mirror of
https://github.com/adlerosn/rede-especificacoes-tecnicas-em-redes
synced 2024-07-05 17:00:12 +00:00
116 lines
4.4 KiB
Python
Executable File
116 lines
4.4 KiB
Python
Executable File
#!/usr/bin/env python3
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# -*- encoding: utf-8 -*-
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import json
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import sqlite3
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import graphviz
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from pathlib import Path
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from .documents import fromFile as DocumentFromFile
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from .document_finder import classes as docClasses
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from .document_finder import find_references as referenceFinder
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def generate_graph():
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rootsrc, rootname = Path("rootdoc.txt").read_text().splitlines()
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analyzedDocPaths = list()
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pendingDocCchMgr = [docClasses[rootsrc](rootname)]
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graph = dict()
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while len(pendingDocCchMgr) > 0:
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docCchMgr, *pendingDocCchMgr = pendingDocCchMgr
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docPath = docCchMgr.cached()
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currName = f"{docCchMgr.__class__.__name__}: {docCchMgr._identifier}"
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if docPath is not None:
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currName = str(docPath)[6:]
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if currName not in graph:
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graph[currName] = {
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'name': currName,
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'type': docCchMgr.__class__.__name__,
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'doc_id': docCchMgr._identifier,
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'monitored': False if docPath is None else docPath.exists(),
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'pub_date': docCchMgr.publication_date(docPath),
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'in_force': docCchMgr.is_in_force(docPath),
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'mention_freq': dict(),
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}
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if docPath in analyzedDocPaths:
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continue
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analyzedDocPaths.append(docPath)
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docFF = DocumentFromFile(str(docPath))
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print(f"Document @ {currName}")
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if docFF is None:
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continue
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doc = docFF.parse()
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newReferences = referenceFinder(doc, docCchMgr.context(docPath))
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for newReference in newReferences:
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newDocPath = newReference.cached()
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newName = f"{newReference.__class__.__name__}: {newReference._identifier}"
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if newDocPath is not None:
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newName = str(newDocPath)[6:]
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graph[currName]['mention_freq'][newName] = graph[currName]['mention_freq'].get(newName, 0) + 1
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pendingDocCchMgr = sorted(
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[*pendingDocCchMgr, *newReferences],
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key=lambda dcm: (not dcm.is_cached(), dcm.slowness(), dcm._identifier)
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)
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Path('graph.json').write_text(json.dumps(graph))
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def main():
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if not Path('graph.json').exists():
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generate_graph()
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graph = json.loads(Path('graph.json').read_text())
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# to_sqlite
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if Path('graph.db').exists():
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Path('graph.db').unlink()
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sqldb = sqlite3.connect('graph.db')
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cur = sqldb.cursor()
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cur.execute('''CREATE TABLE node (
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name VARCHAR(255),
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type VARCHAR(255),
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doc_id VARCHAR(255),
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monitored bool,
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pub_date VARCHAR(255),
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in_force bool)''')
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cur.execute('''CREATE TABLE edge (
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node_src INTEGER,
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node_dst INTEGER,
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mentions INTEGER,
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FOREIGN KEY(node_src) REFERENCES node(rowid) ON UPDATE CASCADE ON DELETE CASCADE,
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FOREIGN KEY(node_dst) REFERENCES node(rowid) ON UPDATE CASCADE ON DELETE CASCADE)''')
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node_name_to_id = dict()
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for node in graph.values():
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cur.execute(
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'''INSERT INTO node(name,type,doc_id,monitored,pub_date,in_force) VALUES(?,?,?,?,?,?)''',
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(node['name'], node['type'], node['doc_id'], node['monitored'], node['pub_date'], node['in_force'])
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)
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node_name_to_id[node['name']] = cur.lastrowid
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for node in graph.values():
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node_src_nm = node['name']
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node_src = node_name_to_id[node_src_nm]
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for node_dst_nm, frequency in node['mention_freq'].items():
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node_dst = node_name_to_id[node_dst_nm]
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cur.execute(
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'''INSERT INTO edge(node_src,node_dst,mentions) VALUES(?,?,?)''',
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(node_src, node_dst, frequency)
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)
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cur.close()
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sqldb.commit()
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Path('graph.sql').write_text('\n'.join(sqldb.iterdump()))
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sqldb.close()
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# to_graphviz
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gv = graphviz.Digraph()
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for node in graph.values():
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gv.node(
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str(node_name_to_id[node['name']]),
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label='\n'.join(list(map(str, filter(
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lambda a: a is not None,
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[node['type'], node['doc_id'], node['pub_date']]
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))))
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)
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for node in graph.values():
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node_src_nm = node['name']
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node_src = node_name_to_id[node_src_nm]
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for node_dst_nm, frequency in node['mention_freq'].items():
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node_dst = node_name_to_id[node_dst_nm]
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gv.edge(str(node_src), str(node_dst), str(frequency))
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gv.save('graph.gv') # takes "forever" to render, "never" finishes
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