本文整理汇总了Python中haystack.constants.DJANGO_CT属性的典型用法代码示例。如果您正苦于以下问题：Python constants.DJANGO_CT属性的具体用法？Python constants.DJANGO_CT怎么用？Python constants.DJANGO_CT使用的例子？那么恭喜您, 这里精选的属性代码示例或许可以为您提供帮助。您也可以进一步了解该属性所在类haystack.constants的用法示例。
在下文中一共展示了constants.DJANGO_CT属性的6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: clear
# 需要导入模块: from haystack import constants [as 别名]
# 或者: from haystack.constants import DJANGO_CT [as 别名]
def clear(self, models=[], commit=True):
if not self.setup_complete:
self.setup()
self.index = self.index.refresh()
try:
if not models:
self.delete_index()
else:
models_to_delete = []
for model in models:
models_to_delete.append(u"%s:%s" % (DJANGO_CT, get_model_ct(model)))
self.index.delete_by_query(q=self.parser.parse(u" OR ".join(models_to_delete)))
except Exception as e:
if not self.silently_fail:
raise
self.log.error("Failed to clear documents from Whoosh: %s", e) 示例2: clear
# 需要导入模块: from haystack import constants [as 别名]
# 或者: from haystack.constants import DJANGO_CT [as 别名]
def clear(self, models=None, commit=True):
if not self.setup_complete:
self.setup()
self.index = self.index.refresh()
if models is not None:
assert isinstance(models, (list, tuple))
try:
if models is None:
self.delete_index()
else:
models_to_delete = []
for model in models:
models_to_delete.append(u"%s:%s" % (DJANGO_CT, get_model_ct(model)))
self.index.delete_by_query(q=self.parser.parse(u" OR ".join(models_to_delete)))
except Exception as e:
if not self.silently_fail:
raise
if models is not None:
self.log.error("Failed to clear Whoosh index of models '%s': %s", ','.join(models_to_delete),
e, exc_info=True)
else:
self.log.error("Failed to clear Whoosh index: %s", e, exc_info=True) 示例3: build_schema
# 需要导入模块: from haystack import constants [as 别名]
# 或者: from haystack.constants import DJANGO_CT [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4: build_schema
# 需要导入模块: from haystack import constants [as 别名]
# 或者: from haystack.constants import DJANGO_CT [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)) 示例5: build_schema
# 需要导入模块: from haystack import constants [as 别名]
# 或者: from haystack.constants import DJANGO_CT [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:
# 调用结巴分词
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6: build_schema
# 需要导入模块: from haystack import constants [as 别名]
# 或者: from haystack.constants import DJANGO_CT [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=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))