Release: 1.2.19 | Release Date: April 15, 2019

# SQLAlchemy 1.2 Documentation

# Base Type API

class `sqlalchemy.types.``TypeEngine`

  Bases: `sqlalchemy.sql.visitors.Visitable`

  The ultimate base class for all SQL datatypes.

  Common subclasses of `TypeEngine` include `String`, `Integer`, and `Boolean`.

  For an overview of the SQLAlchemy typing system, see Column and Data Types.

  See also

  Column and Data Types

  class `Comparator`(expr)

    Bases: `sqlalchemy.sql.operators.ColumnOperators`

    Base class for custom comparison operations defined at the type level. See `TypeEngine.comparator_factory`.

    `operate`(default_comparator, op, *other, **kwargs)

      Operate on an argument.

      This is the lowest level of operation, raises `NotImplementedError` by default.

      Overriding this on a subclass can allow common behavior to be applied to all operations. For example, overriding `ColumnOperators` to apply `func.lower()` to the left and right side:

          class MyComparator(ColumnOperators):
              def operate(self, op, other):
                  return op(func.lower(self), func.lower(other))

      Parameters

        - op – Operator callable.

        - *other – the ‘other’ side of the operation. Will be a single scalar for most operations.

        - **kwargs – modifiers. These may be passed by special operators such as `ColumnOperators.contains()`.

    `reverse_operate`(default_comparator, op, other, **kwargs)

      Reverse operate on an argument.

      Usage is the same as `operate()`.

  `adapt`(cls, **kw)

    Produce an “adapted” form of this type, given an “impl” class to work with.

    This method is used internally to associate generic types with “implementation” types that are specific to a particular dialect.

  `bind_expression`(bindvalue)

    “Given a bind value (i.e. a `BindParameter` instance), return a SQL expression in its place.

    This is typically a SQL function that wraps the existing bound parameter within the statement. It is used for special data types that require literals being wrapped in some special database function in order to coerce an application-level value into a database-specific format. It is the SQL analogue of the `TypeEngine.bind_processor()` method.

    The method is evaluated at statement compile time, as opposed to statement construction time.

    Note that this method, when implemented, should always return the exact same structure, without any conditional logic, as it may be used in an executemany() call against an arbitrary number of bound parameter sets.

    See also

    Applying SQL-level Bind/Result Processing

  `bind_processor`(dialect)

    Return a conversion function for processing bind values.

    Returns a callable which will receive a bind parameter value as the sole positional argument and will return a value to send to the DB-API.

    If processing is not necessary, the method should return `None`.

    Parameters

      dialect – Dialect instance in use.

  `coerce_compared_value`(op, value)

    Suggest a type for a ‘coerced’ Python value in an expression.

    Given an operator and value, gives the type a chance to return a type which the value should be coerced into.

    The default behavior here is conservative; if the right-hand side is already coerced into a SQL type based on its Python type, it is usually left alone.

    End-user functionality extension here should generally be via `TypeDecorator`, which provides more liberal behavior in that it defaults to coercing the other side of the expression into this type, thus applying special Python conversions above and beyond those needed by the DBAPI to both ides. It also provides the public method `TypeDecorator.coerce_compared_value()` which is intended for end-user customization of this behavior.

  `column_expression`(colexpr)

    Given a SELECT column expression, return a wrapping SQL expression.

    This is typically a SQL function that wraps a column expression as rendered in the columns clause of a SELECT statement. It is used for special data types that require columns to be wrapped in some special database function in order to coerce the value before being sent back to the application. It is the SQL analogue of the `TypeEngine.result_processor()` method.

    The method is evaluated at statement compile time, as opposed to statement construction time.

    See also

    Applying SQL-level Bind/Result Processing

  `comparator_factory`

    Bases: `sqlalchemy.sql.operators.ColumnOperators`

    A `TypeEngine.Comparator` class which will apply to operations performed by owning `ColumnElement` objects.

    The `comparator_factory` attribute is a hook consulted by the core expression system when column and SQL expression operations are performed. When a `TypeEngine.Comparator` class is associated with this attribute, it allows custom re-definition of all existing operators, as well as definition of new operators. Existing operators include those provided by Python operator overloading such as `operators.ColumnOperators.__add__()` and `operators.ColumnOperators.__eq__()`, those provided as standard attributes of `operators.ColumnOperators` such as `operators.ColumnOperators.like()` and `operators.ColumnOperators.in_()`.

    Rudimentary usage of this hook is allowed through simple subclassing of existing types, or alternatively by using `TypeDecorator`. See the documentation section Redefining and Creating New Operators for examples.

    alias of `TypeEngine.Comparator`

  `compare_against_backend`(dialect, conn_type)

    Compare this type against the given backend type.

    This function is currently not implemented for SQLAlchemy types, and for all built in types will return `None`. However, it can be implemented by a user-defined type where it can be consumed by schema comparison tools such as Alembic autogenerate.

    A future release of SQLAlchemy will potentially implement this method for builtin types as well.

    The function should return True if this type is equivalent to the given type; the type is typically reflected from the database so should be database specific. The dialect in use is also passed. It can also return False to assert that the type is not equivalent.

    Parameters

      - dialect – a `Dialect` that is involved in the comparison.

      - conn_type – the type object reflected from the backend.

    New in version 1.0.3.

  `compare_values`(x, y)

    Compare two values for equality.

  `compile`(dialect=None)

    Produce a string-compiled form of this `TypeEngine`.

    When called with no arguments, uses a “default” dialect to produce a string result.

    Parameters

      dialect – a `Dialect` instance.

  `dialect_impl`(dialect)

    Return a dialect-specific implementation for this `TypeEngine`.

  `evaluates_none`()

    Return a copy of this type which has the `should_evaluate_none` flag set to True.

    E.g.:

        Table(
            'some_table', metadata,
            Column(
                String(50).evaluates_none(),
                nullable=True,
                server_default='no value')
        )

    The ORM uses this flag to indicate that a positive value of `None` is passed to the column in an INSERT statement, rather than omitting the column from the INSERT statement which has the effect of firing off column-level defaults. It also allows for types which have special behavior associated with the Python None value to indicate that the value doesn’t necessarily translate into SQL NULL; a prime example of this is a JSON type which may wish to persist the JSON value `'null'`.

    In all cases, the actual NULL SQL value can be always be persisted in any column by using the `null` SQL construct in an INSERT statement or associated with an ORM-mapped attribute.

    Note

    The “evaluates none” flag does not apply to a value of `None` passed to `Column.default` or `Column.server_default`; in these cases, `None` still means “no default”.

    New in version 1.1.

    See also

    Forcing NULL on a column with a default - in the ORM documentation

    `postgresql.JSON.none_as_null` - PostgreSQL JSON interaction with this flag.

    `TypeEngine.should_evaluate_none` - class-level flag

  `get_dbapi_type`(dbapi)

    Return the corresponding type object from the underlying DB-API, if any.

    > This can be useful for calling `setinputsizes()`, for example.

  `hashable` = True

    Flag, if False, means values from this type aren’t hashable.

    Used by the ORM when uniquing result lists.

  `literal_processor`(dialect)

    Return a conversion function for processing literal values that are to be rendered directly without using binds.

    This function is used when the compiler makes use of the “literal_binds” flag, typically used in DDL generation as well as in certain scenarios where backends don’t accept bound parameters.

    New in version 0.9.0.

  `python_type`

    Return the Python type object expected to be returned by instances of this type, if known.

    Basically, for those types which enforce a return type, or are known across the board to do such for all common DBAPIs (like `int` for example), will return that type.

    If a return type is not defined, raises `NotImplementedError`.

    Note that any type also accommodates NULL in SQL which means you can also get back `None` from any type in practice.

  `result_processor`(dialect, coltype)

    Return a conversion function for processing result row values.

    Returns a callable which will receive a result row column value as the sole positional argument and will return a value to return to the user.

    If processing is not necessary, the method should return `None`.

    Parameters

      - dialect – Dialect instance in use.

      - coltype – DBAPI coltype argument received in cursor.description.

  `should_evaluate_none` = False

    If True, the Python constant `None` is considered to be handled explicitly by this type.

    The ORM uses this flag to indicate that a positive value of `None` is passed to the column in an INSERT statement, rather than omitting the column from the INSERT statement which has the effect of firing off column-level defaults. It also allows types which have special behavior for Python None, such as a JSON type, to indicate that they’d like to handle the None value explicitly.

    To set this flag on an existing type, use the `TypeEngine.evaluates_none()` method.

    See also

    `TypeEngine.evaluates_none()`

    New in version 1.1.

  `with_variant`(type_, dialect_name)

    Produce a new type object that will utilize the given type when applied to the dialect of the given name.

    e.g.:

        from sqlalchemy.types import String
        from sqlalchemy.dialects import mysql

        s = String()

        s = s.with_variant(mysql.VARCHAR(collation='foo'), 'mysql')

    The construction of `TypeEngine.with_variant()` is always from the “fallback” type to that which is dialect specific. The returned type is an instance of `Variant`, which itself provides a `Variant.with_variant()` that can be called repeatedly.

    Parameters

      - type_ – a `TypeEngine` that will be selected as a variant from the originating type, when a dialect of the given name is in use.

      - dialect_name – base name of the dialect which uses this type. (i.e. `'postgresql'`, `'mysql'`, etc.)

class `sqlalchemy.types.``Concatenable`

  A mixin that marks a type as supporting ‘concatenation’, typically strings.

  class `Comparator`(expr)

    Bases: `sqlalchemy.types.Comparator`

  `comparator_factory`

    alias of `Concatenable.Comparator`

class `sqlalchemy.types.``Indexable`

  A mixin that marks a type as supporting indexing operations, such as array or JSON structures.

  New in version 1.1.0.

  class `Comparator`(expr)

    Bases: `sqlalchemy.types.Comparator`

  `comparator_factory`

    alias of `Indexable.Comparator`

class `sqlalchemy.types.``NullType`

  Bases: `sqlalchemy.types.TypeEngine`

  An unknown type.

  `NullType` is used as a default type for those cases where a type cannot be determined, including:

  - During table reflection, when the type of a column is not recognized by the `Dialect`

  - When constructing SQL expressions using plain Python objects of unknown types (e.g. `somecolumn == my_special_object`)

  - When a new `Column` is created, and the given type is passed as `None` or is not passed at all.

  The `NullType` can be used within SQL expression invocation without issue, it just has no behavior either at the expression construction level or at the bind-parameter/result processing level. `NullType` will result in a `CompileError` if the compiler is asked to render the type itself, such as if it is used in a `cast()` operation or within a schema creation operation such as that invoked by `MetaData.create_all()` or the `CreateTable` construct.

class `sqlalchemy.types.``Variant`(base, mapping)

  Bases: `sqlalchemy.types.TypeDecorator`

  A wrapping type that selects among a variety of implementations based on dialect in use.

  The `Variant` type is typically constructed using the `TypeEngine.with_variant()` method.

  See also

  `TypeEngine.with_variant()` for an example of use.

  Members

    with_variant, __init__