Python types.ARRAY属性代码示例

# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import ARRAY [as 别名]
def get_columns(self, connection, table_name, schema=None, **kw):
        table = self._get_table(connection, table_name, schema)
        columns = self._get_columns_helper(table.schema, [])
        result = []
        for col in columns:
            try:
                coltype = _type_map[col.field_type]
            except KeyError:
                util.warn("Did not recognize type '%s' of column '%s'" % (col.field_type, col.name))

            result.append({
                'name': col.name,
                'type': types.ARRAY(coltype) if col.mode == 'REPEATED' else coltype,
                'nullable': col.mode == 'NULLABLE' or col.mode == 'REPEATED',
                'default': None,
            })

        return result 

# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import ARRAY [as 别名]
def test_arrays_pg(self, connection):
        metadata = self.metadata
        t1 = Table(
            "t",
            metadata,
            Column("x", postgresql.ARRAY(Float)),
            Column("y", postgresql.ARRAY(REAL)),
            Column("z", postgresql.ARRAY(postgresql.DOUBLE_PRECISION)),
            Column("q", postgresql.ARRAY(Numeric)),
        )
        metadata.create_all()
        connection.execute(
            t1.insert(), x=[5], y=[5], z=[6], q=[decimal.Decimal("6.4")]
        )
        row = connection.execute(t1.select()).first()
        eq_(row, ([5], [5], [6], [decimal.Decimal("6.4")])) 

# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import ARRAY [as 别名]
def test_arrays_base(self, connection):
        metadata = self.metadata
        t1 = Table(
            "t",
            metadata,
            Column("x", sqltypes.ARRAY(Float)),
            Column("y", sqltypes.ARRAY(REAL)),
            Column("z", sqltypes.ARRAY(postgresql.DOUBLE_PRECISION)),
            Column("q", sqltypes.ARRAY(Numeric)),
        )
        metadata.create_all()
        connection.execute(
            t1.insert(), x=[5], y=[5], z=[6], q=[decimal.Decimal("6.4")]
        )
        row = connection.execute(t1.select()).first()
        eq_(row, ([5], [5], [6], [decimal.Decimal("6.4")])) 

# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import ARRAY [as 别名]
def test_array_literal_getitem_multidim(self):
        obj = postgresql.array(
            [postgresql.array([1, 2]), postgresql.array([3, 4])]
        )

        self.assert_compile(
            obj,
            "ARRAY[ARRAY[%(param_1)s, %(param_2)s], "
            "ARRAY[%(param_3)s, %(param_4)s]]",
        )
        self.assert_compile(
            obj[1],
            "(ARRAY[ARRAY[%(param_1)s, %(param_2)s], "
            "ARRAY[%(param_3)s, %(param_4)s]])[%(param_5)s]",
        )
        self.assert_compile(
            obj[1][0],
            "(ARRAY[ARRAY[%(param_1)s, %(param_2)s], "
            "ARRAY[%(param_3)s, %(param_4)s]])[%(param_5)s][%(param_6)s]",
        ) 

# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import ARRAY [as 别名]
def test_array_getitem_slice_type(self):
        m = MetaData()
        arrtable = Table(
            "arrtable",
            m,
            Column("intarr", postgresql.ARRAY(Integer)),
            Column("strarr", postgresql.ARRAY(String)),
        )

        # type affinity is Array...
        is_(arrtable.c.intarr[1:3].type._type_affinity, ARRAY)
        is_(arrtable.c.strarr[1:3].type._type_affinity, ARRAY)

        # but the slice returns the actual type
        assert isinstance(arrtable.c.intarr[1:3].type, postgresql.ARRAY)
        assert isinstance(arrtable.c.strarr[1:3].type, postgresql.ARRAY) 

# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import ARRAY [as 别名]
def test_array_plus_native_enum_create(self):
        m = MetaData()
        t = Table(
            "t",
            m,
            Column(
                "data_1",
                self.ARRAY(postgresql.ENUM("a", "b", "c", name="my_enum_1")),
            ),
            Column(
                "data_2",
                self.ARRAY(types.Enum("a", "b", "c", name="my_enum_2")),
            ),
        )

        t.create(testing.db)
        eq_(
            set(e["name"] for e in inspect(testing.db).get_enums()),
            set(["my_enum_1", "my_enum_2"]),
        )
        t.drop(testing.db)
        eq_(inspect(testing.db).get_enums(), []) 

# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import ARRAY [as 别名]
def test_any_array_expression(self, t_fixture):
        t = t_fixture

        self.assert_compile(
            5 == any_(t.c.arrval[5:6] + postgresql.array([3, 4])),
            "%(param_1)s = ANY (tab1.arrval[%(arrval_1)s:%(arrval_2)s] || "
            "ARRAY[%(param_2)s, %(param_3)s])",
            checkparams={
                "arrval_2": 6,
                "param_1": 5,
                "param_3": 4,
                "arrval_1": 5,
                "param_2": 3,
            },
            dialect="postgresql",
        ) 

# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import ARRAY [as 别名]
def test_all_array_expression(self, t_fixture):
        t = t_fixture

        self.assert_compile(
            5 == all_(t.c.arrval[5:6] + postgresql.array([3, 4])),
            "%(param_1)s = ALL (tab1.arrval[%(arrval_1)s:%(arrval_2)s] || "
            "ARRAY[%(param_2)s, %(param_3)s])",
            checkparams={
                "arrval_2": 6,
                "param_1": 5,
                "param_3": 4,
                "arrval_1": 5,
                "param_2": 3,
            },
            dialect="postgresql",
        ) 

# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import ARRAY [as 别名]
def test_querying_table(metadata):
    """
    Create an object for test table.

    """

    # When using pytest-xdist, we don't want concurrent table creations
    # across test processes so we assign a unique name for table based on
    # the current worker id.
    worker_id = os.environ.get('PYTEST_XDIST_WORKER', 'master')
    return Table(
        'test_querying_table_' + worker_id, metadata,
        Column('id', types.Integer, autoincrement=True, primary_key=True),
        Column('serial', types.Integer, Sequence("serial_seq")),
        Column('t_string', types.String(60), onupdate='updated'),
        Column('t_list', types.ARRAY(types.String(60))),
        Column('t_enum', types.Enum(MyEnum)),
        Column('t_int_enum', types.Enum(MyIntEnum)),
        Column('t_datetime', types.DateTime()),
        Column('t_date', types.DateTime()),
        Column('t_interval', types.Interval()),
        Column('uniq_uuid', PG_UUID, nullable=False, unique=True, default=uuid4),
    ) 

# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import ARRAY [as 别名]
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 

# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import ARRAY [as 别名]
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 

# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import ARRAY [as 别名]
def test_compare_array_of_integer_text(self):
        self._compare_default_roundtrip(
            ARRAY(Integer), text("(ARRAY[]::integer[])")
        ) 

# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import ARRAY [as 别名]
def test_postgresql_array_type(self):

        eq_ignore_whitespace(
            autogenerate.render._repr_type(
                ARRAY(Integer), self.autogen_context
            ),
            "postgresql.ARRAY(sa.Integer())",
        )

        eq_ignore_whitespace(
            autogenerate.render._repr_type(
                ARRAY(DateTime(timezone=True)), self.autogen_context
            ),
            "postgresql.ARRAY(sa.DateTime(timezone=True))",
        )

        eq_ignore_whitespace(
            autogenerate.render._repr_type(
                ARRAY(BYTEA, as_tuple=True, dimensions=2), self.autogen_context
            ),
            "postgresql.ARRAY(postgresql.BYTEA(), "
            "as_tuple=True, dimensions=2)",
        )

        assert (
            "from sqlalchemy.dialects import postgresql"
            in self.autogen_context.imports
        ) 

# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import ARRAY [as 别名]
def test_generic_array_type(self):

        eq_ignore_whitespace(
            autogenerate.render._repr_type(
                types.ARRAY(Integer), self.autogen_context
            ),
            "sa.ARRAY(sa.Integer())",
        )

        eq_ignore_whitespace(
            autogenerate.render._repr_type(
                types.ARRAY(DateTime(timezone=True)), self.autogen_context
            ),
            "sa.ARRAY(sa.DateTime(timezone=True))",
        )

        assert (
            "from sqlalchemy.dialects import postgresql"
            not in self.autogen_context.imports
        )

        eq_ignore_whitespace(
            autogenerate.render._repr_type(
                types.ARRAY(BYTEA, as_tuple=True, dimensions=2),
                self.autogen_context,
            ),
            "sa.ARRAY(postgresql.BYTEA(), as_tuple=True, dimensions=2)",
        )

        assert (
            "from sqlalchemy.dialects import postgresql"
            in self.autogen_context.imports
        ) 

# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import ARRAY [as 别名]
def test_array_type_user_defined_inner(self):
        def repr_type(typestring, object_, autogen_context):
            if typestring == "type" and isinstance(object_, String):
                return "foobar.MYVARCHAR"
            else:
                return False

        self.autogen_context.opts.update(render_item=repr_type)

        eq_ignore_whitespace(
            autogenerate.render._repr_type(
                ARRAY(String), self.autogen_context
            ),
            "postgresql.ARRAY(foobar.MYVARCHAR)",
        )