mirror of https://github.com/CIRCL/AIL-framework
94 lines
3.0 KiB
Python
94 lines
3.0 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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#
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# This file is part of AIL framework - Analysis Information Leak framework
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#
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the GNU Affero General Public License as published by
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# the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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#
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# Copyright (c) 2014 Alexandre Dulaunoy - a@foo.be
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import argparse
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import gzip
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import os
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import sys
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sys.path.append(os.path.join(os.environ['AIL_BIN'], 'lib/'))
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import ConfigLoader
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def readdoc(path=None):
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if path is None:
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return False
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f = gzip.open(path, 'r')
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return f.read()
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config_loader = ConfigLoader.ConfigLoader()
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# Indexer configuration - index dir and schema setup
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indexpath = os.path.join(os.environ['AIL_HOME'], config_loader.get_config_str("Indexer", "path"))
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indexertype = config_loader.get_config_str("Indexer", "type")
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argParser = argparse.ArgumentParser(description='Fulltext search for AIL')
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argParser.add_argument('-q', action='append', help='query to lookup (one or more)')
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argParser.add_argument('-n', action='store_true', default=False, help='return numbers of indexed documents')
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argParser.add_argument('-t', action='store_true', default=False, help='dump top 500 terms')
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argParser.add_argument('-l', action='store_true', default=False, help='dump all terms encountered in indexed documents')
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argParser.add_argument('-f', action='store_true', default=False, help='dump each matching document')
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argParser.add_argument('-v', action='store_true', default=False, help='Include filepath')
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argParser.add_argument('-s', action='append', help='search similar documents')
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args = argParser.parse_args()
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from whoosh import index
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from whoosh.fields import Schema, TEXT, ID
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schema = Schema(title=TEXT(stored=True), path=ID(stored=True), content=TEXT)
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ix = index.open_dir(indexpath)
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from whoosh.qparser import QueryParser
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if args.n:
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print(ix.doc_count_all())
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exit(0)
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if args.l:
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xr = ix.searcher().reader()
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for x in xr.lexicon("content"):
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print (x)
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exit(0)
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if args.t:
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xr = ix.searcher().reader()
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for x in xr.most_frequent_terms("content", number=500, prefix=''):
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print (x)
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exit(0)
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if args.s:
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# By default, the index is not storing the vector of the document (Whoosh
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# document schema). It won't work if you don't change the schema of the
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# index for the content. It depends of your storage strategy.
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docnum = ix.searcher().document_number(path=args.s)
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r = ix.searcher().more_like(docnum, "content")
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for hit in r:
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print(hit["path"])
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exit(0)
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if args.q is None:
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argParser.print_help()
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exit(1)
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with ix.searcher() as searcher:
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query = QueryParser("content", ix.schema).parse(" ".join(args.q))
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results = searcher.search(query, limit=None)
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for x in results:
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if args.f:
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if args.v:
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print (x.items()[0][1])
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print (readdoc(path=x.items()[0][1]))
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else:
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print (x.items()[0][1])
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print
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