def test_termkey():
with TempStorage("termkey") as st:
tw = TermIndexWriter(st.create_file("test.trm"))
tw.add(("alfa", u("bravo")), FileTermInfo(1.0, 3))
tw.add(("alfa", u('\xc3\xa6\xc3\xaf\xc5\ufffd\xc3\xba')), FileTermInfo(4.0, 6))
tw.add(("text", u('\xe6\u2014\xa5\xe6\u0153\xac\xe8\xaa\u017e')), FileTermInfo(7.0, 9))
tw.close()
tr = TermIndexReader(st.open_file("test.trm"))
assert ("alfa", u("bravo")) in tr
assert ("alfa", u('\xc3\xa6\xc3\xaf\xc5\ufffd\xc3\xba')) in tr
assert ("text", u('\xe6\u2014\xa5\xe6\u0153\xac\xe8\xaa\u017e')) in tr
tr.close()
def test_termkey():
with TempStorage("termkey") as st:
tw = TermIndexWriter(st.create_file("test.trm"))
tw.add(("alfa", u("bravo")), FileTermInfo(1.0, 3))
tw.add(("alfa", u('\xc3\xa6\xc3\xaf\xc5\ufffd\xc3\xba')),
FileTermInfo(4.0, 6))
tw.add(("text", u('\xe6\u2014\xa5\xe6\u0153\xac\xe8\xaa\u017e')),
FileTermInfo(7.0, 9))
tw.close()
tr = TermIndexReader(st.open_file("test.trm"))
assert ("alfa", u("bravo")) in tr
assert ("alfa", u('\xc3\xa6\xc3\xaf\xc5\ufffd\xc3\xba')) in tr
assert ("text", u('\xe6\u2014\xa5\xe6\u0153\xac\xe8\xaa\u017e')) in tr
tr.close()
def test_termindex():
terms = [("a", "alfa"), ("a", "bravo"), ("a", "charlie"), ("a", "delta"),
("b", "able"), ("b", "baker"), ("b", "dog"), ("b", "easy")]
st = RamStorage()
tw = TermIndexWriter(st.create_file("test.trm"))
for i, t in enumerate(terms):
tw.add(t, FileTermInfo(1.0, i))
tw.close()
tr = TermIndexReader(st.open_file("test.trm"))
for i, (t1, t2) in enumerate(zip(tr.keys(), terms)):
assert_equal(t1, t2)
ti = tr.get(t1)
assert_equal(ti.weight(), 1.0)
assert_equal(ti.doc_frequency(), i)
def test_termindex():
terms = [("a", "alfa"), ("a", "bravo"), ("a", "charlie"), ("a", "delta"),
("b", "able"), ("b", "baker"), ("b", "dog"), ("b", "easy")]
st = RamStorage()
tw = TermIndexWriter(st.create_file("test.trm"))
for i, t in enumerate(terms):
tw.add(t, FileTermInfo(1.0, i))
tw.close()
tr = TermIndexReader(st.open_file("test.trm"))
for i, (t1, t2) in enumerate(zip(tr.keys(), terms)):
assert_equal(t1, t2)
ti = tr.get(t1)
assert_equal(ti.weight(), 1.0)
assert_equal(ti.doc_frequency(), i)
def test_random_termkeys():
def random_fieldname():
return "".join(chr(random.randint(65, 90)) for _ in xrange(1, 20))
def random_token():
return "".join(unichr(random.randint(0, 0xd7ff)) for _ in xrange(1, 20))
domain = sorted([(random_fieldname(), random_token()) for _ in xrange(1000)])
st = RamStorage()
tw = TermIndexWriter(st.create_file("test.trm"))
for term in domain:
tw.add(term, FileTermInfo(1.0, 1))
tw.close()
tr = TermIndexReader(st.open_file("test.trm"))
for term in domain:
assert term in tr
def test_random_termkeys():
def random_fieldname():
return "".join(chr(random.randint(65, 90)) for _ in xrange(1, 20))
def random_token():
return "".join(
unichr(random.randint(0, 0xd7ff)) for _ in xrange(1, 20))
domain = sorted([(random_fieldname(), random_token())
for _ in xrange(1000)])
st = RamStorage()
tw = TermIndexWriter(st.create_file("test.trm"))
for term in domain:
tw.add(term, FileTermInfo(1.0, 1))
tw.close()
tr = TermIndexReader(st.open_file("test.trm"))
for term in domain:
assert term in tr
class SegmentWriter(IndexWriter):
def __init__(self,
ix,
poolclass=None,
procs=0,
blocklimit=128,
timeout=0.0,
delay=0.1,
name=None,
**poolargs):
self.writelock = ix.lock("WRITELOCK")
if not try_for(self.writelock.acquire, timeout=timeout, delay=delay):
raise LockError
self.ix = ix
self.storage = ix.storage
self.indexname = ix.indexname
self.is_closed = False
info = ix._read_toc()
self.schema = info.schema
self.segments = info.segments
self.blocklimit = blocklimit
self.segment_number = info.segment_counter + 1
self.generation = info.generation + 1
self._doc_offsets = []
base = 0
for s in self.segments:
self._doc_offsets.append(base)
base += s.doc_count_all()
self.name = name or "_%s_%s" % (self.indexname, self.segment_number)
self.docnum = 0
self.fieldlength_totals = defaultdict(int)
self._added = False
self._unique_cache = {}
# Create a temporary segment to use its .*_filename attributes
segment = Segment(self.name, 0, None, None)
# Terms index
tf = self.storage.create_file(segment.termsindex_filename)
self.termsindex = TermIndexWriter(tf)
# Term postings file
pf = self.storage.create_file(segment.termposts_filename)
self.postwriter = FilePostingWriter(pf, blocklimit=blocklimit)
if self.schema.has_vectored_fields():
# Vector index
vf = self.storage.create_file(segment.vectorindex_filename)
self.vectorindex = TermVectorWriter(vf)
# Vector posting file
vpf = self.storage.create_file(segment.vectorposts_filename)
self.vpostwriter = FilePostingWriter(vpf, stringids=True)
else:
self.vectorindex = None
self.vpostwriter = None
# Stored fields file
sf = self.storage.create_file(segment.storedfields_filename)
self.storedfields = StoredFieldWriter(sf, self.schema.stored_names())
# Field lengths file
self.lengthfile = self.storage.create_file(
segment.fieldlengths_filename)
# Create the pool
if poolclass is None:
if procs > 1:
from whoosh.filedb.multiproc import MultiPool
poolclass = MultiPool
else:
poolclass = TempfilePool
self.pool = poolclass(self.schema, procs=procs, **poolargs)
def _check_state(self):
if self.is_closed:
raise IndexingError("This writer is closed")
def add_field(self, fieldname, fieldspec):
self._check_state()
if self._added:
raise Exception("Can't modify schema after adding data to writer")
super(SegmentWriter, self).add_field(fieldname, fieldspec)
def remove_field(self, fieldname):
self._check_state()
if self._added:
raise Exception("Can't modify schema after adding data to writer")
super(SegmentWriter, self).remove_field(fieldname)
def _document_segment(self, docnum):
#Returns the index.Segment object containing the given document
#number.
offsets = self._doc_offsets
if len(offsets) == 1: return 0
return bisect_right(offsets, docnum) - 1
def _segment_and_docnum(self, docnum):
#Returns an (index.Segment, segment_docnum) pair for the segment
#containing the given document number.
segmentnum = self._document_segment(docnum)
offset = self._doc_offsets[segmentnum]
segment = self.segments[segmentnum]
return segment, docnum - offset
def has_deletions(self):
"""
:returns: True if this index has documents that are marked deleted but
haven't been optimized out of the index yet.
"""
return any(s.has_deletions() for s in self.segments)
def delete_document(self, docnum, delete=True):
self._check_state()
segment, segdocnum = self._segment_and_docnum(docnum)
segment.delete_document(segdocnum, delete=delete)
def deleted_count(self):
"""
:returns: the total number of deleted documents in the index.
"""
return sum(s.deleted_count() for s in self.segments)
def is_deleted(self, docnum):
segment, segdocnum = self._segment_and_docnum(docnum)
return segment.is_deleted(segdocnum)
def searcher(self):
self._check_state()
from whoosh.filedb.fileindex import FileIndex
return FileIndex(self.storage, indexname=self.indexname).searcher()
def add_reader(self, reader):
self._check_state()
startdoc = self.docnum
has_deletions = reader.has_deletions()
if has_deletions:
docmap = {}
fieldnames = set(self.schema.names())
# Add stored documents, vectors, and field lengths
for docnum in xrange(reader.doc_count_all()):
if (not has_deletions) or (not reader.is_deleted(docnum)):
d = dict(item
for item in reader.stored_fields(docnum).iteritems()
if item[0] in fieldnames)
# We have to append a dictionary for every document, even if
# it's empty.
self.storedfields.append(d)
if has_deletions:
docmap[docnum] = self.docnum
for fieldname, length in reader.doc_field_lengths(docnum):
if fieldname in fieldnames:
self.pool.add_field_length(self.docnum, fieldname,
length)
for fieldname in reader.vector_names():
if (fieldname in fieldnames
and reader.has_vector(docnum, fieldname)):
vpostreader = reader.vector(docnum, fieldname)
self._add_vector_reader(self.docnum, fieldname,
vpostreader)
self.docnum += 1
for fieldname, text, _, _ in reader:
if fieldname in fieldnames:
postreader = reader.postings(fieldname, text)
while postreader.is_active():
docnum = postreader.id()
valuestring = postreader.value()
if has_deletions:
newdoc = docmap[docnum]
else:
newdoc = startdoc + docnum
self.pool.add_posting(fieldname, text, newdoc,
postreader.weight(), valuestring)
postreader.next()
self._added = True
def add_document(self, **fields):
self._check_state()
schema = self.schema
# Sort the keys
fieldnames = sorted(
[name for name in fields.keys() if not name.startswith("_")])
# Check if the caller gave us a bogus field
for name in fieldnames:
if name not in schema:
raise UnknownFieldError("No field named %r in %s" %
(name, schema))
self.storedfields
storedvalues = {}
docnum = self.docnum
for fieldname in fieldnames:
value = fields.get(fieldname)
if value is not None:
field = schema[fieldname]
if field.indexed:
self.pool.add_content(docnum, fieldname, field, value)
vformat = field.vector
if vformat:
vlist = sorted((w, weight, valuestring)
for w, freq, weight, valuestring in
vformat.word_values(value, mode="index"))
self._add_vector(docnum, fieldname, vlist)
if field.stored:
# Caller can override the stored value by including a key
# _stored_<fieldname>
storedvalue = value
storedname = "_stored_" + fieldname
if storedname in fields:
storedvalue = fields[storedname]
storedvalues[fieldname] = storedvalue
self._added = True
self.storedfields.append(storedvalues)
self.docnum += 1
def update_document(self, **fields):
self._check_state()
_unique_cache = self._unique_cache
# Check which of the supplied fields are unique
unique_fields = [
name for name, field in self.schema.items()
if name in fields and field.unique
]
if not unique_fields:
raise IndexingError("None of the fields in %r"
" are unique" % fields.keys())
# Delete documents matching the unique terms
delset = set()
for name in unique_fields:
field = self.schema[name]
text = field.to_text(fields[name])
# If we've seen an update_document with this unique field before...
if name in _unique_cache:
# Get the cache for this field
term2docnum = _unique_cache[name]
# If the cache is None, that means we've seen this field once
# before but didn't cache it the first time. Cache it now.
if term2docnum is None:
# Read the first document number found for every term in
# this field and cache the mapping from term to doc num
term2docnum = {}
s = self.searcher()
term2docnum = dict(s.first_ids(name))
s.close()
_unique_cache[name] = term2docnum
# Look up the cached document number for this term
if text in term2docnum:
delset.add(term2docnum[text])
else:
# This is the first time we've seen an update_document with
# this field. Mark it by putting None in the cache for this
# field, but don't cache it. We'll only build the cache if we
# see an update_document on this field again. This is to
# prevent caching a field even when the user is only going to
# call update_document once.
reader = self.searcher().reader()
try:
delset.add(reader.postings(name, text).id())
_unique_cache[name] = None
except TermNotFound:
pass
finally:
reader.close()
# Delete the old docs
for docnum in delset:
self.delete_document(docnum)
# Add the given fields
self.add_document(**fields)
def _add_vector(self, docnum, fieldname, vlist):
vpostwriter = self.vpostwriter
offset = vpostwriter.start(self.schema[fieldname].vector)
for text, weight, valuestring in vlist:
assert isinstance(text, unicode), "%r is not unicode" % text
vpostwriter.write(text, weight, valuestring, 0)
vpostwriter.finish()
self.vectorindex.add((docnum, fieldname), offset)
def _add_vector_reader(self, docnum, fieldname, vreader):
vpostwriter = self.vpostwriter
offset = vpostwriter.start(self.schema[fieldname].vector)
while vreader.is_active():
# text, weight, valuestring, fieldlen
vpostwriter.write(vreader.id(), vreader.weight(), vreader.value(),
0)
vreader.next()
vpostwriter.finish()
self.vectorindex.add((docnum, fieldname), offset)
def _close_all(self):
self.is_closed = True
self.termsindex.close()
self.postwriter.close()
self.storedfields.close()
if not self.lengthfile.is_closed:
self.lengthfile.close()
if self.vectorindex:
self.vectorindex.close()
if self.vpostwriter:
self.vpostwriter.close()
def _getsegment(self):
return Segment(self.name, self.docnum, self.pool.fieldlength_totals(),
self.pool.fieldlength_maxes())
def commit(self, mergetype=None, optimize=False, merge=True):
"""Finishes writing and saves all additions and changes to disk.
There are four possible ways to use this method::
# Merge small segments but leave large segments, trying to
# balance fast commits with fast searching:
writer.commit()
# Merge all segments into a single segment:
writer.commit(optimize=True)
# Don't merge any existing segments:
writer.commit(merge=False)
# Use a custom merge function
writer.commit(mergetype=my_merge_function)
:param mergetype: a custom merge function taking an Index object,
Writer object, and segment list as arguments, and returning a
new segment list. If you supply a ``mergetype`` function,
the values of the ``optimize`` and ``merge`` arguments are ignored.
:param optimize: if True, all existing segments are merged with the
documents you've added to this writer (and the value of the
``merge`` argument is ignored).
:param merge: if False, do not merge small segments.
"""
self._check_state()
try:
if mergetype:
pass
elif optimize:
mergetype = OPTIMIZE
elif not merge:
mergetype = NO_MERGE
else:
mergetype = MERGE_SMALL
# Call the merge policy function. The policy may choose to merge other
# segments into this writer's pool
new_segments = mergetype(self, self.segments)
# Tell the pool we're finished adding information, it should add its
# accumulated data to the lengths, terms index, and posting files.
if self._added:
self.pool.finish(self.docnum, self.lengthfile, self.termsindex,
self.postwriter)
# Create a Segment object for the segment created by this writer and
# add it to the list of remaining segments returned by the merge policy
# function
new_segments.append(self._getsegment())
# Close all files, write a new TOC with the new segment list, and
# release the lock.
self._close_all()
from whoosh.filedb.fileindex import _write_toc, _clean_files
_write_toc(self.storage, self.schema, self.indexname,
self.generation, self.segment_number, new_segments)
readlock = self.ix.lock("READLOCK")
readlock.acquire(True)
try:
_clean_files(self.storage, self.indexname, self.generation,
new_segments)
finally:
readlock.release()
finally:
self.writelock.release()
def cancel(self):
self._check_state()
try:
self.pool.cancel()
self._close_all()
finally:
self.writelock.release()
class SegmentWriter(IndexWriter):
def __init__(self, ix, poolclass=None, procs=0, blocklimit=128, timeout=0.0, delay=0.1, name=None, **poolargs):
self.writelock = ix.lock("WRITELOCK")
if not try_for(self.writelock.acquire, timeout=timeout, delay=delay):
raise LockError
self.ix = ix
self.storage = ix.storage
self.indexname = ix.indexname
self.is_closed = False
info = ix._read_toc()
self.schema = info.schema
self.segments = info.segments
self.blocklimit = blocklimit
self.segment_number = info.segment_counter + 1
self.generation = info.generation + 1
self._doc_offsets = []
base = 0
for s in self.segments:
self._doc_offsets.append(base)
base += s.doc_count_all()
self.name = name or "_%s_%s" % (self.indexname, self.segment_number)
self.docnum = 0
self.fieldlength_totals = defaultdict(int)
self._added = False
self._unique_cache = {}
# Create a temporary segment to use its .*_filename attributes
segment = Segment(self.name, 0, None, None)
# Terms index
tf = self.storage.create_file(segment.termsindex_filename)
self.termsindex = TermIndexWriter(tf)
# Term postings file
pf = self.storage.create_file(segment.termposts_filename)
self.postwriter = FilePostingWriter(pf, blocklimit=blocklimit)
if self.schema.has_vectored_fields():
# Vector index
vf = self.storage.create_file(segment.vectorindex_filename)
self.vectorindex = TermVectorWriter(vf)
# Vector posting file
vpf = self.storage.create_file(segment.vectorposts_filename)
self.vpostwriter = FilePostingWriter(vpf, stringids=True)
else:
self.vectorindex = None
self.vpostwriter = None
# Stored fields file
sf = self.storage.create_file(segment.storedfields_filename)
self.storedfields = StoredFieldWriter(sf, self.schema.stored_names())
# Field lengths file
self.lengthfile = self.storage.create_file(segment.fieldlengths_filename)
# Create the pool
if poolclass is None:
if procs > 1:
from whoosh.filedb.multiproc import MultiPool
poolclass = MultiPool
else:
poolclass = TempfilePool
self.pool = poolclass(self.schema, procs=procs, **poolargs)
def _check_state(self):
if self.is_closed:
raise IndexingError("This writer is closed")
def add_field(self, fieldname, fieldspec):
self._check_state()
if self._added:
raise Exception("Can't modify schema after adding data to writer")
super(SegmentWriter, self).add_field(fieldname, fieldspec)
def remove_field(self, fieldname):
self._check_state()
if self._added:
raise Exception("Can't modify schema after adding data to writer")
super(SegmentWriter, self).remove_field(fieldname)
def _document_segment(self, docnum):
# Returns the index.Segment object containing the given document
# number.
offsets = self._doc_offsets
if len(offsets) == 1:
return 0
return bisect_right(offsets, docnum) - 1
def _segment_and_docnum(self, docnum):
# Returns an (index.Segment, segment_docnum) pair for the segment
# containing the given document number.
segmentnum = self._document_segment(docnum)
offset = self._doc_offsets[segmentnum]
segment = self.segments[segmentnum]
return segment, docnum - offset
def has_deletions(self):
"""
:returns: True if this index has documents that are marked deleted but
haven't been optimized out of the index yet.
"""
return any(s.has_deletions() for s in self.segments)
def delete_document(self, docnum, delete=True):
self._check_state()
segment, segdocnum = self._segment_and_docnum(docnum)
segment.delete_document(segdocnum, delete=delete)
def deleted_count(self):
"""
:returns: the total number of deleted documents in the index.
"""
return sum(s.deleted_count() for s in self.segments)
def is_deleted(self, docnum):
segment, segdocnum = self._segment_and_docnum(docnum)
return segment.is_deleted(segdocnum)
def searcher(self):
self._check_state()
from whoosh.filedb.fileindex import FileIndex
return FileIndex(self.storage, indexname=self.indexname).searcher()
def add_reader(self, reader):
self._check_state()
startdoc = self.docnum
has_deletions = reader.has_deletions()
if has_deletions:
docmap = {}
fieldnames = set(self.schema.names())
# Add stored documents, vectors, and field lengths
for docnum in xrange(reader.doc_count_all()):
if (not has_deletions) or (not reader.is_deleted(docnum)):
d = dict(item for item in reader.stored_fields(docnum).iteritems() if item[0] in fieldnames)
# We have to append a dictionary for every document, even if
# it's empty.
self.storedfields.append(d)
if has_deletions:
docmap[docnum] = self.docnum
for fieldname, length in reader.doc_field_lengths(docnum):
if fieldname in fieldnames:
self.pool.add_field_length(self.docnum, fieldname, length)
for fieldname in reader.vector_names():
if fieldname in fieldnames and reader.has_vector(docnum, fieldname):
vpostreader = reader.vector(docnum, fieldname)
self._add_vector_reader(self.docnum, fieldname, vpostreader)
self.docnum += 1
for fieldname, text, _, _ in reader:
if fieldname in fieldnames:
postreader = reader.postings(fieldname, text)
while postreader.is_active():
docnum = postreader.id()
valuestring = postreader.value()
if has_deletions:
newdoc = docmap[docnum]
else:
newdoc = startdoc + docnum
self.pool.add_posting(fieldname, text, newdoc, postreader.weight(), valuestring)
postreader.next()
self._added = True
def add_document(self, **fields):
self._check_state()
schema = self.schema
# Sort the keys
fieldnames = sorted([name for name in fields.keys() if not name.startswith("_")])
# Check if the caller gave us a bogus field
for name in fieldnames:
if name not in schema:
raise UnknownFieldError("No field named %r in %s" % (name, schema))
self.storedfields
storedvalues = {}
docnum = self.docnum
for fieldname in fieldnames:
value = fields.get(fieldname)
if value is not None:
field = schema[fieldname]
if field.indexed:
self.pool.add_content(docnum, fieldname, field, value)
vformat = field.vector
if vformat:
vlist = sorted(
(w, weight, valuestring)
for w, freq, weight, valuestring in vformat.word_values(value, mode="index")
)
self._add_vector(docnum, fieldname, vlist)
if field.stored:
# Caller can override the stored value by including a key
# _stored_<fieldname>
storedvalue = value
storedname = "_stored_" + fieldname
if storedname in fields:
storedvalue = fields[storedname]
storedvalues[fieldname] = storedvalue
self._added = True
self.storedfields.append(storedvalues)
self.docnum += 1
def update_document(self, **fields):
self._check_state()
_unique_cache = self._unique_cache
# Check which of the supplied fields are unique
unique_fields = [name for name, field in self.schema.items() if name in fields and field.unique]
if not unique_fields:
raise IndexingError("None of the fields in %r" " are unique" % fields.keys())
# Delete documents matching the unique terms
delset = set()
for name in unique_fields:
field = self.schema[name]
text = field.to_text(fields[name])
# If we've seen an update_document with this unique field before...
if name in _unique_cache:
# Get the cache for this field
term2docnum = _unique_cache[name]
# If the cache is None, that means we've seen this field once
# before but didn't cache it the first time. Cache it now.
if term2docnum is None:
# Read the first document number found for every term in
# this field and cache the mapping from term to doc num
term2docnum = {}
s = self.searcher()
term2docnum = dict(s.first_ids(name))
s.close()
_unique_cache[name] = term2docnum
# Look up the cached document number for this term
if text in term2docnum:
delset.add(term2docnum[text])
else:
# This is the first time we've seen an update_document with
# this field. Mark it by putting None in the cache for this
# field, but don't cache it. We'll only build the cache if we
# see an update_document on this field again. This is to
# prevent caching a field even when the user is only going to
# call update_document once.
reader = self.searcher().reader()
try:
delset.add(reader.postings(name, text).id())
_unique_cache[name] = None
except TermNotFound:
pass
finally:
reader.close()
# Delete the old docs
for docnum in delset:
self.delete_document(docnum)
# Add the given fields
self.add_document(**fields)
def _add_vector(self, docnum, fieldname, vlist):
vpostwriter = self.vpostwriter
offset = vpostwriter.start(self.schema[fieldname].vector)
for text, weight, valuestring in vlist:
assert isinstance(text, unicode), "%r is not unicode" % text
vpostwriter.write(text, weight, valuestring, 0)
vpostwriter.finish()
self.vectorindex.add((docnum, fieldname), offset)
def _add_vector_reader(self, docnum, fieldname, vreader):
vpostwriter = self.vpostwriter
offset = vpostwriter.start(self.schema[fieldname].vector)
while vreader.is_active():
# text, weight, valuestring, fieldlen
vpostwriter.write(vreader.id(), vreader.weight(), vreader.value(), 0)
vreader.next()
vpostwriter.finish()
self.vectorindex.add((docnum, fieldname), offset)
def _close_all(self):
self.is_closed = True
self.termsindex.close()
self.postwriter.close()
self.storedfields.close()
if not self.lengthfile.is_closed:
self.lengthfile.close()
if self.vectorindex:
self.vectorindex.close()
if self.vpostwriter:
self.vpostwriter.close()
def _getsegment(self):
return Segment(self.name, self.docnum, self.pool.fieldlength_totals(), self.pool.fieldlength_maxes())
def commit(self, mergetype=None, optimize=False, merge=True):
"""Finishes writing and saves all additions and changes to disk.
There are four possible ways to use this method::
# Merge small segments but leave large segments, trying to
# balance fast commits with fast searching:
writer.commit()
# Merge all segments into a single segment:
writer.commit(optimize=True)
# Don't merge any existing segments:
writer.commit(merge=False)
# Use a custom merge function
writer.commit(mergetype=my_merge_function)
:param mergetype: a custom merge function taking an Index object,
Writer object, and segment list as arguments, and returning a
new segment list. If you supply a ``mergetype`` function,
the values of the ``optimize`` and ``merge`` arguments are ignored.
:param optimize: if True, all existing segments are merged with the
documents you've added to this writer (and the value of the
``merge`` argument is ignored).
:param merge: if False, do not merge small segments.
"""
self._check_state()
try:
if mergetype:
pass
elif optimize:
mergetype = OPTIMIZE
elif not merge:
mergetype = NO_MERGE
else:
mergetype = MERGE_SMALL
# Call the merge policy function. The policy may choose to merge other
# segments into this writer's pool
new_segments = mergetype(self, self.segments)
# Tell the pool we're finished adding information, it should add its
# accumulated data to the lengths, terms index, and posting files.
if self._added:
self.pool.finish(self.docnum, self.lengthfile, self.termsindex, self.postwriter)
# Create a Segment object for the segment created by this writer and
# add it to the list of remaining segments returned by the merge policy
# function
new_segments.append(self._getsegment())
# Close all files, write a new TOC with the new segment list, and
# release the lock.
self._close_all()
from whoosh.filedb.fileindex import _write_toc, _clean_files
_write_toc(self.storage, self.schema, self.indexname, self.generation, self.segment_number, new_segments)
readlock = self.ix.lock("READLOCK")
readlock.acquire(True)
try:
_clean_files(self.storage, self.indexname, self.generation, new_segments)
finally:
readlock.release()
finally:
self.writelock.release()
def cancel(self):
self._check_state()
try:
self.pool.cancel()
self._close_all()
finally:
self.writelock.release()