Mercurial > repos > shellac > sam_consensus_v3
annotate env/lib/python3.9/site-packages/rdflib_jsonld/serializer.py @ 0:4f3585e2f14b draft default tip
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author | shellac |
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date | Mon, 22 Mar 2021 18:12:50 +0000 |
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1 # -*- coding: utf-8 -*- |
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2 """ |
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3 This serialiser will output an RDF Graph as a JSON-LD formatted document. See: |
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4 |
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5 http://json-ld.org/ |
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6 |
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7 Example usage:: |
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8 |
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9 >>> from rdflib.plugin import register, Serializer |
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10 >>> register('json-ld', Serializer, 'rdflib_jsonld.serializer', 'JsonLDSerializer') |
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11 |
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12 >>> from rdflib import Graph |
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13 |
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14 >>> testrdf = ''' |
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15 ... @prefix dc: <http://purl.org/dc/terms/> . |
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16 ... <http://example.org/about> |
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17 ... dc:title "Someone's Homepage"@en . |
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18 ... ''' |
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19 |
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20 >>> g = Graph().parse(data=testrdf, format='n3') |
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21 |
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22 >>> print((g.serialize(format='json-ld', indent=4).decode())) |
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23 [ |
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24 { |
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25 "@id": "http://example.org/about", |
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26 "http://purl.org/dc/terms/title": [ |
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27 { |
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28 "@language": "en", |
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29 "@value": "Someone's Homepage" |
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30 } |
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31 ] |
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32 } |
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33 ] |
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34 |
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35 """ |
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36 |
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37 # NOTE: This code writes the entire JSON object into memory before serialising, |
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38 # but we should consider streaming the output to deal with arbitrarily large |
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39 # graphs. |
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40 |
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41 import warnings |
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42 |
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43 from rdflib.serializer import Serializer |
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44 from rdflib.graph import Graph |
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45 from rdflib.term import URIRef, Literal, BNode |
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46 from rdflib.namespace import RDF, XSD |
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47 |
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48 from ._compat import str |
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49 from .context import Context, UNDEF |
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50 from .util import json |
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51 from .keys import CONTEXT, GRAPH, ID, VOCAB, LIST, SET, LANG |
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52 |
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53 __all__ = ['JsonLDSerializer', 'from_rdf'] |
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54 |
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55 |
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56 PLAIN_LITERAL_TYPES = set([XSD.boolean, XSD.integer, XSD.double, XSD.string]) |
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57 |
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58 |
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59 class JsonLDSerializer(Serializer): |
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60 def __init__(self, store): |
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61 super(JsonLDSerializer, self).__init__(store) |
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62 |
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63 def serialize(self, stream, base=None, encoding=None, **kwargs): |
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64 # TODO: docstring w. args and return value |
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65 encoding = encoding or 'utf-8' |
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66 if encoding not in ('utf-8', 'utf-16'): |
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67 warnings.warn("JSON should be encoded as unicode. " + |
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68 "Given encoding was: %s" % encoding) |
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69 |
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70 context_data = kwargs.get('context') |
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71 use_native_types = kwargs.get('use_native_types', False), |
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72 use_rdf_type = kwargs.get('use_rdf_type', False) |
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73 auto_compact = kwargs.get('auto_compact', False) |
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74 |
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75 indent = kwargs.get('indent', 2) |
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76 separators = kwargs.get('separators', (',', ': ')) |
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77 sort_keys = kwargs.get('sort_keys', True) |
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78 ensure_ascii = kwargs.get('ensure_ascii', False) |
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79 |
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80 obj = from_rdf(self.store, context_data, base, |
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81 use_native_types, use_rdf_type, |
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82 auto_compact=auto_compact) |
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83 |
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84 data = json.dumps(obj, indent=indent, separators=separators, |
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85 sort_keys=sort_keys, ensure_ascii=ensure_ascii) |
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86 |
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87 stream.write(data.encode(encoding, 'replace')) |
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88 |
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89 |
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90 def from_rdf(graph, context_data=None, base=None, |
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91 use_native_types=False, use_rdf_type=False, |
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92 auto_compact=False, startnode=None, index=False): |
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93 # TODO: docstring w. args and return value |
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94 # TODO: support for index and startnode |
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95 |
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96 if not context_data and auto_compact: |
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97 context_data = dict( |
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98 (pfx, str(ns)) |
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99 for (pfx, ns) in graph.namespaces() if pfx and |
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100 str(ns) != "http://www.w3.org/XML/1998/namespace") |
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101 |
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102 if isinstance(context_data, Context): |
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103 context = context_data |
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104 context_data = context.to_dict() |
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105 else: |
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106 context = Context(context_data, base=base) |
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107 |
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108 converter = Converter(context, use_native_types, use_rdf_type) |
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109 result = converter.convert(graph) |
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110 |
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111 if converter.context.active: |
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112 if isinstance(result, list): |
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113 result = {context.get_key(GRAPH): result} |
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114 result[CONTEXT] = context_data |
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115 |
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116 return result |
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117 |
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118 |
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119 class Converter(object): |
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120 |
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121 def __init__(self, context, use_native_types, use_rdf_type): |
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122 self.context = context |
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123 self.use_native_types = context.active or use_native_types |
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124 self.use_rdf_type = use_rdf_type |
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125 |
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126 def convert(self, graph): |
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127 # TODO: bug in rdflib dataset parsing (nquads et al): |
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128 # plain triples end up in separate unnamed graphs (rdflib issue #436) |
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129 if graph.context_aware: |
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130 default_graph = Graph() |
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131 graphs = [default_graph] |
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132 for g in graph.contexts(): |
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133 if isinstance(g.identifier, URIRef): |
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134 graphs.append(g) |
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135 else: |
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136 default_graph += g |
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137 else: |
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138 graphs = [graph] |
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139 |
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140 context = self.context |
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141 |
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142 objs = [] |
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143 for g in graphs: |
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144 obj = {} |
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145 graphname = None |
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146 |
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147 if isinstance(g.identifier, URIRef): |
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148 graphname = context.shrink_iri(g.identifier) |
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149 obj[context.id_key] = graphname |
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150 |
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151 nodes = self.from_graph(g) |
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152 |
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153 if not graphname and len(nodes) == 1: |
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154 obj.update(nodes[0]) |
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155 else: |
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156 if not nodes: |
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157 continue |
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158 obj[context.graph_key] = nodes |
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159 |
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160 if objs and objs[0].get(context.get_key(ID)) == graphname: |
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161 objs[0].update(obj) |
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162 else: |
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163 objs.append(obj) |
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164 |
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165 if len(graphs) == 1 and len(objs) == 1 and not self.context.active: |
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166 default = objs[0] |
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167 items = default.get(context.graph_key) |
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168 if len(default) == 1 and items: |
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169 objs = items |
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170 elif len(objs) == 1 and self.context.active: |
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171 objs = objs[0] |
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172 |
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173 return objs |
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174 |
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175 def from_graph(self, graph): |
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176 nodemap = {} |
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177 |
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178 for s in set(graph.subjects()): |
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179 ## only iri:s and unreferenced (rest will be promoted to top if needed) |
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180 if isinstance(s, URIRef) or (isinstance(s, BNode) |
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181 and not any(graph.subjects(None, s))): |
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182 self.process_subject(graph, s, nodemap) |
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183 |
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184 return list(nodemap.values()) |
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185 |
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186 def process_subject(self, graph, s, nodemap): |
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187 if isinstance(s, URIRef): |
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188 node_id = self.context.shrink_iri(s) |
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189 elif isinstance(s, BNode): |
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190 node_id = s.n3() |
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191 else: |
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192 node_id = None |
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193 |
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194 #used_as_object = any(graph.subjects(None, s)) |
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195 if node_id in nodemap: |
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196 return None |
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197 |
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198 node = {} |
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199 node[self.context.id_key] = node_id |
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200 nodemap[node_id] = node |
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201 |
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202 for p, o in graph.predicate_objects(s): |
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203 self.add_to_node(graph, s, p, o, node, nodemap) |
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204 |
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205 return node |
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206 |
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207 def add_to_node(self, graph, s, p, o, s_node, nodemap): |
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208 context = self.context |
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209 |
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210 if isinstance(o, Literal): |
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211 datatype = str(o.datatype) if o.datatype else None |
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212 language = o.language |
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213 term = context.find_term(str(p), datatype, language=language) |
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214 else: |
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215 containers = [LIST, None] if graph.value(o, RDF.first) else [None] |
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216 for container in containers: |
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217 for coercion in (ID, VOCAB, UNDEF): |
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218 term = context.find_term(str(p), coercion, container) |
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219 if term: |
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220 break |
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221 if term: |
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222 break |
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223 |
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224 node = None |
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225 use_set = not context.active |
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226 |
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227 if term: |
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228 p_key = term.name |
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229 |
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230 if term.type: |
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231 node = self.type_coerce(o, term.type) |
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232 elif term.language and o.language == term.language: |
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233 node = str(o) |
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234 elif context.language and ( |
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235 term.language is None and o.language is None): |
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236 node = str(o) |
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237 |
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238 if term.container == SET: |
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239 use_set = True |
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240 elif term.container == LIST: |
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241 node = [self.type_coerce(v, term.type) or self.to_raw_value(graph, s, v, nodemap) |
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242 for v in self.to_collection(graph, o)] |
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243 elif term.container == LANG and language: |
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244 value = s_node.setdefault(p_key, {}) |
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245 values = value.get(language) |
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246 node = str(o) |
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247 if values: |
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248 if not isinstance(values, list): |
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249 value[language] = values = [values] |
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250 values.append(node) |
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251 else: |
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252 value[language] = node |
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253 return |
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254 |
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255 else: |
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256 p_key = context.to_symbol(p) |
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257 # TODO: for coercing curies - quite clumsy; unify to_symbol and find_term? |
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258 key_term = context.terms.get(p_key) |
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259 if key_term and (key_term.type or key_term.container): |
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260 p_key = p |
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261 if not term and p == RDF.type and not self.use_rdf_type: |
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262 if isinstance(o, URIRef): |
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263 node = context.to_symbol(o) |
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264 p_key = context.type_key |
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265 |
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266 if node is None: |
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267 node = self.to_raw_value(graph, s, o, nodemap) |
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268 |
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269 value = s_node.get(p_key) |
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270 if value: |
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271 if not isinstance(value, list): |
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272 value = [value] |
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273 value.append(node) |
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274 elif use_set: |
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275 value = [node] |
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276 else: |
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277 value = node |
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278 s_node[p_key] = value |
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279 |
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280 def type_coerce(self, o, coerce_type): |
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281 if coerce_type == ID: |
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282 if isinstance(o, URIRef): |
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283 return self.context.shrink_iri(o) |
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284 elif isinstance(o, BNode): |
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285 return o.n3() |
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286 else: |
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287 return o |
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288 elif coerce_type == VOCAB and isinstance(o, URIRef): |
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289 return self.context.to_symbol(o) |
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290 elif isinstance(o, Literal) and str(o.datatype) == coerce_type: |
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291 return o |
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292 else: |
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293 return None |
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294 |
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295 def to_raw_value(self, graph, s, o, nodemap): |
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296 context = self.context |
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297 coll = self.to_collection(graph, o) |
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298 if coll is not None: |
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299 coll = [self.to_raw_value(graph, s, lo, nodemap) |
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300 for lo in self.to_collection(graph, o)] |
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301 return {context.list_key: coll} |
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302 elif isinstance(o, BNode): |
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303 embed = False # TODO: self.context.active or using startnode and only one ref |
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304 onode = self.process_subject(graph, o, nodemap) |
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305 if onode: |
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306 if embed and not any(s2 for s2 in graph.subjects(None, o) if s2 != s): |
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307 return onode |
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308 else: |
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309 nodemap[onode[context.id_key]] = onode |
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310 return {context.id_key: o.n3()} |
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311 elif isinstance(o, URIRef): |
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312 # TODO: embed if o != startnode (else reverse) |
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313 return {context.id_key: context.shrink_iri(o)} |
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314 elif isinstance(o, Literal): |
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315 # TODO: if compact |
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316 native = self.use_native_types and o.datatype in PLAIN_LITERAL_TYPES |
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317 if native: |
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318 v = o.toPython() |
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319 else: |
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320 v = str(o) |
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321 if o.datatype: |
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322 if native: |
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323 if self.context.active: |
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324 return v |
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325 else: |
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326 return {context.value_key: v} |
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327 return {context.type_key: context.to_symbol(o.datatype), |
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328 context.value_key: v} |
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329 elif o.language and o.language != context.language: |
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330 return {context.lang_key: o.language, |
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331 context.value_key: v} |
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332 elif not context.active or context.language and not o.language: |
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333 return {context.value_key: v} |
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334 else: |
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335 return v |
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336 |
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337 def to_collection(self, graph, l): |
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338 if l != RDF.nil and not graph.value(l, RDF.first): |
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339 return None |
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340 list_nodes = [] |
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341 chain = set([l]) |
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342 while l: |
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343 if l == RDF.nil: |
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344 return list_nodes |
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345 if isinstance(l, URIRef): |
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346 return None |
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347 first, rest = None, None |
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348 for p, o in graph.predicate_objects(l): |
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349 if not first and p == RDF.first: |
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350 first = o |
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351 elif not rest and p == RDF.rest: |
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352 rest = o |
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353 elif p != RDF.type or o != RDF.List: |
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354 return None |
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355 list_nodes.append(first) |
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356 l = rest |
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357 if l in chain: |
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358 return None |
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359 chain.add(l) |
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360 |