Mercurial > code > home > repos > homeauto
annotate service/mqtt_to_rdf/stmt_chunk.py @ 1669:9d00adef0b22
rm used parameter
| author | drewp@bigasterisk.com |
|---|---|
| date | Tue, 21 Sep 2021 23:20:16 -0700 |
| parents | 89e53cb8a01c |
| children | 80f4e741ca4f |
| rev | line source |
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1 import itertools |
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2 import logging |
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3 from dataclasses import dataclass |
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4 from typing import Iterable, Iterator, List, Optional, Set, Tuple, cast |
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5 |
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6 from rdflib.graph import Graph |
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7 from rdflib.namespace import RDF |
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8 from rdflib.term import BNode, Literal, Node, URIRef, Variable |
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9 |
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10 from candidate_binding import CandidateBinding |
| 1669 | 11 from inference_types import Inconsistent |
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12 |
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13 log = logging.getLogger('infer') |
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14 |
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15 INDENT = ' ' |
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16 |
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17 ChunkPrimaryTriple = Tuple[Optional[Node], Node, Optional[Node]] |
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18 |
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19 |
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20 @dataclass |
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21 class AlignedRuleChunk: |
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22 """a possible association between a rule chunk and a workingSet chunk. You can test |
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23 whether the association would still be possible under various additional bindings.""" |
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24 ruleChunk: 'Chunk' |
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25 workingSetChunk: 'Chunk' |
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26 |
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27 def __post_init__(self): |
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28 if not self.matches(): |
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29 raise Inconsistent() |
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30 |
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31 def newBindingIfMatched(self, prevBindings: CandidateBinding) -> CandidateBinding: |
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32 """supposing this rule did match the statement, what new bindings would |
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33 that produce? |
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34 |
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35 raises Inconsistent if the existing bindings mean that our aligned |
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36 chunks can no longer match. |
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37 """ |
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38 outBinding = CandidateBinding({}) |
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39 for rt, ct in zip(self.ruleChunk._allTerms(), self.workingSetChunk._allTerms()): |
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40 if isinstance(rt, (Variable, BNode)): |
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41 if prevBindings.contains(rt) and prevBindings.applyTerm(rt) != ct: |
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42 msg = f'{rt=} {ct=} {prevBindings=}' if log.isEnabledFor(logging.DEBUG) else '' |
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43 raise Inconsistent(msg) |
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44 if outBinding.contains(rt) and outBinding.applyTerm(rt) != ct: |
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45 # maybe this can happen, for stmts like ?x :a ?x . |
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46 raise Inconsistent("outBinding inconsistent with itself") |
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47 outBinding.addNewBindings(CandidateBinding({rt: ct})) |
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48 else: |
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49 if rt != ct: |
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50 # getting here means prevBindings was set to something our |
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51 # rule statement disagrees with. |
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52 raise Inconsistent(f'{rt=} != {ct=}') |
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53 return outBinding |
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54 |
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55 def matches(self) -> bool: |
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56 """could this rule, with its BindableTerm wildcards, match workingSetChunk?""" |
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57 for selfTerm, otherTerm in zip(self.ruleChunk._allTerms(), self.workingSetChunk._allTerms()): |
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58 if not isinstance(selfTerm, (Variable, BNode)) and selfTerm != otherTerm: |
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59 return False |
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60 return True |
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61 |
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62 |
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63 @dataclass |
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64 class Chunk: # rename this |
| 1661 | 65 """A statement, maybe with variables in it, except *the subject or object |
| 66 can be rdf lists*. This is done to optimize list comparisons (a lot) at the | |
| 67 very minor expense of not handling certain exotic cases, such as a branching | |
| 68 list. | |
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69 |
| 1661 | 70 Example: (?x ?y) math:sum ?z . <-- this becomes one Chunk. |
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71 |
| 1661 | 72 A function call in a rule is always contained in exactly one chunk. |
| 73 | |
| 74 https://www.w3.org/TeamSubmission/n3/#:~:text=Implementations%20may%20treat%20list%20as%20a%20data%20type | |
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75 """ |
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76 # all immutable |
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77 primary: ChunkPrimaryTriple |
| 1653 | 78 subjList: Optional[List[Node]] = None |
| 79 objList: Optional[List[Node]] = None | |
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80 |
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81 def __post_init__(self): |
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82 if not (((self.primary[0] is not None) ^ (self.subjList is not None)) and |
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83 ((self.primary[2] is not None) ^ (self.objList is not None))): |
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84 raise TypeError("invalid chunk init") |
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85 self.predicate = self.primary[1] |
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86 self.sortKey = (self.primary, tuple(self.subjList or []), tuple(self.objList or [])) |
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87 |
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88 def __hash__(self): |
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89 return hash(self.sortKey) |
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90 |
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91 def __lt__(self, other): |
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92 return self.sortKey < other.sortKey |
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93 |
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94 def _allTerms(self) -> Iterator[Node]: |
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95 """the terms in `primary` plus the lists. Output order is undefined but stable between same-sized Chunks""" |
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96 yield self.primary[1] |
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97 if self.primary[0] is not None: |
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98 yield self.primary[0] |
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99 else: |
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100 yield from cast(List[Node], self.subjList) |
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101 if self.primary[2] is not None: |
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102 yield self.primary[2] |
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103 else: |
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104 yield from cast(List[Node], self.objList) |
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105 |
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106 def ruleMatchesFrom(self, workingSet: 'ChunkedGraph') -> Iterator[AlignedRuleChunk]: |
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107 """Chunks from workingSet where self, which may have BindableTerm wildcards, could match that workingSet Chunk.""" |
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108 # if log.isEnabledFor(logging.DEBUG): |
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109 # log.debug(f'{INDENT*6} computing {self}.ruleMatchesFrom({workingSet}') |
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110 allChunksIter = workingSet.allChunks() |
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111 if "stable failures please": |
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112 allChunksIter = sorted(allChunksIter) |
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113 for chunk in allChunksIter: |
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114 try: |
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115 aligned = AlignedRuleChunk(self, chunk) |
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116 except Inconsistent: |
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117 continue |
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118 yield aligned |
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119 |
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120 def __repr__(self): |
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121 pre = ('+'.join('%s' % elem for elem in self.subjList) + '+' if self.subjList else '') |
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122 post = ('+' + '+'.join('%s' % elem for elem in self.objList) if self.objList else '') |
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123 return pre + repr(self.primary) + post |
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124 |
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125 def isFunctionCall(self, functionsFor) -> bool: |
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126 return bool(list(functionsFor(cast(URIRef, self.predicate)))) |
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127 |
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128 def isStatic(self) -> bool: |
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129 return all(_termIsStatic(s) for s in self._allTerms()) |
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130 |
| 1669 | 131 def apply(self, cb: CandidateBinding) -> 'Chunk': |
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132 """Chunk like this one but with cb substitutions applied. If the flag is |
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133 True, we raise BindingUnknown instead of leaving a term unbound""" |
| 1669 | 134 fn = lambda t: cb.applyTerm(t, failUnbound=False) |
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135 return Chunk( |
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136 ( |
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137 fn(self.primary[0]) if self.primary[0] is not None else None, # |
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138 fn(self.primary[1]), # |
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139 fn(self.primary[2]) if self.primary[2] is not None else None), |
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140 subjList=[fn(t) for t in self.subjList] if self.subjList else None, |
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141 objList=[fn(t) for t in self.objList] if self.objList else None, |
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142 ) |
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143 |
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144 |
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145 def _termIsStatic(term: Optional[Node]) -> bool: |
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146 return isinstance(term, (URIRef, Literal)) or term is None |
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147 |
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148 |
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149 def applyChunky(cb: CandidateBinding, |
| 1669 | 150 g: Iterable[AlignedRuleChunk]) -> Iterator[AlignedRuleChunk]: |
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151 for aligned in g: |
| 1669 | 152 bound = aligned.ruleChunk.apply(cb) |
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153 try: |
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154 yield AlignedRuleChunk(bound, aligned.workingSetChunk) |
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155 except Inconsistent: |
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156 pass |
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157 |
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158 |
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159 class ChunkedGraph: |
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160 """a Graph converts 1-to-1 with a ChunkedGraph, where the Chunks have |
| 1652 | 161 combined some statements together. (The only exception is that bnodes for |
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162 rdf lists are lost)""" |
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163 |
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164 def __init__( |
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165 self, |
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166 graph: Graph, |
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167 functionsFor # get rid of this- i'm just working around a circular import |
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168 ): |
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169 self.chunksUsedByFuncs: Set[Chunk] = set() |
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170 self.staticChunks: Set[Chunk] = set() |
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171 self.patternChunks: Set[Chunk] = set() |
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172 |
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173 firstNodes = {} |
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174 restNodes = {} |
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175 graphStmts = set() |
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176 for s, p, o in graph: |
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177 if p == RDF['first']: |
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178 firstNodes[s] = o |
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179 elif p == RDF['rest']: |
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180 restNodes[s] = o |
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181 else: |
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182 graphStmts.add((s, p, o)) |
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183 |
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184 def gatherList(start): |
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185 lst = [] |
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186 cur = start |
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187 while cur != RDF['nil']: |
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188 lst.append(firstNodes[cur]) |
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189 cur = restNodes[cur] |
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190 return lst |
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191 |
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192 for s, p, o in graphStmts: |
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193 subjList = objList = None |
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194 if s in firstNodes: |
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195 subjList = gatherList(s) |
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196 s = None |
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197 if o in firstNodes: |
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198 objList = gatherList(o) |
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199 o = None |
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200 c = Chunk((s, p, o), subjList=subjList, objList=objList) |
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201 |
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202 if c.isFunctionCall(functionsFor): |
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203 self.chunksUsedByFuncs.add(c) |
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204 elif c.isStatic(): |
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205 self.staticChunks.add(c) |
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206 else: |
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207 self.patternChunks.add(c) |
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208 |
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209 def allPredicatesExceptFunctions(self) -> Set[Node]: |
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210 return set(ch.predicate for ch in itertools.chain(self.staticChunks, self.patternChunks)) |
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211 |
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212 def noPredicatesAppear(self, preds: Iterable[Node]) -> bool: |
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213 return self.allPredicatesExceptFunctions().isdisjoint(preds) |
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214 |
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215 def __bool__(self): |
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216 return bool(self.chunksUsedByFuncs) or bool(self.staticChunks) or bool(self.patternChunks) |
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217 |
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218 def __repr__(self): |
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219 return f'ChunkedGraph({self.__dict__})' |
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220 |
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221 def allChunks(self) -> Iterable[Chunk]: |
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222 yield from itertools.chain(self.staticChunks, self.patternChunks, self.chunksUsedByFuncs) |
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223 |
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224 def __contains__(self, ch: Chunk) -> bool: |
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225 return ch in self.allChunks() |