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Code Editor : sqltypes.py
# sql/sqltypes.py # Copyright (C) 2005-2014 the SQLAlchemy authors and contributors # <see AUTHORS file> # # This module is part of SQLAlchemy and is released under # the MIT License: http://www.opensource.org/licenses/mit-license.php """SQL specific types. """ import datetime as dt import codecs from .type_api import TypeEngine, TypeDecorator, to_instance from .elements import quoted_name, type_coerce, _defer_name from .default_comparator import _DefaultColumnComparator from .. import exc, util, processors from .base import _bind_or_error, SchemaEventTarget from . import operators from .. import event from ..util import pickle import decimal if util.jython: import array class _DateAffinity(object): """Mixin date/time specific expression adaptations. Rules are implemented within Date,Time,Interval,DateTime, Numeric, Integer. Based on http://www.postgresql.org/docs/current/static /functions-datetime.html. """ @property def _expression_adaptations(self): raise NotImplementedError() class Comparator(TypeEngine.Comparator): _blank_dict = util.immutabledict() def _adapt_expression(self, op, other_comparator): othertype = other_comparator.type._type_affinity return ( op, to_instance( self.type._expression_adaptations. get(op, self._blank_dict). get(othertype, NULLTYPE)) ) comparator_factory = Comparator class Concatenable(object): """A mixin that marks a type as supporting 'concatenation', typically strings.""" class Comparator(TypeEngine.Comparator): def _adapt_expression(self, op, other_comparator): if (op is operators.add and isinstance( other_comparator, (Concatenable.Comparator, NullType.Comparator) )): return operators.concat_op, self.expr.type else: return op, self.expr.type comparator_factory = Comparator class String(Concatenable, TypeEngine): """The base for all string and character types. In SQL, corresponds to VARCHAR. Can also take Python unicode objects and encode to the database's encoding in bind params (and the reverse for result sets.) The `length` field is usually required when the `String` type is used within a CREATE TABLE statement, as VARCHAR requires a length on most databases. """ __visit_name__ = 'string' def __init__(self, length=None, collation=None, convert_unicode=False, unicode_error=None, _warn_on_bytestring=False ): """ Create a string-holding type. :param length: optional, a length for the column for use in DDL and CAST expressions. May be safely omitted if no ``CREATE TABLE`` will be issued. Certain databases may require a ``length`` for use in DDL, and will raise an exception when the ``CREATE TABLE`` DDL is issued if a ``VARCHAR`` with no length is included. Whether the value is interpreted as bytes or characters is database specific. :param collation: Optional, a column-level collation for use in DDL and CAST expressions. Renders using the COLLATE keyword supported by SQLite, MySQL, and Postgresql. E.g.:: >>> from sqlalchemy import cast, select, String >>> print select([cast('some string', String(collation='utf8'))]) SELECT CAST(:param_1 AS VARCHAR COLLATE utf8) AS anon_1 .. versionadded:: 0.8 Added support for COLLATE to all string types. :param convert_unicode: When set to ``True``, the :class:`.String` type will assume that input is to be passed as Python ``unicode`` objects, and results returned as Python ``unicode`` objects. If the DBAPI in use does not support Python unicode (which is fewer and fewer these days), SQLAlchemy will encode/decode the value, using the value of the ``encoding`` parameter passed to :func:`.create_engine` as the encoding. When using a DBAPI that natively supports Python unicode objects, this flag generally does not need to be set. For columns that are explicitly intended to store non-ASCII data, the :class:`.Unicode` or :class:`.UnicodeText` types should be used regardless, which feature the same behavior of ``convert_unicode`` but also indicate an underlying column type that directly supports unicode, such as ``NVARCHAR``. For the extremely rare case that Python ``unicode`` is to be encoded/decoded by SQLAlchemy on a backend that does natively support Python ``unicode``, the value ``force`` can be passed here which will cause SQLAlchemy's encode/decode services to be used unconditionally. :param unicode_error: Optional, a method to use to handle Unicode conversion errors. Behaves like the ``errors`` keyword argument to the standard library's ``string.decode()`` functions. This flag requires that ``convert_unicode`` is set to ``force`` - otherwise, SQLAlchemy is not guaranteed to handle the task of unicode conversion. Note that this flag adds significant performance overhead to row-fetching operations for backends that already return unicode objects natively (which most DBAPIs do). This flag should only be used as a last resort for reading strings from a column with varied or corrupted encodings. """ if unicode_error is not None and convert_unicode != 'force': raise exc.ArgumentError("convert_unicode must be 'force' " "when unicode_error is set.") self.length = length self.collation = collation self.convert_unicode = convert_unicode self.unicode_error = unicode_error self._warn_on_bytestring = _warn_on_bytestring def literal_processor(self, dialect): def process(value): value = value.replace("'", "''") return "'%s'" % value return process def bind_processor(self, dialect): if self.convert_unicode or dialect.convert_unicode: if dialect.supports_unicode_binds and \ self.convert_unicode != 'force': if self._warn_on_bytestring: def process(value): if isinstance(value, util.binary_type): util.warn("Unicode type received non-unicode" "bind param value.") return value return process else: return None else: encoder = codecs.getencoder(dialect.encoding) warn_on_bytestring = self._warn_on_bytestring def process(value): if isinstance(value, util.text_type): return encoder(value, self.unicode_error)[0] elif warn_on_bytestring and value is not None: util.warn("Unicode type received non-unicode bind " "param value") return value return process else: return None def result_processor(self, dialect, coltype): wants_unicode = self.convert_unicode or dialect.convert_unicode needs_convert = wants_unicode and \ (dialect.returns_unicode_strings is not True or self.convert_unicode in ('force', 'force_nocheck')) needs_isinstance = ( needs_convert and dialect.returns_unicode_strings and self.convert_unicode != 'force_nocheck' ) if needs_convert: to_unicode = processors.to_unicode_processor_factory( dialect.encoding, self.unicode_error) if needs_isinstance: return processors.to_conditional_unicode_processor_factory( dialect.encoding, self.unicode_error) else: return processors.to_unicode_processor_factory( dialect.encoding, self.unicode_error) else: return None @property def python_type(self): if self.convert_unicode: return util.text_type else: return str def get_dbapi_type(self, dbapi): return dbapi.STRING class Text(String): """A variably sized string type. In SQL, usually corresponds to CLOB or TEXT. Can also take Python unicode objects and encode to the database's encoding in bind params (and the reverse for result sets.) In general, TEXT objects do not have a length; while some databases will accept a length argument here, it will be rejected by others. """ __visit_name__ = 'text' class Unicode(String): """A variable length Unicode string type. The :class:`.Unicode` type is a :class:`.String` subclass that assumes input and output as Python ``unicode`` data, and in that regard is equivalent to the usage of the ``convert_unicode`` flag with the :class:`.String` type. However, unlike plain :class:`.String`, it also implies an underlying column type that is explicitly supporting of non-ASCII data, such as ``NVARCHAR`` on Oracle and SQL Server. This can impact the output of ``CREATE TABLE`` statements and ``CAST`` functions at the dialect level, and can also affect the handling of bound parameters in some specific DBAPI scenarios. The encoding used by the :class:`.Unicode` type is usually determined by the DBAPI itself; most modern DBAPIs feature support for Python ``unicode`` objects as bound values and result set values, and the encoding should be configured as detailed in the notes for the target DBAPI in the :ref:`dialect_toplevel` section. For those DBAPIs which do not support, or are not configured to accommodate Python ``unicode`` objects directly, SQLAlchemy does the encoding and decoding outside of the DBAPI. The encoding in this scenario is determined by the ``encoding`` flag passed to :func:`.create_engine`. When using the :class:`.Unicode` type, it is only appropriate to pass Python ``unicode`` objects, and not plain ``str``. If a plain ``str`` is passed under Python 2, a warning is emitted. If you notice your application emitting these warnings but you're not sure of the source of them, the Python ``warnings`` filter, documented at http://docs.python.org/library/warnings.html, can be used to turn these warnings into exceptions which will illustrate a stack trace:: import warnings warnings.simplefilter('error') For an application that wishes to pass plain bytestrings and Python ``unicode`` objects to the ``Unicode`` type equally, the bytestrings must first be decoded into unicode. The recipe at :ref:`coerce_to_unicode` illustrates how this is done. See also: :class:`.UnicodeText` - unlengthed textual counterpart to :class:`.Unicode`. """ __visit_name__ = 'unicode' def __init__(self, length=None, **kwargs): """ Create a :class:`.Unicode` object. Parameters are the same as that of :class:`.String`, with the exception that ``convert_unicode`` defaults to ``True``. """ kwargs.setdefault('convert_unicode', True) kwargs.setdefault('_warn_on_bytestring', True) super(Unicode, self).__init__(length=length, **kwargs) class UnicodeText(Text): """An unbounded-length Unicode string type. See :class:`.Unicode` for details on the unicode behavior of this object. Like :class:`.Unicode`, usage the :class:`.UnicodeText` type implies a unicode-capable type being used on the backend, such as ``NCLOB``, ``NTEXT``. """ __visit_name__ = 'unicode_text' def __init__(self, length=None, **kwargs): """ Create a Unicode-converting Text type. Parameters are the same as that of :class:`.Text`, with the exception that ``convert_unicode`` defaults to ``True``. """ kwargs.setdefault('convert_unicode', True) kwargs.setdefault('_warn_on_bytestring', True) super(UnicodeText, self).__init__(length=length, **kwargs) class Integer(_DateAffinity, TypeEngine): """A type for ``int`` integers.""" __visit_name__ = 'integer' def get_dbapi_type(self, dbapi): return dbapi.NUMBER @property def python_type(self): return int def literal_processor(self, dialect): def process(value): return str(value) return process @util.memoized_property def _expression_adaptations(self): # TODO: need a dictionary object that will # handle operators generically here, this is incomplete return { operators.add: { Date: Date, Integer: self.__class__, Numeric: Numeric, }, operators.mul: { Interval: Interval, Integer: self.__class__, Numeric: Numeric, }, operators.div: { Integer: self.__class__, Numeric: Numeric, }, operators.truediv: { Integer: self.__class__, Numeric: Numeric, }, operators.sub: { Integer: self.__class__, Numeric: Numeric, }, } class SmallInteger(Integer): """A type for smaller ``int`` integers. Typically generates a ``SMALLINT`` in DDL, and otherwise acts like a normal :class:`.Integer` on the Python side. """ __visit_name__ = 'small_integer' class BigInteger(Integer): """A type for bigger ``int`` integers. Typically generates a ``BIGINT`` in DDL, and otherwise acts like a normal :class:`.Integer` on the Python side. """ __visit_name__ = 'big_integer' class Numeric(_DateAffinity, TypeEngine): """A type for fixed precision numbers, such as ``NUMERIC`` or ``DECIMAL``. This type returns Python ``decimal.Decimal`` objects by default, unless the :paramref:`.Numeric.asdecimal` flag is set to False, in which case they are coerced to Python ``float`` objects. .. note:: The :class:`.Numeric` type is designed to receive data from a database type that is explicitly known to be a decimal type (e.g. ``DECIMAL``, ``NUMERIC``, others) and not a floating point type (e.g. ``FLOAT``, ``REAL``, others). If the database column on the server is in fact a floating-point type type, such as ``FLOAT`` or ``REAL``, use the :class:`.Float` type or a subclass, otherwise numeric coercion between ``float``/``Decimal`` may or may not function as expected. .. note:: The Python ``decimal.Decimal`` class is generally slow performing; cPython 3.3 has now switched to use the `cdecimal <http://pypi.python.org/pypi/cdecimal/>`_ library natively. For older Python versions, the ``cdecimal`` library can be patched into any application where it will replace the ``decimal`` library fully, however this needs to be applied globally and before any other modules have been imported, as follows:: import sys import cdecimal sys.modules["decimal"] = cdecimal Note that the ``cdecimal`` and ``decimal`` libraries are **not compatible with each other**, so patching ``cdecimal`` at the global level is the only way it can be used effectively with various DBAPIs that hardcode to import the ``decimal`` library. """ __visit_name__ = 'numeric' _default_decimal_return_scale = 10 def __init__(self, precision=None, scale=None, decimal_return_scale=None, asdecimal=True): """ Construct a Numeric. :param precision: the numeric precision for use in DDL ``CREATE TABLE``. :param scale: the numeric scale for use in DDL ``CREATE TABLE``. :param asdecimal: default True. Return whether or not values should be sent as Python Decimal objects, or as floats. Different DBAPIs send one or the other based on datatypes - the Numeric type will ensure that return values are one or the other across DBAPIs consistently. :param decimal_return_scale: Default scale to use when converting from floats to Python decimals. Floating point values will typically be much longer due to decimal inaccuracy, and most floating point database types don't have a notion of "scale", so by default the float type looks for the first ten decimal places when converting. Specfiying this value will override that length. Types which do include an explicit ".scale" value, such as the base :class:`.Numeric` as well as the MySQL float types, will use the value of ".scale" as the default for decimal_return_scale, if not otherwise specified. .. versionadded:: 0.9.0 When using the ``Numeric`` type, care should be taken to ensure that the asdecimal setting is apppropriate for the DBAPI in use - when Numeric applies a conversion from Decimal->float or float-> Decimal, this conversion incurs an additional performance overhead for all result columns received. DBAPIs that return Decimal natively (e.g. psycopg2) will have better accuracy and higher performance with a setting of ``True``, as the native translation to Decimal reduces the amount of floating- point issues at play, and the Numeric type itself doesn't need to apply any further conversions. However, another DBAPI which returns floats natively *will* incur an additional conversion overhead, and is still subject to floating point data loss - in which case ``asdecimal=False`` will at least remove the extra conversion overhead. """ self.precision = precision self.scale = scale self.decimal_return_scale = decimal_return_scale self.asdecimal = asdecimal @property def _effective_decimal_return_scale(self): if self.decimal_return_scale is not None: return self.decimal_return_scale elif getattr(self, "scale", None) is not None: return self.scale else: return self._default_decimal_return_scale def get_dbapi_type(self, dbapi): return dbapi.NUMBER def literal_processor(self, dialect): def process(value): return str(value) return process @property def python_type(self): if self.asdecimal: return decimal.Decimal else: return float def bind_processor(self, dialect): if dialect.supports_native_decimal: return None else: return processors.to_float def result_processor(self, dialect, coltype): if self.asdecimal: if dialect.supports_native_decimal: # we're a "numeric", DBAPI will give us Decimal directly return None else: util.warn('Dialect %s+%s does *not* support Decimal ' 'objects natively, and SQLAlchemy must ' 'convert from floating point - rounding ' 'errors and other issues may occur. Please ' 'consider storing Decimal numbers as strings ' 'or integers on this platform for lossless ' 'storage.' % (dialect.name, dialect.driver)) # we're a "numeric", DBAPI returns floats, convert. return processors.to_decimal_processor_factory( decimal.Decimal, self.scale if self.scale is not None else self._default_decimal_return_scale) else: if dialect.supports_native_decimal: return processors.to_float else: return None @util.memoized_property def _expression_adaptations(self): return { operators.mul: { Interval: Interval, Numeric: self.__class__, Integer: self.__class__, }, operators.div: { Numeric: self.__class__, Integer: self.__class__, }, operators.truediv: { Numeric: self.__class__, Integer: self.__class__, }, operators.add: { Numeric: self.__class__, Integer: self.__class__, }, operators.sub: { Numeric: self.__class__, Integer: self.__class__, } } class Float(Numeric): """Type representing floating point types, such as ``FLOAT`` or ``REAL``. This type returns Python ``float`` objects by default, unless the :paramref:`.Float.asdecimal` flag is set to True, in which case they are coerced to ``decimal.Decimal`` objects. .. note:: The :class:`.Float` type is designed to receive data from a database type that is explicitly known to be a floating point type (e.g. ``FLOAT``, ``REAL``, others) and not a decimal type (e.g. ``DECIMAL``, ``NUMERIC``, others). If the database column on the server is in fact a Numeric type, such as ``DECIMAL`` or ``NUMERIC``, use the :class:`.Numeric` type or a subclass, otherwise numeric coercion between ``float``/``Decimal`` may or may not function as expected. """ __visit_name__ = 'float' scale = None def __init__(self, precision=None, asdecimal=False, decimal_return_scale=None, **kwargs): """ Construct a Float. :param precision: the numeric precision for use in DDL ``CREATE TABLE``. :param asdecimal: the same flag as that of :class:`.Numeric`, but defaults to ``False``. Note that setting this flag to ``True`` results in floating point conversion. :param decimal_return_scale: Default scale to use when converting from floats to Python decimals. Floating point values will typically be much longer due to decimal inaccuracy, and most floating point database types don't have a notion of "scale", so by default the float type looks for the first ten decimal places when converting. Specfiying this value will override that length. Note that the MySQL float types, which do include "scale", will use "scale" as the default for decimal_return_scale, if not otherwise specified. .. versionadded:: 0.9.0 :param \**kwargs: deprecated. Additional arguments here are ignored by the default :class:`.Float` type. For database specific floats that support additional arguments, see that dialect's documentation for details, such as :class:`sqlalchemy.dialects.mysql.FLOAT`. """ self.precision = precision self.asdecimal = asdecimal self.decimal_return_scale = decimal_return_scale if kwargs: util.warn_deprecated("Additional keyword arguments " "passed to Float ignored.") def result_processor(self, dialect, coltype): if self.asdecimal: return processors.to_decimal_processor_factory( decimal.Decimal, self._effective_decimal_return_scale) else: return None @util.memoized_property def _expression_adaptations(self): return { operators.mul: { Interval: Interval, Numeric: self.__class__, }, operators.div: { Numeric: self.__class__, }, operators.truediv: { Numeric: self.__class__, }, operators.add: { Numeric: self.__class__, }, operators.sub: { Numeric: self.__class__, } } class DateTime(_DateAffinity, TypeEngine): """A type for ``datetime.datetime()`` objects. Date and time types return objects from the Python ``datetime`` module. Most DBAPIs have built in support for the datetime module, with the noted exception of SQLite. In the case of SQLite, date and time types are stored as strings which are then converted back to datetime objects when rows are returned. """ __visit_name__ = 'datetime' def __init__(self, timezone=False): """Construct a new :class:`.DateTime`. :param timezone: boolean. If True, and supported by the backend, will produce 'TIMESTAMP WITH TIMEZONE'. For backends that don't support timezone aware timestamps, has no effect. """ self.timezone = timezone def get_dbapi_type(self, dbapi): return dbapi.DATETIME @property def python_type(self): return dt.datetime @util.memoized_property def _expression_adaptations(self): return { operators.add: { Interval: self.__class__, }, operators.sub: { Interval: self.__class__, DateTime: Interval, }, } class Date(_DateAffinity, TypeEngine): """A type for ``datetime.date()`` objects.""" __visit_name__ = 'date' def get_dbapi_type(self, dbapi): return dbapi.DATETIME @property def python_type(self): return dt.date @util.memoized_property def _expression_adaptations(self): return { operators.add: { Integer: self.__class__, Interval: DateTime, Time: DateTime, }, operators.sub: { # date - integer = date Integer: self.__class__, # date - date = integer. Date: Integer, Interval: DateTime, # date - datetime = interval, # this one is not in the PG docs # but works DateTime: Interval, }, } class Time(_DateAffinity, TypeEngine): """A type for ``datetime.time()`` objects.""" __visit_name__ = 'time' def __init__(self, timezone=False): self.timezone = timezone def get_dbapi_type(self, dbapi): return dbapi.DATETIME @property def python_type(self): return dt.time @util.memoized_property def _expression_adaptations(self): return { operators.add: { Date: DateTime, Interval: self.__class__ }, operators.sub: { Time: Interval, Interval: self.__class__, }, } class _Binary(TypeEngine): """Define base behavior for binary types.""" def __init__(self, length=None): self.length = length def literal_processor(self, dialect): def process(value): value = value.decode(dialect.encoding).replace("'", "''") return "'%s'" % value return process @property def python_type(self): return util.binary_type # Python 3 - sqlite3 doesn't need the `Binary` conversion # here, though pg8000 does to indicate "bytea" def bind_processor(self, dialect): if dialect.dbapi is None: return None DBAPIBinary = dialect.dbapi.Binary def process(value): if value is not None: return DBAPIBinary(value) else: return None return process # Python 3 has native bytes() type # both sqlite3 and pg8000 seem to return it, # psycopg2 as of 2.5 returns 'memoryview' if util.py2k: def result_processor(self, dialect, coltype): if util.jython: def process(value): if value is not None: if isinstance(value, array.array): return value.tostring() return str(value) else: return None else: process = processors.to_str return process else: def result_processor(self, dialect, coltype): def process(value): if value is not None: value = bytes(value) return value return process def coerce_compared_value(self, op, value): """See :meth:`.TypeEngine.coerce_compared_value` for a description.""" if isinstance(value, util.string_types): return self else: return super(_Binary, self).coerce_compared_value(op, value) def get_dbapi_type(self, dbapi): return dbapi.BINARY class LargeBinary(_Binary): """A type for large binary byte data. The Binary type generates BLOB or BYTEA when tables are created, and also converts incoming values using the ``Binary`` callable provided by each DB-API. """ __visit_name__ = 'large_binary' def __init__(self, length=None): """ Construct a LargeBinary type. :param length: optional, a length for the column for use in DDL statements, for those BLOB types that accept a length (i.e. MySQL). It does *not* produce a small BINARY/VARBINARY type - use the BINARY/VARBINARY types specifically for those. May be safely omitted if no ``CREATE TABLE`` will be issued. Certain databases may require a *length* for use in DDL, and will raise an exception when the ``CREATE TABLE`` DDL is issued. """ _Binary.__init__(self, length=length) class Binary(LargeBinary): """Deprecated. Renamed to LargeBinary.""" def __init__(self, *arg, **kw): util.warn_deprecated('The Binary type has been renamed to ' 'LargeBinary.') LargeBinary.__init__(self, *arg, **kw) class SchemaType(SchemaEventTarget): """Mark a type as possibly requiring schema-level DDL for usage. Supports types that must be explicitly created/dropped (i.e. PG ENUM type) as well as types that are complimented by table or schema level constraints, triggers, and other rules. :class:`.SchemaType` classes can also be targets for the :meth:`.DDLEvents.before_parent_attach` and :meth:`.DDLEvents.after_parent_attach` events, where the events fire off surrounding the association of the type object with a parent :class:`.Column`. .. seealso:: :class:`.Enum` :class:`.Boolean` """ def __init__(self, name=None, schema=None, metadata=None, inherit_schema=False, quote=None): if name is not None: self.name = quoted_name(name, quote) else: self.name = None self.schema = schema self.metadata = metadata self.inherit_schema = inherit_schema if self.metadata: event.listen( self.metadata, "before_create", util.portable_instancemethod(self._on_metadata_create) ) event.listen( self.metadata, "after_drop", util.portable_instancemethod(self._on_metadata_drop) ) def _set_parent(self, column): column._on_table_attach(util.portable_instancemethod(self._set_table)) def _set_table(self, column, table): if self.inherit_schema: self.schema = table.schema event.listen( table, "before_create", util.portable_instancemethod( self._on_table_create) ) event.listen( table, "after_drop", util.portable_instancemethod(self._on_table_drop) ) if self.metadata is None: # TODO: what's the difference between self.metadata # and table.metadata here ? event.listen( table.metadata, "before_create", util.portable_instancemethod(self._on_metadata_create) ) event.listen( table.metadata, "after_drop", util.portable_instancemethod(self._on_metadata_drop) ) def copy(self, **kw): return self.adapt(self.__class__) def adapt(self, impltype, **kw): schema = kw.pop('schema', self.schema) # don't associate with MetaData as the hosting type # is already associated with it, avoid creating event # listeners metadata = kw.pop('metadata', None) return impltype(name=self.name, schema=schema, metadata=metadata, inherit_schema=self.inherit_schema, **kw) @property def bind(self): return self.metadata and self.metadata.bind or None def create(self, bind=None, checkfirst=False): """Issue CREATE ddl for this type, if applicable.""" if bind is None: bind = _bind_or_error(self) t = self.dialect_impl(bind.dialect) if t.__class__ is not self.__class__ and isinstance(t, SchemaType): t.create(bind=bind, checkfirst=checkfirst) def drop(self, bind=None, checkfirst=False): """Issue DROP ddl for this type, if applicable.""" if bind is None: bind = _bind_or_error(self) t = self.dialect_impl(bind.dialect) if t.__class__ is not self.__class__ and isinstance(t, SchemaType): t.drop(bind=bind, checkfirst=checkfirst) def _on_table_create(self, target, bind, **kw): t = self.dialect_impl(bind.dialect) if t.__class__ is not self.__class__ and isinstance(t, SchemaType): t._on_table_create(target, bind, **kw) def _on_table_drop(self, target, bind, **kw): t = self.dialect_impl(bind.dialect) if t.__class__ is not self.__class__ and isinstance(t, SchemaType): t._on_table_drop(target, bind, **kw) def _on_metadata_create(self, target, bind, **kw): t = self.dialect_impl(bind.dialect) if t.__class__ is not self.__class__ and isinstance(t, SchemaType): t._on_metadata_create(target, bind, **kw) def _on_metadata_drop(self, target, bind, **kw): t = self.dialect_impl(bind.dialect) if t.__class__ is not self.__class__ and isinstance(t, SchemaType): t._on_metadata_drop(target, bind, **kw) class Enum(String, SchemaType): """Generic Enum Type. The Enum type provides a set of possible string values which the column is constrained towards. By default, uses the backend's native ENUM type if available, else uses VARCHAR + a CHECK constraint. .. seealso:: :class:`~.postgresql.ENUM` - PostgreSQL-specific type, which has additional functionality. """ __visit_name__ = 'enum' def __init__(self, *enums, **kw): """Construct an enum. Keyword arguments which don't apply to a specific backend are ignored by that backend. :param \*enums: string or unicode enumeration labels. If unicode labels are present, the `convert_unicode` flag is auto-enabled. :param convert_unicode: Enable unicode-aware bind parameter and result-set processing for this Enum's data. This is set automatically based on the presence of unicode label strings. :param metadata: Associate this type directly with a ``MetaData`` object. For types that exist on the target database as an independent schema construct (Postgresql), this type will be created and dropped within ``create_all()`` and ``drop_all()`` operations. If the type is not associated with any ``MetaData`` object, it will associate itself with each ``Table`` in which it is used, and will be created when any of those individual tables are created, after a check is performed for its existence. The type is only dropped when ``drop_all()`` is called for that ``Table`` object's metadata, however. :param name: The name of this type. This is required for Postgresql and any future supported database which requires an explicitly named type, or an explicitly named constraint in order to generate the type and/or a table that uses it. :param native_enum: Use the database's native ENUM type when available. Defaults to True. When False, uses VARCHAR + check constraint for all backends. :param schema: Schema name of this type. For types that exist on the target database as an independent schema construct (Postgresql), this parameter specifies the named schema in which the type is present. .. note:: The ``schema`` of the :class:`.Enum` type does not by default make use of the ``schema`` established on the owning :class:`.Table`. If this behavior is desired, set the ``inherit_schema`` flag to ``True``. :param quote: Set explicit quoting preferences for the type's name. :param inherit_schema: When ``True``, the "schema" from the owning :class:`.Table` will be copied to the "schema" attribute of this :class:`.Enum`, replacing whatever value was passed for the ``schema`` attribute. This also takes effect when using the :meth:`.Table.tometadata` operation. .. versionadded:: 0.8 """ self.enums = enums self.native_enum = kw.pop('native_enum', True) convert_unicode = kw.pop('convert_unicode', None) if convert_unicode is None: for e in enums: if isinstance(e, util.text_type): convert_unicode = True break else: convert_unicode = False if self.enums: length = max(len(x) for x in self.enums) else: length = 0 String.__init__(self, length=length, convert_unicode=convert_unicode, ) SchemaType.__init__(self, **kw) def __repr__(self): return util.generic_repr(self, to_inspect=[Enum, SchemaType], ) def _should_create_constraint(self, compiler): return not self.native_enum or \ not compiler.dialect.supports_native_enum @util.dependencies("sqlalchemy.sql.schema") def _set_table(self, schema, column, table): if self.native_enum: SchemaType._set_table(self, column, table) e = schema.CheckConstraint( type_coerce(column, self).in_(self.enums), name=_defer_name(self.name), _create_rule=util.portable_instancemethod( self._should_create_constraint) ) assert e.table is table def adapt(self, impltype, **kw): schema = kw.pop('schema', self.schema) metadata = kw.pop('metadata', None) if issubclass(impltype, Enum): return impltype(name=self.name, schema=schema, metadata=metadata, convert_unicode=self.convert_unicode, native_enum=self.native_enum, inherit_schema=self.inherit_schema, *self.enums, **kw) else: return super(Enum, self).adapt(impltype, **kw) class PickleType(TypeDecorator): """Holds Python objects, which are serialized using pickle. PickleType builds upon the Binary type to apply Python's ``pickle.dumps()`` to incoming objects, and ``pickle.loads()`` on the way out, allowing any pickleable Python object to be stored as a serialized binary field. To allow ORM change events to propagate for elements associated with :class:`.PickleType`, see :ref:`mutable_toplevel`. """ impl = LargeBinary def __init__(self, protocol=pickle.HIGHEST_PROTOCOL, pickler=None, comparator=None): """ Construct a PickleType. :param protocol: defaults to ``pickle.HIGHEST_PROTOCOL``. :param pickler: defaults to cPickle.pickle or pickle.pickle if cPickle is not available. May be any object with pickle-compatible ``dumps` and ``loads`` methods. :param comparator: a 2-arg callable predicate used to compare values of this type. If left as ``None``, the Python "equals" operator is used to compare values. """ self.protocol = protocol self.pickler = pickler or pickle self.comparator = comparator super(PickleType, self).__init__() def __reduce__(self): return PickleType, (self.protocol, None, self.comparator) def bind_processor(self, dialect): impl_processor = self.impl.bind_processor(dialect) dumps = self.pickler.dumps protocol = self.protocol if impl_processor: def process(value): if value is not None: value = dumps(value, protocol) return impl_processor(value) else: def process(value): if value is not None: value = dumps(value, protocol) return value return process def result_processor(self, dialect, coltype): impl_processor = self.impl.result_processor(dialect, coltype) loads = self.pickler.loads if impl_processor: def process(value): value = impl_processor(value) if value is None: return None return loads(value) else: def process(value): if value is None: return None return loads(value) return process def compare_values(self, x, y): if self.comparator: return self.comparator(x, y) else: return x == y class Boolean(TypeEngine, SchemaType): """A bool datatype. Boolean typically uses BOOLEAN or SMALLINT on the DDL side, and on the Python side deals in ``True`` or ``False``. """ __visit_name__ = 'boolean' def __init__(self, create_constraint=True, name=None): """Construct a Boolean. :param create_constraint: defaults to True. If the boolean is generated as an int/smallint, also create a CHECK constraint on the table that ensures 1 or 0 as a value. :param name: if a CHECK constraint is generated, specify the name of the constraint. """ self.create_constraint = create_constraint self.name = name def _should_create_constraint(self, compiler): return not compiler.dialect.supports_native_boolean @util.dependencies("sqlalchemy.sql.schema") def _set_table(self, schema, column, table): if not self.create_constraint: return e = schema.CheckConstraint( type_coerce(column, self).in_([0, 1]), name=_defer_name(self.name), _create_rule=util.portable_instancemethod( self._should_create_constraint) ) assert e.table is table @property def python_type(self): return bool def literal_processor(self, dialect): if dialect.supports_native_boolean: def process(value): return "true" if value else "false" else: def process(value): return str(1 if value else 0) return process def bind_processor(self, dialect): if dialect.supports_native_boolean: return None else: return processors.boolean_to_int def result_processor(self, dialect, coltype): if dialect.supports_native_boolean: return None else: return processors.int_to_boolean class Interval(_DateAffinity, TypeDecorator): """A type for ``datetime.timedelta()`` objects. The Interval type deals with ``datetime.timedelta`` objects. In PostgreSQL, the native ``INTERVAL`` type is used; for others, the value is stored as a date which is relative to the "epoch" (Jan. 1, 1970). Note that the ``Interval`` type does not currently provide date arithmetic operations on platforms which do not support interval types natively. Such operations usually require transformation of both sides of the expression (such as, conversion of both sides into integer epoch values first) which currently is a manual procedure (such as via :attr:`~sqlalchemy.sql.expression.func`). """ impl = DateTime epoch = dt.datetime.utcfromtimestamp(0) def __init__(self, native=True, second_precision=None, day_precision=None): """Construct an Interval object. :param native: when True, use the actual INTERVAL type provided by the database, if supported (currently Postgresql, Oracle). Otherwise, represent the interval data as an epoch value regardless. :param second_precision: For native interval types which support a "fractional seconds precision" parameter, i.e. Oracle and Postgresql :param day_precision: for native interval types which support a "day precision" parameter, i.e. Oracle. """ super(Interval, self).__init__() self.native = native self.second_precision = second_precision self.day_precision = day_precision def adapt(self, cls, **kw): if self.native and hasattr(cls, '_adapt_from_generic_interval'): return cls._adapt_from_generic_interval(self, **kw) else: return self.__class__( native=self.native, second_precision=self.second_precision, day_precision=self.day_precision, **kw) @property def python_type(self): return dt.timedelta def bind_processor(self, dialect): impl_processor = self.impl.bind_processor(dialect) epoch = self.epoch if impl_processor: def process(value): if value is not None: value = epoch + value return impl_processor(value) else: def process(value): if value is not None: value = epoch + value return value return process def result_processor(self, dialect, coltype): impl_processor = self.impl.result_processor(dialect, coltype) epoch = self.epoch if impl_processor: def process(value): value = impl_processor(value) if value is None: return None return value - epoch else: def process(value): if value is None: return None return value - epoch return process @util.memoized_property def _expression_adaptations(self): return { operators.add: { Date: DateTime, Interval: self.__class__, DateTime: DateTime, Time: Time, }, operators.sub: { Interval: self.__class__ }, operators.mul: { Numeric: self.__class__ }, operators.truediv: { Numeric: self.__class__ }, operators.div: { Numeric: self.__class__ } } @property def _type_affinity(self): return Interval def coerce_compared_value(self, op, value): """See :meth:`.TypeEngine.coerce_compared_value` for a description.""" return self.impl.coerce_compared_value(op, value) class REAL(Float): """The SQL REAL type.""" __visit_name__ = 'REAL' class FLOAT(Float): """The SQL FLOAT type.""" __visit_name__ = 'FLOAT' class NUMERIC(Numeric): """The SQL NUMERIC type.""" __visit_name__ = 'NUMERIC' class DECIMAL(Numeric): """The SQL DECIMAL type.""" __visit_name__ = 'DECIMAL' class INTEGER(Integer): """The SQL INT or INTEGER type.""" __visit_name__ = 'INTEGER' INT = INTEGER class SMALLINT(SmallInteger): """The SQL SMALLINT type.""" __visit_name__ = 'SMALLINT' class BIGINT(BigInteger): """The SQL BIGINT type.""" __visit_name__ = 'BIGINT' class TIMESTAMP(DateTime): """The SQL TIMESTAMP type.""" __visit_name__ = 'TIMESTAMP' def get_dbapi_type(self, dbapi): return dbapi.TIMESTAMP class DATETIME(DateTime): """The SQL DATETIME type.""" __visit_name__ = 'DATETIME' class DATE(Date): """The SQL DATE type.""" __visit_name__ = 'DATE' class TIME(Time): """The SQL TIME type.""" __visit_name__ = 'TIME' class TEXT(Text): """The SQL TEXT type.""" __visit_name__ = 'TEXT' class CLOB(Text): """The CLOB type. This type is found in Oracle and Informix. """ __visit_name__ = 'CLOB' class VARCHAR(String): """The SQL VARCHAR type.""" __visit_name__ = 'VARCHAR' class NVARCHAR(Unicode): """The SQL NVARCHAR type.""" __visit_name__ = 'NVARCHAR' class CHAR(String): """The SQL CHAR type.""" __visit_name__ = 'CHAR' class NCHAR(Unicode): """The SQL NCHAR type.""" __visit_name__ = 'NCHAR' class BLOB(LargeBinary): """The SQL BLOB type.""" __visit_name__ = 'BLOB' class BINARY(_Binary): """The SQL BINARY type.""" __visit_name__ = 'BINARY' class VARBINARY(_Binary): """The SQL VARBINARY type.""" __visit_name__ = 'VARBINARY' class BOOLEAN(Boolean): """The SQL BOOLEAN type.""" __visit_name__ = 'BOOLEAN' class NullType(TypeEngine): """An unknown type. :class:`.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 :class:`.Dialect` * When constructing SQL expressions using plain Python objects of unknown types (e.g. ``somecolumn == my_special_object``) * When a new :class:`.Column` is created, and the given type is passed as ``None`` or is not passed at all. The :class:`.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. :class:`.NullType` will result in a :exc:`.CompileError` if the compiler is asked to render the type itself, such as if it is used in a :func:`.cast` operation or within a schema creation operation such as that invoked by :meth:`.MetaData.create_all` or the :class:`.CreateTable` construct. """ __visit_name__ = 'null' _isnull = True def literal_processor(self, dialect): def process(value): return "NULL" return process class Comparator(TypeEngine.Comparator): def _adapt_expression(self, op, other_comparator): if isinstance(other_comparator, NullType.Comparator) or \ not operators.is_commutative(op): return op, self.expr.type else: return other_comparator._adapt_expression(op, self) comparator_factory = Comparator NULLTYPE = NullType() BOOLEANTYPE = Boolean() STRINGTYPE = String() INTEGERTYPE = Integer() _type_map = { int: Integer(), float: Numeric(), bool: BOOLEANTYPE, decimal.Decimal: Numeric(), dt.date: Date(), dt.datetime: DateTime(), dt.time: Time(), dt.timedelta: Interval(), util.NoneType: NULLTYPE } if util.py3k: _type_map[bytes] = LargeBinary() _type_map[str] = Unicode() else: _type_map[unicode] = Unicode() _type_map[str] = String() # back-assign to type_api from . import type_api type_api.BOOLEANTYPE = BOOLEANTYPE type_api.STRINGTYPE = STRINGTYPE type_api.INTEGERTYPE = INTEGERTYPE type_api.NULLTYPE = NULLTYPE type_api._type_map = _type_map # this one, there's all kinds of ways to play it, but at the EOD # there's just a giant dependency cycle between the typing system and # the expression element system, as you might expect. We can use # importlaters or whatnot, but the typing system just necessarily has # to have some kind of connection like this. right now we're injecting the # _DefaultColumnComparator implementation into the TypeEngine.Comparator # interface. Alternatively TypeEngine.Comparator could have an "impl" # injected, though just injecting the base is simpler, error free, and more # performant. class Comparator(_DefaultColumnComparator): BOOLEANTYPE = BOOLEANTYPE TypeEngine.Comparator.__bases__ = ( Comparator, ) + TypeEngine.Comparator.__bases__
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