import os
from whoosh import index
from whoosh.fields import Schema, ID, TEXT, NGRAM
# 인덱스 데이터를 저장할 디렉터리 지정하기
INDEX_DIR = "indexdir"
# 인덱스 전용 스키마 정의하기
schema = Schema(
# 인덱스 유닛 ID로 글의 URL 사용하기
post_url=ID(unique=True, stored=True),
# 본문을 N그램으로 인덱스화
body=NGRAM(stored=True),
)
def get_or_create_index():
# 인덱스 전용 디렉터리가 없다면 만들기
if not os.path.exists(INDEX_DIR):
os.mkdir(INDEX_DIR)
# 인덱스 전용 파일 만들기
ix = index.create_in(INDEX_DIR, schema)
return ix
# 이미 인덱스 전용 디렉터리가 있는 경우
# 기존의 인덱스 파일 열어서 사용하기
ix = index.open_dir(INDEX_DIR)
return ix
def build_schema(self, fields):
schema_fields = {
ID: WHOOSH_ID(stored=True, unique=True),
DJANGO_CT: WHOOSH_ID(stored=True),
DJANGO_ID: WHOOSH_ID(stored=True),
}
# Grab the number of keys that are hard-coded into Haystack.
# We'll use this to (possibly) fail slightly more gracefully later.
initial_key_count = len(schema_fields)
content_field_name = ""
for _, field_class in fields.items():
if field_class.is_multivalued:
if field_class.indexed is False:
schema_fields[field_class.index_fieldname] = IDLIST(
stored=True, field_boost=field_class.boost)
else:
schema_fields[field_class.index_fieldname] = KEYWORD(
stored=True,
commas=True,
scorable=True,
field_boost=field_class.boost,
)
elif field_class.field_type in ["date", "datetime"]:
schema_fields[field_class.index_fieldname] = DATETIME(
stored=field_class.stored, sortable=True)
elif field_class.field_type == "integer":
schema_fields[field_class.index_fieldname] = NUMERIC(
stored=field_class.stored,
numtype=int,
field_boost=field_class.boost,
)
elif field_class.field_type == "float":
schema_fields[field_class.index_fieldname] = NUMERIC(
stored=field_class.stored,
numtype=float,
field_boost=field_class.boost,
)
elif field_class.field_type == "boolean":
# Field boost isn't supported on BOOLEAN as of 1.8.2.
schema_fields[field_class.index_fieldname] = BOOLEAN(
stored=field_class.stored)
elif field_class.field_type == "ngram":
schema_fields[field_class.index_fieldname] = NGRAM(
minsize=3,
maxsize=15,
stored=field_class.stored,
field_boost=field_class.boost,
)
elif field_class.field_type == "edge_ngram":
schema_fields[field_class.index_fieldname] = NGRAMWORDS(
minsize=2,
maxsize=15,
at="start",
stored=field_class.stored,
field_boost=field_class.boost,
)
else:
schema_fields[field_class.index_fieldname] = TEXT(
stored=True,
analyzer=StemmingAnalyzer(),
field_boost=field_class.boost,
sortable=True,
)
if field_class.document is True:
content_field_name = field_class.index_fieldname
schema_fields[field_class.index_fieldname].spelling = True
# Fail more gracefully than relying on the backend to die if no fields
# are found.
if len(schema_fields) <= initial_key_count:
raise SearchBackendError(
"No fields were found in any search_indexes. Please correct this before attempting to search."
)
return (content_field_name, Schema(**schema_fields))
class GroupSchema(SchemaClass):
pk = ID(stored=True, unique=True)
name = TEXT(stored=True, spelling=True)
content = NGRAM(minsize=1, phrase=True)
def build_schema(self, fields):
schema_fields = {
ID: WHOOSH_ID(stored=True, unique=True),
DJANGO_CT: WHOOSH_ID(stored=True),
DJANGO_ID: WHOOSH_ID(stored=True),
}
# Grab the number of keys that are hard-coded into Haystack.
# We'll use this to (possibly) fail slightly more gracefully later.
initial_key_count = len(schema_fields)
content_field_name = ''
for field_name, field_class in fields.items():
if field_class.is_multivalued:
if field_class.indexed is False:
schema_fields[field_class.index_fieldname] = IDLIST(
stored=True, field_boost=field_class.boost)
else:
schema_fields[field_class.index_fieldname] = KEYWORD(
stored=True,
commas=True,
scorable=True,
field_boost=field_class.boost)
elif field_class.field_type in ['date', 'datetime']:
schema_fields[field_class.index_fieldname] = DATETIME(
stored=field_class.stored, sortable=True)
elif field_class.field_type == 'integer':
schema_fields[field_class.index_fieldname] = NUMERIC(
stored=field_class.stored,
numtype=int,
field_boost=field_class.boost)
elif field_class.field_type == 'float':
schema_fields[field_class.index_fieldname] = NUMERIC(
stored=field_class.stored,
numtype=float,
field_boost=field_class.boost)
elif field_class.field_type == 'boolean':
# Field boost isn't supported on BOOLEAN as of 1.8.2.
schema_fields[field_class.index_fieldname] = BOOLEAN(
stored=field_class.stored)
elif field_class.field_type == 'ngram':
schema_fields[field_class.index_fieldname] = NGRAM(
minsize=3,
maxsize=15,
stored=field_class.stored,
field_boost=field_class.boost)
elif field_class.field_type == 'edge_ngram':
schema_fields[field_class.index_fieldname] = NGRAMWORDS(
minsize=2,
maxsize=15,
at='start',
stored=field_class.stored,
field_boost=field_class.boost)
else:
# 但在 django haystack 中为 Whoosh 指定的分词器是英文分词器，可能会使得搜索结果不理想，我们把这个分词器替换成 jieba 中文分词器
schema_fields[field_class.index_fieldname] = TEXT(
stored=True,
analyzer=ChineseAnalyzer(),
field_boost=field_class.boost,
sortable=True)
if field_class.document is True:
content_field_name = field_class.index_fieldname
schema_fields[field_class.index_fieldname].spelling = True
# Fail more gracefully than relying on the backend to die if no fields
# are found.
if len(schema_fields) <= initial_key_count:
raise SearchBackendError(
"No fields were found in any search_indexes. Please correct this before attempting to search."
)
return (content_field_name, Schema(**schema_fields))
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
from whoosh import index
from whoosh.fields import Schema, STORED, NGRAM
from whoosh.qparser import QueryParser
from whoosh.analysis import NgramAnalyzer
INDEX_DIR = "/tmp/indexdir"
schema = Schema(title=NGRAM(stored=True))
def open_index(indexdir):
if not os.path.exists(indexdir):
os.mkdir(indexdir)
index.create_in(indexdir, schema)
return index.open_dir(indexdir)
def register(filename, indexdir=INDEX_DIR):
ix = open_index(indexdir)
writer = ix.writer()
for line in open(filename):
writer.add_document(title=line.strip().decode('utf-8'))
writer.commit(optimize=True)
ix.close()
import cPickle as pickle
ROOT = os.path.dirname(os.path.abspath(__file__))
SRCDIR = os.path.join(ROOT, 'source')
BUILDDIR = os.path.join(ROOT, 'build', 'web')
INDEXDIR = os.path.join(BUILDDIR, "data", "db")
print("SRC:{0}, BUILD:{1}, INDEX:{2}".format(SRCDIR, BUILDDIR, INDEXDIR))
uri = os.environ.get('DATABASE_URL') # DATABSE_URL is given
storage = SQLAlchemyStorage(uri)
whoosh = whooshsearch.WhooshSearch
whoosh.schema = Schema(path=ID(stored=True, unique=True),
title=TEXT(field_boost=2.0, stored=True),
text=NGRAM(stored=True))
search = whoosh(INDEXDIR)
support = WebSupport(srcdir=SRCDIR,
builddir=BUILDDIR,
search=search,
storage=storage)
#### flask part
from flask import Flask, render_template, abort, g, request, jsonify, url_for
from jinja2 import Environment, FileSystemLoader
app = Flask(__name__)
#app.debug = True #
all_fields = ['info', 'value', 'comment', 'tags']
# If field is None, search in all
if not fields:
search_fields = all_fields
elif isinstance(fields, list):
for f in fields:
if f not in all_fields:
raise Exception('Invalid Fieldname')
search_fields = fields
else:
search_fields = [fields]
if not os.path.exists("indexdir"):
os.mkdir("indexdir")
ix = open_dir("indexdir")
mparser = MultifieldParser(search_fields, schema=ix.schema, group=OrGroup)
with ix.searcher() as searcher:
q = mparser.parse(query)
responses = searcher.search(q, limit=None)
return Counter([r['eid'] for r in responses])
if __name__ == '__main__':
from connector import SnapshotConnector
connector = SnapshotConnector()
schema = Schema(eid=ID(stored=True),
info=NGRAM(minsize=5, phrase=True),
value=KEYWORD(lowercase=True),
comment=NGRAM(minsize=5, phrase=True),
tags=KEYWORD(lowercase=True))
index_all(connector, schema)
