query that can be |
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222 | # used with @@. So this adds a where clause like "WHERE search_vector |
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223 | # @@ plaint_tsquery(<search string>)" |
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224 | q = self._session.query(CEDA_Observation). \ |
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225 | join(MO_Observation).join(MO_ObservationCollection.identifier). \ |
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226 | filter('md_identifier.code_search_vector @@ to_tsquery(:terms)') |
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227 | # This binds the :terms placeholder to the searchterms string. User input |
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228 | # should always be put into queries this way to prevent SQL injection. |
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229 | q = q.params(terms=keywords) |
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230 | return q.all() |
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231 | |
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232 | |
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233 | def extractCollectionIdentifierByTitle(self, i_title): |
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234 | """ |
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235 | Searches for an MD_Identifier from a CEDA_ObservationCollection contains a specific title (observation.identifier.code) |
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236 | @param i_title: the CEDA_ObservationCollection.identifier.title value to search for |
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237 | @return: a tuple containing a CEDA_ObservationCollection and the CEDA_ObservationCollection.idenfitier element having the title |
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238 | """ |
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239 | return self._session.query(CEDA_ObservationCollection, MD_Identifier). \ |
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240 | join(MO_ObservationCollection).join(MO_ObservationCollection.identifier). \ |
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241 | join(MD_Identifier.authority).filter(CI_Citation.title.like('%' + i_title + '%')) |
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242 | |
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243 | def extractObservationsForProject(self, project): |
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244 | """ |
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245 | Searches for the CEDA_Observation associated with a CEDA_Project |
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246 | @param project: a CEDA_Project instance |
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247 | @return: a tuple containing the associated CEDA_Observation |
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248 | """ |
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249 | return self._session.query(CEDA_Observation). \ |
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250 | join(CEDA_Observation, MO_Observation.inSupportOf).filter(CEDA_Project.id == project.id) |
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251 | |
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252 | def extractProjectObservationCollections(self, project): |
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253 | """ |
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254 | Searches for the Observation_Collections associated with a CEDA_Project |
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255 | @param project: a CEDA_Project instance |
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256 | @return: a tuple containing the associated CEDA_ObservationCollection |
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257 | """ |
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258 | mo_obs = self._session.query(MO_Observation).join(CEDA_Project).filter(CEDA_Project.id == project.id).subquery() |
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259 | obsers = self._session.query(CEDA_Observation).join(mo_obs, CEDA_Observation.id == mo_obs.c.id).one() |
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260 | #print "obsers: " + str(intSession.query(CEDA_Observation).join(mo_obs, CEDA_Observation.id == mo_obs.c.id).count()) |
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261 | |
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262 | cos = self._session.query(CEDA_ObservationCollection).all() |
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263 | co = self._session.query(MO_ObservationCollection).join(MO_ObservationCollection.member).filter(MO_ObservationCollection.member.contains(obsers)) |
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264 | |
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265 | observations = self._session.query(MO_ObservationCollection).join(CEDA_Observation). \ |
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266 | filter(obsers.any(CEDA_Observation.id==obsers.c.id)) |
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267 | print "observation:" + str(observations.count()) |
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268 | return observations |
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269 | |
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270 | def search(self, clazz, inst_id): |
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271 | ret = EPB.search(clazz, inst_id, self._session) |
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272 | return ret |
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273 | |
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274 | def searchSelectiveLoad(self, clazz, inst_id, attributes): |
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275 | """ |
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276 | Searches a required instance by id loading selectively \ |
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277 | the specified fields. The parameter "attributes" is a single string or a list of attributes |
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278 | owned by the instance of "clazz". Furthermore such list may contain |
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279 | also the children of the main attributes. For example "attrs" may look |
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280 | like |
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281 | ['resultAccumulation', 'identifier.authority', 'resultTime.position.dateTime8601.month', \ |
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282 | 'relatedParty.party', 'result.source.function', 'permission', \ |
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283 | 'geographicExtent', 'phenomenonTime', 'keywords', 'description', \ |
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284 | 'inSupportOf.abstract', 'dataLineage'] |
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285 | the first parameter refers to the main class so is equivalent to |
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286 | clazz.resultAccumulation |
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287 | the second parameter is equivalent to invoke |
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288 | clazz.identifier.authority |
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289 | As single string "attributes" could be as well just 'identifier.authority' |
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290 | @param clazz: the class type to search for |
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291 | @param inst_id: the instance id for which the search is done |
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292 | @param attributes: a single string or a list of attributes to load |
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293 | @param session: a session to use for the query. By default a new one is created automatically at start and closed at the end |
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294 | @return the required instance |
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295 | """ |
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296 | ret = EPB.searchSelectiveLoad(clazz, inst_id, attributes, self._session) |
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297 | return ret |
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298 | |
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299 | def loadAttributes(self, instance, attributes): |
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300 | """ |
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301 | Returns the attribute of an instance. The parameter "attributes" is a single string or a list of attributes |
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302 | owned by the instance of "clazz". Furthermore such list may contain |
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303 | also the children of the main attributes. For example "attrs" may look |
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304 | like |
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305 | ['resultAccumulation', 'identifier.authority', 'resultTime.position.dateTime8601.month', \ |
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306 | 'relatedParty.party', 'result.source.function', 'permission', \ |
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307 | 'geographicExtent', 'phenomenonTime', 'keywords', 'description', \ |
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308 | 'inSupportOf.abstract', 'dataLineage'] |
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309 | the first parameter refers to the main class so is equivalent to |
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310 | clazz.resultAccumulation |
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311 | the second parameter is equivalent to invoke |
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312 | clazz.identifier.authority |
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313 | As single string "attributes" could be as well just 'identifier.authority' |
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314 | @param instance: an instance containing the appropriate id |
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315 | @param attributes: the attribute value required |
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316 | @param session: the session to use for the operation |
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317 | @return: the given instance filled with the required attributes. |
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318 | """ |
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319 | instance = self._session.merge(instance) |
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320 | EPB.loadAttributes(instance, attributes, self._session) |
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321 | return instance |
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322 | |
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323 | def executeNative(self, sqlNative): |
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324 | return EPB.executeNative(sqlNative, self._session) |
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