# Copyright 2012 Matt Chaput. All rights reserved.
#
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# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
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# 2. Redistributions in binary form must reproduce the above copyright
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#
# THIS SOFTWARE IS PROVIDED BY MATT CHAPUT ``AS IS'' AND ANY EXPRESS OR
# IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
# MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO
# EVENT SHALL MATT CHAPUT OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
# INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA,
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# LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
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# EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
# The views and conclusions contained in the software and documentation are
# those of the authors and should not be interpreted as representing official
# policies, either expressed or implied, of Matt Chaput.
"""
This module contains "collector" objects. Collectors provide a way to gather
"raw" results from a :class:` whoosh.matching.Matcher` object, implement
sorting, filtering, collation, etc., and produce a
:class:` whoosh.searching.Results` object.
The basic collectors are:
TopCollector
Returns the top N matching results sorted by score, using block-quality
optimizations to skip blocks of documents that can't contribute to the top
N. The :meth:` whoosh.searching.Searcher.search` method uses this type of
collector by default or when you specify a ``limit``.
UnlimitedCollector
Returns all matching results sorted by score. The
:meth:` whoosh.searching.Searcher.search` method uses this type of collector
when you specify ``limit=None`` or you specify a limit equal to or greater
than the number of documents in the searcher.
SortingCollector
Returns all matching results sorted by a :class:` whoosh.sorting.Facet`
object. The :meth:` whoosh.searching.Searcher.search` method uses this type
of collector when you use the ``sortedby`` parameter.
Here's an example of a simple collector that instead of remembering the matched
documents just counts up the number of matches::
class CountingCollector(Collector):
def prepare(self, top_searcher, q, context):
# Always call super method in prepare
Collector.prepare(self, top_searcher, q, context)
self.count = 0
def collect(self, sub_docnum):
self.count += 1
c = CountingCollector()
mysearcher.search_with_collector(myquery, c)
print(c.count)
There are also several wrapping collectors that extend or modify the
functionality of other collectors. The meth:` whoosh.searching.Searcher.search`
method uses many of these when you specify various parameters.
NOTE: collectors are not designed to be reentrant or thread-safe. It is
generally a good idea to create a new collector for each search.
"""
import os
import threading
from abc import abstractmethod
from array import array
from bisect import insort
from collections import defaultdict
from heapq import heapify, heappush, heapreplace
from whoosh import sorting
from whoosh.searching import Results, TimeLimit
from whoosh.util import now
# Functions
def ilen(iterator):
total = 0
for _ in iterator:
total += 1
return total
# Base class
[docs]class Collector:
"""Base class for collectors."""
[docs] def prepare(self, top_searcher, q, context):
"""This method is called before a search.
Subclasses can override this to perform set-up work, but
they should still call the superclass's method because it sets several
necessary attributes on the collector object:
self.top_searcher
The top-level searcher.
self.q
The query object
self.context
``context.needs_current`` controls whether a wrapping collector
requires that this collector's matcher be in a valid state at every
call to ``collect()``. If this is ``False``, the collector is free
to use faster methods that don't necessarily keep the matcher
updated, such as ``matcher.all_ids()``.
:param top_searcher: the top-level :class:` whoosh.searching.Searcher`
object.
:param q: the :class:` whoosh.query.Query` object being searched for.
:param context: a :class:` whoosh.searching.SearchContext` object
containing information about the search.
"""
self.top_searcher = top_searcher
self.q = q
self.context = context
self.starttime = now()
self.runtime = None
self.docset = set()
def run(self):
# Collect matches for each sub-searcher
try:
for subsearcher, offset in self.top_searcher.leaf_searchers():
self.set_subsearcher(subsearcher, offset)
self.collect_matches()
finally:
self.finish()
[docs] def set_subsearcher(self, subsearcher, offset):
"""This method is called each time the collector starts on a new
sub-searcher.
Subclasses can override this to perform set-up work, but
they should still call the superclass's method because it sets several
necessary attributes on the collector object:
self.subsearcher
The current sub-searcher. If the top-level searcher is atomic, this
is the same as the top-level searcher.
self.offset
The document number offset of the current searcher. You must add
this number to the document number passed to
:meth:`Collector.collect` to get the top-level document number
for use in results.
self.matcher
A :class:` whoosh.matching.Matcher` object representing the matches
for the query in the current sub-searcher.
"""
self.subsearcher = subsearcher
self.offset = offset
self.matcher = self.q.matcher(subsearcher, self.context)
[docs] def computes_count(self):
"""Returns True if the collector naturally computes the exact number of
matching documents. Collectors that use block optimizations will return
False since they might skip blocks containing matching documents.
Note that if this method returns False you can still call :meth:`count`,
but it means that method might have to do more work to calculate the
number of matching documents.
"""
return True
[docs] def all_ids(self):
"""Returns a sequence of docnums matched in this collector. (Only valid
after the collector is run.)
The default implementation is based on the docset. If a collector does
not maintain the docset, it will need to override this method.
"""
return self.docset
[docs] def count(self):
"""Returns the total number of documents matched in this collector.
(Only valid after the collector is run.)
The default implementation is based on the docset. If a collector does
not maintain the docset, it will need to override this method.
"""
return len(self.docset)
[docs] def collect_matches(self):
"""This method calls :meth:`Collector.matches` and then for each
matched document calls :meth:`Collector.collect`. Sub-classes that
want to intervene between finding matches and adding them to the
collection (for example, to filter out certain documents) can override
this method.
"""
collect = self.collect
for sub_docnum in self.matches():
collect(sub_docnum)
[docs] @abstractmethod
def collect(self, sub_docnum):
"""This method is called for every matched document. It should do the
work of adding a matched document to the results, and it should return
an object to use as a "sorting key" for the given document (such as the
document's score, a key generated by a facet, or just None). Subclasses
must implement this method.
If you want the score for the current document, use
``self.matcher.score()``.
Overriding methods should add the current document offset
(``self.offset``) to the ``sub_docnum`` to get the top-level document
number for the matching document to add to results.
:param sub_docnum: the document number of the current match within the
current sub-searcher. You must add ``self.offset`` to this number
to get the document's top-level document number.
"""
raise NotImplementedError
[docs] @abstractmethod
def sort_key(self, sub_docnum):
"""Returns a sorting key for the current match. This should return the
same value returned by :meth:`Collector.collect`, but without the side
effect of adding the current document to the results.
If the collector has been prepared with ``context.needs_current=True``,
this method can use ``self.matcher`` to get information, for example
the score. Otherwise, it should only use the provided ``sub_docnum``,
since the matcher may be in an inconsistent state.
Subclasses must implement this method.
"""
raise NotImplementedError
[docs] def remove(self, global_docnum):
"""Removes a document from the collector. Not that this method uses the
global document number as opposed to :meth:`Collector.collect` which
takes a segment-relative docnum.
"""
items = self.items
for i in range(len(items)):
if items[i][1] == global_docnum:
items.pop(i)
return
raise KeyError(global_docnum)
def _step_through_matches(self):
matcher = self.matcher
while matcher.is_active():
yield matcher.id()
matcher.next()
[docs] def matches(self):
"""Yields a series of relative document numbers for matches
in the current subsearcher.
"""
# We jump through a lot of hoops to avoid stepping through the matcher
# "manually" if we can because all_ids() is MUCH faster
if self.context.needs_current:
return self._step_through_matches()
else:
return self.matcher.all_ids()
[docs] def finish(self):
"""This method is called after a search.
Subclasses can override this to perform set-up work, but
they should still call the superclass's method because it sets several
necessary attributes on the collector object:
self.runtime
The time (in seconds) the search took.
"""
self.runtime = now() - self.starttime
def _results(self, items, **kwargs):
# Fills in a Results object with the invariant information and the
# given "items" (a list of (score, docnum) tuples)
r = Results(self.top_searcher, self.q, items, **kwargs)
r.runtime = self.runtime
r.collector = self
return r
[docs] @abstractmethod
def results(self):
"""Returns a :class:`~ whoosh.searching.Results` object containing the
results of the search. Subclasses must implement this method
"""
raise NotImplementedError
# Scored collectors
[docs]class ScoredCollector(Collector):
"""Base class for collectors that sort the results based on document score."""
def __init__(self, replace=10):
"""
:param replace: Number of matches between attempts to replace the
matcher with a more efficient version.
"""
Collector.__init__(self)
self.replace = replace
[docs] def prepare(self, top_searcher, q, context):
# This collector requires a valid matcher at each step
Collector.prepare(self, top_searcher, q, context)
if top_searcher.weighting.use_final:
self.final_fn = top_searcher.weighting.final
else:
self.final_fn = None
# Heap containing top N (score, 0-docnum) pairs
self.items = []
# Minimum score a document must have to make it into the top N. This is
# used by the block-quality optimizations
self.minscore = 0
# Number of times the matcher was replaced (for debugging)
self.replaced_times = 0
# Number of blocks skipped by quality optimizations (for debugging)
self.skipped_times = 0
[docs] def sort_key(self, sub_docnum):
return 0 - self.matcher.score()
def _collect(self, global_docnum, score):
# Concrete subclasses should override this method to collect matching
# documents
raise NotImplementedError
def _use_block_quality(self):
# Concrete subclasses should override this method to return True if the
# collector should use block quality optimizations
return False
[docs] def collect(self, sub_docnum):
# Do common work to calculate score and top-level document number
global_docnum = self.offset + sub_docnum
score = self.matcher.score()
if self.final_fn:
score = self.final_fn(self.top_searcher, global_docnum, score)
# Call specialized method on subclass
return self._collect(global_docnum, score)
[docs] def matches(self):
minscore = self.minscore
matcher = self.matcher
usequality = self._use_block_quality()
replace = self.replace
replacecounter = 0
# A flag to indicate whether we should check block quality at the start
# of the next loop
checkquality = True
while matcher.is_active():
# If the replacement counter has reached 0, try replacing the
# matcher with a more efficient version
if replace:
if replacecounter == 0 or self.minscore != minscore:
self.matcher = matcher = matcher.replace(minscore or 0)
self.replaced_times += 1
if not matcher.is_active():
break
usequality = self._use_block_quality()
replacecounter = self.replace
if self.minscore != minscore:
checkquality = True
minscore = self.minscore
replacecounter -= 1
# If we're using block quality optimizations, and the checkquality
# flag is true, try to skip ahead to the next block with the
# minimum required quality
if usequality and checkquality and minscore is not None:
self.skipped_times += matcher.skip_to_quality(minscore)
# Skipping ahead might have moved the matcher to the end of the
# posting list
if not matcher.is_active():
break
yield matcher.id()
# Move to the next document. This method returns True if the
# matcher has entered a new block, so we should check block quality
# again.
checkquality = matcher.next()
[docs]class TopCollector(ScoredCollector):
"""A collector that only returns the top "N" scored results."""
def __init__(self, limit=10, usequality=True, **kwargs):
"""
:param limit: the maximum number of results to return.
:param usequality: whether to use block-quality optimizations. This may
be useful for debugging.
"""
ScoredCollector.__init__(self, **kwargs)
self.limit = limit
self.usequality = usequality
self.total = 0
def _use_block_quality(self):
return (
self.usequality
and not self.top_searcher.weighting.use_final
and self.matcher.supports_block_quality()
)
def computes_count(self):
return not self._use_block_quality()
def all_ids(self):
# Since this collector can skip blocks, it doesn't track the total
# number of matching documents, so if the user asks for all matched
# docs we need to re-run the search using docs_for_query
return self.top_searcher.docs_for_query(self.q)
def count(self):
if self.computes_count():
return self.total
else:
return ilen(self.all_ids())
# ScoredCollector.collect calls this
def _collect(self, global_docnum, score):
items = self.items
self.total += 1
# Document numbers are negated before putting them in the heap so that
# higher document numbers have lower "priority" in the queue. Lower
# document numbers should always come before higher document numbers
# with the same score to keep the order stable.
if len(items) < self.limit:
# The heap isn't full, so add this document
heappush(items, (score, 0 - global_docnum))
# Negate score to act as sort key so higher scores appear first
return 0 - score
elif score > items[0][0]:
# The heap is full, but if this document has a high enough
# score to make the top N, add it to the heap
heapreplace(items, (score, 0 - global_docnum))
self.minscore = items[0][0]
# Negate score to act as sort key so higher scores appear first
return 0 - score
else:
return 0
def remove(self, global_docnum):
negated = 0 - global_docnum
items = self.items
# Remove the document if it's on the list (it may not be since
# TopCollector forgets documents that don't make the top N list)
for i in range(len(items)):
if items[i][1] == negated:
items.pop(i)
# Restore the heap invariant
heapify(items)
self.minscore = items[0][0] if items else 0
return
def results(self):
# The items are stored (postive score, negative docnum) so the heap
# keeps the highest scores and lowest docnums, in order from lowest to
# highest. Since for the results we want the highest scores first,
# sort the heap in reverse order
items = self.items
items.sort(reverse=True)
# De-negate the docnums for presentation to the user
items = [(score, 0 - docnum) for score, docnum in items]
return self._results(items)
[docs]class UnlimitedCollector(ScoredCollector):
"""A collector that returns **all** scored results."""
def __init__(self, reverse=False):
ScoredCollector.__init__(self)
self.reverse = reverse
# ScoredCollector.collect calls this
def _collect(self, global_docnum, score):
self.items.append((score, global_docnum))
self.docset.add(global_docnum)
# Negate score to act as sort key so higher scores appear first
return 0 - score
def results(self):
# Sort by negated scores so that higher scores go first, then by
# document number to keep the order stable when documents have the
# same score
self.items.sort(key=lambda x: (0 - x[0], x[1]), reverse=self.reverse)
return self._results(self.items, docset=self.docset)
# Sorting collector
[docs]class SortingCollector(Collector):
"""A collector that returns results sorted by a given
:class:` whoosh.sorting.Facet` object. See :doc:`/facets` for more
information.
"""
def __init__(self, sortedby, limit=10, reverse=False):
"""
:param sortedby: see :doc:`/facets`.
:param reverse: If True, reverse the overall results. Note that you
can reverse individual facets in a multi-facet sort key as well.
"""
Collector.__init__(self)
self.sortfacet = sorting.MultiFacet.from_sortedby(sortedby)
self.limit = limit
self.reverse = reverse
def prepare(self, top_searcher, q, context):
self.categorizer = self.sortfacet.categorizer(top_searcher)
# If the categorizer requires a valid matcher, then tell the child
# collector that we need it
rm = context.needs_current or self.categorizer.needs_current
Collector.prepare(self, top_searcher, q, context.set(needs_current=rm))
# List of (sortkey, docnum) pairs
self.items = []
def set_subsearcher(self, subsearcher, offset):
Collector.set_subsearcher(self, subsearcher, offset)
self.categorizer.set_searcher(subsearcher, offset)
def sort_key(self, sub_docnum):
return self.categorizer.key_for(self.matcher, sub_docnum)
def collect(self, sub_docnum):
global_docnum = self.offset + sub_docnum
sortkey = self.sort_key(sub_docnum)
self.items.append((sortkey, global_docnum))
self.docset.add(global_docnum)
return sortkey
def results(self):
items = self.items
items.sort(reverse=self.reverse)
if self.limit:
items = items[: self.limit]
return self._results(items, docset=self.docset)
class UnsortedCollector(Collector):
def prepare(self, top_searcher, q, context):
Collector.prepare(self, top_searcher, q, context.set(weighting=None))
self.items = []
def collect(self, sub_docnum):
global_docnum = self.offset + sub_docnum
self.items.append((None, global_docnum))
self.docset.add(global_docnum)
def results(self):
items = self.items
return self._results(items, docset=self.docset)
# Wrapping collectors
[docs]class WrappingCollector(Collector):
"""Base class for collectors that wrap other collectors."""
def __init__(self, child):
self.child = child
@property
def top_searcher(self):
return self.child.top_searcher
@property
def context(self):
return self.child.context
[docs] def prepare(self, top_searcher, q, context):
self.child.prepare(top_searcher, q, context)
[docs] def set_subsearcher(self, subsearcher, offset):
self.child.set_subsearcher(subsearcher, offset)
self.subsearcher = subsearcher
self.matcher = self.child.matcher
self.offset = self.child.offset
[docs] def all_ids(self):
return self.child.all_ids()
[docs] def count(self):
return self.child.count()
[docs] def collect_matches(self):
for sub_docnum in self.matches():
self.collect(sub_docnum)
[docs] def sort_key(self, sub_docnum):
return self.child.sort_key(sub_docnum)
[docs] def collect(self, sub_docnum):
return self.child.collect(sub_docnum)
[docs] def remove(self, global_docnum):
return self.child.remove(global_docnum)
[docs] def matches(self):
return self.child.matches()
[docs] def finish(self):
self.child.finish()
[docs] def results(self):
return self.child.results()
# Allow and disallow collector
[docs]class FilterCollector(WrappingCollector):
"""A collector that lets you allow and/or restrict certain document numbers
in the results::
uc = collectors.UnlimitedCollector()
ins = query.Term("chapter", "rendering")
outs = query.Term("status", "restricted")
fc = FilterCollector(uc, allow=ins, restrict=outs)
mysearcher.search_with_collector(myquery, fc)
print(fc.results())
This collector discards a document if:
* The allowed set is not None and a document number is not in the set, or
* The restrict set is not None and a document number is in the set.
(So, if the same document number is in both sets, that document will be
discarded.)
If you have a reference to the collector, you can use
``FilterCollector.filtered_count`` to get the number of matching documents
filtered out of the results by the collector.
"""
def __init__(self, child, allow=None, restrict=None):
"""
:param child: the collector to wrap.
:param allow: a query, Results object, or set-like object containing
docnument numbers that are allowed in the results, or None (meaning
everything is allowed).
:param restrict: a query, Results object, or set-like object containing
document numbers to disallow from the results, or None (meaning
nothing is disallowed).
"""
self.child = child
self.allow = allow
self.restrict = restrict
def prepare(self, top_searcher, q, context):
self.child.prepare(top_searcher, q, context)
allow = self.allow
restrict = self.restrict
ftc = top_searcher._filter_to_comb
self._allow = ftc(allow) if allow else None
self._restrict = ftc(restrict) if restrict else None
self.filtered_count = 0
def all_ids(self):
child = self.child
_allow = self._allow
_restrict = self._restrict
for global_docnum in child.all_ids():
if (_allow and global_docnum not in _allow) or (
_restrict and global_docnum in _restrict
):
continue
yield global_docnum
def count(self):
child = self.child
if child.computes_count():
return child.count()
else:
return ilen(self.all_ids())
def collect_matches(self):
child = self.child
_allow = self._allow
_restrict = self._restrict
if _allow is not None or _restrict is not None:
filtered_count = self.filtered_count
for sub_docnum in child.matches():
global_docnum = self.offset + sub_docnum
if (_allow is not None and global_docnum not in _allow) or (
_restrict is not None and global_docnum in _restrict
):
filtered_count += 1
continue
child.collect(sub_docnum)
self.filtered_count = filtered_count
else:
# If there was no allow or restrict set, don't do anything special,
# just forward the call to the child collector
child.collect_matches()
def results(self):
r = self.child.results()
r.collector = self
r.filtered_count = self.filtered_count
r.allowed = self.allow
r.restricted = self.restrict
return r
# Facet grouping collector
[docs]class FacetCollector(WrappingCollector):
"""A collector that creates groups of documents based on
:class:` whoosh.sorting.Facet` objects. See :doc:`/facets` for more
information.
This collector is used if you specify a ``groupedby`` parameter in the
:meth:` whoosh.searching.Searcher.search` method. You can use the
:meth:` whoosh.searching.Results.groups` method to access the facet groups.
If you have a reference to the collector can also use
``FacetedCollector.facetmaps`` to access the groups directly::
uc = collectors.UnlimitedCollector()
fc = FacetedCollector(uc, sorting.FieldFacet("category"))
mysearcher.search_with_collector(myquery, fc)
print(fc.facetmaps)
"""
def __init__(self, child, groupedby, maptype=None):
"""
:param groupedby: see :doc:`/facets`.
:param maptype: a :class:` whoosh.sorting.FacetMap` type to use for any
facets that don't specify their own.
"""
self.child = child
self.facets = sorting.Facets.from_groupedby(groupedby)
self.maptype = maptype
def prepare(self, top_searcher, q, context):
facets = self.facets
# For each facet we're grouping by:
# - Create a facetmap (to hold the groups)
# - Create a categorizer (to generate document keys)
self.facetmaps = {}
self.categorizers = {}
# Set needs_current to True if any of the categorizers require the
# current document to work
needs_current = context.needs_current
for facetname, facet in facets.items():
self.facetmaps[facetname] = facet.map(self.maptype)
ctr = facet.categorizer(top_searcher)
self.categorizers[facetname] = ctr
needs_current = needs_current or ctr.needs_current
context = context.set(needs_current=needs_current)
self.child.prepare(top_searcher, q, context)
def set_subsearcher(self, subsearcher, offset):
WrappingCollector.set_subsearcher(self, subsearcher, offset)
# Tell each categorizer about the new subsearcher and offset
for categorizer in self.categorizers.values():
categorizer.set_searcher(self.child.subsearcher, self.child.offset)
def collect(self, sub_docnum):
matcher = self.child.matcher
global_docnum = sub_docnum + self.child.offset
# We want the sort key for the document so we can (by default) sort
# the facet groups
sortkey = self.child.collect(sub_docnum)
# For each facet we're grouping by
for name, categorizer in self.categorizers.items():
add = self.facetmaps[name].add
# We have to do more work if the facet allows overlapping groups
if categorizer.allow_overlap:
for key in categorizer.keys_for(matcher, sub_docnum):
add(categorizer.key_to_name(key), global_docnum, sortkey)
else:
key = categorizer.key_for(matcher, sub_docnum)
key = categorizer.key_to_name(key)
add(key, global_docnum, sortkey)
return sortkey
def results(self):
r = self.child.results()
r._facetmaps = self.facetmaps
return r
# Collapsing collector
[docs]class CollapseCollector(WrappingCollector):
"""A collector that collapses results based on a facet. That is, it
eliminates all but the top N results that share the same facet key.
Documents with an empty key for the facet are never eliminated.
The "top" results within each group is determined by the result ordering
(e.g. highest score in a scored search) or an optional second "ordering"
facet.
If you have a reference to the collector you can use
``CollapseCollector.collapsed_counts`` to access the number of documents
eliminated based on each key::
tc = TopCollector(limit=20)
cc = CollapseCollector(tc, "group", limit=3)
mysearcher.search_with_collector(myquery, cc)
print(cc.collapsed_counts)
See :ref:`collapsing` for more information.
"""
def __init__(self, child, keyfacet, limit=1, order=None):
"""
:param child: the collector to wrap.
:param keyfacet: a :class:` whoosh.sorting.Facet` to use for collapsing.
All but the top N documents that share a key will be eliminated
from the results.
:param limit: the maximum number of documents to keep for each key.
:param order: an optional :class:` whoosh.sorting.Facet` to use
to determine the "top" document(s) to keep when collapsing. The
default (``orderfaceet=None``) uses the results order (e.g. the
highest score in a scored search).
"""
self.child = child
self.keyfacet = sorting.MultiFacet.from_sortedby(keyfacet)
self.limit = limit
if order:
self.orderfacet = sorting.MultiFacet.from_sortedby(order)
else:
self.orderfacet = None
def prepare(self, top_searcher, q, context):
# Categorizer for getting the collapse key of a document
self.keyer = self.keyfacet.categorizer(top_searcher)
# Categorizer for getting the collapse order of a document
self.orderer = None
if self.orderfacet:
self.orderer = self.orderfacet.categorizer(top_searcher)
# Dictionary mapping keys to lists of (sortkey, global_docnum) pairs
# representing the best docs for that key
self.lists = defaultdict(list)
# Dictionary mapping keys to the number of documents that have been
# filtered out with that key
self.collapsed_counts = defaultdict(int)
# Total number of documents filtered out by collapsing
self.collapsed_total = 0
# If the keyer or orderer require a valid matcher, tell the child
# collector we need it
needs_current = (
context.needs_current
or self.keyer.needs_current
or (self.orderer and self.orderer.needs_current)
)
self.child.prepare(top_searcher, q, context.set(needs_current=needs_current))
def set_subsearcher(self, subsearcher, offset):
WrappingCollector.set_subsearcher(self, subsearcher, offset)
# Tell the keyer and (optional) orderer about the new subsearcher
self.keyer.set_searcher(subsearcher, offset)
if self.orderer:
self.orderer.set_searcher(subsearcher, offset)
def all_ids(self):
child = self.child
limit = self.limit
counters = defaultdict(int)
for subsearcher, offset in child.subsearchers():
self.set_subsearcher(subsearcher, offset)
matcher = child.matcher
keyer = self.keyer
for sub_docnum in child.matches():
ckey = keyer.key_for(matcher, sub_docnum)
if ckey is not None:
if ckey in counters and counters[ckey] >= limit:
continue
else:
counters[ckey] += 1
yield offset + sub_docnum
def count(self):
if self.child.computes_count():
return self.child.count() - self.collapsed_total
else:
return ilen(self.all_ids())
def collect_matches(self):
lists = self.lists
limit = self.limit
keyer = self.keyer
orderer = self.orderer
collapsed_counts = self.collapsed_counts
child = self.child
matcher = child.matcher
offset = child.offset
for sub_docnum in child.matches():
# Collapsing category key
ckey = keyer.key_to_name(keyer.key_for(matcher, sub_docnum))
if not ckey:
# If the document isn't in a collapsing category, just add it
child.collect(sub_docnum)
else:
global_docnum = offset + sub_docnum
if orderer:
# If user specified a collapse order, use it
sortkey = orderer.key_for(child.matcher, sub_docnum)
else:
# Otherwise, use the results order
sortkey = child.sort_key(sub_docnum)
# Current list of best docs for this collapse key
best = lists[ckey]
add = False
if len(best) < limit:
# If the heap is not full yet, just add this document
add = True
elif sortkey < best[-1][0]:
# If the heap is full but this document has a lower sort
# key than the highest key currently on the heap, replace
# the "least-best" document
# Tell the child collector to remove the document
child.remove(best.pop()[1])
add = True
if add:
insort(best, (sortkey, global_docnum))
child.collect(sub_docnum)
else:
# Remember that a document was filtered
collapsed_counts[ckey] += 1
self.collapsed_total += 1
def results(self):
r = self.child.results()
r.collapsed_counts = self.collapsed_counts
return r
# Time limit collector
[docs]class TimeLimitCollector(WrappingCollector):
"""A collector that raises a :class:`TimeLimit` exception if the search
does not complete within a certain number of seconds::
uc = collectors.UnlimitedCollector()
tlc = TimeLimitedCollector(uc, timelimit=5.8)
try:
mysearcher.search_with_collector(myquery, tlc)
except collectors.TimeLimit:
print("The search ran out of time!")
# We can still get partial results from the collector
print(tlc.results())
IMPORTANT: On Unix systems (systems where signal.SIGALRM is defined), the
code uses signals to stop searching immediately when the time limit is
reached. On Windows, the OS does not support this functionality, so the
search only checks the time between each found document, so if a matcher
is slow the search could exceed the time limit.
"""
def __init__(self, child, timelimit, greedy=False, use_alarm=True):
"""
:param child: the collector to wrap.
:param timelimit: the maximum amount of time (in seconds) to
allow for searching. If the search takes longer than this, it will
raise a ``TimeLimit`` exception.
:param greedy: if ``True``, the collector will finish adding the most
recent hit before raising the ``TimeLimit`` exception.
:param use_alarm: if ``True`` (the default), the collector will try to
use signal.SIGALRM (on UNIX).
"""
self.child = child
self.timelimit = timelimit
self.greedy = greedy
if use_alarm:
import signal
self.use_alarm = use_alarm and hasattr(signal, "SIGALRM")
else:
self.use_alarm = False
self.timer = None
self.timedout = False
def prepare(self, top_searcher, q, context):
self.child.prepare(top_searcher, q, context)
self.timedout = False
if self.use_alarm:
import signal
signal.signal(signal.SIGALRM, self._was_signaled)
# Start a timer thread. If the timer fires, it will call this object's
# _timestop() method
self.timer = threading.Timer(self.timelimit, self._timestop)
self.timer.start()
def _timestop(self):
# Called when the timer expires
self.timer = None
# Set an attribute that will be noticed in the collect_matches() loop
self.timedout = True
if self.use_alarm:
import signal
os.kill(os.getpid(), signal.SIGALRM)
def _was_signaled(self, signum, frame):
raise TimeLimit
def collect_matches(self):
child = self.child
greedy = self.greedy
for sub_docnum in child.matches():
# If the timer fired since the last loop and we're not greedy,
# raise the exception
if self.timedout and not greedy:
raise TimeLimit
child.collect(sub_docnum)
# If the timer fired since we entered the loop or it fired earlier
# but we were greedy, raise now
if self.timedout:
raise TimeLimit
def finish(self):
if self.timer:
self.timer.cancel()
self.timer = None
self.child.finish()
# Matched terms collector
[docs]class TermsCollector(WrappingCollector):
"""A collector that remembers which terms appeared in which terms appeared
in each matched document.
This collector is used if you specify ``terms=True`` in the
:meth:` whoosh.searching.Searcher.search` method.
If you have a reference to the collector can also use
``TermsCollector.termslist`` to access the term lists directly::
uc = collectors.UnlimitedCollector()
tc = TermsCollector(uc)
mysearcher.search_with_collector(myquery, tc)
# tc.termdocs is a dictionary mapping (fieldname, text) tuples to
# sets of document numbers
print(tc.termdocs)
# tc.docterms is a dictionary mapping docnums to lists of
# (fieldname, text) tuples
print(tc.docterms)
"""
def __init__(self, child, settype=set):
self.child = child
self.settype = settype
def prepare(self, top_searcher, q, context):
# This collector requires a valid matcher at each step
self.child.prepare(top_searcher, q, context.set(needs_current=True))
# A dictionary mapping (fieldname, text) pairs to arrays of docnums
self.termdocs = defaultdict(lambda: array("I"))
# A dictionary mapping docnums to lists of (fieldname, text) pairs
self.docterms = defaultdict(list)
def set_subsearcher(self, subsearcher, offset):
WrappingCollector.set_subsearcher(self, subsearcher, offset)
# Store a list of all the term matchers in the matcher tree
self.termmatchers = list(self.child.matcher.term_matchers())
def collect(self, sub_docnum):
child = self.child
termdocs = self.termdocs
docterms = self.docterms
child.collect(sub_docnum)
global_docnum = child.offset + sub_docnum
# For each term matcher...
for tm in self.termmatchers:
# If the term matcher is matching the current document...
if tm.is_active() and tm.id() == sub_docnum:
# Add it to the list of matching documents for the term
term = tm.term()
termdocs[term].append(global_docnum)
docterms[global_docnum].append(term)
def results(self):
r = self.child.results()
r.termdocs = dict(self.termdocs)
r.docterms = dict(self.docterms)
return r