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Edit: sqltypes.cpython-312.pyc
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These rules are currently used by the numeric, integer and date types which have detailed cross-expression coercion rules. c � � t � ��N��NotImplementedError��selfs �H/opt/hc_python/lib64/python3.12/site-packages/sqlalchemy/sql/sqltypes.py�_expression_adaptationsz+HasExpressionLookup._expression_adaptations] s � �!�#�#� c �< � e Zd ZdZej Z dd�Zy)� HasExpressionLookup.Comparator� c � � |j j }t r t | j t � sJ �| j j j || j � j || j � }||u r||j fS || j j u r|| j fS |t |� fS rG ) �type�_type_affinityr � isinstancerE rM �get� _blank_dictr" )rK �op�other_comparator� othertype�lookups rL �_adapt_expressionz0HasExpressionLookup.Comparator._adapt_expressionf s� � � )�-�-�<�<�I� �!�$�)�)�-@�A�A�A��Y�Y�6�6�:�:��D�$�$���c�)�T�Y�Y�'� � ��"�� ,� 1� 1�2�2��4�9�9�3�3�3��D�I�I��&��K�� /�0�0rN N�rX r7 rY zTypeEngine.Comparator[Any]�returnz$Tuple[OperatorType, TypeEngine[Any]])�__name__� __module__� __qualname__� __slots__r, � EMPTY_DICTrW r\ rQ rN rL � ComparatorrP a s1 � �� ��o�o� � 1� � 1� 9� 1� 2� 1rN rd �_ComparatorFactory[Any]�comparator_factoryN) r_ r` ra �__doc__�propertyrM r$ rd rA rf �__annotations__rQ rN rL rE rE U s@ � �� �$� �$�1�Z�*�*�3�/� 1�. 3=��/�<rN rE c �P � e Zd ZU dZ G d� dej e � ZeZded< y)� ConcatenablezOA mixin that marks a type as supporting 'concatenation', typically strings.c �0 � � e Zd ZdZ d� fd� Z� xZS )�Concatenable.ComparatorrQ c �� �� |t j u rPt |t j t j f� r&t j | j j fS t �| �) ||� S rG ) r �addrU rk rd �NullType� concat_op�exprrS �superr\ )rK rX rY � __class__s �rL r\ z)Concatenable.Comparator._adapt_expression� s] �� � �Y�]�]�"�z� � �(�(�(�*=�*=�>�(� !�*�*�D�I�I�N�N�:�:� �w�0��5E�F�FrN r] )r_ r` ra rb r\ � __classcell__�rt s @rL rd rm s3 �� �� � G� � G� 9� G� 2� G� GrN rd re rf N� r_ r` ra rg r$ rd r? rf ri rQ rN rL rk rk { s. � ��G�Z�*�*�2�.� G� 3=��/�<rN rk c �P � e Zd ZU dZ G d� dej e � ZeZded< y)� IndexablezhA mixin that marks a type as supporting indexing operations, such as array or JSON structures. c � � e Zd ZdZd� Zd� Zy)�Indexable.ComparatorrQ c � � t � �rG rH )rK �indexs rL �_setup_getitemz#Indexable.Comparator._setup_getitem� s � �%�'� 'rN c �T � | j |� \ }}}| j |||�� S )N)� result_type)r~ �operate)rK r} � adjusted_op�adjusted_right_exprr� s rL � __getitem__z Indexable.Comparator.__getitem__� s> � � �#�#�E�*� ��#���<�<�� 0�k� � � rN N)r_ r` ra rb r~ r� rQ rN rL rd r{ � s � �� � (� rN rd re rf Nrw rQ rN rL ry ry � s, � �� �Z�*�*�2�.� � 3=��/�<rN ry c �\ � e Zd ZdZdZ d d d�Zd� Zd� Zd� Zd� Z d � Z e d � � Z d � Z y)�Stringz�The base for all string and character types. In SQL, corresponds to VARCHAR. 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. �stringNc � � || _ || _ y)a 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.: .. sourcecode:: pycon+sql >>> from sqlalchemy import cast, select, String >>> print(select(cast("some string", String(collation="utf8")))) {printsql}SELECT CAST(:param_1 AS VARCHAR COLLATE utf8) AS anon_1 .. note:: In most cases, the :class:`.Unicode` or :class:`.UnicodeText` datatypes should be used for a :class:`_schema.Column` that expects to store non-ascii data. These datatypes will ensure that the correct types are used on the database. N)�length� collation)rK r� r� s rL �__init__zString.__init__� s � �H �� �"��rN c �4 � | j � }||_ |S rG )�copyr� )rK r� �new_types rL �_with_collationzString._with_collation� s � ��9�9�;�� &����rN c �: � |j � rt S t S rG )�isascii�_STRING�_UNICODE�rK �values rL �_resolve_for_literalzString._resolve_for_literal� s � � �=�=�?��N��OrN c � �� �fd�}|S )Nc � �� | j dd� } �j j r| j dd� } d| z S )N�'�''�%z%%�'%s')�replace�identifier_preparer�_double_percents�r� �dialects �rL �processz)String.literal_processor.<locals>.process� s< �� ��M�M�#�t�,�E��*�*�;�;� � � �c�4�0���E�>� !rN rQ �rK r� r� s ` rL �literal_processorzString.literal_processor� � �� � "� �rN c � � y rG rQ �rK r� s rL �bind_processorzString.bind_processor� � � �rN c � � y rG rQ �rK r� �coltypes rL �result_processorzString.result_processor� r� rN c � � t S rG ��strrJ s rL � python_typezString.python_type� � � �� rN c � � |j S rG )�STRING�rK �dbapis rL �get_dbapi_typezString.get_dbapi_type � � ��|�|�rN )NN)r� � Optional[int]r� � Optional[str])r_ r` ra rg �__visit_name__r� r� r� r� r� r� rh r� r� rQ rN rL r� r� � s` � �� �N� !%�#'�%#� �%#� !�%#�N� � ��� �� �� rN r� c � � e Zd ZdZdZy)�Textz�A variably sized string type. In SQL, usually corresponds to CLOB or TEXT. In general, TEXT objects do not have a length; while some databases will accept a length argument here, it will be rejected by others. �textN�r_ r` ra rg r� rQ rN rL r� r� � � �� �NrN r� c � � e Zd ZdZdZy)�Unicodea� A variable length Unicode string type. The :class:`.Unicode` type is a :class:`.String` subclass that assumes input and output strings that may contain non-ASCII characters, and for some backends implies an underlying column type that is explicitly supporting of non-ASCII data, such as ``NVARCHAR`` on Oracle Database and SQL Server. This will impact the output of ``CREATE TABLE`` statements and ``CAST`` functions at the dialect level. The character encoding used by the :class:`.Unicode` type that is used to transmit and receive data to the database is usually determined by the DBAPI itself. All modern DBAPIs accommodate non-ASCII strings but may have different methods of managing database encodings; if necessary, this encoding should be configured as detailed in the notes for the target DBAPI in the :ref:`dialect_toplevel` section. In modern SQLAlchemy, use of the :class:`.Unicode` datatype does not imply any encoding/decoding behavior within SQLAlchemy itself. In Python 3, all string objects are inherently Unicode capable, and SQLAlchemy does not produce bytestring objects nor does it accommodate a DBAPI that does not return Python Unicode objects in result sets for string values. .. warning:: Some database backends, particularly SQL Server with pyodbc, are known to have undesirable behaviors regarding data that is noted as being of ``NVARCHAR`` type as opposed to ``VARCHAR``, including datatype mismatch errors and non-use of indexes. See the section on :meth:`.DialectEvents.do_setinputsizes` for background on working around unicode character issues for backends like SQL Server with pyodbc as well as cx_Oracle. .. seealso:: :class:`.UnicodeText` - unlengthed textual counterpart to :class:`.Unicode`. :meth:`.DialectEvents.do_setinputsizes` �unicodeNr� rQ rN rL r� r� s � �%�N �NrN r� c � � e Zd ZdZdZy)� UnicodeTexta# An unbounded-length Unicode string type. See :class:`.Unicode` for details on the unicode behavior of this object. 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Typically generates a ``SMALLINT`` in DDL, and otherwise acts like a normal :class:`.Integer` on the Python side. � small_integerNr� rQ rN rL r� r� | s � �� %�NrN r� c � � e Zd ZdZdZy)� BigIntegerz�A type for bigger ``int`` integers. Typically generates a ``BIGINT`` in DDL, and otherwise acts like a normal :class:`.Integer` on the Python side. � big_integerNr� rQ rN rL r� r� � s � �� #�NrN r� �_Nc � � e Zd ZdZdZerej dd�� ZdZ e d dd�� Z e d dd�� Z d dd�Z e d � � Z d � Zd � Ze d � � Zd � Zd� Zej& d� � Zy)r� a� Base for non-integer numeric types, such as ``NUMERIC``, ``FLOAT``, ``DECIMAL``, and other variants. The :class:`.Numeric` datatype when used directly will render DDL corresponding to precision numerics if available, such as ``NUMERIC(precision, scale)``. The :class:`.Float` subclass will attempt to render a floating-point datatype such as ``FLOAT(precision)``. :class:`.Numeric` returns Python ``decimal.Decimal`` objects by default, based on the default value of ``True`` for the :paramref:`.Numeric.asdecimal` parameter. If this parameter is set to False, returned values are coerced to Python ``float`` objects. The :class:`.Float` subtype, being more specific to floating point, defaults the :paramref:`.Float.asdecimal` flag to False so that the default Python datatype is ``float``. .. note:: When using a :class:`.Numeric` datatype against a database type that returns Python floating point values to the driver, the accuracy of the decimal conversion indicated by :paramref:`.Numeric.asdecimal` may be limited. The behavior of specific numeric/floating point datatypes is a product of the SQL datatype in use, the Python :term:`DBAPI` in use, as well as strategies that may be present within the SQLAlchemy dialect in use. Users requiring specific precision/ scale are encouraged to experiment with the available datatypes in order to determine the best results. �numericc � � y rG rQ rJ s rL rT zNumeric._type_affinity� � � �7:rN � c � � y rG rQ �rK � precision�scale�decimal_return_scale� asdecimals rL r� zNumeric.__init__� � � � rN c � � y rG rQ r� s rL r� zNumeric.__init__� r� rN Nc �< � || _ || _ || _ || _ y)aw 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. Specifying 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. When using the ``Numeric`` type, care should be taken to ensure that the asdecimal setting is appropriate 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. N)r� r� r� r� r� s rL r� zNumeric.__init__� s" � �b #����� �$8��!�"��rN c �| � | j � | j S t | dd � � | j S | j S )Nr� )r� �getattrr� � _default_decimal_return_scalerJ s rL � _effective_decimal_return_scalez'Numeric._effective_decimal_return_scale s? � � � $� $� 0��,�,� ,� �T�7�D� )� 5��:�:� ��5�5� 5rN c � � |j S rG r� r� s rL r� zNumeric.get_dbapi_type r� rN c � � d� }|S )Nc � � t | � S rG r� r� s rL r� z*Numeric.literal_processor.<locals>.process s � ��u�:� rN rQ r� s rL r� zNumeric.literal_processor s � � � �rN c �F � | j rt j S t S rG )r� �decimal�Decimal�floatrJ s rL r� zNumeric.python_type s � � �>�>��?�?� "��LrN c �< � |j ry t j S rG )�supports_native_decimalr- �to_floatr� s rL r� zNumeric.bind_processor s � � � *� *�� �&�&� &rN c � � | j rW|j ry t j t j | j �| j � S | j � S |j rt j S y rG ) r� r r- � to_decimal_processor_factoryr� r� r� r� r r� s rL r� zNumeric.result_processor% su � � �>�>��.�.�� "�>�>��O�O� �:�:�1� � � �� � "� ?� ?� � � �.�.�!�*�*�*�rN c � � t j t t t | j t | j it j t | j t | j it j t | j t | j it j t | j t | j iiS rG ) r r� r� r� rt r� r� ro r� rJ s rL rM z Numeric._expression_adaptations: s� � � �M�M��(��� � ��� � � � � � ��� � ��� � � � �M�M�G�T�^�^�W�d�n�n�M� �M�M�G�T�^�^�W�d�n�n�M� � rN )r^ zType[Numeric[_N]])....) rK �Numeric[decimal.Decimal]r� r� r� r� r� r� r� � Literal[True]) rK zNumeric[float]r� r� r� r� r� r� r� �Literal[False])NNNT)r� r� r� r� r� r� r� �bool)r_ r` ra rg r� r r, r� rT r� r r� rh r� r� r� r� r� r� r� rM rQ rN rL r� r� � sY � � �> �N�� � "� "�:� #�:�$&�!� � $'� "�.1�#&� �&� � � � � � ,� � !� � � � � $'� "�.1�$'� � � � � � � � ,� � "� � � � $(� #�.2� � 4#� �4#� �4#� ,� 4#� � 4#�l �6� �6� �� �� �� '� �* ��� � � rN r� c � � e Zd ZdZdZdZe d d d�� Ze d d d�� Z d d d�Zd� Zy) �Floata 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. When a :paramref:`.Float.precision` is not provided in a :class:`_types.Float` type some backend may compile this type as an 8 bytes / 64 bit float datatype. To use a 4 bytes / 32 bit float datatype a precision <= 24 can usually be provided or the :class:`_types.REAL` type can be used. This is known to be the case in the PostgreSQL and MSSQL dialects that render the type as ``FLOAT`` that's in both an alias of ``DOUBLE PRECISION``. Other third party dialects may have similar behavior. r Nc � � y rG rQ �rK r� r� r� s rL r� zFloat.__init__a � � � rN c � � y rG rQ r s rL r� zFloat.__init__i r rN c �. � || _ || _ || _ y)aa Construct a Float. :param precision: the numeric precision for use in DDL ``CREATE TABLE``. Backends **should** attempt to ensure this precision indicates a number of digits for the generic :class:`_sqltypes.Float` datatype. .. note:: For the Oracle Database backend, the :paramref:`_sqltypes.Float.precision` parameter is not accepted when rendering DDL, as Oracle Database does not support float precision specified as a number of decimal places. Instead, use the Oracle Database-specific :class:`_oracle.FLOAT` datatype and specify the :paramref:`_oracle.FLOAT.binary_precision` parameter. This is new in version 2.0 of SQLAlchemy. To create a database agnostic :class:`_types.Float` that separately specifies binary precision for Oracle Database, use :meth:`_types.TypeEngine.with_variant` as follows:: from sqlalchemy import Column from sqlalchemy import Float from sqlalchemy.dialects import oracle Column( "float_data", Float(5).with_variant(oracle.FLOAT(binary_precision=16), "oracle"), ) :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. Specifying 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. N)r� r� r� r s rL r� zFloat.__init__q s � �b #���"���$8��!rN c � � | j r.t j t j | j � S |j rt j S y rG )r� r- r r� r� r� r r r� s rL r� zFloat.result_processor� sE � � �>�>� �:�:�����!E�!E�� � � ,� ,� �&�&� &�rN )...)rK z Float[float]r� r� r� r r� r� )rK zFloat[decimal.Decimal]r� r� r� r r� r� )NFN)rK z Float[_N]r� r� r� r r� r� ) r_ r` ra rg r� r� r r� r� rQ rN rL r r K s� � ��" �N� �E� � $'�$'�.1� �� � � � "� � ,� � � � � $'�#&�.1� �$� � � � !� � ,� � � � $(� �.2� 39��39� �39� �39� ,� 39�jrN r c � � e Zd ZdZdZy)�Doublez�A type for double ``FLOAT`` floating point types. Typically generates a ``DOUBLE`` or ``DOUBLE_PRECISION`` in DDL, and otherwise acts like a normal :class:`.Float` on the Python side. .. versionadded:: 2.0 �doubleNr� rQ rN rL r r � � � �� �NrN r c �& � e Zd Zd� Zd� Zd� Zdd�Zy)�_RenderISO8601NoTc �& � | j |d � S rG ��_literal_processor_portionr� s rL �_literal_processor_datetimez-_RenderISO8601NoT._literal_processor_datetime� s � ��.�.�w��=�=rN c �& � | j |d� S )Nr r r� s rL �_literal_processor_datez)_RenderISO8601NoT._literal_processor_date� s � ��.�.�w��:�:rN c �& � | j |d� S )N���r r� s rL �_literal_processor_timez)_RenderISO8601NoT._literal_processor_time� s � ��.�.�w��;�;rN Nc �, �� �dv sJ ����fd�}|S d� }|S )N)Nr r c �P �� d| j � j d� � � d�S )Nr� �T)� isoformat�split)r� �_portions �rL r� z=_RenderISO8601NoT._literal_processor_portion.<locals>.process� s* �� � �U�_�_� .� 4� 4�S� 9�(� C� D�A�H�HrN c �J � d| j � j dd� � d�S )Nr� r$ � )r% r� r� s rL r� z=_RenderISO8601NoT._literal_processor_portion.<locals>.process� s& � � �U�_�_� .� 6� 6�s�C� @� A��E�ErN rQ )rK r� r' r� s ` rL r z,_RenderISO8601NoT._literal_processor_portion� s1 �� ��=�(�(�(� � � I� �� F� �rN rG )r_ r` ra r r r! r rQ rN rL r r � s � �>�;�<� rN r c �d � e Zd ZdZdZd d d�Zd� Zd� Zd� Ze d� � Z e j d� � Z y ) �DateTimea� 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. For the time representation within the datetime type, some backends include additional options, such as timezone support and fractional seconds support. For fractional seconds, use the dialect-specific datatype, such as :class:`.mysql.TIME`. For timezone support, use at least the :class:`_types.TIMESTAMP` datatype, if not the dialect-specific datatype object. �datetimec � � || _ y)a� Construct a new :class:`.DateTime`. :param timezone: boolean. Indicates that the datetime type should enable timezone support, if available on the **base date/time-holding type only**. It is recommended to make use of the :class:`_types.TIMESTAMP` datatype directly when using this flag, as some databases include separate generic date/time-holding types distinct from the timezone-capable TIMESTAMP datatype, such as Oracle Database. N��timezone�rK r/ s rL r� zDateTime.__init__� s � � !�� rN c � � |j S rG ��DATETIMEr� s rL r� zDateTime.get_dbapi_type� � � ��~�~� rN c �J � |j d u}|r| j st S | S rG )�tzinfor/ �DATETIME_TIMEZONE�rK r� � with_timezones rL r� z DateTime._resolve_for_literal s$ � � � � �D�0� � �� � �$� $��KrN c �$ � | j |� S rG )r r� s rL r� zDateTime.literal_processor s � ��/�/��8�8rN c �" � t j S rG )�dtr, rJ s rL r� zDateTime.python_type s � ��{�{�rN c � � t j t | j it j t | j t t iiS rG )r ro r� rt r� r+ rJ s rL rM z DateTime._expression_adaptations s6 � � �M�M�H�d�n�n�5� �M�M�H�d�n�n�h��I� � rN N�F�r/ r )r_ r` ra rg r� r� r� r� r� rh r� r, r� rM rQ rN rL r+ r+ � sP � ��" �N� !� ��9� �� �� ��� � � rN r+ c �T � e Zd ZdZdZd� Zed� � Zd� Ze j d� � Z y)r� z'A type for ``datetime.date()`` objects.�datec � � |j S rG r2 r� s rL r� zDate.get_dbapi_type r4 rN c �" � t j S rG )r< rA rJ s rL r� zDate.python_type! � � ��w�w�rN c �$ � | j |� S rG )r r� s rL r� zDate.literal_processor% � � ��+�+�G�4�4rN c �� � t j t | j t t t t it j t | j t t t t t t iiS rG ) r ro r� rt r� r+ �Timer� r� rJ s rL rM z Date._expression_adaptations( sU � � �M�M��� � ��(��h� � �M�M��� � ��g��(� �(� � � rN N) r_ r` ra rg r� r� rh r� r� r, r� rM rQ rN rL r� r� sB � �1��N� � �� ��5� ��� � � rN r� c �d � e Zd ZdZdZd d d�Zd� Zed� � Zd� Z e j d� � Z d� Z y ) rH z'A type for ``datetime.time()`` objects.�timec � � || _ y rG r. r0 s rL r� z Time.__init__F s � � �� rN c � � |j S rG r2 r� s rL r� zTime.get_dbapi_typeI r4 rN c �" � t j S rG )r< rJ rJ s rL r� zTime.python_typeL rD rN c �J � |j d u}|r| j st S | S rG )r6 r/ � TIME_TIMEZONEr8 s rL r� zTime._resolve_for_literalP s$ � � � � �D�0� � �� � � � ��KrN c � � t j t t t | j it j t t t | j iiS rG )r ro r� r+ r� rt r� rH rJ s rL rM z Time._expression_adaptationsW s: � � �M�M�D�(�H�d�n�n�E� �M�M�D�(�H�d�n�n�E� � rN c �$ � | j |� S rG )r! r� s rL r� zTime.literal_processora rF rN Nr> r? )r_ r` ra rg r� r� r� rh r� r� r, r� rM r� rQ rN rL rH rH A sL � �1��N�!� � �� ��� ��� � � �5rN rH c �~ � � e Zd ZdZd d d�Zej d d�� Zd� Ze d� � Z d� Z d� Z � fd�Z d � Z� xZS ) �_Binaryz&Define base behavior for binary types.c � � || _ y rG �r� �rK r� s rL r� z_Binary.__init__h s � � �� rN c � � t S rG )� LargeBinaryrJ s rL �_generic_type_affinityz _Binary._generic_type_affinityk s � � �rN c � �� �fd�}|S )Nc �d �� | j �j � j dd� } d| z S )Nr� r� r� )�decode�$_legacy_binary_type_literal_encodingr� r� s �rL r� z*_Binary.literal_processor.<locals>.processr s7 �� � �L�L��<�<���g�c�4� � � �E�>� !rN rQ r� s ` rL r� z_Binary.literal_processorq r� rN c � � t S rG ��bytesrJ s rL r� z_Binary.python_type| s � �� rN c �X �� |j �y |j j ��fd�}|S )Nc � �� | � �| � S y rG rQ )r� � DBAPIBinarys �rL r� z'_Binary.bind_processor.<locals>.process� s �� �� �"�5�)�)�rN )r� �Binary)rK r� r� rc s @rL r� z_Binary.bind_processor� s+ �� � �=�=� �� �m�m�*�*� � � �rN c �& � |j ry d� }|S )Nc � � | � t | � } | S rG r_ r� s rL r� z)_Binary.result_processor.<locals>.process� s � �� � �e� ���LrN )�returns_native_bytes)rK r� r� r� s rL r� z_Binary.result_processor� s � � � '� '�� � �rN c �H �� t |t � r| S t �| � ||� S �z@See :meth:`.TypeEngine.coerce_compared_value` for a description.�rU r� rs �coerce_compared_value�rK rX r� rt s �rL rk z _Binary.coerce_compared_value� �& �� � �e�S� !��K��7�0��U�;� ;rN c � � |j S rG )�BINARYr� s rL r� z_Binary.get_dbapi_type� r� rN rG �r� r� )r^ zType[TypeEngine[bytes]])r_ r` ra rg r� r, r� rY r� rh r� r� r� rk r� ru rv s @rL rS rS e sZ �� �0� � � � �� �� �� � �� �� �" �<� rN rS c � � e Zd ZdZdZddd�Zy)rX a A type for large binary byte data. The :class:`.LargeBinary` type corresponds to a large and/or unlengthed binary type for the target platform, such as BLOB on MySQL and BYTEA for PostgreSQL. It also handles the necessary conversions for the DBAPI. � large_binaryNc �2 � t j | |�� y)z� Construct a LargeBinary type. :param length: optional, a length for the column for use in DDL statements, for those binary types that accept a length, such as the MySQL BLOB type. rU N)rS r� rV s rL r� zLargeBinary.__init__� s � � ����f��-rN rG rp )r_ r` ra rg r� r� rQ rN rL rX rX � s � �� $�N� .rN rX c �� � � e Zd ZU dZdZded< d dd�Zd� Zd� Zd� Z d � Z e dd �� Z e dd �� Z d� fd � Z dd �Z dd�Zd� Zd� Zd� Zd� Zd� Z� xZS )� SchemaTypea� Add capabilities to a type which allow for schema-level DDL to be associated with a type. 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The :class:`.Enum` type provides a set of possible string values which the column is constrained towards. The :class:`.Enum` type will make use of the backend's native "ENUM" type if one is available; otherwise, it uses a VARCHAR datatype. An option also exists to automatically produce a CHECK constraint when the VARCHAR (so called "non-native") variant is produced; see the :paramref:`.Enum.create_constraint` flag. The :class:`.Enum` type also provides in-Python validation of string values during both read and write operations. When reading a value from the database in a result set, the string value is always checked against the list of possible values and a ``LookupError`` is raised if no match is found. When passing a value to the database as a plain string within a SQL statement, if the :paramref:`.Enum.validate_strings` parameter is set to True, a ``LookupError`` is raised for any string value that's not located in the given list of possible values; note that this impacts usage of LIKE expressions with enumerated values (an unusual use case). The source of enumerated values may be a list of string values, or alternatively a PEP-435-compliant enumerated class. For the purposes of the :class:`.Enum` datatype, this class need only provide a ``__members__`` method. When using an enumerated class, the enumerated objects are used both for input and output, rather than strings as is the case with a plain-string enumerated type:: import enum from sqlalchemy import Enum class MyEnum(enum.Enum): one = 1 two = 2 three = 3 t = Table("data", MetaData(), Column("value", Enum(MyEnum))) connection.execute(t.insert(), {"value": MyEnum.two}) assert connection.scalar(t.select()) is MyEnum.two Above, the string names of each element, e.g. "one", "two", "three", are persisted to the database; the values of the Python Enum, here indicated as integers, are **not** used; the value of each enum can therefore be any kind of Python object whether or not it is persistable. In order to persist the values and not the names, the :paramref:`.Enum.values_callable` parameter may be used. The value of this parameter is a user-supplied callable, which is intended to be used with a PEP-435-compliant enumerated class and returns a list of string values to be persisted. For a simple enumeration that uses string values, a callable such as ``lambda x: [e.value for e in x]`` is sufficient. .. seealso:: :ref:`orm_declarative_mapped_column_enums` - background on using the :class:`_sqltypes.Enum` datatype with the ORM's :ref:`ORM Annotated Declarative <orm_declarative_mapped_column>` feature. :class:`_postgresql.ENUM` - PostgreSQL-specific type, which has additional functionality. :class:`.mysql.ENUM` - MySQL-specific type �enumc �( � | j ||� y)a� Construct an enum. Keyword arguments which don't apply to a specific backend are ignored by that backend. :param \*enums: either exactly one PEP-435 compliant enumerated type or one or more string labels. :param create_constraint: defaults to False. When creating a non-native enumerated type, also build a CHECK constraint on the database against the valid values. .. note:: it is strongly recommended that the CHECK constraint have an explicit name in order to support schema-management concerns. This can be established either by setting the :paramref:`.Enum.name` parameter or by setting up an appropriate naming convention; see :ref:`constraint_naming_conventions` for background. .. versionchanged:: 1.4 - this flag now defaults to False, meaning no CHECK constraint is generated for a non-native enumerated type. :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. The value of the :paramref:`_schema.MetaData.schema` parameter of the :class:`_schema.MetaData` object, if set, will be used as the default value of the :paramref:`_types.Enum.schema` on this object if an explicit value is not otherwise supplied. .. versionchanged:: 1.4.12 :class:`_types.Enum` inherits the :paramref:`_schema.MetaData.schema` parameter of the :class:`_schema.MetaData` object if present, when passed using the :paramref:`_types.Enum.metadata` parameter. :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. If a PEP-435 enumerated class was used, its name (converted to lower case) is used by default. :param native_enum: Use the database's native ENUM type when available. Defaults to True. When False, uses VARCHAR + check constraint for all backends. When False, the VARCHAR length can be controlled with :paramref:`.Enum.length`; currently "length" is ignored if native_enum=True. :param length: Allows specifying a custom length for the VARCHAR when a non-native enumeration datatype is used. By default it uses the length of the longest value. .. versionchanged:: 2.0.0 The :paramref:`.Enum.length` parameter is used unconditionally for ``VARCHAR`` rendering regardless of the :paramref:`.Enum.native_enum` parameter, for those backends where ``VARCHAR`` is used for enumerated datatypes. :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. If not present, the schema name will be taken from the :class:`_schema.MetaData` collection if passed as :paramref:`_types.Enum.metadata`, for a :class:`_schema.MetaData` that includes the :paramref:`_schema.MetaData.schema` parameter. .. versionchanged:: 1.4.12 :class:`_types.Enum` inherits the :paramref:`_schema.MetaData.schema` parameter of the :class:`_schema.MetaData` object if present, when passed using the :paramref:`_types.Enum.metadata` parameter. Otherwise, if the :paramref:`_types.Enum.inherit_schema` flag is set to ``True``, the schema will be inherited from the associated :class:`_schema.Table` object if any; when :paramref:`_types.Enum.inherit_schema` is at its default of ``False``, the owning table's schema is **not** used. :param quote: Set explicit quoting preferences for the type's name. :param inherit_schema: When ``True``, the "schema" from the owning :class:`_schema.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:`_schema.Table.to_metadata` operation. :param validate_strings: when True, string values that are being passed to the database in a SQL statement will be checked for validity against the list of enumerated values. Unrecognized values will result in a ``LookupError`` being raised. :param values_callable: A callable which will be passed the PEP-435 compliant enumerated type, which should then return a list of string values to be persisted. This allows for alternate usages such as using the string value of an enum to be persisted to the database instead of its name. The callable must return the values to be persisted in the same order as iterating through the Enum's ``__member__`` attribute. For example ``lambda x: [i.value for i in x]``. .. versionadded:: 1.2.3 :param sort_key_function: a Python callable which may be used as the "key" argument in the Python ``sorted()`` built-in. The SQLAlchemy ORM requires that primary key columns which are mapped must be sortable in some way. When using an unsortable enumeration object such as a Python 3 ``Enum`` object, this parameter may be used to set a default sort key function for the objects. By default, the database value of the enumeration is used as the sorting function. .. versionadded:: 1.3.8 :param omit_aliases: A boolean that when true will remove aliases from pep 435 enums. defaults to ``True``. .. versionchanged:: 2.0 This parameter now defaults to True. N)� _enum_init)rK �enumsr� s rL r� z Enum.__init__� s � �H ����r�"rN c �L � | j � | j gS | j S rG )� enum_classr� rJ s rL �_enums_argumentzEnum._enums_argument~ s# � � �?�?� &��O�O�$� $��:�:� rN c �v �� |j dd� | _ |j dd� | _ |j dd� | _ |j dt � | _ |j dt � }|j d d� | _ |j d d� }| j ||� \ }}| j |||� |j d d� | _ | j r$t d � | j D � � x| _ }n d x| _ }|t ur |s|�||k rt d|�d|��� �|}dx| j d< | j d< t �| �E |�� | j$ r6|r4|j' d| j$ j( j+ � � t, j# | |j dd� |j dd� |j dd� |j dd� |j dd� |j dd� |j dd� �� y)z�internal init for :class:`.Enum` and subclasses. friendly init helper used by subclasses to remove all the Enum-specific keyword arguments from kw. 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The :class:`.Boolean` datatype currently has two levels of assertion that the values persisted are simple true/false values. For all backends, only the Python values ``None``, ``True``, ``False``, ``1`` or ``0`` are accepted as parameter values. For those backends that don't support a "native boolean" datatype, an option exists to also create a CHECK constraint on the target column .. versionchanged:: 1.2 the :class:`.Boolean` datatype now asserts that incoming Python values are already in pure boolean form. �booleanTNc � � || _ || _ || _ |r+| j j |j � | _ yy)a� Construct a Boolean. :param create_constraint: defaults to False. 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. .. note:: it is strongly recommended that the CHECK constraint have an explicit name in order to support schema-management concerns. This can be established either by setting the :paramref:`.Boolean.name` parameter or by setting up an appropriate naming convention; see :ref:`constraint_naming_conventions` for background. .. versionchanged:: 1.4 - this flag now defaults to False, meaning no CHECK constraint is generated for a non-native enumerated type. :param name: if a CHECK constraint is generated, specify the name of the constraint. 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The Interval type deals with ``datetime.timedelta`` objects. In PostgreSQL and Oracle Database, 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`). r N)r6 Tc �L �� t �| � � || _ || _ || _ y)aV Construct an Interval object. :param native: when True, use the actual INTERVAL type provided by the database, if supported (currently PostgreSQL, Oracle Database). 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 Database and PostgreSQL :param day_precision: for native interval types which support a "day precision" parameter, i.e. Oracle Database. N)rs r� r �second_precision� day_precision)rK r r� r� rt s �rL r� zInterval.__init__ s' �� �, ���� �� � 0�� � *��rN c � � e Zd ZdZy)�Interval.ComparatorrQ N)r_ r` ra rb rQ rN rL rd r� ; s � � � rN rd c �" � t j S rG )r< � timedeltarJ s rL r� zInterval.python_typeC s � ��|�|�rN c �0 � t j | |fi |��S rG )r� r� r' s rL r) zInterval.adapt_to_emulatedG s � � �&�&�t�X�<��<�<rN c �: � | j j ||� S rG )r\ rk )rK rX r� s rL rk z Interval.coerce_compared_valueJ s � ��!�!�7�7��E�B�BrN c �� ��� t r t | j t � sJ �| j j |� }| j �|r|� d��fd� }|S d�fd� }|S )Nc �( �� | ��| z }nd } �|� S rG rQ �r� �dt_value�epochrZ s ��rL r� z(Interval.bind_processor.<locals>.processW s$ �� � �$� $�u�}�H� #�H�+�H�5�5rN c � �� | ��| z }|S d }|S rG rQ )r� r� r� s �rL r� z(Interval.bind_processor.<locals>.processb s' �� � �$� $�u�}�H� �� $�H� �rN )r� �Optional[dt.timedelta]r^ r )r rU r\ r+ r� r� )rK r� r] r� r� rZ s @@rL r� zInterval.bind_processorM s~ �� � � �d� 0� 0�(�;� ;�;� �+�+�:�:�7�C��� � �� �#1� � 6�-� 6�� 6�( �� �-� �� � �rN c �� ��� t r t | j t � sJ �| j j ||� }| j �|r |�d��fd� }|S d�fd� }|S )Nc �$ �� �| � }|�y |�z S rG rQ r� s ��rL r� z*Interval.result_processor.<locals>.processw s! �� �/��6���#� � �%�'�'rN c � �� | �y | �z S rG rQ )r� r� s �rL r� z*Interval.result_processor.<locals>.process s �� ��=� � �u�}�$rN )r� r r^ r� )r rU r\ r+ r� r� )rK r� r� r] r� r� rZ s @@rL r� zInterval.result_processorm s` �� � � �d� 0� 0�(�;� ;�;� �+�+�<�<�W�g�N��� � �� �#1� � (� �� %� �rN )TNN)r r r� r� r� r� )r� r> r^ z _BindProcessorType[dt.timedelta])r� r> r� r r^ z"_ResultProcessorType[dt.timedelta])r_ r` ra rg r+ rT r< r, � fromtimestampr/ �utcr� r� rf r� r# rd rA r� rf rh r� r) rk r� r� ru rv s @rL r� r� s� �� � � �D� �K�K� %� %�a���� � � 9� A� A�� A� N�E��H� �*.�'+� +��+� (�+� %� +�6�� � ��%��$�$�S�)�� $�� � � � �=�C� � � � )� �@� ��),�� +�rN r� c � � e Zd ZdZd ZdZ ej d� Z ddd�Z G d� de e � Z G d� de � Z G d � d e � Z G d � d e � Z G d � de � Z G d� dej$ e ej$ e � ZeZed� � Zed� � Zej2 d� � Zej4 d� � Zd� Z d� Z d� Z y)�JSONa} Represent a SQL JSON type. .. note:: :class:`_types.JSON` is provided as a facade for vendor-specific JSON types. Since it supports JSON SQL operations, it only works on backends that have an actual JSON type, currently: * PostgreSQL - see :class:`sqlalchemy.dialects.postgresql.JSON` and :class:`sqlalchemy.dialects.postgresql.JSONB` for backend-specific notes * MySQL - see :class:`sqlalchemy.dialects.mysql.JSON` for backend-specific notes * SQLite as of version 3.9 - see :class:`sqlalchemy.dialects.sqlite.JSON` for backend-specific notes * Microsoft SQL Server 2016 and later - see :class:`sqlalchemy.dialects.mssql.JSON` for backend-specific notes :class:`_types.JSON` is part of the Core in support of the growing popularity of native JSON datatypes. The :class:`_types.JSON` type stores arbitrary JSON format data, e.g.:: data_table = Table( "data_table", metadata, Column("id", Integer, primary_key=True), Column("data", JSON), ) with engine.connect() as conn: conn.execute( data_table.insert(), {"data": {"key1": "value1", "key2": "value2"}} ) **JSON-Specific Expression Operators** The :class:`_types.JSON` datatype provides these additional SQL operations: * Keyed index operations:: data_table.c.data["some key"] * Integer index operations:: data_table.c.data[3] * Path index operations:: data_table.c.data[("key_1", "key_2", 5, ..., "key_n")] * Data casters for specific JSON element types, subsequent to an index or path operation being invoked:: data_table.c.data["some key"].as_integer() .. versionadded:: 1.3.11 Additional operations may be available from the dialect-specific versions of :class:`_types.JSON`, such as :class:`sqlalchemy.dialects.postgresql.JSON` and :class:`sqlalchemy.dialects.postgresql.JSONB` which both offer additional PostgreSQL-specific operations. **Casting JSON Elements to Other Types** Index operations, i.e. those invoked by calling upon the expression using the Python bracket operator as in ``some_column['some key']``, return an expression object whose type defaults to :class:`_types.JSON` by default, so that further JSON-oriented instructions may be called upon the result type. However, it is likely more common that an index operation is expected to return a specific scalar element, such as a string or integer. In order to provide access to these elements in a backend-agnostic way, a series of data casters are provided: * :meth:`.JSON.Comparator.as_string` - return the element as a string * :meth:`.JSON.Comparator.as_boolean` - return the element as a boolean * :meth:`.JSON.Comparator.as_float` - return the element as a float * :meth:`.JSON.Comparator.as_integer` - return the element as an integer These data casters are implemented by supporting dialects in order to assure that comparisons to the above types will work as expected, such as:: # integer comparison data_table.c.data["some_integer_key"].as_integer() == 5 # boolean comparison data_table.c.data["some_boolean"].as_boolean() == True .. versionadded:: 1.3.11 Added type-specific casters for the basic JSON data element types. .. note:: The data caster functions are new in version 1.3.11, and supersede the previous documented approaches of using CAST; for reference, this looked like:: from sqlalchemy import cast, type_coerce from sqlalchemy import String, JSON cast(data_table.c.data["some_key"], String) == type_coerce(55, JSON) The above case now works directly as:: data_table.c.data["some_key"].as_integer() == 5 For details on the previous comparison approach within the 1.3.x series, see the documentation for SQLAlchemy 1.2 or the included HTML files in the doc/ directory of the version's distribution. **Detecting Changes in JSON columns when using the ORM** The :class:`_types.JSON` type, when used with the SQLAlchemy ORM, does not detect in-place mutations to the structure. In order to detect these, the :mod:`sqlalchemy.ext.mutable` extension must be used, most typically using the :class:`.MutableDict` class. This extension will allow "in-place" changes to the datastructure to produce events which will be detected by the unit of work. See the example at :class:`.HSTORE` for a simple example involving a dictionary. Alternatively, assigning a JSON structure to an ORM element that replaces the old one will always trigger a change event. **Support for JSON null vs. SQL NULL** When working with NULL values, the :class:`_types.JSON` type recommends the use of two specific constants in order to differentiate between a column that evaluates to SQL NULL, e.g. no value, vs. the JSON-encoded string of ``"null"``. To insert or select against a value that is SQL NULL, use the constant :func:`.null`. This symbol may be passed as a parameter value specifically when using the :class:`_types.JSON` datatype, which contains special logic that interprets this symbol to mean that the column value should be SQL NULL as opposed to JSON ``"null"``:: from sqlalchemy import null conn.execute(table.insert(), {"json_value": null()}) To insert or select against a value that is JSON ``"null"``, use the constant :attr:`_types.JSON.NULL`:: conn.execute(table.insert(), {"json_value": JSON.NULL}) The :class:`_types.JSON` type supports a flag :paramref:`_types.JSON.none_as_null` which when set to True will result in the Python constant ``None`` evaluating to the value of SQL NULL, and when set to False results in the Python constant ``None`` evaluating to the value of JSON ``"null"``. The Python value ``None`` may be used in conjunction with either :attr:`_types.JSON.NULL` and :func:`.null` in order to indicate NULL values, but care must be taken as to the value of the :paramref:`_types.JSON.none_as_null` in these cases. **Customizing the JSON Serializer** The JSON serializer and deserializer used by :class:`_types.JSON` defaults to Python's ``json.dumps`` and ``json.loads`` functions; in the case of the psycopg2 dialect, psycopg2 may be using its own custom loader function. In order to affect the serializer / deserializer, they are currently configurable at the :func:`_sa.create_engine` level via the :paramref:`_sa.create_engine.json_serializer` and :paramref:`_sa.create_engine.json_deserializer` parameters. For example, to turn off ``ensure_ascii``:: engine = create_engine( "sqlite://", json_serializer=lambda obj: json.dumps(obj, ensure_ascii=False), ) .. versionchanged:: 1.3.7 SQLite dialect's ``json_serializer`` and ``json_deserializer`` parameters renamed from ``_json_serializer`` and ``_json_deserializer``. .. seealso:: :class:`sqlalchemy.dialects.postgresql.JSON` :class:`sqlalchemy.dialects.postgresql.JSONB` :class:`sqlalchemy.dialects.mysql.JSON` :class:`sqlalchemy.dialects.sqlite.JSON` F� JSON_NULLc � � || _ y)a� Construct a :class:`_types.JSON` type. :param none_as_null=False: if True, persist the value ``None`` as a SQL NULL value, not the JSON encoding of ``null``. Note that when this flag is False, the :func:`.null` construct can still be used to persist a NULL value, which may be passed directly as a parameter value that is specially interpreted by the :class:`_types.JSON` type as SQL NULL:: from sqlalchemy import null conn.execute(table.insert(), {"data": null()}) .. note:: :paramref:`_types.JSON.none_as_null` does **not** apply to the values passed to :paramref:`_schema.Column.default` and :paramref:`_schema.Column.server_default`; a value of ``None`` passed for these parameters means "no default present". Additionally, when used in SQL comparison expressions, the Python value ``None`` continues to refer to SQL null, and not JSON NULL. The :paramref:`_types.JSON.none_as_null` flag refers explicitly to the **persistence** of the value within an INSERT or UPDATE statement. The :attr:`_types.JSON.NULL` value should be used for SQL expressions that wish to compare to JSON null. .. seealso:: :attr:`.types.JSON.NULL` N�� none_as_null)rK r� s rL r� z JSON.__init__{ s � �D )��rN c �d � e Zd ZdZ e� Z e� Z dd�Z dd�Z d d�Z d d�Z y) �JSON.JSONElementTypez?Common function for index / path elements in a JSON expression.c �8 � | j j |� S rG )�_string�_cached_bind_processorr� s rL �string_bind_processorz*JSON.JSONElementType.string_bind_processor� s � � �<�<�6�6�w�?� ?rN c �8 � | j j |� S rG )r� �_cached_literal_processorr� s rL �string_literal_processorz-JSON.JSONElementType.string_literal_processor� s � � �<�<�9�9�'�B� BrN c �p ��� | j j |� �| j |� �d��fd� }|S )Nc �t �� �rt | t � r �| � } | S �rt | t � r �| � } | S rG )rU r� r� �r� � int_processor�string_processors ��rL r� z4JSON.JSONElementType.bind_processor.<locals>.process� s= �� � �Z��s�%;� )�%� 0�E� � � &�*�U�C�*@� ,�U� 3�E� � rN �r� z Optional[Any]r^ r )�_integerr� r� �rK r� r� r� r� s @@rL r� z#JSON.JSONElementType.bind_processor� s4 �� � �M�M� @� @�� I�M� #� 9� 9�'� B� � � �NrN c �p ��� | j j |� �| j |� �d��fd� }|S )Nc � �� �rt | t � r �| � } | S �rt | t � r �| � } | S t � �rG )rU r� r� rI r� s ��rL r� z7JSON.JSONElementType.literal_processor.<locals>.process� sJ �� � �Z��s�%;� )�%� 0�E� � � &�*�U�C�*@� ,�U� 3�E� � � .�/�/rN r� )r� r� r� r� s @@rL r� z&JSON.JSONElementType.literal_processor� s6 �� � !�M�M� C� C�G� L�M� #� <� <�W� E� � � �NrN N)r� r> r^ z!Optional[_BindProcessorType[str]])r� r> r^ z$Optional[_LiteralProcessorType[str]])r� r> r^ z_BindProcessorType[Any])r� r> r^ z_LiteralProcessorType[Any]) r_ r` ra rg r� r� r� r� r� r� r� r� rQ rN rL �JSONElementTyper� � s] � �M��9���(�� @�"� @� .� @� C�"� C� 1� C� � �"� � '� rN r� c � � e Zd ZdZy)�JSON.JSONIndexType��Placeholder for the datatype of a JSON index value. This allows execution-time processing of JSON index values for special syntaxes. N�r_ r` ra rg rQ rN rL � JSONIndexTyper� � � � � rN r� c � � e Zd ZdZy)�JSON.JSONIntIndexTyper� Nr� rQ rN rL �JSONIntIndexTyper� � r� rN r� c � � e Zd ZdZy)�JSON.JSONStrIndexTyper� Nr� rQ rN rL �JSONStrIndexTyper� � r� rN r� c � � e Zd ZdZdZy)�JSON.JSONPathTypez�Placeholder type for JSON path operations. This allows execution-time processing of a path-based index value into a specific SQL syntax. � json_pathNr� rQ rN rL � JSONPathTyper� � s � � � %�rN r� c �R � e Zd ZU dZdZded< d� Zd� Zd� Zd� Z d � Z dd �Z d � Z d � Z y )�JSON.Comparatorz6Define comparison operations for :class:`_types.JSON`.rQ r� rS c �. � t |t � syt |t j � r_t j t j || j t j t j �� }t j }n~t j t j || j t j t |t � rt j nt j �� }t j }||| j" fS )N)rr �operator�bindparam_type)rU r� �collections_abcr r �expectr �BinaryElementRolerr r �json_path_getitem_opr� r� �json_getitem_opr� r� r� rS )rK r} r� s rL r~ z JSON.Comparator._setup_getitem� s� � � �e�S�)�j���/�/�/� "�(�(��+�+�� ��� &� ;� ;�#'�#4�#4� �� %�9�9��!�(�(��+�+�� ��� &� 6� 6� &�e�S�1� �-�-� !� 2� 2� �� %�4�4���U�D�I�I�-� -rN c �6 � | j t � d� S )a� Consider an indexed value as boolean. This is similar to using :class:`_sql.type_coerce`, and will usually not apply a ``CAST()``. e.g.:: stmt = select(mytable.c.json_column["some_data"].as_boolean()).where( mytable.c.json_column["some_data"].as_boolean() == True ) .. versionadded:: 1.3.11 � as_boolean)�_binary_w_typeri rJ s rL r� zJSON.Comparator.as_boolean � � � �&�&�w�y�,�?� ?rN c �6 � | j t � d� S )a� Consider an indexed value as string. This is similar to using :class:`_sql.type_coerce`, and will usually not apply a ``CAST()``. e.g.:: stmt = select(mytable.c.json_column["some_data"].as_string()).where( mytable.c.json_column["some_data"].as_string() == "some string" ) .. versionadded:: 1.3.11 � as_string)r� r� rJ s rL r� zJSON.Comparator.as_string% s � � �&�&�w�y�+�>� >rN c �6 � | j t � d� S )a� Consider an indexed value as integer. This is similar to using :class:`_sql.type_coerce`, and will usually not apply a ``CAST()``. e.g.:: stmt = select(mytable.c.json_column["some_data"].as_integer()).where( mytable.c.json_column["some_data"].as_integer() == 5 ) .. versionadded:: 1.3.11 � as_integer)r� r� rJ s rL r� zJSON.Comparator.as_integer6 r� rN c �6 � | j t � d� S )a� Consider an indexed value as float. This is similar to using :class:`_sql.type_coerce`, and will usually not apply a ``CAST()``. e.g.:: stmt = select(mytable.c.json_column["some_data"].as_float()).where( mytable.c.json_column["some_data"].as_float() == 29.75 ) .. versionadded:: 1.3.11 �as_float)r� r rJ s rL r� zJSON.Comparator.as_floatG s � � �&�&�u�w� �;� ;rN c �> � | j t |||�� d� S )a� Consider an indexed value as numeric/decimal. This is similar to using :class:`_sql.type_coerce`, and will usually not apply a ``CAST()``. e.g.:: stmt = select(mytable.c.json_column["some_data"].as_numeric(10, 6)).where( mytable.c.json_column["some_data"].as_numeric(10, 6) == 29.75 ) .. versionadded:: 1.4.0b2 )r� � as_numeric)r� r� )rK r� r� r� s rL r� zJSON.Comparator.as_numericX s% � � �&�&�� �5�I�>� �� rN c � � | j S )a� Consider an indexed value as JSON. This is similar to using :class:`_sql.type_coerce`, and will usually not apply a ``CAST()``. e.g.:: stmt = select(mytable.c.json_column["some_data"].as_json()) This is typically the default behavior of indexed elements in any case. Note that comparison of full JSON structures may not be supported by all backends. .. versionadded:: 1.3.11 )rr rJ s rL �as_jsonzJSON.Comparator.as_jsonk s � �& �9�9� rN c �4 � t | j t j � r6| j j t j t j fvr t j d|�d|�d�� �| j j � }||_ |S )Nz The JSON cast operator JSON.z9() only works with a JSON index expression e.g. col['q'].z()) rU rr r �BinaryExpressionr� r r� r� r* �InvalidRequestError�_clonerS )rK r� � method_namerr s rL r� z JSON.Comparator._binary_w_type� s� � � �� � �8�4�4�����#�#��)�)��.�.�,� � �-�-� #�K�1�� � �9�9�#�#�%�D��D�I��KrN N�T)r_ r` ra rg rb ri r~ r� r� r� r� r� r� r� rQ rN rL rd r� � s9 � �D�� �� � .�: @�" ?�" @�" <�" �& �* rN rd c � � t S rG )r� rJ s rL r� zJSON.python_type� rr rN c � � | j S )z)Alias of :attr:`_types.JSON.none_as_null`r� rJ s rL �should_evaluate_nonezJSON.should_evaluate_none� s � � �$�$�$�$rN c � � | | _ y rG r� r� s rL r� zJSON.should_evaluate_none� s � � %�I��rN c � � t � S rG )r� rJ s rL � _str_implzJSON._str_impl� s � ��x�rN c �. � ��� �r �� �fd�}|S �� fd�}|S )Nc � �� | �j u rd } n)t | t j � s| � �j ry �| � } �|� S rG ��NULLrU r �Nullr� )r� � serialized�json_serializerrK �string_processs ���rL r� z*JSON._make_bind_processor.<locals>.process� sG �� ��D�I�I�%� �E� ��x�}�}�5��M�d�&7�&7� � ,�U� 3� �%�j�1�1rN c � �� | �j u rd } n)t | t j � s| � �j ry �| � S rG r� )r� r� rK s ��rL r� z*JSON._make_bind_processor.<locals>.process� s= �� ��D�I�I�%� �E� ��x�}�}�5��M�d�&7�&7� �&�u�-�-rN rQ )rK r� r� r� s ``` rL �_make_bind_processorzJSON._make_bind_processor� s �� � � 2�. �� .� �rN c � � | j j |� }|j xs t j }| j ||� S rG )r� r� �_json_serializer�jsonrY r� )rK r� r� r� s rL r� zJSON.bind_processor� s= � � � � �6�6�w�?��!�2�2�@�d�j�j���(�(� � �I�IrN c � ��� | j j ||� �|j xs t j ���fd�}|S )Nc �. �� | �y �r �| � } �| � S rG rQ )r� �json_deserializerr� s ��rL r� z&JSON.result_processor.<locals>.process� s# �� ��}�� �&�u�-��$�U�+� +rN )r� r� �_json_deserializerr� r` )rK r� r� r� r� r� s @@rL r� zJSON.result_processor� s: �� � � � �8�8��'�J�� #� 6� 6� D�$�*�*�� ,� �rN Nr> )r� r ) r_ r` ra rg r� �hashabler, �symbolr� r� r$ r r� r� r� r� r� ry rd r? rk rf rh r� r� �setterr� r� r� r� r� rQ rN rL r� r� � s � �C�J �N��H� �4�;�;�{� #�D�(�T")�H-�*�S�/� -�^ �� � �=� � �=� �%�� %�^�Y�)�)�"�-�|�/F�/F�r�/J� ^�@ $�� �� �� �%� �%� � � �&� !�&� ���� ���8J� rN r� c �� � � e Zd ZdZd ZdZdZ d dd�Z G d� dej e e e j e e � Z e Z ed� � Zed� � Zd � Zdd �Z� fd �Zd � Zd � Z� xZS )r� a� Represent a SQL Array type. .. note:: This type serves as the basis for all ARRAY operations. However, currently **only the PostgreSQL backend has support for SQL arrays in SQLAlchemy**. It is recommended to use the PostgreSQL-specific :class:`sqlalchemy.dialects.postgresql.ARRAY` type directly when using ARRAY types with PostgreSQL, as it provides additional operators specific to that backend. :class:`_types.ARRAY` is part of the Core in support of various SQL standard functions such as :class:`_functions.array_agg` which explicitly involve arrays; however, with the exception of the PostgreSQL backend and possibly some third-party dialects, no other SQLAlchemy built-in dialect has support for this type. An :class:`_types.ARRAY` type is constructed given the "type" of element:: mytable = Table("mytable", metadata, Column("data", ARRAY(Integer))) The above type represents an N-dimensional array, meaning a supporting backend such as PostgreSQL will interpret values with any number of dimensions automatically. To produce an INSERT construct that passes in a 1-dimensional array of integers:: connection.execute(mytable.insert(), {"data": [1, 2, 3]}) The :class:`_types.ARRAY` type can be constructed given a fixed number of dimensions:: mytable = Table( "mytable", metadata, Column("data", ARRAY(Integer, dimensions=2)) ) Sending a number of dimensions is optional, but recommended if the datatype is to represent arrays of more than one dimension. This number is used: * When emitting the type declaration itself to the database, e.g. ``INTEGER[][]`` * When translating Python values to database values, and vice versa, e.g. an ARRAY of :class:`.Unicode` objects uses this number to efficiently access the string values inside of array structures without resorting to per-row type inspection * When used with the Python ``getitem`` accessor, the number of dimensions serves to define the kind of type that the ``[]`` operator should return, e.g. for an ARRAY of INTEGER with two dimensions:: >>> expr = table.c.column[5] # returns ARRAY(Integer, dimensions=1) >>> expr = expr[6] # returns Integer For 1-dimensional arrays, an :class:`_types.ARRAY` instance with no dimension parameter will generally assume single-dimensional behaviors. SQL expressions of type :class:`_types.ARRAY` have support for "index" and "slice" behavior. The ``[]`` operator produces expression constructs which will produce the appropriate SQL, both for SELECT statements:: select(mytable.c.data[5], mytable.c.data[2:7]) as well as UPDATE statements when the :meth:`_expression.Update.values` method is used:: mytable.update().values( {mytable.c.data[5]: 7, mytable.c.data[2:7]: [1, 2, 3]} ) Indexed access is one-based by default; for zero-based index conversion, set :paramref:`_types.ARRAY.zero_indexes`. The :class:`_types.ARRAY` type also provides for the operators :meth:`.types.ARRAY.Comparator.any` and :meth:`.types.ARRAY.Comparator.all`. The PostgreSQL-specific version of :class:`_types.ARRAY` also provides additional operators. .. container:: topic **Detecting Changes in ARRAY columns when using the ORM** The :class:`_sqltypes.ARRAY` type, when used with the SQLAlchemy ORM, does not detect in-place mutations to the array. In order to detect these, the :mod:`sqlalchemy.ext.mutable` extension must be used, using the :class:`.MutableList` class:: from sqlalchemy import ARRAY from sqlalchemy.ext.mutable import MutableList class SomeOrmClass(Base): # ... data = Column(MutableList.as_mutable(ARRAY(Integer))) This extension will allow "in-place" changes such to the array such as ``.append()`` to produce events which will be detected by the unit of work. Note that changes to elements **inside** the array, including subarrays that are mutated in place, are **not** detected. Alternatively, assigning a new array value to an ORM element that replaces the old one will always trigger a change event. .. seealso:: :class:`sqlalchemy.dialects.postgresql.ARRAY` TFc � � t |t � r t d� �t |t � r |� }|| _ || _ || _ || _ y)a� Construct an :class:`_types.ARRAY`. E.g.:: Column("myarray", ARRAY(Integer)) Arguments are: :param item_type: The data type of items of this array. Note that dimensionality is irrelevant here, so multi-dimensional arrays like ``INTEGER[][]``, are constructed as ``ARRAY(Integer)``, not as ``ARRAY(ARRAY(Integer))`` or such. :param as_tuple=False: Specify whether return results should be converted to tuples from lists. This parameter is not generally needed as a Python list corresponds well to a SQL array. :param dimensions: if non-None, the ARRAY will assume a fixed number of dimensions. This impacts how the array is declared on the database, how it goes about interpreting Python and result values, as well as how expression behavior in conjunction with the "getitem" operator works. See the description at :class:`_types.ARRAY` for additional detail. :param zero_indexes=False: when True, index values will be converted between Python zero-based and SQL one-based indexes, e.g. a value of one will be added to all index values before passing to the database. zUDo not nest ARRAY types; ARRAY(basetype) handles multi-dimensional arrays of basetypeN)rU r� r� rS r� �as_tuple� dimensions� zero_indexes)rK r� r r r s rL r� zARRAY.__init__M sQ � �L �i�� '� �?�� � �i�� &�!� �I�"��� �� �$��� (��rN c � � e Zd ZU dZdZded< d� Zd� Z ej d� d d �� Z ej d� d d �� Z y) �ARRAY.Comparatorz�Define comparison operations for :class:`_types.ARRAY`. More operators are available on the dialect-specific form of this type. See :class:`.postgresql.ARRAY.Comparator`. rQ r� rS c �T � | j }t |t � r�|}|j r1t |j dz |j dz |j � }t |j |j |j | j j �� }t j ||fS |j r|dz }|j �|j dk( r |j }n.d|j dz i} |j |j fi |��}t j ||fS )Nr )�_namer )rS rU �slicer �start�stop�stepr rr �keyr �getitemr r� r� rt )rK r} �arr_type� return_type�slice_�adapt_kws rL r~ z ARRAY.Comparator._setup_getitem� s � ��y�y�H� �%��'� &� ��(�(� !�%�+�+��/�5�:�:��>�5�:�:� N�E� ��K�K����U�Z�Z�t�y�y�}�}��� !�(�(�&�+�=�=��(�(��Q�J�E��&�&�.�(�2E�2E��2J�"*�"4�"4�K� ,�h�.A�.A�A�.E� F�H�"0�(�.�.� �*�*�#�.6�#�K� !�(�(�%��<�<rN c � � t d� �)z�``ARRAY.contains()`` not implemented for the base ARRAY type. Use the dialect-specific ARRAY type. .. seealso:: :class:`_postgresql.ARRAY` - PostgreSQL specific version. zdARRAY.contains() not implemented for the base ARRAY type; please use the dialect-specific ARRAY typerH )rK r� r� s rL �containszARRAY.Comparator.contains� s � � &�I�� rN zsqlalchemy.sql.elementsNc �z � t j j }|r|nt j }| j }|j j | j � j t j |� t j t j ||| j |j �� � S )a Return ``other operator ANY (array)`` clause. .. legacy:: This method is an :class:`_types.ARRAY` - specific construct that is now superseded by the :func:`_sql.any_` function, which features a different calling style. The :func:`_sql.any_` function is also mirrored at the method level via the :meth:`_sql.ColumnOperators.any_` method. Usage of array-specific :meth:`_types.ARRAY.Comparator.any` is as follows:: from sqlalchemy.sql import operators conn.execute( select(table.c.data).where(table.c.data.any(7, operator=operators.lt)) ) :param other: expression to be compared :param operator: an operator object from the :mod:`sqlalchemy.sql.operators` package, defaults to :func:`.operators.eq`. .. seealso:: :func:`_expression.any_` :meth:`.types.ARRAY.Comparator.all` ��elementr� rr r� )r, r6 � sql_elementsr �eqrS �CollectionAggregate� _create_anyrr r� �mirrorr r� r r� r� �rK �otherr� r r s rL �anyzARRAY.Comparator.any� � � �> �~�~�2�2�H�#+�x�� � �H��y�y�H��/�/�;�;�D�I�I�F�N�N�� � ��*�� � ��+�+� !� %� ���#+�#5�#5� � � rN c �z � t j j }|r|nt j }| j }|j j | j � j t j |� t j t j ||| j |j �� � S )a Return ``other operator ALL (array)`` clause. .. legacy:: This method is an :class:`_types.ARRAY` - specific construct that is now superseded by the :func:`_sql.all_` function, which features a different calling style. The :func:`_sql.all_` function is also mirrored at the method level via the :meth:`_sql.ColumnOperators.all_` method. Usage of array-specific :meth:`_types.ARRAY.Comparator.all` is as follows:: from sqlalchemy.sql import operators conn.execute( select(table.c.data).where(table.c.data.all(7, operator=operators.lt)) ) :param other: expression to be compared :param operator: an operator object from the :mod:`sqlalchemy.sql.operators` package, defaults to :func:`.operators.eq`. .. seealso:: :func:`_expression.all_` :meth:`.types.ARRAY.Comparator.any` r )r, r6 r r r rS r � _create_allrr r� r r r� r r� r� r s rL �allzARRAY.Comparator.all� r! rN rG ) r_ r` ra rg rb ri r~ r r, rL r r$ rQ rN rL rd r sb � � � � �� � =�4 � �� � � 6� 7�, � 8�, �\ �� � � 6� 7�, � 8�, rN rd c � � | j S rG )r rJ s rL r� zARRAY.hashable s � ��}�}� rN c � � t S rG )r� rJ s rL r� zARRAY.python_type rr rN c � � ||k( S rG rQ rc s rL re zARRAY.compare_values s � ��A�v� rN c �z � |s9t | j t � r | j j |fi |�� yyy)�Support SchemaEventTargetN)rU r� r r� )rK r� �outerr� s rL r� zARRAY._set_parent s6 � � ��D�N�N�4E�F� &�D�N�N� &� &�v� 4�� 4� G�urN c � �� t �| � |d�� t | j t � r | j j |� yy)r) T)r* N)rs �_set_parent_with_dispatchrU r� r )rK r� r� rt s �rL r, z ARRAY._set_parent_with_dispatch& s= �� � ��)�&��)�=� �d�n�n�&7� 8� �N�N� 4� 4�V� <� 9rN c �z � ��� � j j |� j |� ���y d� ��� �fd�}|S )Nc �, � ddj | � � d�S )N�[r� �])r� r s rL �to_strz'ARRAY.literal_processor.<locals>.to_str5 s � ��t�y�y��*�+�1�-� -rN c �D �� �j | ��j �� }|S rG )�_apply_item_processorr )r� �inner� item_procrK r1 s ���rL r� z(ARRAY.literal_processor.<locals>.process8 s' �� ��.�.��y�$�/�/�6��E� �LrN )r� r� r� )rK r� r� r5 r1 s ` @@rL r� zARRAY.literal_processor. sA �� ��N�N�/�/��8�J�J� � � � � �� .� � �rN c �� � ���� �� t |� }�dk( s ��6|rt |d t t f� s�r ��fd�|D � � S �|� S ����� fd�|D � � S )aA Helper method that can be used by bind_processor(), literal_processor(), etc. to apply an item processor to elements of an array value, taking into account the 'dimensions' for this array type. See the Postgresql ARRAY datatype for usage examples. .. versionadded:: 2.0 r r c 3 �. �K � | ] } �|� �� � y �wrG rQ )r� r� �itemprocs �rL r� z.ARRAY._apply_item_processor.<locals>.<genexpr>Z s �� �� �*D��1�8�A�;��s �c 3 �\ �K � | ]# }|��j |����dz nd �� nd �� �% y �w)Nr )r3 )r� r� �collection_callable�dimr8 rK s ����rL r� z.ARRAY._apply_item_processor.<locals>.<genexpr>^ sO �� �� � '� �A� �}� �.�.�� �#&�?��a���+� � � � �s �),)r� rU �tuple)rK �arrr8 r; r: s ` ```rL r3 zARRAY._apply_item_processor@ ss �� � �;��s�)�C� �1�H��{� �!�#�a�&�4��-�8� �*�*D��*D�D�D�*�3�/�/�&� '� � '� � rN )FNF)r� �_TypeEngineArgument[Any]r r r r� r r r> )r_ r` ra rg r� � _is_arrayr r� ry rd r r rk rf rh r� r� re r� r, r� r3 ru rv s @rL r� r� � s� �� �m�^ �N��I��L�#� �$(� "� 0)�+�0)� �0)� "� 0)� � 0)�dR�� � �X�c�]�+�� � ��� �.�R�h $�� � � � � �� ���5� =��$*rN r� c �V � � e Zd ZU dZdZded< d d�Z d � fd� Zd d�Zd� Z � xZ S ) � TupleTypez(represent the composite type of a Tuple.TzList[TypeEngine[Any]]�typesc � � t |v| _ |D �cg c] }t |t � r |� n|�� c}| _ y c c}w rG )�NULLTYPE� _fully_typedrU rS rB )rK rB r� s rL r� zTupleType.__init__t sE � � $�E� 1��� #� � "� � &�i��6�I�K�I� E� "� �� �� s � ;c �� �� |t j u rt �| � ||� S t t | j |� D ��cg c] \ }}|j ||� �� c}}� S c c}}w rG )r �_NO_VALUE_IN_LISTrs rk rA r rB )rK rX r� r� r rt s �rL rk z TupleType.coerce_compared_value{ sp �� � �H�.�.� .��7�0��U�;� ;� � &)����U�%;��%;� ��T� �-�-�b�$�7�%;��� ��s � A# c � � | j r| S t t | j |� D ��cg c] \ }}|t u r t |� n|�� c}}� S c c}}w rG )rE rA r rB rD �_resolve_value_to_type)rK r� r� r s rL �_resolve_values_to_typesz"TupleType._resolve_values_to_types� s_ � � � � ��K� � &)����U�%;��%;� ��T� 58�8�O�*�4�0��L�%;��� ��s � A c � � t d� �)NzJThe tuple type does not support being fetched as a column in a result row.rH r� s rL r� zTupleType.result_processor� s � �!� +� � rN )rB r> )rX zOptional[OperatorType]r� r r^ rC )r� r r^ rA ) r_ r` ra rg �_is_tuple_typeri r� rk rJ r� ru rv s @rL rA rA m s= �� �2��N� � � � �(� �14� � � � � rN rA .c � � e Zd ZdZd Zy)�REALzlThe SQL REAL type. .. seealso:: :class:`_types.Float` - documentation for the base type. Nr� rQ rN rL rN rN � r� rN rN c � � e Zd ZdZd Zy)�FLOATzmThe SQL FLOAT type. .. seealso:: :class:`_types.Float` - documentation for the base type. Nr� rQ rN rL rP rP � s � �� �NrN rP c � � e Zd ZdZd Zy)�DOUBLEz�The SQL DOUBLE type. .. versionadded:: 2.0 .. seealso:: :class:`_types.Double` - documentation for the base type. Nr� rQ rN rL rR rR � r rN rR c � � e Zd ZdZd Zy)�DOUBLE_PRECISIONz�The SQL DOUBLE PRECISION type. .. versionadded:: 2.0 .. seealso:: :class:`_types.Double` - documentation for the base type. Nr� rQ rN rL rT rT � s � �� (�NrN rT c � � e Zd ZdZd Zy)�NUMERICzqThe SQL NUMERIC type. .. seealso:: :class:`_types.Numeric` - documentation for the base type. Nr� rQ rN rL rV rV � � � �� �NrN rV c � � e Zd ZdZd Zy)�DECIMALzqThe SQL DECIMAL type. .. seealso:: :class:`_types.Numeric` - documentation for the base type. Nr� rQ rN rL rY rY � rW rN rY c � � e Zd ZdZd Zy)�INTEGERzxThe SQL INT or INTEGER type. .. seealso:: :class:`_types.Integer` - documentation for the base type. Nr� rQ rN rL r[ r[ � rW rN r[ c � � e Zd ZdZd Zy)�SMALLINTzwThe SQL SMALLINT type. .. seealso:: :class:`_types.SmallInteger` - documentation for the base type. Nr� rQ rN rL r] r] � s � �� �NrN r] c � � e Zd ZdZd Zy)�BIGINTzsThe SQL BIGINT type. .. seealso:: :class:`_types.BigInteger` - documentation for the base type. Nr� rQ rN rL r_ r_ s � �� �NrN r_ c �0 � � e Zd ZdZd Zdd� fd� Zd� Z� xZS )� TIMESTAMPa' The SQL TIMESTAMP type. :class:`_types.TIMESTAMP` datatypes have support for timezone storage on some backends, such as PostgreSQL and Oracle Database. Use the :paramref:`~types.TIMESTAMP.timezone` argument in order to enable "TIMESTAMP WITH TIMEZONE" for these backends. c �& �� t �| � |�� y)am Construct a new :class:`_types.TIMESTAMP`. :param timezone: boolean. Indicates that the TIMESTAMP type should enable timezone support, if available on the target database. On a per-dialect basis is similar to "TIMESTAMP WITH TIMEZONE". If the target database does not support timezones, this flag is ignored. r. N)rs r� )rK r/ rt s �rL r� zTIMESTAMP.__init__ s �� � ���(��+rN c � � |j S rG )ra r� s rL r� zTIMESTAMP.get_dbapi_type& s � ���� rN r> r? )r_ r` ra rg r� r� r� ru rv s @rL ra ra s �� �� !�N� ,� rN ra c � � e Zd ZdZd Zy)r3 zThe SQL DATETIME type.Nr� rQ rN rL r3 r3 * � � � � �NrN r3 c � � e Zd ZdZd Zy)�DATEzThe SQL DATE type.Nr� rQ rN rL rg rg 0 � � � ��NrN rg c � � e Zd ZdZd Zy)�TIMEzThe SQL TIME type.Nr� rQ rN rL rj rj 6 rh rN rj c � � e Zd ZdZd Zy)�TEXTzThe SQL TEXT type.Nr� rQ rN rL rl rl < rh rN rl c � � e Zd ZdZd Zy)�CLOBzLThe CLOB type. This type is found in Oracle Database and Informix. Nr� rQ rN rL rn rn B s � �� �NrN rn c � � e Zd ZdZd Zy)�VARCHARzThe SQL VARCHAR type.Nr� rQ rN rL rp rp K � � � � �NrN rp c � � e Zd ZdZd Zy)�NVARCHARzThe SQL NVARCHAR type.Nr� rQ rN rL rs rs Q re rN rs c � � e Zd ZdZd Zy)�CHARzThe SQL CHAR type.Nr� rQ rN rL ru ru W rh rN ru c � � e Zd ZdZd Zy)�NCHARzThe SQL NCHAR type.Nr� rQ rN rL rw rw ] s � � � �NrN rw c � � e Zd ZdZd Zy)�BLOBzThe SQL BLOB type.Nr� rQ rN rL ry ry c rh rN ry c � � e Zd ZdZd Zy)ro zThe SQL BINARY type.Nr� rQ rN rL ro ro i s � � � �NrN ro c � � e Zd ZdZd Zy)� VARBINARYzThe SQL VARBINARY type.Nr� rQ rN rL r| r| o s � �!� �NrN r| c � � e Zd ZdZd Zy)�BOOLEANzThe SQL BOOLEAN type.Nr� rQ rN rL r~ r~ u rq rN r~ c �R � e Zd ZdZdZdZd� Z G d� dej e � ZeZ y)rp a 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:`_schema.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:`_schema.MetaData.create_all` or the :class:`.CreateTable` construct. �nullTc � � y rG rQ r� s rL r� zNullType.literal_processor� r� rN c �$ � e Zd ZdZ dd�Zy)�NullType.ComparatorrQ c � � t |t j � st j |� s|| j j fS |j || � S rG )rU rp rd r �is_commutativerr rS r\ )rK rX rY s rL r\ z%NullType.Comparator._adapt_expression� sK � � � �(�"5�"5�� �-�-�b�1��4�9�9�>�>�)�)�'�9�9�"�d�C�CrN Nr] )r_ r` ra rb r\ rQ rN rL rd r� � s, � �� � D� � D� 9� D� 2� DrN rd N) r_ r` ra rg r� �_isnullr� r$ rd r? rf rQ rN rL rp rp { s9 � ��2 �N��G�� D�Z�*�*�2�.� D� $�rN rp c �: � e Zd ZdZdZdej fgZdd�Zy)�TableValueTypez Refers to a table value type.T� _elementsc �| � |D �cg c]& }t j t j |� ��( c}| _ y c c}w rG )r r� r �StrAsPlainColumnRoler� )rK r r s rL r� zTableValueType.__init__� s; � � !� � �� � � �U� 7� 7�� >� � ���� s �+9N)r z*Union[str, _ColumnExpressionArgument[Any]]) r_ r` ra rg �_is_table_valuer' �dp_clauseelement_list�_traverse_internalsr� rQ rN rL r� r� � s( � �'��O� �'�=�=�>��� rN r� c � � e Zd ZdZy)� MatchTypea' Refers to the return type of the MATCH operator. As the :meth:`.ColumnOperators.match` is probably the most open-ended operator in generic SQLAlchemy Core, we can't assume the return type at SQL evaluation time, as MySQL returns a floating point, not a boolean, and other backends might do something different. So this type acts as a placeholder, currently subclassing :class:`.Boolean`. The type allows dialects to inject result-processing functionality if needed, and on MySQL will return floating-point values. Nr� rQ rN rL r� r� � s � � rN r� � _UUID_RETURNc � � � e Zd ZU dZdZdZded< e d dd�� Ze d dd�� Zddd�Ze d � � Z e d � � Z � fd �Z d � Z d � Zd� Z� xZS )�Uuida� Represent a database agnostic UUID datatype. For backends that have no "native" UUID datatype, the value will make use of ``CHAR(32)`` and store the UUID as a 32-character alphanumeric hex string. For backends which are known to support ``UUID`` directly or a similar uuid-storing datatype such as SQL Server's ``UNIQUEIDENTIFIER``, a "native" mode enabled by default allows these types will be used on those backends. In its default mode of use, the :class:`_sqltypes.Uuid` datatype expects **Python uuid objects**, from the Python `uuid <https://docs.python.org/3/library/uuid.html>`_ module:: import uuid from sqlalchemy import Uuid from sqlalchemy import Table, Column, MetaData, String metadata_obj = MetaData() t = Table( "t", metadata_obj, Column("uuid_data", Uuid, primary_key=True), Column("other_data", String), ) with engine.begin() as conn: conn.execute( t.insert(), {"uuid_data": uuid.uuid4(), "other_data": "some data"} ) To have the :class:`_sqltypes.Uuid` datatype work with string-based Uuids (e.g. 32 character hexadecimal strings), pass the :paramref:`_sqltypes.Uuid.as_uuid` parameter with the value ``False``. .. versionadded:: 2.0 .. seealso:: :class:`_sqltypes.UUID` - represents exactly the ``UUID`` datatype without any backend-agnostic behaviors. �uuidNr� r� c � � y rG rQ �rK �as_uuid� native_uuids rL r� z Uuid.__init__ � � � rN c � � y rG rQ r� s rL r� z Uuid.__init__ r� rN c � � || _ || _ y)a^ Construct a :class:`_sqltypes.Uuid` type. :param as_uuid=True: if True, values will be interpreted as Python uuid objects, converting to/from string via the DBAPI. .. versionchanged: 2.0 ``as_uuid`` now defaults to ``True``. :param native_uuid=True: if True, backends that support either the ``UUID`` datatype directly, or a UUID-storing value (such as SQL Server's ``UNIQUEIDENTIFIER`` will be used by those backends. If False, a ``CHAR(32)`` datatype will be used for all backends regardless of native support. N�r� r� r� s rL r� z Uuid.__init__ s � � �� �&��rN c �2 � | j rt S t S rG )r� � _python_UUIDr� rJ s rL r� zUuid.python_type& s � � #�|�|�|�4��4rN c � � | j S rG )r� rJ s rL r z Uuid.native* r rN c �H �� t |t � r| S t �| � ||� S ri rj rl s �rL rk zUuid.coerce_compared_value. rm rN c �l � |j xs | j }|r| j rd� }|S d� }|S y )Nc �" � | � | j } | S rG ��hexr� s rL r� z$Uuid.bind_processor.<locals>.process> s � � �(� %� � �� �LrN c �. � | �| j dd� } | S )N�-� �r� r� s rL r� z$Uuid.bind_processor.<locals>.processF s � � �(� %� � �c�2� 6�� �LrN ��supports_native_uuidr� r� �rK r� �character_based_uuidr� s rL r� zUuid.bind_processor6 sH � ��,�,� ,� D�D�4D�4D�0D� � ��|�|�!� ��!� ��rN c � � |j xs | j }|r| j rd� }|S d� }|S | j sd� }|S y )Nc � � | � t | � } | S rG )r� r� s rL r� z&Uuid.result_processor.<locals>.processW s � � �(� ,�U� 3�� �LrN c �2 � | �t t | � � } | S rG )r� r� r� s rL r� z&Uuid.result_processor.<locals>.process_ s � � �(� #�L��$7� 8�� �LrN c � � | � t | � } | S rG r� r� s rL r� z&Uuid.result_processor.<locals>.processh s � � �(� #�E� �� �LrN r� )rK r� r� r� r� s rL r� zUuid.result_processorO s[ � ��,�,� ,� D�D�4D�4D�0D� � ��|�|�!� ��!� ���<�<�!� ��rN c �t � |j xs | j }| j sd� }|S |rd� }|S d� }|S )Nc �N � d| j dd� j dd� � d�S )Nr� r� r� r� r� r� s rL r� z'Uuid.literal_processor.<locals>.processx s* � � �U�]�]�3�� 3� ;� ;�C�� F� G�q�K�KrN c �" � d| j � d�S )Nr� r� r� s rL r� z'Uuid.literal_processor.<locals>.process s � � ���� �1�/�/rN c �@ � dt | � j dd� � d�S )Nr� r� )r� r� r� s rL r� z'Uuid.literal_processor.<locals>.process� s# � � ��U��!3�!3�C��!>� ?�q�C�CrN r� r� s rL r� zUuid.literal_processorq sS � ��,�,� ,� D�D�4D�4D�0D� � �|�|� L� �N�#�0� ��D� �rN )..)rK zUuid[_python_UUID]r� r r� r )rK z Uuid[str]r� r r� r )TT)r� r r� r )r_ r` ra rg r� r� ri r r� rh r� r rk r� r� r� ru rv s @rL r� r� � s� �� �/�b �N� #�I�}�#� � "%� � � � � � � � � � � � #&� � �� � � � � � � � '�& �5� �5� � � � �<��2 �D rN r� c �V � e Zd ZdZd Zeddd�� Zedd d�� Zd d d�Zed� � Zy) r a� Represent the SQL UUID type. This is the SQL-native form of the :class:`_types.Uuid` database agnostic datatype, and is backwards compatible with the previous PostgreSQL-only version of ``UUID``. The :class:`_sqltypes.UUID` datatype only works on databases that have a SQL datatype named ``UUID``. It will not function for backends which don't have this exact-named type, including SQL Server. For backend-agnostic UUID values with native support, including for SQL Server's ``UNIQUEIDENTIFIER`` datatype, use the :class:`_sqltypes.Uuid` datatype. .. versionadded:: 2.0 .. seealso:: :class:`_sqltypes.Uuid` c � � y rG rQ �rK r� s rL r� z UUID.__init__� s � �JMrN c � � y rG rQ r� s rL r� z UUID.__init__� s � �BErN c � � || _ d| _ y)a Construct a :class:`_sqltypes.UUID` type. :param as_uuid=True: if True, values will be interpreted as Python uuid objects, converting to/from string via the DBAPI. .. versionchanged: 2.0 ``as_uuid`` now defaults to ``True``. TNr� r� s rL r� z UUID.__init__� s � � �� � ��rN c �J � |j d|j � | di |��S )Nr� rQ )r� r� )r� rT r� s rL �adapt_emulated_to_nativez UUID.adapt_emulated_to_native� s � � � � �i�� � �.��y�R�y�rN N).)rK zUUID[_python_UUID]r� r )rK z UUID[str]r� r r� )r� r ) r_ r` ra rg r� r r� � classmethodr� rQ rN rL r r � sC � ��( �N� �M� �M� �E� �E� � �� �rN r r � NUMERICTYPETr. z Dict[Type[Any], TypeEngine[Any]]� _type_mapc � � t t | � d� }|du r t | dd� }|du rSt j | d� }|�5|j t j v rt j d| �d�� �t S |j | � S )NF�__sa_type_engine__zObject z$ is not legal as a SQL literal value) � _type_map_getrS r� r+ �inspectrt � _registrarsr* r� rD r� )r� � _result_type�insps rL rI rI � s� � � ��e��e�4�L��u� � �u�&:�E�B� ��u� � �!�!�%��/�� � � �N�N�j� 4� 4� 4��#�#�CH�J�� � ���0�0� � � rN )r� r r^ rC )�rg � __future__r �collections.abc�abcr� r, r< r� r� r� rQ �typingr r r r r r r r r r r r r r� r r� r� r r r r r �baser r r � cache_keyr r r r r9 r r! r" r# r$ r% r& �visitorsr' r) r* r+ r, �enginer- r. r/ r0 � util.typingr1 r2 r3 r4 �_typingr5 r6 r7 rz r8 r9 r: r; r< r= �engine.interfacesr> r? rA rB rE rk ry r� r� r� r� r� r� r� r� r� r� r r� r� r r r r+ rA r� rJ rH r` rS rX ru r� rJ rN r ri r� r� r� r� r� rA rN rP rR rT rV rY r[ �INTr] r_ ra r3 rg rj rl rn rp rs ru rw ry ro r| r~ rp r� r� r� r� rD � BOOLEANTYPE� STRINGTYPE� INTEGERTYPEr� ri � MATCHTYPE� TABLEVALUEr7 rO r� � _DATETIME�_TIMEr� r� rS r� rV r� rI � INDEXABLErQ rN rL �<module>r� s> ��� #� )� � � � � � � � � � � � � � � � � � � %� � � � � � � � #� "� !� � /� � '� 0� 4� .� %� � '� � � � � � � � "� "� $� #� !��2�,�'� �,�,�/�(�.�+� �T�� �� �e�3� �� �e�,�-��#=�/� #=�L=�?� =�.=�� =�2X �\�:�c�?� X �v �6� �( �f� ( �V $�$� $� - �!�:�c�?� - �`%�7� %�#�� #� �T��w���� 5�6�7��s �!�:�b�>� s �lc�G�B�K� c�L �U�2�Y� � � �2> ��*�J�r�{�{�,C�> �B% � � 1�:�b�g�g�3F� % �P!5� � 1�:�b�g�g�3F� !5�HB �j�� � B �J.�'� .�.hA�"�O� hA�VP '�6�:�x��E�#�t�y�y�.�4I�)J� P '�ff� �v�&� f�RJ-�j�(�J�t�$4� J-�Z�+�Z�� � �-E� �.x�x�*�M�"�,�,�,G� x�vI �9�j��o� I �XW��y�,� �8�C�=�0I�W�t * � �5��c��?�+� * �Z �5��9� � �E�"�I� � �V�B�Z� � (�v�b�z� (� �g�b�k� � �g�b�k� � �g� � �� �|� � �Z� � �� �: �x� � �4� � �4� � �4� � �4� � �f� � �w� � �6� � �G� � �;� � �W� � !�� !� �g� � 0$�z�$� � 0$�f �[�*�S�/� � �� � �~�s�L�9� �y �8�Z� �-� y �x.�4� � �x� 9� 9� .�b �:���i� � �X� ��i� �(/� � � %� 1� �K� � � � � �d�+� ��d�#� ��l� � �J� � ��� �(�� �9�� ��� �5�7��+��$�&� �O�O�W�Y��G�G�T�V��K�K���G�G�U��L�L�(�*���J�� �;�=����I�I�t�D�I�I�� �T�$�)�)�_� /� � +� �$ � � � � �8 #�� � �� �"�� � �� �"�� � �� �!*� *�� �Y� �� �"8�� rN
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