本文整理汇总了Python中whoosh.analysis.StemmingAnalyzer方法的典型用法代码示例。如果您正苦于以下问题：Python analysis.StemmingAnalyzer方法的具体用法？Python analysis.StemmingAnalyzer怎么用？Python analysis.StemmingAnalyzer使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类whoosh.analysis的用法示例。
在下文中一共展示了analysis.StemmingAnalyzer方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: open_index
# 需要导入模块: from whoosh import analysis [as 别名]
# 或者: from whoosh.analysis import StemmingAnalyzer [as 别名]
def open_index(self, index_folder, create_new=False):
self.index_folder = index_folder
if create_new:
if os.path.exists(index_folder):
shutil.rmtree(index_folder)
print "deleted index folder: " + index_folder
if not os.path.exists(index_folder):
os.mkdir(index_folder)
exists = index.exists_in(index_folder)
stemming_analyzer = StemmingAnalyzer()
schema = Schema(
path=ID(stored=True, unique=True)
, filename=TEXT(stored=True, field_boost=100.0)
, tags=KEYWORD(stored=True, scorable=True, field_boost=80.0)
, headlines=KEYWORD(stored=True, scorable=True, field_boost=60.0)
, doubleemphasiswords=KEYWORD(stored=True, scorable=True, field_boost=40.0)
, emphasiswords=KEYWORD(stored=True, scorable=True, field_boost=20.0)
, content=TEXT(stored=True, analyzer=stemming_analyzer)
, time=STORED
)
if not exists:
self.ix = index.create_in(index_folder, schema)
else:
self.ix = index.open_dir(index_folder) 示例2: build_schema
# 需要导入模块: from whoosh import analysis [as 别名]
# 或者: from whoosh.analysis import StemmingAnalyzer [as 别名]
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:
# schema_fields[field_class.index_fieldname] = TEXT(stored=True, analyzer=StemmingAnalyzer(), field_boost=field_class.boost, sortable=True)
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)) 示例3: build_schema
# 需要导入模块: from whoosh import analysis [as 别名]
# 或者: from whoosh.analysis import StemmingAnalyzer [as 别名]
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: # StemmingAnalyzer->ChineseAnalyzer
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))