Téléverser un nouveau fichier
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#!/usr/bin/env python3
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import argparse
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import itertools
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import json
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import tempfile
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from dataclasses import dataclass
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from SPARQLWrapper import SPARQLWrapper
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from bs4 import BeautifulSoup
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import re
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import subprocess
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from functools import lru_cache
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@dataclass
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class Property:
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url: str
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range: str | None = None
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domain: str | None = None
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@staticmethod
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@lru_cache(maxsize=None)
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def from_url(url: str) -> "Property":
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"""
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The property is only defined by its url and is then cached.
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"""
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return Property(url)
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@property
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def name(self) -> str:
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return self.url.split('/')[-1] if self.range else ""
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@property
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def range_name(self) -> str:
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return self.range.split('/')[-1] if self.range else ""
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@dataclass
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class Graph:
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node: str
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children: list[tuple[Property, "Graph"]]
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def to_tikz(self, prefix: str = "0", x: float = 0, depth: int = 0, header: bool = False) -> str:
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tikz = ""
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if header:
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tikz = "\\begin{center}\n"
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tikz += "\\begin{tikzpicture}[y=3cm]\n"
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tikz += f"\\node[draw] ({prefix}) at ({x:.02f}, -{depth}) {{{self.node}}};\n"
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for j, child in enumerate(self.children):
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rel, subgraph = child
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tikz += subgraph.to_tikz(f"{prefix}-{j}", 5 * j / (depth + 1), depth + 1)
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tikz += f"\\draw[->] ({prefix}) -- ({prefix}-{j}) node[midway,above,sloped] {{{rel.name}}};\n"
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if header:
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tikz += "\\end{tikzpicture}\n"
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tikz += "\\end{center}\n"
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return tikz
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def parse_arguments() -> tuple[str, int, int, int]:
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"""
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Parse the command line arguments.
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"""
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parser = argparse.ArgumentParser()
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parser.add_argument('classname', type=str, help="Class name as input from DBPedia")
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parser.add_argument('threshold', type=int, help="Exceptions threshold")
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parser.add_argument('--limit', '-l', type=int, default=1000, help="Limit the number of queried results")
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parser.add_argument('--recursion', '-r', type=int, default=2, help="Max height of keys")
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args = parser.parse_args()
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return args.classname, args.threshold, args.limit, args.recursion
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def query(classname: str, filename: str, limit: int = 1000) -> None:
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"""
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Query DBPedia using SPARQL for values of the given class.
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"""
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sparql = SPARQLWrapper(endpoint='http://dbpedia.org/sparql')
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sparql.setQuery(f"""prefix db-owl: <http://dbpedia.org/ontology/>
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SELECT DISTINCT ?x ?r ?y
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WHERE {{
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?x rdf:type db-owl:{classname} .
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?x ?r ?y .
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}} LIMIT {limit}""")
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sparql.setReturnFormat('tsv')
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results = sparql.query().convert().decode('UTF-8')
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with open(filename, 'w') as f:
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for i, line in enumerate(results.split('\n')):
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if i == 0:
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continue
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if '\t' in line:
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x, r, y = line.split('\t')
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x, r, y = x[1:-1], r[1:-1], y[1:-1]
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f.write(f'<{x}> <{r}> <{y}> .\n')
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def sakey_output(file: str, threshold: int) -> tuple[list[list[str]], list[list[str]]]:
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"""
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Prints the SAKEY output for the given dataset file.
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"""
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process = subprocess.Popen(['java', '-jar', 'material/sakey.jar', file, str(threshold)], stdout=subprocess.PIPE)
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process.wait()
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if process.returncode != 0:
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# There was an error, that was printed in stderr.
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exit(process.returncode)
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with process.stdout as stdout:
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# Read the output from the process.
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content = stdout.read().decode('UTF-8')
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# Parse the output.
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non_keys, _, almost_keys, _ = content.split('\n')
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# Remove header
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non_keys = non_keys.split(':', 1)[1][1:]
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almost_keys = almost_keys.split(':', 1)[1]
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# Quote URLs
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non_keys = re.sub('(\w)]', '\g<1>"]', re.sub('(\w),', '\g<1>",', re.sub('http', '"http', non_keys)))
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almost_keys = re.sub('(\w)]', '\g<1>"]', re.sub('(\w),', '\g<1>",', re.sub('http', '"http', almost_keys)))
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# Parse JSON
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non_keys = json.loads(non_keys)
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almost_keys = json.loads(almost_keys)
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return non_keys, almost_keys
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def find_interesting_keys(keys: list[list[str]]) -> list[list[Property]]:
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"""
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Parse keys to a better structure.
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"""
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interesting_keys = []
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for key in keys:
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# A key is a list of properties.
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# We transform this key into a simple graph key
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# Then we try to find a range and a domain for each property.
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for prop in key:
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prop = Property.from_url(prop)
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if prop.range:
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# This property can be extended.
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interesting_keys.append([Property.from_url(url) for url in key])
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break
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return interesting_keys
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def process(classname: str, threshold: int, limit: int = 1000, recursion: int = 2) -> list[Graph]:
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filename = tempfile.NamedTemporaryFile().name
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query(classname, filename, limit)
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# Parse output from SAKey
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non_keys, almost_keys = sakey_output(filename, threshold)
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i_keys = find_interesting_keys(almost_keys)
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graph_keys = [Graph(classname, [])]
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if recursion <= 1:
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for key in i_keys:
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graph_keys.append(Graph(classname, [(p, Graph(p.range_name, [])) for p in key]))
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else:
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for key in i_keys:
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subgraphs_list = []
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for p in key:
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subgraphs = process(p.range_name, threshold, limit, recursion - 1)
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subgraphs_list.append(subgraphs)
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for subgraphs_array in itertools.product(*subgraphs_list):
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graph_keys.append(Graph(classname, [(p, g) for p, g in zip(key, subgraphs_array)]))
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return graph_keys
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def main() -> None:
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# Parse DBPedia ontology
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with open('datasets/dbpedia.owl') as f:
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ontology = BeautifulSoup(f, 'xml')
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for e in ontology.find_all('ns0:range'):
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url = e.parent.get('rdf:about')
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p = Property.from_url(url)
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resource = e.get('rdf:resource')
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if '#' not in resource:
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p.range = resource
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for e in ontology.find_all('ns0:domain'):
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url = e.parent.get('rdf:about')
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p = Property.from_url(url)
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resource = e.get('rdf:resource')
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if '#' not in resource:
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p.domain = resource
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# Read arguments
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classname, threshold, limit, recursion = parse_arguments()
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# Process this class name
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graph_keys = process(classname, threshold, limit, recursion)
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for graph in graph_keys:
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print(graph.to_tikz(header=True))
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print("\n")
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if __name__ == '__main__':
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main()
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