Release: 2.0.34 | Release Date: September 4, 2024

# SQLAlchemy 2.0 Documentation

# Oracle

Support for the Oracle database.

The following table summarizes current support levels for database release versions.

Supported Oracle versions
Support type | Versions
--- | ---
Fully tested in CI | 18c
Normal support | 11+
Best effort | 9+

## DBAPI Support

The following dialect/DBAPI options are available. Please refer to individual DBAPI sections for connect information.

- cx-Oracle

- python-oracledb

## Auto Increment Behavior

SQLAlchemy Table objects which include integer primary keys are usually assumed to have “autoincrementing” behavior, meaning they can generate their own primary key values upon INSERT. For use within Oracle, two options are available, which are the use of IDENTITY columns (Oracle 12 and above only) or the association of a SEQUENCE with the column.

### Specifying GENERATED AS IDENTITY (Oracle 12 and above)

Starting from version 12 Oracle can make use of identity columns using the `Identity` to specify the autoincrementing behavior:

    t = Table('mytable', metadata,
        Column('id', Integer, Identity(start=3), primary_key=True),
        Column(...), ...
    )

The CREATE TABLE for the above `Table` object would be:

    CREATE TABLE mytable (
        id INTEGER GENERATED BY DEFAULT AS IDENTITY (START WITH 3),
        ...,
        PRIMARY KEY (id)
    )

The `Identity` object support many options to control the “autoincrementing” behavior of the column, like the starting value, the incrementing value, etc. In addition to the standard options, Oracle supports setting `Identity.always` to `None` to use the default generated mode, rendering GENERATED AS IDENTITY in the DDL. It also supports setting `Identity.on_null` to `True` to specify ON NULL in conjunction with a ‘BY DEFAULT’ identity column.

### Using a SEQUENCE (all Oracle versions)

Older version of Oracle had no “autoincrement” feature, SQLAlchemy relies upon sequences to produce these values. With the older Oracle versions, a sequence must always be explicitly specified to enable autoincrement. This is divergent with the majority of documentation examples which assume the usage of an autoincrement-capable database. To specify sequences, use the sqlalchemy.schema.Sequence object which is passed to a Column construct:

    t = Table('mytable', metadata,
          Column('id', Integer, Sequence('id_seq', start=1), primary_key=True),
          Column(...), ...
    )

This step is also required when using table reflection, i.e. autoload_with=engine:

    t = Table('mytable', metadata,
          Column('id', Integer, Sequence('id_seq', start=1), primary_key=True),
          autoload_with=engine
    )

Changed in version 1.4: Added `Identity` construct in a `Column` to specify the option of an autoincrementing column.

## Transaction Isolation Level / Autocommit

The Oracle database supports “READ COMMITTED” and “SERIALIZABLE” modes of isolation. The AUTOCOMMIT isolation level is also supported by the cx_Oracle dialect.

To set using per-connection execution options:

    connection = engine.connect()
    connection = connection.execution_options(
        isolation_level="AUTOCOMMIT"
    )

For `READ COMMITTED` and `SERIALIZABLE`, the Oracle dialect sets the level at the session level using `ALTER SESSION`, which is reverted back to its default setting when the connection is returned to the connection pool.

Valid values for `isolation_level` include:

- `READ COMMITTED`

- `AUTOCOMMIT`

- `SERIALIZABLE`

Note

The implementation for the `Connection.get_isolation_level()` method as implemented by the Oracle dialect necessarily forces the start of a transaction using the Oracle LOCAL_TRANSACTION_ID function; otherwise no level is normally readable.

Additionally, the `Connection.get_isolation_level()` method will raise an exception if the `v$transaction` view is not available due to permissions or other reasons, which is a common occurrence in Oracle installations.

The cx_Oracle dialect attempts to call the `Connection.get_isolation_level()` method when the dialect makes its first connection to the database in order to acquire the “default”isolation level. This default level is necessary so that the level can be reset on a connection after it has been temporarily modified using `Connection.execution_options()` method. In the common event that the `Connection.get_isolation_level()` method raises an exception due to `v$transaction` not being readable as well as any other database-related failure, the level is assumed to be “READ COMMITTED”. No warning is emitted for this initial first-connect condition as it is expected to be a common restriction on Oracle databases.

New in version 1.3.16: added support for AUTOCOMMIT to the cx_oracle dialect as well as the notion of a default isolation level

New in version 1.3.21: Added support for SERIALIZABLE as well as live reading of the isolation level.

Changed in version 1.3.22: In the event that the default isolation level cannot be read due to permissions on the v$transaction view as is common in Oracle installations, the default isolation level is hardcoded to “READ COMMITTED” which was the behavior prior to 1.3.21.

See also

Setting Transaction Isolation Levels including DBAPI Autocommit

## Identifier Casing

In Oracle, the data dictionary represents all case insensitive identifier names using UPPERCASE text. SQLAlchemy on the other hand considers an all-lower case identifier name to be case insensitive. The Oracle dialect converts all case insensitive identifiers to and from those two formats during schema level communication, such as reflection of tables and indexes. Using an UPPERCASE name on the SQLAlchemy side indicates a case sensitive identifier, and SQLAlchemy will quote the name - this will cause mismatches against data dictionary data received from Oracle, so unless identifier names have been truly created as case sensitive (i.e. using quoted names), all lowercase names should be used on the SQLAlchemy side.

## Max Identifier Lengths

Oracle has changed the default max identifier length as of Oracle Server version 12.2. Prior to this version, the length was 30, and for 12.2 and greater it is now 128. This change impacts SQLAlchemy in the area of generated SQL label names as well as the generation of constraint names, particularly in the case where the constraint naming convention feature described at Configuring Constraint Naming Conventions is being used.

To assist with this change and others, Oracle includes the concept of a “compatibility” version, which is a version number that is independent of the actual server version in order to assist with migration of Oracle databases, and may be configured within the Oracle server itself. This compatibility version is retrieved using the query `SELECT value FROM v$parameter WHERE name = 'compatible';`. The SQLAlchemy Oracle dialect, when tasked with determining the default max identifier length, will attempt to use this query upon first connect in order to determine the effective compatibility version of the server, which determines what the maximum allowed identifier length is for the server. If the table is not available, the server version information is used instead.

As of SQLAlchemy 1.4, the default max identifier length for the Oracle dialect is 128 characters. Upon first connect, the compatibility version is detected and if it is less than Oracle version 12.2, the max identifier length is changed to be 30 characters. In all cases, setting the `create_engine.max_identifier_length` parameter will bypass this change and the value given will be used as is:

    engine = create_engine(
        "oracle+cx_oracle://scott:tiger@oracle122",
        max_identifier_length=30)

The maximum identifier length comes into play both when generating anonymized SQL labels in SELECT statements, but more crucially when generating constraint names from a naming convention. It is this area that has created the need for SQLAlchemy to change this default conservatively. For example, the following naming convention produces two very different constraint names based on the identifier length:

    from sqlalchemy import Column
    from sqlalchemy import Index
    from sqlalchemy import Integer
    from sqlalchemy import MetaData
    from sqlalchemy import Table
    from sqlalchemy.dialects import oracle
    from sqlalchemy.schema import CreateIndex

    m = MetaData(naming_convention={"ix": "ix_%(column_0N_name)s"})

    t = Table(
        "t",
        m,
        Column("some_column_name_1", Integer),
        Column("some_column_name_2", Integer),
        Column("some_column_name_3", Integer),
    )

    ix = Index(
        None,
        t.c.some_column_name_1,
        t.c.some_column_name_2,
        t.c.some_column_name_3,
    )

    oracle_dialect = oracle.dialect(max_identifier_length=30)
    print(CreateIndex(ix).compile(dialect=oracle_dialect))

With an identifier length of 30, the above CREATE INDEX looks like:

    CREATE INDEX ix_some_column_name_1s_70cd ON t
    (some_column_name_1, some_column_name_2, some_column_name_3)

However with length=128, it becomes:

    CREATE INDEX ix_some_column_name_1some_column_name_2some_column_name_3 ON t
    (some_column_name_1, some_column_name_2, some_column_name_3)

Applications which have run versions of SQLAlchemy prior to 1.4 on an Oracle server version 12.2 or greater are therefore subject to the scenario of a database migration that wishes to “DROP CONSTRAINT” on a name that was previously generated with the shorter length. This migration will fail when the identifier length is changed without the name of the index or constraint first being adjusted. Such applications are strongly advised to make use of `create_engine.max_identifier_length` in order to maintain control of the generation of truncated names, and to fully review and test all database migrations in a staging environment when changing this value to ensure that the impact of this change has been mitigated.

Changed in version 1.4: the default max_identifier_length for Oracle is 128 characters, which is adjusted down to 30 upon first connect if an older version of Oracle server (compatibility version < 12.2) is detected.

## LIMIT/OFFSET/FETCH Support

Methods like `Select.limit()` and `Select.offset()` make use of `FETCH FIRST N ROW / OFFSET N ROWS` syntax assuming Oracle 12c or above, and assuming the SELECT statement is not embedded within a compound statement like UNION. This syntax is also available directly by using the `Select.fetch()` method.

Changed in version 2.0: the Oracle dialect now uses `FETCH FIRST N ROW / OFFSET N ROWS` for all `Select.limit()` and `Select.offset()` usage including within the ORM and legacy `Query`. To force the legacy behavior using window functions, specify the `enable_offset_fetch=False` dialect parameter to `create_engine()`.

The use of `FETCH FIRST / OFFSET` may be disabled on any Oracle version by passing `enable_offset_fetch=False` to `create_engine()`, which will force the use of “legacy” mode that makes use of window functions. This mode is also selected automatically when using a version of Oracle prior to 12c.

When using legacy mode, or when a `Select` statement with limit/offset is embedded in a compound statement, an emulated approach for LIMIT / OFFSET based on window functions is used, which involves creation of a subquery using `ROW_NUMBER` that is prone to performance issues as well as SQL construction issues for complex statements. However, this approach is supported by all Oracle versions. See notes below.

### Notes on LIMIT / OFFSET emulation (when fetch() method cannot be used)

If using `Select.limit()` and `Select.offset()`, or with the ORM the `Query.limit()` and `Query.offset()` methods on an Oracle version prior to 12c, the following notes apply:

- SQLAlchemy currently makes use of ROWNUM to achieve LIMIT/OFFSET; the exact methodology is taken from https://blogs.oracle.com/oraclemagazine/on-rownum-and-limiting-results .

- the “FIRST_ROWS()” optimization keyword is not used by default. To enable the usage of this optimization directive, specify `optimize_limits=True` to `create_engine()`.

  Changed in version 1.4: The Oracle dialect renders limit/offset integer values using a “post compile” scheme which renders the integer directly before passing the statement to the cursor for execution. The `use_binds_for_limits` flag no longer has an effect.

  See also

  New “post compile” bound parameters used for LIMIT/OFFSET in Oracle, SQL Server.

## RETURNING Support

The Oracle database supports RETURNING fully for INSERT, UPDATE and DELETE statements that are invoked with a single collection of bound parameters (that is, a `cursor.execute()` style statement; SQLAlchemy does not generally support RETURNING with executemany statements). Multiple rows may be returned as well.

Changed in version 2.0: the Oracle backend has full support for RETURNING on parity with other backends.

## ON UPDATE CASCADE

Oracle doesn’t have native ON UPDATE CASCADE functionality. A trigger based solution is available at https://asktom.oracle.com/tkyte/update_cascade/index.html .

When using the SQLAlchemy ORM, the ORM has limited ability to manually issue cascading updates - specify ForeignKey objects using the “deferrable=True, initially=’deferred’” keyword arguments, and specify “passive_updates=False” on each relationship().

## Oracle 8 Compatibility

Warning

The status of Oracle 8 compatibility is not known for SQLAlchemy 2.0.

When Oracle 8 is detected, the dialect internally configures itself to the following behaviors:

- the use_ansi flag is set to False. This has the effect of converting all JOIN phrases into the WHERE clause, and in the case of LEFT OUTER JOIN makes use of Oracle’s (+) operator.

- the NVARCHAR2 and NCLOB datatypes are no longer generated as DDL when the `Unicode` is used - VARCHAR2 and CLOB are issued instead. This because these types don’t seem to work correctly on Oracle 8 even though they are available. The `NVARCHAR` and `NCLOB` types will always generate NVARCHAR2 and NCLOB.

## Synonym/DBLINK Reflection

When using reflection with Table objects, the dialect can optionally search for tables indicated by synonyms, either in local or remote schemas or accessed over DBLINK, by passing the flag `oracle_resolve_synonyms=True` as a keyword argument to the `Table` construct:

    some_table = Table('some_table', autoload_with=some_engine,
                                oracle_resolve_synonyms=True)

When this flag is set, the given name (such as `some_table` above) will be searched not just in the `ALL_TABLES` view, but also within the `ALL_SYNONYMS` view to see if this name is actually a synonym to another name. If the synonym is located and refers to a DBLINK, the oracle dialect knows how to locate the table’s information using DBLINK syntax(e.g. `@dblink`).

`oracle_resolve_synonyms` is accepted wherever reflection arguments are accepted, including methods such as `MetaData.reflect()` and `Inspector.get_columns()`.

If synonyms are not in use, this flag should be left disabled.

## Constraint Reflection

The Oracle dialect can return information about foreign key, unique, and CHECK constraints, as well as indexes on tables.

Raw information regarding these constraints can be acquired using `Inspector.get_foreign_keys()`, `Inspector.get_unique_constraints()`, `Inspector.get_check_constraints()`, and `Inspector.get_indexes()`.

Changed in version 1.2: The Oracle dialect can now reflect UNIQUE and CHECK constraints.

When using reflection at the `Table` level, the `Table` will also include these constraints.

Note the following caveats:

- When using the `Inspector.get_check_constraints()` method, Oracle builds a special “IS NOT NULL” constraint for columns that specify “NOT NULL”. This constraint is not returned by default; to include the “IS NOT NULL” constraints, pass the flag `include_all=True`:

      from sqlalchemy import create_engine, inspect

      engine = create_engine("oracle+cx_oracle://s:t@dsn")
      inspector = inspect(engine)
      all_check_constraints = inspector.get_check_constraints(
          "some_table", include_all=True)

- in most cases, when reflecting a `Table`, a UNIQUE constraint will not be available as a `UniqueConstraint` object, as Oracle mirrors unique constraints with a UNIQUE index in most cases (the exception seems to be when two or more unique constraints represent the same columns); the `Table` will instead represent these using `Index` with the `unique=True` flag set.

- Oracle creates an implicit index for the primary key of a table; this index is excluded from all index results.

- the list of columns reflected for an index will not include column names that start with SYS_NC.

## Table names with SYSTEM/SYSAUX tablespaces

The `Inspector.get_table_names()` and `Inspector.get_temp_table_names()` methods each return a list of table names for the current engine. These methods are also part of the reflection which occurs within an operation such as `MetaData.reflect()`. By default, these operations exclude the `SYSTEM` and `SYSAUX` tablespaces from the operation. In order to change this, the default list of tablespaces excluded can be changed at the engine level using the `exclude_tablespaces` parameter:

    # exclude SYSAUX and SOME_TABLESPACE, but not SYSTEM
    e = create_engine(
      "oracle+cx_oracle://scott:tiger@xe",
      exclude_tablespaces=["SYSAUX", "SOME_TABLESPACE"])

## DateTime Compatibility

Oracle has no datatype known as `DATETIME`, it instead has only `DATE`, which can actually store a date and time value. For this reason, the Oracle dialect provides a type `DATE` which is a subclass of `DateTime`. This type has no special behavior, and is only present as a “marker” for this type; additionally, when a database column is reflected and the type is reported as `DATE`, the time-supporting `DATE` type is used.

## Oracle Table Options

The CREATE TABLE phrase supports the following options with Oracle in conjunction with the `Table` construct:

- `ON COMMIT`:

      Table(
          "some_table", metadata, ...,
          prefixes=['GLOBAL TEMPORARY'], oracle_on_commit='PRESERVE ROWS')

- `COMPRESS`:

       Table('mytable', metadata, Column('data', String(32)),
           oracle_compress=True)

       Table('mytable', metadata, Column('data', String(32)),
           oracle_compress=6)

      The ``oracle_compress`` parameter accepts either an integer compression
      level, or ``True`` to use the default compression level.

## Oracle Specific Index Options

### Bitmap Indexes

You can specify the `oracle_bitmap` parameter to create a bitmap index instead of a B-tree index:

    Index('my_index', my_table.c.data, oracle_bitmap=True)

Bitmap indexes cannot be unique and cannot be compressed. SQLAlchemy will not check for such limitations, only the database will.

### Index compression

Oracle has a more efficient storage mode for indexes containing lots of repeated values. Use the `oracle_compress` parameter to turn on key compression:

    Index('my_index', my_table.c.data, oracle_compress=True)

    Index('my_index', my_table.c.data1, my_table.c.data2, unique=True,
           oracle_compress=1)

The `oracle_compress` parameter accepts either an integer specifying the number of prefix columns to compress, or `True` to use the default (all columns for non-unique indexes, all but the last column for unique indexes).

## Oracle Data Types

As with all SQLAlchemy dialects, all UPPERCASE types that are known to be valid with Oracle are importable from the top level dialect, whether they originate from `sqlalchemy.types` or from the local dialect:

    from sqlalchemy.dialects.oracle import (
        BFILE,
        BLOB,
        CHAR,
        CLOB,
        DATE,
        DOUBLE_PRECISION,
        FLOAT,
        INTERVAL,
        LONG,
        NCLOB,
        NCHAR,
        NUMBER,
        NVARCHAR,
        NVARCHAR2,
        RAW,
        TIMESTAMP,
        VARCHAR,
        VARCHAR2,
    )

New in version 1.2.19: Added `NCHAR` to the list of datatypes exported by the Oracle dialect.

Types which are specific to Oracle, or have Oracle-specific construction arguments, are as follows:

Object Name | Description
--- | ---
BFILE |
BINARY_DOUBLE |
BINARY_FLOAT |
DATE | Provide the oracle DATE type.
FLOAT | Oracle FLOAT.
INTERVAL |
LONG |
NCLOB |
NUMBER |
NVARCHAR2 | alias of `NVARCHAR`
RAW |
ROWID | Oracle ROWID type.
TIMESTAMP | Oracle implementation of `TIMESTAMP`, which supports additional Oracle-specific modes

class sqlalchemy.dialects.oracle.BFILE

  Members

  __init__()

  Class signature

  class `sqlalchemy.dialects.oracle.BFILE` (`sqlalchemy.types.LargeBinary`)

  method `sqlalchemy.dialects.oracle.BFILE.`__init__(length: int | None = None)

    inherited from the `sqlalchemy.types.LargeBinary.__init__` method of `LargeBinary`

    Construct a LargeBinary type.

    Parameters:

      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.

class sqlalchemy.dialects.oracle.BINARY_DOUBLE

  Members

  __init__()

  Class signature

  class `sqlalchemy.dialects.oracle.BINARY_DOUBLE` (`sqlalchemy.types.Double`)

  method `sqlalchemy.dialects.oracle.BINARY_DOUBLE.`__init__(precision: int | None = None, asdecimal: bool = False, decimal_return_scale: int | None = None)

    inherited from the `sqlalchemy.types.Float.__init__` method of `Float`

    Construct a Float.

    Parameters:

      - 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 `Float` datatype.

        Note

        For the Oracle backend, the `Float.precision` parameter is not accepted when rendering DDL, as Oracle does not support float precision specified as a number of decimal places. Instead, use the Oracle-specific `FLOAT` datatype and specify the `FLOAT.binary_precision` parameter. This is new in version 2.0 of SQLAlchemy.

        To create a database agnostic `Float` that separately specifies binary precision for Oracle, use `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")
            )

      - asdecimal – the same flag as that of `Numeric`, but defaults to `False`. Note that setting this flag to `True` results in floating point conversion.

      - 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.

class sqlalchemy.dialects.oracle.BINARY_FLOAT

  Members

  __init__()

  Class signature

  class `sqlalchemy.dialects.oracle.BINARY_FLOAT` (`sqlalchemy.types.Float`)

  method `sqlalchemy.dialects.oracle.BINARY_FLOAT.`__init__(precision: int | None = None, asdecimal: bool = False, decimal_return_scale: int | None = None)

    inherited from the `sqlalchemy.types.Float.__init__` method of `Float`

    Construct a Float.

    Parameters:

      - 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 `Float` datatype.

        Note

        For the Oracle backend, the `Float.precision` parameter is not accepted when rendering DDL, as Oracle does not support float precision specified as a number of decimal places. Instead, use the Oracle-specific `FLOAT` datatype and specify the `FLOAT.binary_precision` parameter. This is new in version 2.0 of SQLAlchemy.

        To create a database agnostic `Float` that separately specifies binary precision for Oracle, use `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")
            )

      - asdecimal – the same flag as that of `Numeric`, but defaults to `False`. Note that setting this flag to `True` results in floating point conversion.

      - 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.

class sqlalchemy.dialects.oracle.DATE

  Provide the oracle DATE type.

  This type has no special Python behavior, except that it subclasses `DateTime`; this is to suit the fact that the Oracle `DATE` type supports a time value.

  Members

  __init__()

  Class signature

  class `sqlalchemy.dialects.oracle.DATE` (`sqlalchemy.dialects.oracle.types._OracleDateLiteralRender`, `sqlalchemy.types.DateTime`)

  method `sqlalchemy.dialects.oracle.DATE.`__init__(timezone: bool = False)

    inherited from the `sqlalchemy.types.DateTime.__init__` method of `DateTime`

    Construct a new `DateTime`.

    Parameters:

      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 `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.

class sqlalchemy.dialects.oracle.FLOAT

  Oracle FLOAT.

  This is the same as `FLOAT` except that an Oracle-specific `FLOAT.binary_precision` parameter is accepted, and the `Float.precision` parameter is not accepted.

  Oracle FLOAT types indicate precision in terms of “binary precision”, which defaults to 126. For a REAL type, the value is 63. This parameter does not cleanly map to a specific number of decimal places but is roughly equivalent to the desired number of decimal places divided by 0.3103.

  New in version 2.0.

  Members

  __init__()

  Class signature

  class `sqlalchemy.dialects.oracle.FLOAT` (`sqlalchemy.types.FLOAT`)

  method `sqlalchemy.dialects.oracle.FLOAT.`__init__(binary_precision=None, asdecimal=False, decimal_return_scale=None)

    Construct a FLOAT

    Parameters:

      - binary_precision – Oracle binary precision value to be rendered in DDL. This may be approximated to the number of decimal characters using the formula “decimal precision = 0.30103 * binary precision”. The default value used by Oracle for FLOAT / DOUBLE PRECISION is 126.

      - asdecimal – See `Float.asdecimal`

      - decimal_return_scale – See `Float.decimal_return_scale`

class sqlalchemy.dialects.oracle.INTERVAL

  Members

  __init__()

  Class signature

  class `sqlalchemy.dialects.oracle.INTERVAL` (`sqlalchemy.types.NativeForEmulated`, `sqlalchemy.types._AbstractInterval`)

  method `sqlalchemy.dialects.oracle.INTERVAL.`__init__(day_precision=None, second_precision=None)

    Construct an INTERVAL.

    Note that only DAY TO SECOND intervals are currently supported. This is due to a lack of support for YEAR TO MONTH intervals within available DBAPIs.

    Parameters:

      - day_precision – the day precision value. this is the number of digits to store for the day field. Defaults to “2”

      - second_precision – the second precision value. this is the number of digits to store for the fractional seconds field. Defaults to “6”.

class sqlalchemy.dialects.oracle.NCLOB

  Members

  __init__()

  Class signature

  class `sqlalchemy.dialects.oracle.NCLOB` (`sqlalchemy.types.Text`)

  method `sqlalchemy.dialects.oracle.NCLOB.`__init__(length: int | None = None, collation: str | None = None)

    inherited from the `sqlalchemy.types.String.__init__` method of `String`

    Create a string-holding type.

    Parameters:

      - 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.

      - 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

        Note

        In most cases, the `Unicode` or `UnicodeText` datatypes should be used for a `Column` that expects to store non-ascii data. These datatypes will ensure that the correct types are used on the database.

attribute `sqlalchemy.dialects.oracle..`sqlalchemy.dialects.oracle.NVARCHAR2

  alias of `NVARCHAR`

class sqlalchemy.dialects.oracle.NUMBER

  Class signature

  class `sqlalchemy.dialects.oracle.NUMBER` (`sqlalchemy.types.Numeric`, `sqlalchemy.types.Integer`)

class sqlalchemy.dialects.oracle.LONG

  Members

  __init__()

  Class signature

  class `sqlalchemy.dialects.oracle.LONG` (`sqlalchemy.types.Text`)

  method `sqlalchemy.dialects.oracle.LONG.`__init__(length: int | None = None, collation: str | None = None)

    inherited from the `sqlalchemy.types.String.__init__` method of `String`

    Create a string-holding type.

    Parameters:

      - 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.

      - 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

        Note

        In most cases, the `Unicode` or `UnicodeText` datatypes should be used for a `Column` that expects to store non-ascii data. These datatypes will ensure that the correct types are used on the database.

class sqlalchemy.dialects.oracle.RAW

  Class signature

  class `sqlalchemy.dialects.oracle.RAW` (`sqlalchemy.types._Binary`)

class sqlalchemy.dialects.oracle.ROWID

  Oracle ROWID type.

  When used in a cast() or similar, generates ROWID.

  Class signature

  class `sqlalchemy.dialects.oracle.ROWID` (`sqlalchemy.types.TypeEngine`)

class sqlalchemy.dialects.oracle.TIMESTAMP

  Oracle implementation of `TIMESTAMP`, which supports additional Oracle-specific modes

  New in version 2.0.

  Members

  __init__()

  Class signature

  class `sqlalchemy.dialects.oracle.TIMESTAMP` (`sqlalchemy.types.TIMESTAMP`)

  method `sqlalchemy.dialects.oracle.TIMESTAMP.`__init__(timezone: bool = False, local_timezone: bool = False)

    Construct a new `TIMESTAMP`.

    Parameters:

      - timezone – boolean. Indicates that the TIMESTAMP type should use Oracle’s `TIMESTAMP WITH TIME ZONE` datatype.

      - local_timezone – boolean. Indicates that the TIMESTAMP type should use Oracle’s `TIMESTAMP WITH LOCAL TIME ZONE` datatype.

## cx_Oracle

Support for the Oracle database via the cx-Oracle driver.

### DBAPI

Documentation and download information (if applicable) for cx-Oracle is available at: https://oracle.github.io/python-cx_Oracle/

### Connecting

Connect String:

    oracle+cx_oracle://user:pass@hostname:port[/dbname][?service_name=<service>[&key=value&key=value...]]

### DSN vs. Hostname connections

cx_Oracle provides several methods of indicating the target database. The dialect translates from a series of different URL forms.

#### Hostname Connections with Easy Connect Syntax

Given a hostname, port and service name of the target Oracle Database, for example from Oracle’s Easy Connect syntax, then connect in SQLAlchemy using the `service_name` query string parameter:

    engine = create_engine("oracle+cx_oracle://scott:tiger@hostname:port/?service_name=myservice&encoding=UTF-8&nencoding=UTF-8")

The full Easy Connect syntax is not supported. Instead, use a `tnsnames.ora` file and connect using a DSN.

#### Connections with tnsnames.ora or Oracle Cloud

Alternatively, if no port, database name, or `service_name` is provided, the dialect will use an Oracle DSN “connection string”. This takes the “hostname” portion of the URL as the data source name. For example, if the `tnsnames.ora` file contains a Net Service Name of `myalias` as below:

    myalias =
      (DESCRIPTION =
        (ADDRESS = (PROTOCOL = TCP)(HOST = mymachine.example.com)(PORT = 1521))
        (CONNECT_DATA =
          (SERVER = DEDICATED)
          (SERVICE_NAME = orclpdb1)
        )
      )

The cx_Oracle dialect connects to this database service when `myalias` is the hostname portion of the URL, without specifying a port, database name or `service_name`:

    engine = create_engine("oracle+cx_oracle://scott:tiger@myalias/?encoding=UTF-8&nencoding=UTF-8")

Users of Oracle Cloud should use this syntax and also configure the cloud wallet as shown in cx_Oracle documentation Connecting to Autononmous Databases.

#### SID Connections

To use Oracle’s obsolete SID connection syntax, the SID can be passed in a “database name” portion of the URL as below:

    engine = create_engine("oracle+cx_oracle://scott:tiger@hostname:1521/dbname?encoding=UTF-8&nencoding=UTF-8")

Above, the DSN passed to cx_Oracle is created by `cx_Oracle.makedsn()` as follows:

    >>> import cx_Oracle
    >>> cx_Oracle.makedsn("hostname", 1521, sid="dbname")
    '(DESCRIPTION=(ADDRESS=(PROTOCOL=TCP)(HOST=hostname)(PORT=1521))(CONNECT_DATA=(SID=dbname)))'

### Passing cx_Oracle connect arguments

Additional connection arguments can usually be passed via the URL query string; particular symbols like `cx_Oracle.SYSDBA` are intercepted and converted to the correct symbol:

    e = create_engine(
        "oracle+cx_oracle://user:pass@dsn?encoding=UTF-8&nencoding=UTF-8&mode=SYSDBA&events=true")

Changed in version 1.3: the cx_oracle dialect now accepts all argument names within the URL string itself, to be passed to the cx_Oracle DBAPI. As was the case earlier but not correctly documented, the `create_engine.connect_args` parameter also accepts all cx_Oracle DBAPI connect arguments.

To pass arguments directly to `.connect()` without using the query string, use the `create_engine.connect_args` dictionary. Any cx_Oracle parameter value and/or constant may be passed, such as:

    import cx_Oracle
    e = create_engine(
        "oracle+cx_oracle://user:pass@dsn",
        connect_args={
            "encoding": "UTF-8",
            "nencoding": "UTF-8",
            "mode": cx_Oracle.SYSDBA,
            "events": True
        }
    )

Note that the default value for `encoding` and `nencoding` was changed to “UTF-8” in cx_Oracle 8.0 so these parameters can be omitted when using that version, or later.

### Options consumed by the SQLAlchemy cx_Oracle dialect outside of the driver

There are also options that are consumed by the SQLAlchemy cx_oracle dialect itself. These options are always passed directly to `create_engine()` , such as:

    e = create_engine(
        "oracle+cx_oracle://user:pass@dsn", coerce_to_decimal=False)

The parameters accepted by the cx_oracle dialect are as follows:

- `arraysize` - set the cx_oracle.arraysize value on cursors; defaults to `None`, indicating that the driver default should be used (typically the value is 100). This setting controls how many rows are buffered when fetching rows, and can have a significant effect on performance when modified. The setting is used for both `cx_Oracle` as well as `oracledb`.

  Changed in version 2.0.26: - changed the default value from 50 to None, to use the default value of the driver itself.

- `auto_convert_lobs` - defaults to True; See LOB Datatypes.

- `coerce_to_decimal` - see Precision Numerics for detail.

- `encoding_errors` - see Encoding Errors for detail.

### Using cx_Oracle SessionPool

The cx_Oracle library provides its own connection pool implementation that may be used in place of SQLAlchemy’s pooling functionality. This can be achieved by using the `create_engine.creator` parameter to provide a function that returns a new connection, along with setting `create_engine.pool_class` to `NullPool` to disable SQLAlchemy’s pooling:

    import cx_Oracle
    from sqlalchemy import create_engine
    from sqlalchemy.pool import NullPool

    pool = cx_Oracle.SessionPool(
        user="scott", password="tiger", dsn="orclpdb",
        min=2, max=5, increment=1, threaded=True,
        encoding="UTF-8", nencoding="UTF-8"
    )

    engine = create_engine("oracle+cx_oracle://", creator=pool.acquire, poolclass=NullPool)

The above engine may then be used normally where cx_Oracle’s pool handles connection pooling:

    with engine.connect() as conn:
        print(conn.scalar("select 1 FROM dual"))

As well as providing a scalable solution for multi-user applications, the cx_Oracle session pool supports some Oracle features such as DRCP and Application Continuity.

### Using Oracle Database Resident Connection Pooling (DRCP)

When using Oracle’s DRCP, the best practice is to pass a connection class and “purity” when acquiring a connection from the SessionPool. Refer to the cx_Oracle DRCP documentation.

This can be achieved by wrapping `pool.acquire()`:

    import cx_Oracle
    from sqlalchemy import create_engine
    from sqlalchemy.pool import NullPool

    pool = cx_Oracle.SessionPool(
        user="scott", password="tiger", dsn="orclpdb",
        min=2, max=5, increment=1, threaded=True,
        encoding="UTF-8", nencoding="UTF-8"
    )

    def creator():
        return pool.acquire(cclass="MYCLASS", purity=cx_Oracle.ATTR_PURITY_SELF)

    engine = create_engine("oracle+cx_oracle://", creator=creator, poolclass=NullPool)

The above engine may then be used normally where cx_Oracle handles session pooling and Oracle Database additionally uses DRCP:

    with engine.connect() as conn:
        print(conn.scalar("select 1 FROM dual"))

### Unicode

As is the case for all DBAPIs under Python 3, all strings are inherently Unicode strings. In all cases however, the driver requires an explicit encoding configuration.

#### Ensuring the Correct Client Encoding

The long accepted standard for establishing client encoding for nearly all Oracle related software is via the NLS_LANG environment variable. cx_Oracle like most other Oracle drivers will use this environment variable as the source of its encoding configuration. The format of this variable is idiosyncratic; a typical value would be `AMERICAN_AMERICA.AL32UTF8`.

The cx_Oracle driver also supports a programmatic alternative which is to pass the `encoding` and `nencoding` parameters directly to its `.connect()` function. These can be present in the URL as follows:

    engine = create_engine("oracle+cx_oracle://scott:tiger@orclpdb/?encoding=UTF-8&nencoding=UTF-8")

For the meaning of the `encoding` and `nencoding` parameters, please consult Characters Sets and National Language Support (NLS).

See also

Characters Sets and National Language Support (NLS) - in the cx_Oracle documentation.

#### Unicode-specific Column datatypes

The Core expression language handles unicode data by use of the `Unicode` and `UnicodeText` datatypes. These types correspond to the VARCHAR2 and CLOB Oracle datatypes by default. When using these datatypes with Unicode data, it is expected that the Oracle database is configured with a Unicode-aware character set, as well as that the `NLS_LANG` environment variable is set appropriately, so that the VARCHAR2 and CLOB datatypes can accommodate the data.

In the case that the Oracle database is not configured with a Unicode character set, the two options are to use the `NCHAR` and `NCLOB` datatypes explicitly, or to pass the flag `use_nchar_for_unicode=True` to `create_engine()`, which will cause the SQLAlchemy dialect to use NCHAR/NCLOB for the `Unicode` / `UnicodeText` datatypes instead of VARCHAR/CLOB.

Changed in version 1.3: The `Unicode` and `UnicodeText` datatypes now correspond to the `VARCHAR2` and `CLOB` Oracle datatypes unless the `use_nchar_for_unicode=True` is passed to the dialect when `create_engine()` is called.

#### Encoding Errors

For the unusual case that data in the Oracle database is present with a broken encoding, the dialect accepts a parameter `encoding_errors` which will be passed to Unicode decoding functions in order to affect how decoding errors are handled. The value is ultimately consumed by the Python decode function, and is passed both via cx_Oracle’s `encodingErrors` parameter consumed by `Cursor.var()`, as well as SQLAlchemy’s own decoding function, as the cx_Oracle dialect makes use of both under different circumstances.

New in version 1.3.11.

### Fine grained control over cx_Oracle data binding performance with setinputsizes

The cx_Oracle DBAPI has a deep and fundamental reliance upon the usage of the DBAPI `setinputsizes()` call. The purpose of this call is to establish the datatypes that are bound to a SQL statement for Python values being passed as parameters. While virtually no other DBAPI assigns any use to the `setinputsizes()` call, the cx_Oracle DBAPI relies upon it heavily in its interactions with the Oracle client interface, and in some scenarios it is not possible for SQLAlchemy to know exactly how data should be bound, as some settings can cause profoundly different performance characteristics, while altering the type coercion behavior at the same time.

Users of the cx_Oracle dialect are strongly encouraged to read through cx_Oracle’s list of built-in datatype symbols at https://cx-oracle.readthedocs.io/en/latest/api_manual/module.html#database-types. Note that in some cases, significant performance degradation can occur when using these types vs. not, in particular when specifying `cx_Oracle.CLOB`.

On the SQLAlchemy side, the `DialectEvents.do_setinputsizes()` event can be used both for runtime visibility (e.g. logging) of the setinputsizes step as well as to fully control how `setinputsizes()` is used on a per-statement basis.

New in version 1.2.9: Added `DialectEvents.setinputsizes()`

#### Example 1 - logging all setinputsizes calls

The following example illustrates how to log the intermediary values from a SQLAlchemy perspective before they are converted to the raw `setinputsizes()` parameter dictionary. The keys of the dictionary are `BindParameter` objects which have a `.key` and a `.type` attribute:

    from sqlalchemy import create_engine, event

    engine = create_engine("oracle+cx_oracle://scott:tiger@host/xe")

    @event.listens_for(engine, "do_setinputsizes")
    def _log_setinputsizes(inputsizes, cursor, statement, parameters, context):
        for bindparam, dbapitype in inputsizes.items():
                log.info(
                    "Bound parameter name: %s  SQLAlchemy type: %r  "
                    "DBAPI object: %s",
                    bindparam.key, bindparam.type, dbapitype)

#### Example 2 - remove all bindings to CLOB

The `CLOB` datatype in cx_Oracle incurs a significant performance overhead, however is set by default for the `Text` type within the SQLAlchemy 1.2 series. This setting can be modified as follows:

    from sqlalchemy import create_engine, event
    from cx_Oracle import CLOB

    engine = create_engine("oracle+cx_oracle://scott:tiger@host/xe")

    @event.listens_for(engine, "do_setinputsizes")
    def _remove_clob(inputsizes, cursor, statement, parameters, context):
        for bindparam, dbapitype in list(inputsizes.items()):
            if dbapitype is CLOB:
                del inputsizes[bindparam]

### RETURNING Support

The cx_Oracle dialect implements RETURNING using OUT parameters. The dialect supports RETURNING fully.

### LOB Datatypes

LOB datatypes refer to the “large object” datatypes such as CLOB, NCLOB and BLOB. Modern versions of cx_Oracle and oracledb are optimized for these datatypes to be delivered as a single buffer. As such, SQLAlchemy makes use of these newer type handlers by default.

To disable the use of newer type handlers and deliver LOB objects as classic buffered objects with a `read()` method, the parameter `auto_convert_lobs=False` may be passed to `create_engine()`, which takes place only engine-wide.

### Two Phase Transactions Not Supported (use oracledb)

Two phase transactions are not supported under cx_Oracle due to poor driver support. The newer python-oracledb dialect however does support two phase transactions and should be preferred.

### Precision Numerics

SQLAlchemy’s numeric types can handle receiving and returning values as Python `Decimal` objects or float objects. When a `Numeric` object, or a subclass such as `Float`, `DOUBLE_PRECISION` etc. is in use, the `Numeric.asdecimal` flag determines if values should be coerced to `Decimal` upon return, or returned as float objects. To make matters more complicated under Oracle, Oracle’s `NUMBER` type can also represent integer values if the “scale” is zero, so the Oracle-specific `NUMBER` type takes this into account as well.

The cx_Oracle dialect makes extensive use of connection- and cursor-level “outputtypehandler” callables in order to coerce numeric values as requested. These callables are specific to the specific flavor of `Numeric` in use, as well as if no SQLAlchemy typing objects are present. There are observed scenarios where Oracle may sends incomplete or ambiguous information about the numeric types being returned, such as a query where the numeric types are buried under multiple levels of subquery. The type handlers do their best to make the right decision in all cases, deferring to the underlying cx_Oracle DBAPI for all those cases where the driver can make the best decision.

When no typing objects are present, as when executing plain SQL strings, a default “outputtypehandler” is present which will generally return numeric values which specify precision and scale as Python `Decimal` objects. To disable this coercion to decimal for performance reasons, pass the flag `coerce_to_decimal=False` to `create_engine()`:

    engine = create_engine("oracle+cx_oracle://dsn", coerce_to_decimal=False)

The `coerce_to_decimal` flag only impacts the results of plain string SQL statements that are not otherwise associated with a `Numeric` SQLAlchemy type (or a subclass of such).

Changed in version 1.2: The numeric handling system for cx_Oracle has been reworked to take advantage of newer cx_Oracle features as well as better integration of outputtypehandlers.

## python-oracledb

Support for the Oracle database via the python-oracledb driver.

### DBAPI

Documentation and download information (if applicable) for python-oracledb is available at: https://oracle.github.io/python-oracledb/

### Connecting

Connect String:

    oracle+oracledb://user:pass@hostname:port[/dbname][?service_name=<service>[&key=value&key=value...]]

### Description

python-oracledb is released by Oracle to supersede the cx_Oracle driver. It is fully compatible with cx_Oracle and features both a “thin” client mode that requires no dependencies, as well as a “thick” mode that uses the Oracle Client Interface in the same way as cx_Oracle.

See also

cx_Oracle - all of cx_Oracle’s notes apply to the oracledb driver as well, with the exception that oracledb supports two phase transactions.

The SQLAlchemy `oracledb` dialect provides both a sync and an async implementation under the same dialect name. The proper version is selected depending on how the engine is created:

- calling `create_engine()` with `oracle+oracledb://...` will automatically select the sync version, e.g.:

      from sqlalchemy import create_engine
      sync_engine = create_engine("oracle+oracledb://scott:tiger@localhost/?service_name=XEPDB1")

- calling `create_async_engine()` with `oracle+oracledb://...` will automatically select the async version, e.g.:

      from sqlalchemy.ext.asyncio import create_async_engine
      asyncio_engine = create_async_engine("oracle+oracledb://scott:tiger@localhost/?service_name=XEPDB1")

The asyncio version of the dialect may also be specified explicitly using the `oracledb_async` suffix, as:

    from sqlalchemy.ext.asyncio import create_async_engine
    asyncio_engine = create_async_engine("oracle+oracledb_async://scott:tiger@localhost/?service_name=XEPDB1")

New in version 2.0.25: added support for the async version of oracledb.

### Thick mode support

By default the `python-oracledb` is started in thin mode, that does not require oracle client libraries to be installed in the system. The `python-oracledb` driver also support a “thick” mode, that behaves similarly to `cx_oracle` and requires that Oracle Client Interface (OCI) is installed.

To enable this mode, the user may call `oracledb.init_oracle_client` manually, or by passing the parameter `thick_mode=True` to `create_engine()`. To pass custom arguments to `init_oracle_client`, like the `lib_dir` path, a dict may be passed to this parameter, as in:

    engine = sa.create_engine("oracle+oracledb://...", thick_mode={
        "lib_dir": "/path/to/oracle/client/lib", "driver_name": "my-app"
    })

See also

https://python-oracledb.readthedocs.io/en/latest/api_manual/module.html#oracledb.init_oracle_client

### Two Phase Transactions Supported

Two phase transactions are fully supported under oracledb. Starting with oracledb 2.3 two phase transactions are supported also in thin mode. APIs for two phase transactions are provided at the Core level via `Connection.begin_twophase()` and `Session.twophase` for transparent ORM use.

Changed in version 2.0.32: added support for two phase transactions

New in version 2.0.0: added support for oracledb driver.