Python fields.NUMERIC属性代码示例

# 需要导入模块: from whoosh import fields [as 别名]
# 或者: from whoosh.fields import NUMERIC [as 别名]
def __init__(self, config, api):
        self.config = config
        self.api = api
        self.cache_dir = user_cache_dir('fac', appauthor=False)
        self.storage = FileStorage(os.path.join(self.cache_dir, 'index'))

        self.schema = Schema(
            name=TEXT(sortable=True, phrase=True, field_boost=3,
                      analyzer=intraword),
            owner=TEXT(sortable=True, field_boost=2.5,
                       analyzer=intraword),
            title=TEXT(field_boost=2.0, phrase=False),
            summary=TEXT(phrase=True),
            downloads=NUMERIC(sortable=True),
            sort_name=SortColumn(),
            name_id=ID(stored=True),
        )

        try:
            self.index = self.storage.open_index()
        except EmptyIndexError:
            self.index = None

        self.db = JSONFile(os.path.join(self.cache_dir, 'mods.json')) 

# 需要导入模块: from whoosh import fields [as 别名]
# 或者: from whoosh.fields import NUMERIC [as 别名]
def fields_map(self, field_type):
        if field_type == "primary":
            return ID(stored=True, unique=True)
        type_map = {
            'date': types.Date,
            'datetime': types.DateTime,
            'boolean': types.Boolean,
            'integer': types.Integer,
            'float': types.Float
        }
        if isinstance(field_type, str):
            field_type = type_map.get(field_type, types.Text)

        if not isinstance(field_type, type):
            field_type = field_type.__class__

        if issubclass(field_type, (types.DateTime, types.Date)):
            return DATETIME(stored=True, sortable=True)
        elif issubclass(field_type, types.Integer):
            return NUMERIC(stored=True, numtype=int)
        elif issubclass(field_type, types.Float):
            return NUMERIC(stored=True, numtype=float)
        elif issubclass(field_type, types.Boolean):
            return BOOLEAN(stored=True)
        return TEXT(stored=True, analyzer=self.analyzer, sortable=False) 

# 需要导入模块: from whoosh import fields [as 别名]
# 或者: from whoosh.fields import NUMERIC [as 别名]
def __init__(self) -> None:
        self.schema = Schema(id=NUMERIC(unique=True, stored=True), canonical_name=STORED(), name=STORED(), name_tokenized=TEXT(stored=False, analyzer=WhooshConstants.tokenized_analyzer), name_stemmed=TEXT(stored=False, analyzer=WhooshConstants.stem_analyzer), name_normalized=TEXT(stored=False, analyzer=WhooshConstants.normalized_analyzer, field_boost=100.0)) 

# 需要导入模块: from whoosh import fields [as 别名]
# 或者: from whoosh.fields import NUMERIC [as 别名]
def _mail_schema(self):
        return Schema(
            ident=ID(stored=True, unique=True),
            sender=ID(stored=False),
            to=KEYWORD(stored=False, commas=True),
            cc=KEYWORD(stored=False, commas=True),
            bcc=KEYWORD(stored=False, commas=True),
            subject=NGRAMWORDS(stored=False),
            date=NUMERIC(stored=False, sortable=True, bits=64, signed=False),
            body=NGRAMWORDS(stored=False),
            tag=KEYWORD(stored=True, commas=True),
            flags=KEYWORD(stored=True, commas=True),
            raw=TEXT(stored=False)) 

# 需要导入模块: from whoosh import fields [as 别名]
# 或者: from whoosh.fields import NUMERIC [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)) 

# 需要导入模块: from whoosh import fields [as 别名]
# 或者: from whoosh.fields import NUMERIC [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)) 

# 需要导入模块: from whoosh import fields [as 别名]
# 或者: from whoosh.fields import NUMERIC [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)) 

# 需要导入模块: from whoosh import fields [as 别名]
# 或者: from whoosh.fields import NUMERIC [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))