Python types.Integer方法代碼示例

# 需要導入模塊: from sqlalchemy import types [as 別名]
# 或者: from sqlalchemy.types import Integer [as 別名]
def get_type(data_type):
    type_map = {
        "bytes": types.LargeBinary,
        "boolean": types.Boolean,
        "date": types.Date,
        "datetime": types.DateTime,
        "double": types.Numeric,
        "text": types.String,
        "keyword": types.String,
        "integer": types.Integer,
        "half_float": types.Float,
        "geo_point": types.String,
        # TODO get a solution for nested type
        "nested": types.String,
        # TODO get a solution for object
        "object": types.BLOB,
        "long": types.BigInteger,
        "float": types.Float,
        "ip": types.String,
    }
    type_ = type_map.get(data_type)
    if not type_:
        logger.warning(f"Unknown type found {data_type} reverting to string")
        type_ = types.String
    return type_ 

# 需要導入模塊: from sqlalchemy import types [as 別名]
# 或者: from sqlalchemy.types import Integer [as 別名]
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) 

# 需要導入模塊: from sqlalchemy import types [as 別名]
# 或者: from sqlalchemy.types import Integer [as 別名]
def _add_annotation_docs_to_sqlite(dbcon, annotation_docs, item):
    # add full item path for convenience
    annotation_docs.loc[:, "item_name"] = item['name']

    # save tables to sqlite
    annotation_docs.to_sql(
        name='annotation_docs', con=dbcon, if_exists='append',
        dtype={
            'annotation_girder_id': String(),
            '_modelType': String(),
            '_version': Integer(),
            'itemId': String(),
            'item_name': String(),
            'created': String(),
            'creatorId': String(),
            'public': Boolean(),
            'updated': String(),
            'updatedId': String(),
            'groups': String(),
            'element_count': Integer(),
            'element_details': Integer(), },
        index=False,
    ) 

# 需要導入模塊: from sqlalchemy import types [as 別名]
# 或者: from sqlalchemy.types import Integer [as 別名]
def _add_annotation_elements_to_sqlite(dbcon, annotation_elements):
    # drop index relative to JSON since its pretty arbitrary and would
    # change if the same girder client was used to get annotations twice
    # the actual girder ID string is what really matters and should be used
    annotation_elements.drop(
        labels=['annidx', 'elementidx'], axis=1, inplace=True)

    annotation_elements.to_sql(
        name='annotation_elements', con=dbcon, if_exists='append',
        dtype={
            'annotation_girder_id': String(),
            'element_girder_id': String(),
            'type': String(),
            'group': String(),
            'label': String(),
            'color': String(),
            'xmin': Integer(),
            'xmax': Integer(),
            'ymin': Integer(),
            'ymax': Integer(),
            'bbox_area': Integer(),
            'coords_x': String(),
            'coords_y': String(), },
        index=False,
    ) 

# 需要導入模塊: from sqlalchemy import types [as 別名]
# 或者: from sqlalchemy.types import Integer [as 別名]
def set_quality(stage):
    ''' produces cube quality flag '''

    col = 'DRP2QUAL' if stage == '2d' else 'DRP3QUAL'
    label = 'cubequal{0}'.format(stage)
    kwarg = 'DRP{0}QUAL'.format(stage[0])

    @hybrid_property
    def quality(self):
        bits = self.getQualBits(stage=stage)
        return int(bits)

    @quality.expression
    def quality(cls):
        return select([FitsHeaderValue.value.cast(Integer)]).\
                      where(and_(FitsHeaderKeyword.pk==FitsHeaderValue.fits_header_keyword_pk,
                                 FitsHeaderKeyword.label.ilike(kwarg),
                                 FitsHeaderValue.cube_pk==cls.pk)).\
                      label(label)
    return quality 

# 需要導入模塊: from sqlalchemy import types [as 別名]
# 或者: from sqlalchemy.types import Integer [as 別名]
def set_manga_target(targtype):
    ''' produces manga_target flags '''

    label = 'mngtrg{0}'.format(targtype)
    kwarg = 'MNGT%RG{0}'.format(targtype)

    @hybrid_property
    def target(self):
        bits = self.getTargBits(targtype=targtype)
        return int(bits)

    @target.expression
    def target(cls):
        return select([FitsHeaderValue.value.cast(Integer)]).\
                      where(and_(FitsHeaderKeyword.pk==FitsHeaderValue.fits_header_keyword_pk,
                                 FitsHeaderKeyword.label.ilike(kwarg),
                                 FitsHeaderValue.cube_pk==cls.pk)).\
                      label(label)
    return target 

# 需要導入模塊: from sqlalchemy import types [as 別名]
# 或者: from sqlalchemy.types import Integer [as 別名]
def spaxel_factory(classname, clean=None):
    ''' class factory for the spaxelprop tables '''

    if clean:
        classname = 'Clean{0}'.format(classname)
    tablename = classname.lower()

    params = {'__tablename__': tablename, '__table_args__': {'autoload': True, 'schema': 'mangadapdb'}}
    if clean:
        params.update({'pk': Column(Integer, primary_key=True)})

    def newrepr(self):
        return '<{2} (pk={0}, file={1})'.format(self.pk, self.file_pk, classname)

    try:
        newclass = type(classname, (Base, SpaxelAtts,), params)
        newclass.__repr__ = newrepr
    except Exception as e:
        newclass = None

    return newclass


# create the (clean)spaxel models from the DAP datamodel 

# 需要導入模塊: from sqlalchemy import types [as 別名]
# 或者: from sqlalchemy.types import Integer [as 別名]
def visit_column(self, delta):
        table = delta.table
        colspec = self.get_column_specification(delta.result_column)
        if delta.result_column.autoincrement:
            primary_keys = [c for c in table.primary_key.columns
                       if (c.autoincrement and
                            isinstance(c.type, sqltypes.Integer) and
                            not c.foreign_keys)]

            if primary_keys:
                first = primary_keys.pop(0)
                if first.name == delta.current_name:
                    colspec += " AUTO_INCREMENT"
        q = util.safe_quote(table)
        old_col_name = self.preparer.quote(delta.current_name, q)

        self.start_alter_table(table)

        self.append("CHANGE COLUMN %s " % old_col_name)
        self.append(colspec)
        self.execute() 

# 需要導入模塊: from sqlalchemy import types [as 別名]
# 或者: from sqlalchemy.types import Integer [as 別名]
def _adapt_expression(self, op, other_comparator):
            """evaluate the return type of <self> <op> <othertype>,
            and apply any adaptations to the given operator.

            This method determines the type of a resulting binary expression
            given two source types and an operator.   For example, two
            :class:`.Column` objects, both of the type :class:`.Integer`, will
            produce a :class:`.BinaryExpression` that also has the type
            :class:`.Integer` when compared via the addition (``+``) operator.
            However, using the addition operator with an :class:`.Integer`
            and a :class:`.Date` object will produce a :class:`.Date`, assuming
            "days delta" behavior by the database (in reality, most databases
            other than Postgresql don't accept this particular operation).

            The method returns a tuple of the form <operator>, <type>.
            The resulting operator and type will be those applied to the
            resulting :class:`.BinaryExpression` as the final operator and the
            right-hand side of the expression.

            Note that only a subset of operators make usage of
            :meth:`._adapt_expression`,
            including math operators and user-defined operators, but not
            boolean comparison or special SQL keywords like MATCH or BETWEEN.

            """
            return op, other_comparator.type 

# 需要導入模塊: from sqlalchemy import types [as 別名]
# 或者: from sqlalchemy.types import Integer [as 別名]
def define_tables(cls, metadata):
        Table('test_table', metadata,
              Column('id', Integer, primary_key=True),
              Column('data', String(50))
              ) 

# 需要導入模塊: from sqlalchemy import types [as 別名]
# 或者: from sqlalchemy.types import Integer [as 別名]
def test_nullable_reflection(self):
        t = Table('t', self.metadata,
                  Column('a', Integer, nullable=True),
                  Column('b', Integer, nullable=False))
        t.create()
        eq_(
            dict(
                (col['name'], col['nullable'])
                for col in inspect(self.metadata.bind).get_columns('t')
            ),
            {"a": True, "b": False}
        ) 

# 需要導入模塊: from sqlalchemy import types [as 別名]
# 或者: from sqlalchemy.types import Integer [as 別名]
def check_constraint(self, name, source, condition, schema=None, **kw):
        t = sa_schema.Table(source, self.metadata(),
                            sa_schema.Column('x', Integer), schema=schema)
        ck = sa_schema.CheckConstraint(condition, name=name, **kw)
        t.append_constraint(ck)
        return ck 

# 需要導入模塊: from sqlalchemy import types [as 別名]
# 或者: from sqlalchemy.types import Integer [as 別名]
def compare_server_default(self, inspector_column,
                               metadata_column,
                               rendered_metadata_default,
                               rendered_inspector_default):
        # partially a workaround for SQLAlchemy issue #3023; if the
        # column were created without "NOT NULL", MySQL may have added
        # an implicit default of '0' which we need to skip
        if metadata_column.type._type_affinity is sqltypes.Integer and \
            inspector_column.primary_key and \
                not inspector_column.autoincrement and \
                not rendered_metadata_default and \
                rendered_inspector_default == "'0'":
            return False
        else:
            return rendered_inspector_default != rendered_metadata_default 

# 需要導入模塊: from sqlalchemy import types [as 別名]
# 或者: from sqlalchemy.types import Integer [as 別名]
def get_columns(self, connection, table_name, schema=None, **kw):
        # Extend types supported by PrestoDialect as defined in PyHive
        type_map = {
            'bigint': sql_types.BigInteger,
            'integer': sql_types.Integer,
            'boolean': sql_types.Boolean,
            'double': sql_types.Float,
            'varchar': sql_types.String,
            'timestamp': sql_types.TIMESTAMP,
            'date': sql_types.DATE,
            'array<bigint>': sql_types.ARRAY(sql_types.Integer),
            'array<varchar>': sql_types.ARRAY(sql_types.String)
        }

        rows = self._get_table_columns(connection, table_name, schema)
        result = []
        for row in rows:
            try:
                coltype = type_map[row.Type]
            except KeyError:
                logger.warn("Did not recognize type '%s' of column '%s'" % (row.Type, row.Column))
                coltype = sql_types.NullType
            result.append({
                'name': row.Column,
                'type': coltype,
                # newer Presto no longer includes this column
                'nullable': getattr(row, 'Null', True),
                'default': None,
            })
        return result 

# 需要導入模塊: from sqlalchemy import types [as 別名]
# 或者: from sqlalchemy.types import Integer [as 別名]
def test_reflect_select(table, table_using_test_dataset):
    for table in [table, table_using_test_dataset]:
        assert len(table.c) == 18

        assert isinstance(table.c.integer, Column)
        assert isinstance(table.c.integer.type, types.Integer)
        assert isinstance(table.c.timestamp.type, types.TIMESTAMP)
        assert isinstance(table.c.string.type, types.String)
        assert isinstance(table.c.float.type, types.Float)
        assert isinstance(table.c.boolean.type, types.Boolean)
        assert isinstance(table.c.date.type, types.DATE)
        assert isinstance(table.c.datetime.type, types.DATETIME)
        assert isinstance(table.c.time.type, types.TIME)
        assert isinstance(table.c.bytes.type, types.BINARY)
        assert isinstance(table.c['record.age'].type, types.Integer)
        assert isinstance(table.c['record.name'].type, types.String)
        assert isinstance(table.c['nested_record.record.age'].type, types.Integer)
        assert isinstance(table.c['nested_record.record.name'].type, types.String)
        assert isinstance(table.c.array.type, types.ARRAY)

        rows = table.select().execute().fetchall()
        assert len(rows) == 1000