ail-framework/bin/indexer_lookup.py

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