def __init__(self):
# Create index directory
lucene.initVM(lucene.CLASSPATH)
if not os.path.exists(STORE_DIR):
os.mkdir(STORE_DIR)
self.store = lucene.SimpleFSDirectory(lucene.File(STORE_DIR))
self.im = IndexManager()
class IndexFiles(object):
"""Usage: python IndexFiles <doc_directory>"""
def __init__(self):
# Create index directory
lucene.initVM(lucene.CLASSPATH)
if not os.path.exists(STORE_DIR):
os.mkdir(STORE_DIR)
self.store = lucene.SimpleFSDirectory(lucene.File(STORE_DIR))
self.im = IndexManager()
def index_files(self, add=[], remove=[]):
'''
Index (add/remove/update) a given list of files
'''
# Show ticker
#ticker = Ticker()
#threading.Thread(target=ticker.run).start()
history = {'+': add,
'-': remove}
self.__index(history)
def index_folder(self, folder):
'''
Index a folder
'''
# Get list of files indexed
history = self.im.get_files_to_index(folder)
print '\n%s files to be indexed' % len(history['+'])
self.__index(history)
def __index(self, history):
# Get content for all files
print '\nFetching content'
docs = self.__fetch_files(history)
# Detect language for each file and group by it
batches = self.__detect_language(docs)
# Remove missing and updated files
if history['-']:
analyzer = lucene.StandardAnalyzer(lucene.Version.LUCENE_CURRENT)
writer = lucene.IndexWriter(self.store, analyzer, \
lucene.IndexWriter.MaxFieldLength.LIMITED)
for path in history['-']:
writer.deleteDocuments(lucene.Term("path", path))
print 'deleted %s' % path
writer.optimize()
writer.close()
self.im.mark_as_indexed([], history['-'])
# For each batch of files with the same language, analyze and index it
for language, batch in batches.iteritems():
if language:
print '\nIndexing %s file(s) in %s' % (len(batch), language)
else:
print '\nIndexing %s file(s) without a detectable language' % len(batch)
language = DEFAULT_LANGUAGE
# Initialize analyzer with a language-specific stemmer
analyzer = lucene.SnowballAnalyzer(lucene.Version.LUCENE_CURRENT, \
language)
writer = lucene.IndexWriter(self.store, analyzer,
lucene.IndexWriter.MaxFieldLength.LIMITED)
writer.setMaxFieldLength(1048576)
# Index files
indexed = []
for document in batch:
writer.addDocument(document)
print document['path']
indexed.append(document['path'])
writer.optimize()
writer.close()
self.im.mark_as_indexed(indexed, [])
#ticker.tick = False
def __detect_language(self, docs):
'''
Adds a 'language' field to documents which have content in a supported
language
'''
batches = {}
l = NGram('libs/LM') # Textcat language detector
for doc in docs:
language = ''
if doc['content'] and len(doc['content']) > 5:
language = l.classify(str(doc['content'][:1000].encode('utf8')))
if language not in SUPPORTED_LANGUAGES:
language = ''
if not language:
language = DEFAULT_LANGUAGE
language = language.capitalize()
doc.add(lucene.Field("language", language,
lucene.Field.Store.YES,
lucene.Field.Index.NOT_ANALYZED))
if language not in batches:
batches[language] = []
batches[language].append(doc)
return batches
def __fetch_files(self, history):
files_list = get_files(history)
docs = []
for f in files_list:
try:
doc = lucene.Document()
doc.add(lucene.Field("name", f['filename'],
lucene.Field.Store.YES,
lucene.Field.Index.NOT_ANALYZED))
doc.add(lucene.Field("path", f['path'],
lucene.Field.Store.YES,
lucene.Field.Index.NOT_ANALYZED))
doc.add(lucene.Field("content", f['content'],
lucene.Field.Store.YES,
lucene.Field.Index.ANALYZED,
lucene.Field.TermVector.WITH_POSITIONS_OFFSETS))
docs.append(doc)
except Exception, e:
print 'could not index %s: %s' % (f['path'], e)
return docs
