Executing SQL

Executing SQL statements is the primary way in which a Python application communicates with Oracle Database. Statements are executed using the methods :meth:`Cursor.execute()` or :meth:`Cursor.executemany()`. Statements include queries, Data Manipulation Language (DML), and Data Definition Language (DDL). A few other specialty statements can also be executed.

PL/SQL statements are discussed in :ref:`plsqlexecution`. Other chapters contain information on specific data types and features. See :ref:`batchstmnt`, :ref:`lobdata`, :ref:`jsondatatype`, and :ref:`xmldatatype`.

Python-oracledb can be used to execute individual statements, one at a time. Once a statement has finished execution, only then will the next statement execute. If you try to execute statements concurrently, the statements are queued and run consecutively in the order they are in the code.

Python-oracledb does not read SQL*Plus ".sql" files. To read SQL files, use a technique like the one in run_sql_script() in samples/sample_env.py.

SQL statements should not contain a trailing semicolon (";") or forward slash ("/"). This will fail:

cursor.execute("select * from MyTable;")

This is correct:

cursor.execute("select * from MyTable")

SQL Queries

Queries (statements beginning with SELECT or WITH) can only be executed using the method :meth:`Cursor.execute()`. Rows can then be iterated over, or can be fetched using one of the methods :meth:`Cursor.fetchone()`, :meth:`Cursor.fetchmany()` or :meth:`Cursor.fetchall()`. There is a :ref:`default type mapping <defaultfetchtypes>` to Python types that can be optionally :ref:`overridden <outputtypehandlers>`.

Important

Interpolating or concatenating user data with SQL statements, for example cursor.execute("SELECT * FROM mytab WHERE mycol = '" + myvar + "'"), is a security risk and impacts performance. Use :ref:`bind variables <bind>` instead. For example, cursor.execute("SELECT * FROM mytab WHERE mycol = :mybv", mybv=myvar).

Fetch Methods

Rows can be fetched in various ways.

After :meth:`Cursor.execute()`, the cursor is returned as a convenience. This allows code to iterate over rows like:
```
cursor = connection.cursor()
for row in cursor.execute("select * from MyTable"):
    print(row)
```

Rows can also be fetched one at a time using the method :meth:`Cursor.fetchone()`:

cursor = connection.cursor()
cursor.execute("select * from MyTable")
while True:
    row = cursor.fetchone()
    if row is None:
        break
    print(row)

If rows need to be processed in batches, the method :meth:`Cursor.fetchmany()` can be used. The size of the batch is controlled by the size parameter, which defaults to the value of :attr:`Cursor.arraysize`.
```
cursor = connection.cursor()
cursor.execute("select * from MyTable")
num_rows = 10
while True:
    rows = cursor.fetchmany(size=num_rows)
    if not rows:
        break
    for row in rows:
        print(row)
```
Note the size parameter only affects the number of rows returned to the application, not to the internal buffer size used for tuning fetch performance. That internal buffer size is controlled only by changing :attr:`Cursor.arraysize`, see :ref:`tuningfetch`.
If all of the rows need to be fetched and can be contained in memory, the method :meth:`Cursor.fetchall()` can be used.
```
cursor = connection.cursor()
cursor.execute("select * from MyTable")
rows = cursor.fetchall()
for row in rows:
    print(row)
```
The fetch methods return data as tuples. To return results as dictionaries, see :ref:`rowfactories`.

Closing Cursors

Once cursors are no longer needed, they should be closed in order to reclaim resources in the database. Note cursors may be used to execute multiple statements before being closed.

Cursors can be closed in various ways:

A cursor will be closed automatically when the variable referencing it goes out of scope (and no further references are retained). A with context manager block is a convenient and preferred way to ensure this. For example:
```
with connection.cursor() as cursor:
    for row in cursor.execute("select * from MyTable"):
        print(row)
```
This code ensures that once the block is completed, the cursor is closed and database resources can be reclaimed. In addition, any attempt to use the variable cursor outside of the block will fail.
Cursors can be explicitly closed by calling :meth:`~Cursor.close()`
```
cursor = connection.cursor()

...

cursor.close()
```

Query Column Metadata

After executing a query, the column metadata such as column names and data types can be obtained using :attr:`Cursor.description`:

with connection.cursor() as cursor:
    cursor.execute("select * from MyTable")
    for column in cursor.description:
        print(column)

This could result in metadata like:

('ID', <class 'oracledb.DB_TYPE_NUMBER'>, 39, None, 38, 0, 0)
('NAME', <class 'oracledb.DB_TYPE_VARCHAR'>, 20, 20, None, None, 1)

To extract the column names from a query you can use code like:

with connection.cursor() as cursor:
    cursor.execute("select * from locations")
    columns = [col[0] for col in cursor.description]
    print(columns)
    for r in cursor:
        print(r)

This will print:

['LOCATION_ID', 'STREET_ADDRESS', 'POSTAL_CODE', 'CITY', 'STATE_PROVINCE', 'COUNTRY_ID']
(1000, '1297 Via Cola di Rie', '00989', 'Roma', None, 'IT')
(1100, '93091 Calle della Testa', '10934', 'Venice', None, 'IT')
. . .

Fetch Data Types

The following table provides a list of all of the data types that python-oracledb knows how to fetch. The middle column gives the type that is returned in the :ref:`query metadata <querymetadata>`. The last column gives the type of Python object that is returned by default. Python types can be changed with :ref:`Output Type Handlers <outputtypehandlers>`.

.. list-table-with-summary::
    :header-rows: 1
    :class: wy-table-responsive
    :widths: 1 1 1
    :align: left
    :summary: The first column is the Oracle Database Type. The second column is the oracledb Database Type that is returned in the query metadata. The third column is the type of Python object that is returned by default.

    * - Oracle Database Type
      - oracledb Database Type
      - Default Python type
    * - BFILE
      - :attr:`oracledb.DB_TYPE_BFILE`
      - :ref:`oracledb.LOB <lobobj>`
    * - BINARY_DOUBLE
      - :attr:`oracledb.DB_TYPE_BINARY_DOUBLE`
      - float
    * - BINARY_FLOAT
      - :attr:`oracledb.DB_TYPE_BINARY_FLOAT`
      - float
    * - BLOB
      - :attr:`oracledb.DB_TYPE_BLOB`
      - :ref:`oracledb.LOB <lobobj>`
    * - CHAR
      - :attr:`oracledb.DB_TYPE_CHAR`
      - str
    * - CLOB
      - :attr:`oracledb.DB_TYPE_CLOB`
      - :ref:`oracledb.LOB <lobobj>`
    * - CURSOR
      - :attr:`oracledb.DB_TYPE_CURSOR`
      - :ref:`oracledb.Cursor <cursorobj>`
    * - DATE
      - :attr:`oracledb.DB_TYPE_DATE`
      - datetime.datetime
    * - INTERVAL DAY TO SECOND
      - :attr:`oracledb.DB_TYPE_INTERVAL_DS`
      - datetime.timedelta
    * - INTERVAL YEAR TO MONTH
      - :data:`oracledb.DB_TYPE_INTERVAL_YM`
      - :ref:`oracledb.IntervalYM <interval_ym>`
    * - JSON
      - :attr:`oracledb.DB_TYPE_JSON`
      - dict, list or a scalar value [4]_
    * - LONG
      - :attr:`oracledb.DB_TYPE_LONG`
      - str
    * - LONG RAW
      - :attr:`oracledb.DB_TYPE_LONG_RAW`
      - bytes
    * - NCHAR
      - :attr:`oracledb.DB_TYPE_NCHAR`
      - str
    * - NCLOB
      - :attr:`oracledb.DB_TYPE_NCLOB`
      - :ref:`oracledb.LOB <lobobj>`
    * - NUMBER
      - :attr:`oracledb.DB_TYPE_NUMBER`
      - float or int [1]_
    * - NVARCHAR2
      - :attr:`oracledb.DB_TYPE_NVARCHAR`
      - str
    * - OBJECT [3]_
      - :attr:`oracledb.DB_TYPE_OBJECT`
      - :ref:`oracledb.Object <dbobjecttype>`
    * - RAW
      - :attr:`oracledb.DB_TYPE_RAW`
      - bytes
    * - ROWID
      - :attr:`oracledb.DB_TYPE_ROWID`
      - str
    * - TIMESTAMP
      - :attr:`oracledb.DB_TYPE_TIMESTAMP`
      - datetime.datetime
    * - TIMESTAMP WITH LOCAL TIME ZONE
      - :attr:`oracledb.DB_TYPE_TIMESTAMP_LTZ`
      - datetime.datetime [2]_
    * - TIMESTAMP WITH TIME ZONE
      - :attr:`oracledb.DB_TYPE_TIMESTAMP_TZ`
      - datetime.datetime [2]_
    * - UROWID
      - :attr:`oracledb.DB_TYPE_ROWID`, :attr:`oracledb.DB_TYPE_UROWID`
      - str
    * - VARCHAR2
      - :attr:`oracledb.DB_TYPE_VARCHAR`
      - str

[1]

If the precision and scale obtained from query column metadata indicate that the value can be expressed as an integer, the value will be returned as an int. If the column is unconstrained (no precision and scale specified), the value will be returned as a float or an int depending on whether the value itself is an integer. In all other cases the value is returned as a float.

[2]	The timestamps returned are naive timestamps without any time zone information present.

[3]	These include all user-defined types such as VARRAY, NESTED TABLE, etc.

[4]	If the JSON is an object, then a dict is returned. If it is an array, then a list is returned. If it is a scalar value, then that particular scalar value is returned.

Changing Fetched Data

Data returned by python-oracledb queries can be changed by using output type handlers, by using "outconverters", or by using row factories.

Changing Fetched Data Types with Output Type Handlers

Sometimes the default conversion from an Oracle Database type to a Python type must be changed in order to prevent data loss or to fit the purposes of the Python application. In such cases, an output type handler can be specified for queries. This asks the database to do a conversion from the column type to a different type before the data is returned from the database to python-oracledb. If the database does not support such a mapping, an error will be returned. Output type handlers only affect query output and do not affect values returned from :meth:`Cursor.callfunc()` or :meth:`Cursor.callproc()`.

Output type handlers can be specified on a :attr:`connection <Connection.outputtypehandler>` or on a :attr:`cursor <Cursor.outputtypehandler>`. If specified on a cursor, fetch type handling is only changed on that particular cursor. If specified on a connection, all cursors created by that connection will have their fetch type handling changed.

The output type handler is expected to be a function with the following signature:

handler(cursor, metadata)

The metadata parameter is a :ref:`FetchInfo object<fetchinfoobj>`, which is the same value found in :attr:`Cursor.description`.

The function is called once for each column that is going to be fetched. The function is expected to return a :ref:`variable object <varobj>` (generally by a call to :func:`Cursor.var()`) or the value None. The value None indicates that the default type should be used.

For example:

def output_type_handler(cursor, metadata):
    if metadata.type_code is oracledb.DB_TYPE_NUMBER:
        return cursor.var(oracledb.DB_TYPE_VARCHAR, arraysize=cursor.arraysize)

This output type handler is called once for each column in the SELECT query. For each numeric column, the database will now return a string representation of each row's value. Using it in a query:

cursor.outputtypehandler = output_type_handler

cursor.execute("select 123 from dual")
r = cursor.fetchone()
print(r)

prints ('123',) showing the number was converted to a string. Without the type handler, the output would have been (123,).

When creating variables using :meth:`Cursor.var()` in a handler, the arraysize parameter should be the same as the :attr:`~Cursor.arraysize` of the query cursor. In python-oracledb Thick mode, the query (and var()) arraysize multiplied by the byte size of the particular column must be less than INT_MAX.

To unset an output type handler, set it to None. For example if you had previously set a type handler on a cursor, you can remove it with:

cursor.outputtypehandler = None

Other examples of output handlers are shown in :ref:`numberprecision`, :ref:`directlobs`, and :ref:`fetching-raw-data`. Also see samples such as samples/type_handlers_json_strings.py.

Changing Query Results with Outconverters

Python-oracledb "outconverters" can be used with :ref:`output type handlers <outputtypehandlers>` to change returned data.

For example, to convert numbers to strings:

def output_type_handler(cursor, metadata):

    def out_converter(d):
        if isinstance(d, str):
            return f"{d} was a string"
        else:
            return f"{d} was not a string"

    if metadata.type_code is oracledb.DB_TYPE_NUMBER:
        return cursor.var(oracledb.DB_TYPE_VARCHAR,
             arraysize=cursor.arraysize, outconverter=out_converter)

The output type handler is called once for each column in the SELECT query. For each numeric column, the database will now return a string representation of each row's value, and the outconverter will be called for each of those values.

Using it in a query:

cursor.outputtypehandler = output_type_handler

cursor.execute("select 123 as col1, 'abc' as col2 from dual")
for r in cursor.fetchall():
    print(r)

prints:

('123 was a string', 'abc')

This shows that the number was first converted to a string by the database, as requested in the output type handler. The out_converter function then appended "was a string" to the data before the value was returned to the application.

Note outconverters are not called for NULL data values unless the :meth:`Cursor.var()` parameter convert_nulls is True.

Another example of an outconverter is shown in :ref:`fetching VECTORs as lists <vecoutputtypehandlerlist>`.

Changing Query Results with Rowfactories

Python-oracledb "rowfactories" are methods called for each row retrieved from the database. The :meth:`Cursor.rowfactory` method is called with the tuple fetched from the database before it is returned to the application. The method can convert the tuple to a different value.

For example, to fetch each row of a query as a dictionary:

cursor.execute("select * from locations where location_id = 1000")

columns = [col[0] for col in cursor.description]
cursor.rowfactory = lambda *args: dict(zip(columns, args))
data = cursor.fetchone()
print(data)

The output is:

{'LOCATION_ID': 1000, 'STREET_ADDRESS': '1297 Via Cola di Rie',
'POSTAL_CODE': '00989', 'CITY': 'Roma', 'STATE_PROVINCE': None,
'COUNTRY_ID': 'IT'}

Also see how JSON_OBJECT is used in :ref:`jsondatatype`.

If you join tables where the same column name occurs in both tables with different meanings or values, then use a column alias in the query. Otherwise, only one of the similarly named columns will be included in the dictionary:

select
    cat_name,
    cats.color as cat_color,
    dog_name,
    dogs.color
from cats, dogs

An example showing an :ref:`output type handler <outputtypehandlers>`, an :ref:`outconverter <outconverters>`, and a row factory is:

def output_type_handler(cursor, metadata):

    def out_converter(d):
        if type(d) is str:
            return f"{d} was a string"
        else:
            return f"{d} was not a string"

    if metadata.type_code is oracledb.DB_TYPE_NUMBER:
        return cursor.var(oracledb.DB_TYPE_VARCHAR,
            arraysize=cursor.arraysize, outconverter=out_converter)

cursor.outputtypehandler = output_type_handler

cursor.execute("select 123 as col1, 'abc' as col2 from dual")

columns = [col[0] for col in cursor.description]
cursor.rowfactory = lambda *args: dict(zip(columns, args))
for r in cursor.fetchall():
    print(r)

The database converts the number to a string before it is returned to python-oracledb. The outconverter appends "was a string" to this value. Finally the row factory changes the complete row to a dictionary. The output is:

{'COL1': '123 was a string', 'COL2': 'abc'}

Fetched Number Precision

Oracle Database uses decimal numbers and these cannot be converted seamlessly to binary number representations like Python floats. In addition, the range of Oracle numbers exceeds that of floating point numbers. Python has decimal objects which do not have these limitations. In python-oracledb you can set oracledb.defaults.fetch_decimals so that Decimals are returned to the application, ensuring that numeric precision is not lost when fetching certain numbers.

The following code sample demonstrates the issue:

cursor.execute("create table test_float (X number(5, 3))")
cursor.execute("insert into test_float values (7.1)")

cursor.execute("select * from test_float")
val, = cursor.fetchone()
print(val, "* 3 =", val * 3)

This displays 7.1 * 3 = 21.299999999999997

Using Python decimal objects, however, there is no loss of precision:

oracledb.defaults.fetch_decimals = True

cursor.execute("select * from test_float")
val, = cursor.fetchone()
print(val, "* 3 =", val * 3)

This displays 7.1 * 3 = 21.3

See samples/return_numbers_as_decimals.py

An equivalent, longer, older coding idiom to :attr:`Defaults.fetch_decimals` is to use an :ref:`output type handler <outputtypehandlers>` do the conversion.

import decimal

def number_to_decimal(cursor, metadata):
    if metadata.type_code is oracledb.DB_TYPE_NUMBER:
        return cursor.var(decimal.Decimal, arraysize=cursor.arraysize)

cursor.outputtypehandler = number_to_decimal

cursor.execute("select * from test_float")
val, = cursor.fetchone()
print(val, "* 3 =", val * 3)

This displays 7.1 * 3 = 21.3

The Python decimal.Decimal converter gets called with the string representation of the Oracle number. The output from decimal.Decimal is returned in the output tuple.

Scrollable Cursors

Scrollable cursors enable applications to move backwards, forwards, to skip rows, and to move to a particular row in a query result set. The result set is cached on the database server until the cursor is closed. In contrast, regular cursors are restricted to moving forward.

Note

Scrollable cursors are only supported in the python-oracledb Thick mode. See :ref:`enablingthick`.

A scrollable cursor is created by setting the parameter scrollable=True when creating the cursor. The method :meth:`Cursor.scroll()` is used to move to different locations in the result set.

Examples are:

cursor = connection.cursor(scrollable=True)
cursor.execute("select * from ChildTable order by ChildId")

cursor.scroll(mode="last")
print("LAST ROW:", cursor.fetchone())

cursor.scroll(mode="first")
print("FIRST ROW:", cursor.fetchone())

cursor.scroll(8, mode="absolute")
print("ROW 8:", cursor.fetchone())

cursor.scroll(6)
print("SKIP 6 ROWS:", cursor.fetchone())

cursor.scroll(-4)
print("SKIP BACK 4 ROWS:", cursor.fetchone())

Fetching Oracle Database Objects and Collections

Oracle Database named object types and user-defined types can be fetched directly in queries. Each item is represented as a :ref:`Python object <dbobjecttype>` corresponding to the Oracle Database object. This Python object can be traversed to access its elements. Attributes including :attr:`DbObjectType.name` and :attr:`DbObjectType.iscollection`, and methods including :meth:`DbObject.aslist` and :meth:`DbObject.asdict` are available.

For example, if a table mygeometrytab contains a column geometry of Oracle's predefined Spatial object type SDO_GEOMETRY, then it can be queried and printed:

cursor.execute("select geometry from mygeometrytab")
for obj, in cursor:
    dumpobject(obj)

Where dumpobject() is defined as:

def dumpobject(obj, prefix = ""):
    if obj.type.iscollection:
        print(prefix, "[")
        for value in obj.aslist():
            if isinstance(value, oracledb.Object):
                dumpobject(value, prefix + "  ")
            else:
                print(prefix + "  ", repr(value))
        print(prefix, "]")
    else:
        print(prefix, "{")
        for attr in obj.type.attributes:
            value = getattr(obj, attr.name)
            if isinstance(value, oracledb.Object):
                print(prefix + "   " + attr.name + ":")
                dumpobject(value, prefix + "  ")
            else:
                print(prefix + "   " + attr.name + ":", repr(value))
        print(prefix, "}")

This might produce output like:

{
  SDO_GTYPE: 2003
  SDO_SRID: None
  SDO_POINT:
  {
    X: 1
    Y: 2
    Z: 3
  }
  SDO_ELEM_INFO:
  [
    1
    1003
    3
  ]
  SDO_ORDINATES:
  [
    1
    1
    5
    7
  ]
}

Other information on using Oracle objects is in :ref:`Using Bind Variables <bind>`.

Performance-sensitive applications should consider using scalar types instead of objects. If you do use objects, avoid calling :meth:`Connection.gettype()` unnecessarily, and avoid objects with large numbers of attributes.

Limiting Rows

Query data is commonly broken into one or more sets:

To give an upper bound on the number of rows that a query has to process, which can help improve database scalability.
To perform 'Web pagination' that allows moving from one set of rows to a next, or previous, set on demand.
For fetching of all data in consecutive small sets for batch processing. This happens because the number of records is too large for Python to handle at one time.

The latter can be handled by calling :meth:`Cursor.fetchmany()` with one execution of the SQL query.

'Web pagination' and limiting the maximum number of rows are detailed in this section. For each 'page' of results, a SQL query is executed to get the appropriate set of rows from a table. Since the query may be executed more than once, ensure to use :ref:`bind variables <bind>` for row numbers and row limits.

Oracle Database 12c SQL introduced an OFFSET / FETCH clause which is similar to the LIMIT keyword of MySQL. In Python, you can fetch a set of rows using:

myoffset = 0       // do not skip any rows (start at row 1)
mymaxnumrows = 20  // get 20 rows

sql =
  """SELECT last_name
     FROM employees
     ORDER BY last_name
     OFFSET :offset ROWS FETCH NEXT :maxnumrows ROWS ONLY"""

cursor = connection.cursor()
for row in cursor.execute(sql, offset=myoffset, maxnumrows=mymaxnumrows):
    print(row)

In applications where the SQL query is not known in advance, this method sometimes involves appending the OFFSET clause to the 'real' user query. Be very careful to avoid SQL injection security issues.

For Oracle Database 11g and earlier there are several alternative ways to limit the number of rows returned. The old, canonical paging query is:

SELECT *
FROM (SELECT a.*, ROWNUM AS rnum
      FROM (YOUR_QUERY_GOES_HERE -- including the order by) a
      WHERE ROWNUM <= MAX_ROW)
WHERE rnum >= MIN_ROW

Here, MIN_ROW is the row number of first row and MAX_ROW is the row number of the last row to return. For example:

SELECT *
FROM (SELECT a.*, ROWNUM AS rnum
      FROM (SELECT last_name FROM employees ORDER BY last_name) a
      WHERE ROWNUM <= 20)
WHERE rnum >= 1

This always has an 'extra' column, here called RNUM.

An alternative and preferred query syntax for Oracle Database 11g uses the analytic ROW_NUMBER() function. For example, to get the 1st to 20th names the query is:

SELECT last_name FROM
(SELECT last_name,
        ROW_NUMBER() OVER (ORDER BY last_name) AS myr
        FROM employees)
WHERE myr BETWEEN 1 and 20

Ensure to use :ref:`bind variables <bind>` for the upper and lower limit values.

Fetching Raw Data

Sometimes python-oracledb may have problems converting data stored in the database to Python strings. This can occur if the data stored in the database does not match the character set defined by the database. The encoding_errors parameter to :meth:`Cursor.var()` permits the data to be returned with some invalid data replaced, but for additional control the parameter bypass_decode can be set to True and python-oracledb will bypass the decode step and return bytes instead of str for data stored in the database as strings. The data can then be examined and corrected as required. This approach should only be used for troubleshooting and correcting invalid data, not for general use!

The following sample demonstrates how to use this feature:

# define output type handler
def return_strings_as_bytes(cursor, metadata):
    if metadata.type_code is oracledb.DB_TYPE_VARCHAR:
        return cursor.var(str, arraysize=cursor.arraysize,
                          bypass_decode=True)

# set output type handler on cursor before fetching data
with connection.cursor() as cursor:
    cursor.outputtypehandler = return_strings_as_bytes
    cursor.execute("select content, charset from SomeTable")
    data = cursor.fetchall()

This will produce output as:

[(b'Fianc\xc3\xa9', b'UTF-8')]

Note that last \xc3\xa9 is é in UTF-8. Since this is valid UTF-8 you can then perform a decode on the data (the part that was bypassed):

value = data[0][0].decode("UTF-8")

This will return the value "Fiancé".

If you want to save b'Fianc\xc3\xa9' into the database directly without using a Python string, you will need to create a variable using :meth:`Cursor.var()` that specifies the type as :data:`~oracledb.DB_TYPE_VARCHAR` (otherwise the value will be treated as :data:`~oracledb.DB_TYPE_RAW`). The following sample demonstrates this:

with oracledb.connect(user="hr", password=userpwd,
                       dsn="dbhost.example.com/orclpdb") as conn:
    with conn.cursor() cursor:
        var = cursor.var(oracledb.DB_TYPE_VARCHAR)
        var.setvalue(0, b"Fianc\xc4\x9b")
        cursor.execute("""
            update SomeTable set
                SomeColumn = :param
            where id = 1""",
            param=var)

Warning

The database will assume that the bytes provided are in the character set expected by the database so only use this for troubleshooting or as directed.

Querying Corrupt Data

If queries fail with the error "codec can't decode byte" when you select data, then:

Check if your :ref:`character set <globalization>` is correct. Review the :ref:`database character sets <findingcharset>`. Check with :ref:`fetching-raw-data`. Note that the encoding used for all character data in python-oracledb is "UTF-8".
Check for corrupt data in the database.

If data really is corrupt, you can pass options to the internal decode() used by python-oracledb to allow it to be selected and prevent the whole query failing. Do this by creating an :ref:`outputtypehandler <outputtypehandlers>` and setting encoding_errors. For example to replace corrupt characters in character columns:

def output_type_handler(cursor, metadata):
    if metadata.type_code is oracledb.DB_TYPE_VARCHAR:
        return cursor.var(metadata.type_code, size,
                          arraysize=cursor.arraysize,
                          encoding_errors="replace")

cursor.outputtypehandler = output_type_handler

cursor.execute("select column1, column2 from SomeTableWithBadData")

Other codec behaviors can be chosen for encoding_errors, see Error Handlers.

INSERT and UPDATE Statements

SQL Data Manipulation Language statements (DML) such as INSERT and UPDATE can easily be executed with python-oracledb. For example:

cursor = connection.cursor()
cursor.execute("insert into MyTable values (:idbv, :nmbv)", [1, "Fredico"])

Do not concatenate or interpolate user data into SQL statements. See :ref:`bind` instead.

See :ref:`txnmgmnt` for best practices on committing and rolling back data changes.

When handling multiple data values, use :meth:`~Cursor.executemany()` for performance. See :ref:`batchstmnt`

Inserting NULLs

Oracle requires a type, even for null values. When you pass the value None, then python-oracledb assumes the type is STRING. If this is not the desired type, you can explicitly set it. For example, to insert a null :ref:`Oracle Spatial SDO_GEOMETRY <spatial>` object:

type_obj = connection.gettype("SDO_GEOMETRY")
cursor = connection.cursor()
cursor.setinputsizes(type_obj)
cursor.execute("insert into sometable values (:1)", [None])

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sql_execution.rst

sql_execution.rst

Executing SQL

SQL Queries

Fetch Methods

Closing Cursors

Query Column Metadata

Fetch Data Types

Changing Fetched Data

Changing Fetched Data Types with Output Type Handlers

Changing Query Results with Outconverters

Changing Query Results with Rowfactories

Fetched Number Precision

Scrollable Cursors

Fetching Oracle Database Objects and Collections

Limiting Rows

Fetching Raw Data

Querying Corrupt Data

INSERT and UPDATE Statements

Inserting NULLs

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sql_execution.rst

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sql_execution.rst

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Executing SQL

SQL Queries

Fetch Methods

Closing Cursors

Query Column Metadata

Fetch Data Types

Changing Fetched Data

Changing Fetched Data Types with Output Type Handlers

Changing Query Results with Outconverters

Changing Query Results with Rowfactories

Fetched Number Precision

Scrollable Cursors

Fetching Oracle Database Objects and Collections

Limiting Rows

Fetching Raw Data

Querying Corrupt Data

INSERT and UPDATE Statements

Inserting NULLs