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        <h1 class="headerTitle">Python and Oracle Database Tutorial: The New Wave of Scripting</h1>
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<h1></h1>

  <h2>Contents</h2>

  <ul>
    <li><a href="#overview" >Overview</a></li>
    <li><a href="#preface" >Setup</a></li>
    <li><a href="#connecting">Connecting to Oracle</a>
      <ul>
        <li>1.1 Creating a basic connection</li>
        <li>1.2 Indentation indicates code structure</li>
        <li>1.3 Executing a query</li>
        <li>1.4 Closing connections</li>
        <li>1.5 Checking versions</li>
        <li>1.6 Using the ConnectParams builder class</li>
        <li>1.7 Checking Connection Health</li>
      </ul>
    </li>
    <li><a href="#pooling">Connection Pooling</a>
      <ul>
        <li>2.1 Connection pooling</li>
        <li>2.2 Connection pool experiments</li>
        <li>2.3 Creating a DRCP Connection</li>
        <li>2.4 Connection pooling and DRCP</li>
        <li>2.5 More DRCP investigation</li>
      </ul>
    </li>
    <li><a href="#fetching">Fetching Data</a>
      <ul>
        <li>3.1 A simple query</li>
        <li>3.2 Using fetchone()</li>
        <li>3.3 Using fetchmany()</li>
        <li>3.4 Tuning with arraysize and prefetchrows</li>
      </ul>
    </li>
    <li><a href="#binding">Binding Data</a>
      <ul>
        <li>4.1 Binding in queries</li>
        <li>4.2 Binding in inserts</li>
        <li>4.3 Batcherrors</li>
      </ul>
    </li>
    <li><a href="#plsql">PL/SQL</a>
      <ul>
        <li>5.1 PL/SQL functions</li>
        <li>5.2 PL/SQL procedures</li>
      </ul>
    </li>
    <li><a href="#handlers">Type Handlers</a>
      <ul>
        <li>6.1 Basic output type handler</li>
        <li>6.2 Output type handlers and variable converters</li>
        <li>6.3 Input type handlers</li>
      </ul>
    </li>
    <li> <a href="#lobs">LOBs</a>
      <ul>
        <li>7.1 Fetching a CLOB using a locator</li>
        <li>7.2 Fetching a CLOB as a string</li>
      </ul>
    </li>
    <li> <a href="#rowfactory">Rowfactory functions</a>
      <ul>
        <li>8.1 Rowfactory for mapping column names</li>
      </ul>
    </li>
    <li><a href="#subclass">Subclassing connections and cursors</a>
      <ul>
        <li>9.1 Subclassing connections</li>
        <li>9.2 Subclassing cursors</li>
      </ul>
    </li>
    <li><a href="#thick">Python-oracledb Thick mode</a>
      <ul>
      <li>10.1 Review the Oracle Client library path</li>
      <li>10.2 Review the configuration files for thick mode</li>
      </ul>
    </li>
    <li><a href="#scrollable">Scrollable cursors</a>
      <ul>
      <li>11.1 Working with scrollable cursors</li>
      </ul>
    </li>
    <li><a href="#bindnamedobj">Binding named objects</a>
      <ul>
      <li>12.1 How to bind named objects</li>
      </ul>
    </li>
    <li><a href="#typehandlers">Input and Output Type Handlers with named objects</a>
      <ul>
      <li>13.1 Input type handlers with named objects</li>
      <li>13.2 Output type handlers with named objects</li>
      </ul>
    </li>
    <li><a href="#aq">Advanced Queuing</a>
      <ul>
        <li>14.1 Message passing with Oracle Advanced Queuing</li>
      </ul>
    </li>
    <li><a href="#soda">Simple Oracle Document Access (SODA)</a>
      <ul>
        <li>15.1 Inserting JSON Documents</li>
        <li>15.2 Searching SODA Documents</li>
      </ul>
    </li>
    <li><a href="#summary" >Summary</a></li>
    <li><a href="#primer" >Appendix: Python Primer</a></li>
    <li><a href="#resources" >Resources</a></li>
</ul>

  <h2><a name="overview">Overview</a></h2>

  <p>This tutorial is a primary guide on using Python with Oracle Database. It contains both beginner and advanced materials. Choose the content that interests you and your skill level. The tutorial has scripts to run and modify, and has suggested solutions.</p>

<p>Python is a popular general purpose dynamic scripting language. The python-oracledb driver provides Python APIs to access Oracle Database. It is an upgrade for the hugely popular <a href="https://oracle.github.io/python-cx_Oracle/">cx_Oracle</a> interface.
</p>


  <p>If you are new to Python, review the <a href="#primer">Appendix: Python Primer</a> to gain an understanding of the language. </p>
<p>When you have finished this tutorial, we recommend reviewing the <a href="http://python-oracledb.readthedocs.org/en/latest/index.html" >python-oracledb documentation</a>.</p>

  <p>The original copy of these instructions that you are reading is <a
  href="https://oracle.github.io/python-oracledb/samples/tutorial/Python-and-Oracle-Database-The-New-Wave-of-Scripting.html"
  >here</a>.</p>

<h3><a name="architecture">Python-oracledb Architecture</a></h3>

<p>The python-oracledb driver enables access to Oracle Database using either
one of two modes.  Both modes have comprehensive functionality supporting the
Python Database API v2.0 Specification.  By default, python-oracledb runs in a
&quot;thin&quot; mode, which connects directly to Oracle Database.  This mode
does not need Oracle Client libraries. However, some additional features are
available when python-oracledb uses them.  Python-oracledb applications that
load the Oracle Client libraries via an application script runtime option are
said to be in &quot;thick&quot; mode.  This tutorial has examples in both
modes.</p>

<p><img src="resources/python-oracledb-arch.svg" alt="Python python-oracledb architecture" width=800/></p>
<p>The database can be on the same machine as Python, or it can be remote.</p>
<h2><a name="preface">Setup</a></h2>

  <ul>

    <li><h4 id="installsw">Install software</h4>

      <p>Install Python 3 if not already available.  It can be obtained from
      your operating system package library or from <a
      href="https://www.python.org/">python.org</a>.  On Windows, use Python 3.7
      or later.  On macOS, use Python 3.7 or later.  On Linux, use Python 3.6 or
      later.</p>

      <p>Install <a
      href="https://pypi.org/project/oracledb/">python-oracledb</a> with
      a command like <code>pip install oracledb --upgrade</code></p>

      <p>Ensure you can access an Oracle Database.</p>

<!--
      <p>To get going, follow either of the quick start instructions:</p>

      <ul>
        <li><p><a href="https://www.oracle.com/database/technologies/appdev/python/quickstartpythononprem.html" >Quick Start: Developing Python Applications for Oracle Database (On-Premises)</a></p></li>

        <li><p><a
          href="https://www.oracle.com/database/technologies/appdev/python/quickstartpython.html"
          >Quick Start: Developing Python Applications for Oracle Autonomous Database</a></p></li>
      </ul>
-->
    </li>

      <li>
        <h4 id="downloadscripts">Download the tutorial scripts</h4>

        <p>The Python scripts used in this example are in the <a href="https://github.com/oracle/python-oracledb/tree/main/samples/tutorial" >python-oracledb GitHub repository</a>.</p>

        <p>Download a zip file of the repository from <a href="https://github.com/oracle/python-oracledb/archive/main.zip" >here</a> and unzip it. Alternatively you can use 'git' to clone the repository.</p>
<p><code>git clone https://github.com/oracle/python-oracledb.git</code></p>

        <p>The <code>samples/tutorial</code> directory has scripts to run and modify. The <code>samples/tutorial/solutions</code> directory has scripts with suggested code changes. The <code>samples/tutorial/sql</code> directory has all the SQL scripts used by the Python files to create database tables and other objects.</p>

      </li>
      <li>
          <h4>Review the privileged database credentials used for creating the schema</h4>

          <p>Review <code>db_config_sys.py</code> in the <code>tutorial</code> directory. This file is included in other Python files for creating and dropping the tutorial user.</p>

          <p>Edit <code>db_config_sys.py</code> file and change the default values to match the system connection information for your environment.  Alternatively, you can set the given environment variables in your terminal window. For example, the default username is "<em>SYSTEM</em>" unless the environment variable "<em>PYTHON_SYSUSER</em>" contains a different username. The default system connection string is for the "<em>orclpdb</em>" database service on the same machine as Python. In Python Database API terminology, the connection string parameter is called the "data source name", or "dsn".  Using environment variables is convenient because you will not be asked to re-enter the password when you run scripts:</p>

<pre>
user = os.environ.get("PYTHON_SYSUSER", "SYSTEM")

dsn = os.environ.get("PYTHON_SYS_CONNECT_STRING", "localhost/orclpdb")

pw = os.environ.get("PYTHON_SYSPASSWORD")
if pw is None:
    pw = getpass.getpass("Enter password for %s: " % user)
</pre>

          <p>Substitute the admin values for your environment. If you are using Oracle Autonomous Database (ADB), use the <em>ADMIN</em> user instead of <em>SYSTEM</em>. The tutorial instructions may need adjusting, depending on how you have set up your environment.</p>
    </li>

      <li><h4 id="createdbuser">Create a database user</h4>

          <p>If you have an existing user, you may be able to use it for most examples (some examples may require extra permissions).</p>

          <p>If you need to create a new user  for this tutorial, review the grants created in <code>samples/tutorial/sql/create_user.sql</code> by opening it in your favorite text editor. Then open a terminal window and run  <code>create_user.py</code>  to execute the <code>create_user.sql</code> script and create the sample user. This tutorial uses the name <code>pythondemo</code>:</p>
<pre>
<strong>python create_user.py</strong></pre>

<p>The example above connects as the <em>SYSTEM (or ADMIN</em> for ADB<em>) </em> user using <code>db_config_sys</code> file discussed in the earlier section.  The connection string is "<em>localhost/orclpdb</em>", meaning use the database service "<em>orclpdb</em>" running on localhost (the computer you are running your Python scripts on).</p>
<p>If it runs successfully, you will see something similar below:</p>
<pre>Enter password for SYSTEM:
Enter password for pythondemo:
Creating user...
SQL File Name:  D:\python-oracledb\samples\tutorial\sql\create_user.sql
Done.</pre>
<p> The new user <em>pythondemo</em> is created.</p>
<p>When the tutorial is finished, ensure that all the database sessions connected to the tutorial user <em>pythondemo</em> are closed and then run <code>drop_user.py</code> to remove the tutorial user.</p>
      </li>

    <li>
      <h4 id="installsampleenv">Install the tables and other database objects for the tutorial</h4>

          <p>Once you have a database user, then you can create the key tutorial tables and database objects for the tutorial by running <code>setup_tutorial.py</code> (the environment setup file), using your values for the tutorial username, password and connection string:</p>

<pre>
<strong>python setup_tutorial.py</strong></pre>
<p>On successful completion of the run, You will see something like:</p>
<pre>Setting up the sample tables and other DB objects for the tutorial...
SQL File Name:  D:\python-oracledb\samples\tutorial\sql\setup_tutorial.sql
Done.</pre>
<p>This will call the <code>setup_tutorial.sql</code> file from <code>tutorials/sql</code> directory to setup some sample tables and  database objects required for running the examples in the tutorial.</p>
    </li>

     <li>
          <h4>Review the connection credentials used by the tutorial scripts</h4>

          <p>Review <code>db_config.py</code> (thin mode), and <code>db_config.sql</code> files in the <code>tutorial</code> and <code>tutorial/sql </code>directories respectively. These are included in other Python and SQL files for setting up the database connection.</p>

          <p>Edit <code>db_config.py</code> file and change the default values to match the connection information for your environment.  Alternatively, you can set the given environment variables in your terminal window. For example, the default username is "<em>pythondemo</em>" unless the environment variable "<em>PYTHON_USER</em>" contains a different username. The default connection string is for the '<em>orclpdb</em>' database service on the same machine as Python. In Python Database API terminology, the connection string parameter is called the "data source name", or "dsn".  Using environment variables is convenient because you will not be asked to re-enter the password when you run scripts:</p>

<pre>
user = os.environ.get("PYTHON_USER", "pythondemo")

dsn = os.environ.get("PYTHON_CONNECT_STRING", "localhost/orclpdb")

pw = os.environ.get("PYTHON_PASSWORD")
if pw is None:
    pw = getpass.getpass("Enter password for %s: " % user)
</pre>

<p>Also, change the database username and connection string in the SQL configuration file <code>db_config.sql</code> based on your environment settings:</p>

<pre>
-- Default database username
def user = "<strong>pythondemo</strong>"

-- Default database connection string
def connect_string = "<strong>localhost/orclpdb</strong>"

-- Prompt for the password
accept pw char prompt 'Enter database password for &amp;user: ' hide
</pre>

          <p>The tutorial instructions may need adjusting, depending on how you have set up your environment.</p>
     </li>

        <li><h4> Runtime Naming</h4>

          <p>At runtime, the module name of the python-oracledb package is <code>oracledb</code>:</p>

        <pre>import oracledb</pre></li>

         <li><h4>Python-oracledb defaults</h4>
        <p>A singleton <code>oracledb.defaults</code> contains attributes that can be used to adjust the default behavior of python-oracledb. Attributes not supported in a mode (<em>thin</em> or <em>thick</em>) will be ignored in that mode.</p>
        <p>Open <code>defaults.py</code> in an editor. This will look like:</p>
        <pre>import oracledb

print("Default array size:", <strong>oracledb.defaults.arraysize</strong>)</pre>
Run the script:
<pre><strong>python defaults.py</strong></pre>
It displays:
<pre>Default array size: 100</pre>
<p> This gives the default array size tuning parameter that will be useful in Section 3.4 of this tutorial.</p>
<p>The default values can also be edited using the <code>defaults</code> attribute. All the default values that can be set and read with <code>defaults</code> attribute are available in the <a href="http://python-oracledb.readthedocs.io/en/latest/index.html">python-oracledb documentation</a>.</p></li>
</ul>

<h2><a name="connecting">1. Connecting to Oracle</a></h2>

<p>You can connect from Python to a local, remote or cloud Oracle Database. <em>Documentation link for further reading: <a
href="https://python-oracledb.readthedocs.io/en/latest/user_guide/connection_handling.html"
>Connecting to Oracle Database</a></em>.</p>

      <ul>
        <li>
          <h4>1.1 Creating a basic connection</h4>
          <p>Review the code contained in <code>connect.py</code> :</p>
          <pre>
import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)
print("Database version:", con.version)
</pre>

          <p>The python-oracledb module is imported to provide the API for accessing the Oracle database. Many inbuilt and third-party modules can be included in Python scripts this way.</p>

          <p> The username, the password and the connection string that you configured in the
<code>db_config.py</code> module is passed to the <code>connect()</code> method. By default, Oracle's Easy Connect connection string syntax is used. It consists of the hostname of your machine, <code>localhost</code>, and the database service name <code>orclpdb</code>. (In Python Database API terminology, the connection string parameter is called the "data source name", or "dsn").</p>

          <p>Open a command terminal and change to the <code>tutorial</code> directory:</p>

          <pre><strong>cd samples/tutorial</strong></pre>

          <p>Run the Python script:</p>

          <pre><strong>python connect.py</strong></pre>

          <p>The version number of the database should be displayed. An exception is raised if the connection fails. Adjust the username, password, or connection string parameters to invalid values to see the exception.</p>

          <p>Python-oracledb also supports "<em>external authentication</em>", which allows connections without needing usernames and passwords to be embedded in the code. Authentication would then be performed by, for
 example, LDAP or Oracle Wallets.</p>

        </li>

        <li>
          <h4>1.2 Indentation indicates code structure</h4>

          <p>In Python, there are no statement terminators, begin/end keywords, or braces to indicate code blocks.</p>

          <p>Open <code>connect.py</code> in an editor. Indent the print statement with some spaces:</p>

          <pre>
import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)
  print("Database version:", con.version)
</pre>

          <p>Save the script and run it again:</p>

          <pre><strong>python connect.py</strong> </pre>

          <p>This raises an exception about the indentation. The number of spaces or tabs must be consistent in each block; otherwise, the Python interpreter will either raise an exception or execute code unexpectedly.  </p>

          <p>Python may not always be able to identify accidental from deliberate indentation. <em>Check if your indentation is correct before running each example.  Make sure to indent all statement blocks equally.</em> <b>Note that the sample files use spaces, not tabs.</b> </p>

        </li>

        <li>
          <h4>1.3 Executing a query</h4>

          <p>Open <code>query.py</code> in an editor.  It looks like:</p>

          <pre>
import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)
</pre>

   <p>Edit the file and add the code shown in bold below:</p>

<pre>
import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)

<strong>cur = con.cursor()
cur.execute("select * from dept order by deptno")
res = cur.fetchall()
for row in res:
    print(row)</strong>
</pre>

          <p>Make sure the <code>print(row)</code> line is indented. This tutorial uses spaces, not tabs.</p>

          <p>The code executes a query and fetches all data.</p>

          <p>Save the file and run it:</p>

          <pre><strong>python query.py</strong></pre>

          <p>In each loop iteration, a new row is stored in
          <code>row</code> variable as a Python "tuple" and is displayed.</p>

          <p>Fetching data is described further in <a href="#fetching" >Section 3</a>. </p>
        </li>

        <li>
          <h4>1.4 Closing connections</h4>

          <p>Connections and other resources used by python-oracledb will automatically be closed at the end of scope.  This is a common programming style that takes care of the correct order of resource closure.</p>

          <p>Resources can also be explicitly closed to free up database resources if they are no longer needed.  This is strongly recommended in blocks of code that remain active for some time.</p>

          <p>Open <code>query.py</code> in an editor and add calls to close the cursor and connection like:</p>

          <pre>
import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)

cur = con.cursor()
cur.execute("select * from dept order by deptno")
res = cur.fetchall()
for row in res:
    print(row)

<strong>cur.close()</strong>
<strong>con.close()</strong>
</pre>

          <p>Running the script completes without error:</p>

          <pre><strong>python query.py</strong></pre>

          <p>If you swap the order of the two <code>close()</code> calls you will see an error.</p>
        </li>

        <li>
          <h4>1.5 Checking versions</h4>

          <p>Review the code contained in <code>versions.py</code>:</p>

          <pre>
import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)

print(oracledb.__version__) # two underscores before and after the version</pre>

          <p>Run the script:</p>

          <pre><strong>python versions.py</strong></pre>

          <p>This gives the version of the python-oracledb interface.</p>

          <p>Edit the file to print the version of the database, and the Oracle client libraries used by python-oracledb:</p>

          <pre>
import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)

print(oracledb.__version__)
<strong>print("Database version:", con.version)</strong>
</pre>

          <p>When the script is run, it will display:</p>

          <pre>
1.0.0
Database version: 19.3.0.0.0</pre>

          <p>Any python-oracledb installation can connect to older and newer
          Oracle Database versions.  By checking the Oracle Database
          version numbers, the application can make use of
          the best Oracle features available.</p>

        </li>
        <li>
        <h4>1.6 Using the ConnectParams builder class</h4>
        <p>
        A connection property builder function <code>oracledb.ConnectParams()</code> has been added. It returns a new <em>ConnectParams</em> object. The object can be passed to <code>oracledb.connect()</code> or
<code>oracledb.create_pool()</code>.</p>

        <p>Open <code>connect_params2.py</code> in a text editor. It looks like:</p>
        <pre>import oracledb
import db_config

params = oracledb.ConnectParams(host="localhost", port=1521, service_name="orclpdb")
con = oracledb.connect(user=db_config.user, password=db_config.pw, params=params)
print("Database version:", con.version)</pre>
        When the script is run (<code><strong>python connect_params2.py</strong></code>), it will display:
        <pre>Database version: 19.3.0.0.</pre>
        <p>
        The use of <code>ConnectParams()</code> is optional. Users can continue to use previous approaches. The list of parameters for the <code>ConnectParams</code> class is available in the python-oracledb documentation.</p>
        <p>Notes:</p>
        <ul>
          <li>If the <code>params</code> parameter is specified and keyword parameters are also specified, then the <code>params</code> parameter is updated with the values from the keyword parameters before being used to create the connection. </li>
          <li>If the <code>dsn</code> parameter is specified and the <code>params</code> parameter is specified, then the <code>params</code> parameter is updated with the contents of the <code>dsn</code> parameter before being used to create the connection.</li>
       </ul>
     </li>
     <li>
     <h4>1.7 Checking  Connection Health</h4>
     <p>The function <code>Connection.is_healthy()</code> checks the usability of a database connection locally. This function returns a boolean value indicating the health status of a connection.</p>
<p>Connections may become unusable in several cases, such as if the network socket is broken, if an Oracle error indicates the connection is unusable or after receiving a planned down notification from the database.
This function is best used before starting a new database request on an existing standalone connection. Pooled connections internally perform this check before returning a connection to the application. If this function returns <code>False</code>, the connection should be not be used by the application and a new connection should be established instead.</p>
<p>Open <code>connect_health.py</code> in a text editor. It looks like:</p>
       <pre>import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)
if con.is_healthy():
    print("Healthy connection!")
else:
    print("Unusable connection. Please check the database and network settings.")</pre>
<p>When the script is run (<code><strong>python connect_health.py</strong></code>), it will display (when the connection is OK):</p>
        <pre>Healthy Connection!</pre>
<p>To fully check a connection's health, use <code>Connection.ping()</code> which performs a round-trip to the database.</p></li>
   </ul>
    <h2><a name="pooling">2. Connection Pooling</a></h2>

<p>Connection pooling is important for performance  when multi-threaded applications frequently connect and disconnect from the database. Pooling also gives the best support for Oracle's High Availability (HA) features.
<em>Documentation link for further reading: <a
      href="https://python-oracledb.readthedocs.io/en/latest/user_guide/connection_handling.html#connection-pooling">Connection Pooling</a></em>.</p>

      <ul>
        <li> <h4>2.1 Connection pooling</h4>

      <p>Review the code contained in <code>connect_pool.py</code>:</p>
<pre>
import oracledb
import threading
import db_config

pool = oracledb.<strong>create_pool</strong>(user=db_config.user, password=db_config.pw, dsn=db_config.dsn,
                            min=2, max=5, increment=1, getmode=oracledb.POOL_GETMODE_WAIT)

def Query():
    con = pool.<strong>acquire</strong>()
    cur = con.cursor()
    for i in range(4):
        cur.execute("select myseq.nextval from dual")
        seqval, = cur.fetchone()
        print("Thread", threading.current_thread().name, "fetched sequence =", seqval)

thread1 = threading.Thread(name='#1', target=Query)
thread1.start()

thread2 = threading.Thread(name='#2', target=Query)
thread2.start()

thread1.join()
thread2.join()

print("All done!")
</pre>

          <p>The <code>create_pool()</code> function creates a pool of Oracle connections for the user.  Connections in the pool can be used by python-oracledb by calling <code>pool.acquire()</code>.
          The initial pool size is 2 connections.  The maximum size is 5 connections. When the pool needs to grow, then a single new connection will be created at a time based on the <code>increment</code> parameter. The pool can shrink back to the minimum size of 2 when the connections are no longer in use.</p>

          <p>The <code>def Query():</code> line creates a method that is called by each thread.</p>

          <p>In the <code>Query</code> method, the <code>pool.acquire()</code> call gets one connection from the pool (as long as less than 5 are already in use).  This connection is used in a loop of 4 iterations to query the sequence <code>myseq</code>. At the end of the method, python-oracledb will automatically close the cursor and release the connection back to the pool for reuse.</p>

          <p>The <code>seqval, = cur.fetchone()</code> line fetches a row and puts the single value contained in the result tuple into the variable <code>seqval</code>. Without the comma, the value in <code>seqval</code> would be a tuple like
          "<code>(1,)</code>".</p>

          <p>Two threads are created, each invoking the
          <code>Query()</code> method.</p>

          <p>In a command terminal, run:</p>

          <pre><strong>python connect_pool.py</strong></pre>

<p>The output shows the interleaved query results as each thread fetches values independently.  The order of interleaving may vary from run to run.</p>

</li>

    <li>
      <h4>2.2 Connection pool experiments</h4>


<p>Review <code>connect_pool2.py</code>, which has a loop for the number of threads, each iteration invoking the <code>Query()</code> method:</p>

<pre>
import oracledb
import threading
import db_config

pool = oracledb.create_pool(user=db_config.user, password=db_config.pw, dsn=db_config.dsn,
                            min=2, max=5, increment=1, getmode=oracledb.POOL_GETMODE_WAIT)

def Query():
    con = pool.acquire()
    cur = con.cursor()
    for i in range(4):
        cur.execute("select myseq.nextval from dual")
        seqval, = cur.fetchone()
        print("Thread", threading.current_thread().name, "fetched sequence =", seqval)

<strong>numberOfThreads = 2
threadArray = []

for i in range(numberOfThreads):
    thread = threading.Thread(name='#' + str(i), target=Query)
    threadArray.append(thread)
    thread.start()

for t in threadArray:
    t.join()</strong>

print("All done!")
</pre>

<p>In a command terminal, run:</p>

<pre><strong>python connect_pool2.py</strong></pre>

<p>Experiment with different values of the pool parameters and
<code>numberOfThreads</code>.  Larger initial pool sizes will make the pool creation slower, but the connections will be available immediately when needed.
</p>

<p>Try changing <code>getmode</code> to
<code>oracledb.POOL_GETMODE_WAIT</code>.  When <code>numberOfThreads</code>
exceeds the maximum size of the pool, the <code>acquire()</code> call will now
generate an error such as "<em>ORA-24459: OCISessionGet() timed out waiting for pool to create new connections</em>".  </p>

<p>Pool configurations where <code>min</code> is the same as
<code>max</code> (and <code>increment = 0</code>) are often
recommended as a best practice for the optimum performance. Pools with such configurations are referred to as &quot;<em>static pools</em>&quot;. This configuration avoids connection storms on the database server.</p>

</li>

    <li>
      <h4>2.3 Creating a DRCP Connection</h4>

  <p>Database Resident Connection Pooling allows multiple Python processes on multiple machines to share a small pool of database server processes.</p>

  <p>Below left is a diagram without DRCP. Every application standalone connection (or python-oracledb connection-pool connection) has its own database server process. Standalone application <code>connect()</code> and close calls require the expensive create and destroy of those database server processes.
  Python-oracledb connection pools reduce these costs by keeping database server processes open, but every python-oracledb connection pool will require its own set of database server processes, even if they are not doing database work: these idle server processes consume database host resources. Below right is a diagram with DRCP.  Scripts and Python processes can share database servers from a pre-created pool of servers and return them when they are not in use.
  </p>

  <table cellspacing="0" cellpadding="30" border="0" >
    <tr>
      <td>
        <img width="400" src="resources/python_nopool.png" alt="Picture of 3-tier application architecture without DRCP showing connections from multiple application processes each going to a server process in the database tier" />
        <div align="center"><p><strong>Without DRCP</strong></p></div>
      </td>
      <td>
        <img width="400" src="resources/python_pool.png" alt="Picture of 3-tier application architecture with DRCP showing connections from multiple application processes going to a pool of server processes in the database tier" />
        <div align="center"><p><strong>With DRCP</strong></p></div>
      </td>
    </tr>
  </table>

  <p>DRCP is useful when the database host machine does not have enough memory to handle the number of database server processes required. If DRCP is enabled, it is best used in conjunction with python-oracledb's connection pooling.
  However, the default 'dedicated' server process model is generally recommended if the database host memory is large enough. This can be with or without a python-oracledb connection pool, depending on the connection rate.</p>

  <p>Batch scripts doing long running jobs should generally use dedicated connections. Both dedicated and DRCP servers can be used together in the same application or database.</p>
  <h4 id="startdrcp">Start the Database Resident Connection Pool (DRCP)</h4>

    <p name="startdrcp">If you are running a local or remote Oracle Database (that is not an ADB), start the DRCP pool. Note that the DRCP pool is  started in an Oracle Autonomous Database by default.</p>

   <p>Run SQL*Plus with SYSDBA privileges, for example:</p>

<pre>
sqlplus -l sys/syspassword@localhost/orclcdb as sysdba
</pre>

          <p>and execute the command:</p>

<pre>
execute dbms_connection_pool.start_pool()
</pre>

   <p>Note: If you are using Oracle Database 21c,</p>
          <p>Run <code>show parameter enable_per_pdb_drcp</code> in SQL*Plus.</p>
          <p>If this shows TRUE,</p>
          <p>then you will  need to run the <code>execute</code> command in a pluggable database, not a container database.</p>
    <h4>Connect to the Oracle Database through DRCP</h4>
  <p>Review the code contained in <code>connect_drcp.py</code>:</p>

  <pre>
import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn + "<strong>:pooled</strong>",
                       cclass=&quot;PYTHONDEMO&quot;, purity=oracledb.PURITY_SELF)
print("Database version:", con.version)
</pre>

  <p> This is similar to <code>connect.py</code> but
  &quot;<code>:pooled</code>&quot; is appended to the connection string, telling
  the database to use a pooled server. A Connection Class "PYTHONDEMO" is also passed into the <code>connect()</code> method to allow grouping of database servers to applications. Note that with Autonomous Database, the connection string has a different form, see the <a
  href="https://docs.oracle.com/en/cloud/paas/autonomous-database/adbsa/connect-drcp.html#GUID-E1337EC6-4A78-4199-84F0-A2739055F3FA"
  >ADB documentation</a>. </p>

  <p> The &quot;purity&quot; of the connection is defined as the <code>PURITY_SELF</code> constant, meaning the session state (such as the default date format) might be retained between connection calls, giving performance benefits. Session information will be discarded if a pooled server is later reused by an  application with a different connection class name.</p>

  <p>Applications that should never share session information should use a different connection class and/or use <code>PURITY_NEW</code> to force creation of a new session. This reduces overall scalability but prevents applications from misusing the session information.  The default purity for connections created with <code>connect()</code> is <code>PURITY_NEW</code>.</p>

  <p>Run <code>connect_drcp.py </code>in a terminal window.</p>

  <pre><strong>python connect_drcp.py</strong></pre>

  <p>The output is simply the version of the database.</p>

  </li>

    <li>
      <h4>2.4 Connection pooling and DRCP</h4>

      <p>DRCP works well with python-oracledb's connection pooling.  The
      default purity for pooled connections is <code>PURITY_SELF</code>.</p>

  <p>Edit <code>connect_pool2.py</code>, reset any changed pool options, and modify it to use DRCP:</p>
  <pre>
import oracledb
import threading
import db_config

pool = oracledb.create_pool(user=db_config.user, password=db_config.pw, dsn=db_config.dsn <strong>+ ":pooled"</strong>,
                            min=2, max=5, increment=1, getmode=oracledb.POOL_GETMODE_WAIT,
                            <strong>cclass="PYTHONDEMO", purity=oracledb.PURITY_SELF</strong>)

def Query():
    con = pool.acquire()
    cur = conn.cursor()
    for i in range(4):
        cur.execute("select myseq.nextval from dual")
        seqval, = cur.fetchone()
        print("Thread", threading.current_thread().name, "fetched sequence =", seqval)

numberOfThreads = 2
threadArray = []

for i in range(numberOfThreads):
    thread = threading.Thread(name='#' + str(i), target=Query)
    threadArray.append(thread)
    thread.start()

for t in threadArray:
    t.join()

print("All done!")
</pre>

      <p>The script logic does not need to be changed to benefit from
      DRCP connection pooling.</p>

      <p>Run the script:</p>

      <pre><strong>python connect_pool2.py</strong></pre>

      <p>Optionally, you can run <strong>drcp_query.py</strong> to check the DRCP pool statistics.</p>

      <pre><strong>python drcp_query.py</strong></pre>

      <p>This will prompt for the SYSTEM (or ADMIN user), the password, and the database connection string. For running the file, you will need to connect to the container database in Oracle Database v19 or lower.  From Oracle Database 21c onwards, you can enable DRCP in pluggable databases.</p>

      <p>Note that with ADB, this view does not contain rows, so running this script is not useful. For other Oracle Databases, the script shows the number of connection requests made to the pool since the database was started ("NUM_REQUESTS"), how many of those reused a pooled server's session ("NUM_HITS"), and how many had to create new sessions ("NUM_MISSES"). Typically the goal is a low number of misses.</p>
      <p> If the file is run successfully, you should see something like </p>
      <pre>Looking at DRCP Pool stats...

(CCLASS_NAME, NUM_REQUESTS, NUM_HITS, NUM_MISSES)
-------------------------------------------------
('PYTHONDEMO.SHARED', 5, 0, 5)
('PYTHONDEMO.PYTHONDEMO', 4, 2, 2)
('SYSTEM.SHARED', 11, 0, 11)
Done.</pre>
      <p>To see the pool configuration, you can query DBA_CPOOL_INFO.</p>
    </li>

    <li>
      <h4>2.5 More DRCP investigation</h4>

      <p>To further explore the behaviors of python-oracledb connection pooling and DRCP pooling, you could try changing the purity to <code>oracledb.PURITY_NEW</code> to see the effect on the DRCP NUM_MISSES statistic.</p>

      <p>Another experiement is to include the <code>time</code> module at the file
      top:</p>

      <pre>
import time</pre>

      <p>and add calls to <code>time.sleep(1)</code> in the code, for
      example in the query loop.  Then look at the way the threads execute.  Use
      <code>drcp_query.sql</code> to monitor the pool's behavior.</p>

    </li>
  </ul>

  <h2><a name="fetching">3. Fetching Data</a> </h2>


  <p>Executing SELECT queries is the primary way to get data from Oracle Database. <em>Documentation link for further reading: <a
  href="https://python-oracledb.readthedocs.io/en/latest/user_guide/sql_execution.html"
  >SQL Queries</a></em>.</p>

  <ul>
  <li><h4>3.1 A simple query</h4>

  <p>There are several functions you can use to query an Oracle database, but the basics of querying are always the same:</p>

  <p>1. Execute the statement.<br />
  2. Bind data values (optional).<br />
  3. Fetch the results from the database.</p>

    <p>Review the code contained in <code>query2.py</code>:</p>

<pre>
import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)

cur = con.cursor()
cur.execute("select * from dept order by deptno")
for deptno, dname, loc in cur:
    print("Department number: ", deptno)
    print("Department name: ", dname)
    print("Department location:", loc)
</pre>

    <p>The <code>cursor()</code> method opens a cursor for statements to use.</p>

    <p>The <code>execute()</code> method parses and executes the statement.</p>

    <p>The loop fetches each row from the cursor and unpacks the returned
    tuple into the variables <code>deptno</code>, <code>dname</code>,
    <code>loc</code>, which are then printed.</p>

    <p>Run the script in a terminal window:</p>

    <pre><strong>python query2.py</strong></pre>

    <p>The output is:</p>

    <pre>Department number:  10
Department name:  ACCOUNTING
Department location: NEW YORK
Department number:  20
Department name:  RESEARCH
Department location: DALLAS
Department number:  30
Department name:  SALES
Department location: CHICAGO
Department number:  40
Department name:  OPERATIONS
Department location: BOSTON</pre>

  </li>

<li><h4>3.2 Using fetchone()</h4>

  <p>When the number of rows is large, the <code>fetchall()</code> call may use too much memory.</p>

  <p>Review the code contained in <code>query_one.py</code>:</p>

<pre>
import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, password=db_config.dsn)
cur = con.cursor()

cur.execute("select * from dept order by deptno")
row = cur.fetchone()
print(row)

row = cur.fetchone()
print(row)
</pre>

  <p>This uses the <code>fetchone()</code> method to return just a single row as a
  tuple. When called multiple time, consecutive rows are returned:</p>

  <p>Run the script in a terminal window:</p>

  <pre><strong>python query_one.py</strong></pre>

  <p>The first two rows of the table are printed.</p>

</li>

<li><h4>3.3 Using fetchmany()</h4>

  <p>Review the code contained in <code>query_many.py</code>:</p>

  <pre>
import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)
cur = con.cursor()

cur.execute("select * from dept order by deptno")
num_rows =  3
res = cur.fetchmany(num_rows)
print(res)
</pre>

  <p>The <code>fetchmany()</code> method returns a list of tuples. By default the maximum number of rows that can be returned is specified by the cursor attribute <code>arraysize</code> (which defaults to 100).  Here the <code>numRows</code> parameter specifies that three rows should be returned.</p>

  <p>Run the script in a terminal window:</p>

  <pre><strong>python query_many.py</strong></pre>

  <p>The first three rows of the table are returned as a list
  (Python's name for an array) of tuples.</p>

  <p>You can access elements of the lists by position indexes.  To see this,
  edit the file and add:</p>

  <pre>
<strong>print(res[0])</strong>    # first row
<strong>print(res[0][1])</strong> # second element of first row
</pre>

  </li>
  <li><h4>3.4 Tuning with arraysize and prefetchrows</h4>

  <p>This section demonstrates a way to improve query performance by increasing the number of rows returned in each batch from Oracle to the Python program.</p>

  <p>Row prefetching and array fetching are internal buffering techniques to reduce round-trips to the database. The difference is the code layer that is doing the buffering, and when the buffering occurs.</p>

  <p>The <a href="#installsampleenv">environment setup file</a> has already created the <em>bigtab</em> table with a large number of rows (to be used by the <code>query_arraysize.py</code> file) by internally running the sql script below:</p>
  <pre>create table bigtab (mycol varchar2(20));

begin
 for i in 1..20000
 loop
  insert into bigtab (mycol) values (dbms_random.string('A',20));
 end loop;
end;</pre>
  <p>The setup file has also inserted around 20000 string values in the <em>bigtab</em> table.</p>


    <p>Review the code contained in <code>query_arraysize.py</code>:</p>

<pre>
import oracledb
import time
import db_config

con = oracledb.connect(name=db_config.user, password=db_config.pw, dsn=db_config.dsn)

start = time.time()

cur = con.cursor()
cur.prefetchrows = 100
cur.arraysize = 100
cur.execute("select * from bigtab")
res = cur.fetchall()
# print(res)  # uncomment to display the query results

elapsed = (time.time() - start)
print(elapsed, "seconds")
</pre>

    <p>This uses the 'time' module to measure elapsed time of the query. The <em>prefetchrows</em> and <em>arraysize</em> values are 100. This causes batches of 100 records at a time to be returned from the database to a cache in Python.
    These values can be tuned to reduce the number of &quot;round-trips&quot;
    made to the database, often reducing network load and reducing the number of context switches on the database server. The <code>fetchone()</code>,
    <code>fetchmany()</code> and <code>fetchall()</code> methods will read from the cache before requesting more data from the database.</p>

    <p>In a terminal window, run:</p>

    <pre><strong>python query_arraysize.py</strong></pre>

    <p>Rerun a few times to see the average times.</p>

    <p>Experiment with different prefetchrows and arraysize values.  For example, edit <code>query_arraysize.py</code> and change the arraysize
    to:</p>

    <pre>cur.arraysize = <strong>2000</strong></pre>

    <p>Rerun the script to compare the performance of different
    arraysize settings.</p>

    <p>In general, larger array sizes improve performance.  Depending on how fast your system is, you may need to use different values than those given here to see a meaningful time difference.</p>

    <p>There is a time/space tradeoff for increasing the values. Larger values will require more memory in Python for buffering the records.</p>

    <p>If you know the query returns a fixed number of rows, for example, 20 rows, then set arraysize to 20 and prefetchrows to 21.  The addition of one extra row for prefetchrows prevents a round-trip to check for end-of-fetch. The statement execution and fetch will take a total of one round-trip.  This minimizes the load on the database.</p>

    <p>If you know a query only returns a few records,
    decrease the arraysize from the default to reduce memory usage.</p>
  </li>
</ul>

<h2><a name="binding">4. Binding Data</a></h2>

  <p>Bind variables enable you to re-execute statements with new data values
  without the overhead of re-parsing the statement.  Binding improves code reusability, improves application scalability, and can reduce the risk of SQL injection attacks. Using bind variables is strongly recommended.
<em>Documentation link for further reading: <a
  href="https://python-oracledb.readthedocs.io/en/latest/user_guide/bind.html" >Using Bind Variables</a></em>.</p>

  <ul>

    <li><h4>4.1 Binding in queries</h4>

  <p>Review the code contained in <code>bind_query.py</code>:</p>

<pre>
import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)
cur = con.cursor()

sql = "select * from dept where deptno = :id order by deptno"

cur.execute(sql, id=20)
res = cur.fetchall()
print(res)

cur.execute(sql, id=10)
res = cur.fetchall()
print(res)
</pre>

      <p>The statement contains a bind variable "<code>:id</code>" placeholder.
      The statement is executed twice with different values for the
      <code>WHERE</code> clause.</p>

      <p>From a terminal window, run:</p>

      <pre><strong>python bind_query.py</strong></pre>

      <p>The output shows the details for the two departments.</p>

      <p>An arbitrary number of named arguments can be used in an
      <code>execute()</code> call.  Each argument name must match a bind
      variable name.  Alternatively, instead of passing multiple arguments you
      could pass a second argument to <code>execute()</code> that is a sequence
      or a dictionary.  Later examples show these syntaxes.</p>

      <p>To bind a database NULL, use the Python value <code>None</code>.</p>

      <p>python-oracledb uses a cache of executed statements.  As long as the statement you pass to <code>execute()</code> is in that cache, you can use different bind values and still avoid a full statement parse.  The statement cache size is configurable for each connection. To see the default statement cache size, edit <code>bind_query.py</code> and add a line at the end:</p>

<pre>
print(con.stmtcachesize)
</pre>

      <p>Re-run the file.</p>

      <p> You would set the statement cache size to the
      number of unique statements commonly executed in your applications.</p>

    </li>

    <li><h4>4.2 Binding in inserts</h4>

  <p>The <a href="#installsampleenv">environment setup file</a> has already created the <em>mytab</em> table (to be used by the <code>bind_insert.py</code> file) by internally running the sql script below:</p>
  <pre>create table mytab (id number, data varchar2(20), constraint my_pk primary key (id))</pre>
  <p>Now, review the code contained in <code>bind_insert.py</code>:</p>

<pre>
import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)
cur = con.cursor()

rows = [ (1, &quot;First&quot; ), (2, &quot;Second&quot; ),
         (3, &quot;Third&quot; ), (4, &quot;Fourth&quot; ),
         (5, &quot;Fifth&quot; ), (6, &quot;Sixth&quot; ),
         (7, &quot;Seventh&quot; ) ]

cur.executemany(&quot;insert into mytab(id, data) values (:1, :2)", rows)

# Now query the results back

cur2 = con.cursor()
cur2.execute('select * from mytab')
res = cur2.fetchall()
print(res)</pre>

      <p>The '<code>rows</code>' array contains the data to be inserted into the <em>mytab</em> table created earlier.</p>

      <p>The <code>executemany()</code> call inserts all rows.  This call uses "array binding", which is an efficient way to
      insert multiple records.</p>

      <p>The final part of the script queries the results back and displays them as a list of tuples.</p>

      <p>From a terminal window, run:</p>

      <pre><strong>python bind_insert.py</strong></pre>

      <p>The new results are automatically rolled back at the end of
      the script. So, re-running the script will always show the same number of
      rows in the table.</p>

    </li>

    <li><h4>4.3 Batcherrors</h4>

      <p>The <code>Batcherrors</code> features allows invalid data to be identified
      while allowing valid data to be inserted.</p>

      <p>Edit the data values in <code>bind_insert.py</code> and
      create a row with a duplicate key:</p>

<pre>
rows = [ (1, &quot;First&quot; ), (2, &quot;Second&quot; ),
         (3, &quot;Third&quot; ), (4, &quot;Fourth&quot; ),
         (5, &quot;Fifth&quot; ), (6, &quot;Sixth&quot; ),
         <strong>(6, &quot;Duplicate&quot; ),</strong>
         (7, &quot;Seventh&quot; ) ]
</pre>

      <p>From a terminal window, run:</p>

      <pre><strong>python bind_insert.py</strong></pre>

      <p>The duplicate generates the error "ORA-00001: unique
      constraint (PYTHONHOL.MY_PK) violated".  The data is rolled back
      and the query returns no rows.</p>

      <p>Edit the file again and enable <code>batcherrors</code> like:</p>

<pre>
import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)
cur = con.cursor()

rows = [ (1, &quot;First&quot; ), (2, &quot;Second&quot; ),
         (3, &quot;Third&quot; ), (4, &quot;Fourth&quot; ),
         (5, &quot;Fifth&quot; ), (6, &quot;Sixth&quot; ),
         <strong>(6, &quot;Duplicate&quot; ),</strong>
         (7, &quot;Seventh&quot; ) ]

cur.executemany("insert into mytab(id, data) values (:1, :2)", rows<strong>, batcherrors=True</strong>)

<strong>for error in cur.getbatcherrors():
    print("Error", error.message.rstrip(), "at row offset", error.offset)</strong>

# Now query the results back

cur2 = con.cursor()
cur2.execute('select * from mytab')
res = cur2.fetchall()
print(res)
</pre>

      <p>Run the file:</p>

      <pre><strong>python bind_insert.py</strong></pre>

      <p>The new code shows the offending duplicate row: "ORA-00001: unique constraint (PYTHONDEMO.MY_PK) violated at row offset 6".
      This indicates the 6th data value (counting from 0) had a
      problem.</p>

      <p>The other data gets inserted and is queried back.</p>

      <p>At the end of the script, python-oracledb will roll back an uncommitted transaction. If you want to commit results, you can use:</p>

<pre>con.commit()</pre>

      <p>To force python-oracledb to roll back the transaction, use:</p>

<pre>con.rollback()</pre>

</li>

</ul>

<h2><a name="plsql">5. PL/SQL</a></h2>

<p>PL/SQL is Oracle's procedural language extension to SQL. PL/SQL procedures and functions are stored and run in the database. Using PL/SQL lets all database applications reuse logic, no matter how the application accesses the database. Many data-related operations can  be performed in PL/SQL faster than extracting the data into a  program (for example, Python) and then processing it. <em>Documentation link for further reading: <a
  href="https://python-oracledb.readthedocs.io/en/latest/user_guide/plsql_execution.html">PL/SQL Execution</a></em>.</p>

  <ul>
    <li>
      <h4>5.1 PL/SQL function</h4>
  <p>The <a href="#installsampleenv">environment setup file</a> has already created the new table named <strong>ptab</strong> and a PL/SQL stored function <code>myfunc</code> to insert a row into <em>ptab</em> and return double the inserted value by internally running the sql script below:</p>
  <pre>create table ptab (mydata varchar(20), myid number);

create or replace function myfunc(d_p in varchar2, i_p in number) return number as
  begin
    insert into ptab (mydata, myid) values (d_p, i_p);
    return (i_p * 2);
  end;
/</pre>

      <p>The <code>myfunc</code> PL/SQL stored function will be used by the <code>plsql_func.py</code> file below.</p>
      <p>Review the code contained in <code>plsql_func.py</code>:</p>

<pre>
import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)
cur = con.cursor()

res = cur.callfunc('myfunc', int, ('abc', 2))
print(res)
</pre>

      <p>This uses the <code>callfunc()</code> method to execute the function.
      The second parameter is the type of the returned value. It should be one of the types supported by python-oracledb or one of the type constants defined by python-oracledb (such as <em>oracledb.NUMBER</em>). The two PL/SQL function parameters are passed as a tuple, binding them to the function parameter arguments.</p>

      <p>From a terminal window, run:</p>

      <pre><strong>python plsql_func.py</strong></pre>

      <p>The output is a result of the PL/SQL function calculation.</p>

    </li>

    <li><h4>5.2 PL/SQL procedures</h4>

  <p>The <a href="#installsampleenv">environment setup file</a> has already created a PL/SQL
      stored procedure <code>myproc</code> to accept two parameters by internally running the sql script below:</p>
  <pre>create or replace procedure myproc(v1_p in number, v2_p out number) as
begin
  v2_p := v1_p * 2;
end;
/</pre>
<p> The second parameter contains an OUT return value.The <code>myproc</code> PL/SQL stored procedure will be used by the <code>plsql_proc.py</code> file below.</p>

<p>Review the code contained in <code>plsql_proc.py</code>:</p>

<pre>
import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)
cur = con.cursor()

myvar = cur.var(int)
cur.callproc('myproc', (123, myvar))
print(myvar.getvalue())</pre>

      <p>This creates an integer variable <code>myvar</code> to hold
      the value returned by the PL/SQL OUT parameter. The input number
      123 and the output variable name are bound to the procedure call
      parameters using a tuple.</p>

      <p>To call the PL/SQL procedure, the <code>callproc()</code>
      method is used.</p>

      <p>In a terminal window, run:</p>

<pre><strong>python plsql_proc.py</strong></pre>

      <p>The <code>getvalue()</code> method displays the returned
      value.</p>
    </li>
  </ul>

<h2><a name="handlers">6. Type Handlers</a></h2>

<p>Type handlers enable applications to alter data that is fetched from, or sent to, the database. <em>Documentation links for further reading: <a
href="https://python-oracledb.readthedocs.io/en/latest/user_guide/sql_execution.html#changing-fetched-data-types-with-output-type-handlers"
>Changing Fetched Data Types with Output Type Handlers</a> and <a
href="https://python-oracledb.readthedocs.io/en/latest/user_guide/bind.html#changing-bind-data-types-using-an-input-type-handler"
>Changing Bind Data Types using an Input Type Handler</a></em>.</p>

  <ul>
    <li>
      <h4>6.1 Basic output type handler</h4>

      <p>Output type handlers enable applications to change how data
      is fetched from the database.  For example, numbers can be
      returned as strings or decimal objects.  LOBs can be returned as
      strings or bytes.</p>

      <p>A type handler is enabled by setting the
      <code>outputtypehandler</code> attribute on either a cursor or
      the connection. If set on a cursor, it only affects queries executed
      by that cursor. If set on a connection, it affects all queries executed
      on cursors created by that connection.</p>

      <p>Review the code contained in <code>type_output.py</code>:</p>

<pre>
import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)
cur = con.cursor()

print("Standard output...")
for row in cur.execute("select * from dept"):
    print(row)
</pre>

      <p>In a terminal window, run:</p>

      <pre><strong>python type_output.py</strong></pre>

      <p>This shows the department number represented as digits like
      <code>10</code>.</p>

      <p>Add an output type handler to the bottom of the file:</p>

<pre>
<strong>def ReturnNumbersAsStrings(cursor, name, defaultType, size, precision, scale):
    if defaultType == oracledb.NUMBER:
        return cursor.var(str, 9, cursor.arraysize)

print("Output type handler output...")
cur = con.cursor()
cur.outputtypehandler = ReturnNumbersAsStrings
for row in cur.execute("select * from dept"):
    print(row)</strong>
</pre>

      <p>This type handler converts any number columns to strings with
      maximum size 9.</p>

      <p>Run the script again:</p>

      <pre><strong>python type_output.py</strong></pre>

      <p>The new output shows the department numbers are now strings
      within quotes like <code>'10'</code>.</p>

    </li>

    <li><h4>6.2 Output type handlers and variable converters</h4>

      <p>When numbers are fetched from the database, the conversion from Oracle's decimal representation to Python's binary format may need careful handling.  To avoid unexpected issues, the  general recommendation is to do number operations in SQL or PL/SQL, or to use the decimal module in Python.</p>

      <p>Output type handlers can be combined with variable converters
      to change how data is fetched.</p>

      <p>Review <code>type_converter.py</code>:</p>

      <pre>
import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)
cur = con.cursor()

for value, in cur.execute("select 0.1 from dual"):
    print("Value:", value, "* 3 =", value * 3)
</pre>

<p>Run the file:</p>

<pre><strong>python type_converter.py</strong></pre>

      <p>The output is like:</p>

      <pre>Value: 0.1 * 3 = 0.30000000000000004</pre>

      <p>Edit the file and add a type handler that uses a Python decimal converter:</p>

<pre>
import oracledb
<strong>import decimal</strong>
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)
cur = con.cursor()

<strong>def ReturnNumbersAsDecimal(cursor, name, defaultType, size, precision, scale):
    if defaultType == oracledb.NUMBER:
        return cursor.var(str, 9, cursor.arraysize, outconverter=decimal.Decimal)

cur.outputtypehandler = ReturnNumbersAsDecimal</strong>

for value, in cur.execute("select 0.1 from dual"):
    print("Value:", value, "* 3 =", value * 3)
</pre>

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

      <p>Run the file again:</p>

      <pre><strong>python type_converter.py</strong></pre>

      <p>Output is like:</p>

      <pre>Value: 0.1 * 3 = 0.3</pre>

      <p>The code above demonstrates the use of outconverter, but in this particular case, python-oracledb offers a simple convenience attribute to do the same conversion:</p>

<pre>
import oracledb

oracledb.defaults.fetch_decimals = True
</pre></li>

    <li>
      <h4>6.3 Input type handlers</h4>

      <p>Input type handlers enable applications to change how data is bound to statements, or to enable new types to be bound directly without having to be converted individually.</p>

      <p>Review <code>type_input.py</code>, with the addition of a new class and converter (shown in bold):</p>

<pre>
import oracledb
import db_config
import json

con = oracledb.connect(user=db_config.user,
                       password=db_config.pw, dsn=db_config.dsn)
cur = con.cursor()

# Create table
cur.execute("""begin
                 execute immediate 'drop table BuildingTable';
                 exception when others then
                   if sqlcode &lt;&gt; -942 then
                     raise;
                   end if;
               end;""")
cur.execute("""create table BuildingTable (
               ID number(9) not null,
               BuildingDetails varchar2(400),
               constraint TestTempTable_pk primary key (ID))""")

# Create a Python class for a Building
<strong>class Building(object):

    def __init__(self, building_id, description, num_floors):
        self.building_id = building_id
        self.description = description
        self.num_floors = num_floors

    def __repr__(self):
        return "&lt;Building %s: %s&gt;" % (self.building_id, self.description)

    def __eq__(self, other):
        if isinstance(other, Building):
            return other.building_id == self.building_id \
                and other.description == self.description \
                and other.num_floors == self.num_floors
        return NotImplemented

    def to_json(self):
        return json.dumps(self.__dict__)

    @classmethod
    def from_json(cls, value):
        result = json.loads(value)
        return cls(**result)

# Convert a Python building object to SQL JSON type that can be read as a string
def building_in_converter(value):
    return value.to_json()


def input_type_handler(cursor, value, num_elements):
    if isinstance(value, Building):
        return cursor.var(oracledb.STRING, arraysize=num_elements,
                          inconverter=building_in_converter)


building = Building(1, "The First Building", 5)  # Python object
cur.execute("truncate table BuildingTable")
cur.inputtypehandler = input_type_handler
cur.execute("insert into BuildingTable (ID, BuildingDetails) values (:1, :2)",
            (building.building_id, building))
con.commit()</strong>

# Query the row
print("Querying the row just inserted...")
cur.execute("select ID, BuildingDetails from BuildingTable")
for (int_col, string_col) in cur:
    print("Building ID:", int_col)
    print("Building Details in JSON format:", string_col)
</pre>

<p>In the new file, a Python class <code>Building</code> is defined, which holds   basic information about a building.

The <code>Building</code> class is used lower in the code to create a Python instance:</p>

<pre>
building = Building(1, &quot;The First Building&quot;, 5)</pre>

<p>which is then directly bound into the INSERT statement like </p>

<pre>cur.execute("insert into BuildingTable (ID, BuildingDetails) values (:1, :2)", (building.building_id, building))</pre>

<p>The mapping between Python and Oracle objects is handled in
<code>building_in_converter</code> which  creates
an Oracle STRING object from the <code>Building</code> Python object in a JSON format.  The <code>building_in_converter</code> method is called by the input type handler <code>input_type_handler</code>,whenever an instance of <code>Building</code> is inserted with the cursor.</p>

      <p>To confirm the behavior, run the file:</p>

      <pre><strong>python type_input.py</strong></pre>
      <p>You should see the following output:</p>
      <pre>Querying the row just inserted...
Building ID: 1
Building Details in JSON format: {"building_id": 1, "description": "The First Building", "num_floors": 5}</pre>

    </li>

  </ul>

<h2><a name="lobs">7. LOBs</a></h2>

  <p>Oracle Database "LOB" long objects can be streamed using a LOB locator, or worked with directly as strings or bytes. <em>Documentation link
for further reading: <a
  href="https://python-oracledb.readthedocs.io/en/latest/user_guide/lob_data.html"
  >Using CLOB and BLOB Data</a></em>.</p>

  <ul>
    <li>
    <h4>7.1 Fetching a CLOB using a locator</h4>

      <p>Review the code contained in <code>clob.py</code>:</p>

<pre>
import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)
cur = con.cursor()

print("Inserting data...")
cur.execute("truncate table testclobs")
long_string = ""
for i in range(5):
    char = chr(ord('A') + i)
    long_string += char * 250
    cur.execute("insert into testclobs values (:1, :2)",
                   (i + 1, "String data " + longString + ' End of string'))
con.commit()

print("Querying data...")
cur.execute("select * from testclobs where id = :id", {'id': 1})
(id, clob) = cur.fetchone()
print("CLOB length:", clob.size())
clobdata = clob.read()
print("CLOB data:", clobdata)
</pre>

      <p>This inserts some test string data and then fetches one
      record into <code>clob</code>, which is a python-oracledb character
      LOB Object.  Methods on LOB include <code>size()</code> and
      <code>read()</code>.</p>

      <p>To see the output, run the file:</p>

<pre><strong>python clob.py</strong></pre>

      <p>Edit the file and experiment reading chunks of data by giving start character position and length, such as <code>clob.read(1,10)</code>.</p>

    </li>

    <li>
      <h4>7.2 Fetching a CLOB as a string</h4>

      <p>For CLOBs small enough to fit in the application memory, it
      is much faster to fetch them directly as strings.</p>

      <p>Review the code contained in <code>clob_string.py</code>. The differences from <code>clob.py</code> are shown in bold:</p>

<pre>
import oracledb
import db_config

<strong>oracledb.defaults.fetch_lobs = False</strong>

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)
cur = con.cursor()

print("Inserting data...")
cur.execute("truncate table testclobs")
long_string = ""
for i in range(5):
    char = chr(ord('A') + i)
    long_string += char * 250
    cur.execute("insert into testclobs values (:1, :2)",
                (i + 1, "String data " + long_string + ' End of string'))
con.commit()

print("Querying data...")
cur.execute("select * from testclobs where id = :id", {'id': 1})
<strong>(id, clobdata) = cur.fetchone()
print("CLOB length:", len(clobdata))
print("CLOB data:", clobdata)</strong>
</pre>

      <p>Setting <em>oracledb.defaults.fetch_lobs</em> to False causes python-oracledb to fetch the CLOB as a
      string.  Standard Python string functions such as <code>len()</code> can be used on the result.</p>

      <p>The output is the same as for <code>clob.py</code>.  To
      check, run the file:</p>

<pre><strong>python clob_string.py</strong></pre>

    </li>
  </ul>

<h2><a name="rowfactory">8. Rowfactory functions</a></h2>

  <p>Rowfactory functions enable queries to return objects other than
  tuples.  They can be used to provide names for the various columns
  or to return custom objects.</p>

  <ul>
    <li><h4>8.1 Rowfactory for mapping column names</h4>

  <p>Review the code contained in <code>rowfactory.py</code>:</p>

<pre>
import collections
import oracledb
import db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)
cur = con.cursor()

cur.execute("select deptno, dname from dept")
rows = cur.fetchall()

print('Array indexes:')
for row in rows:
    print(row[0], "->", row[1])

print('Loop target variables:')
for c1, c2 in rows:
    print(c1, "->", c2)
</pre>

  <p>This shows two methods of accessing result set items from a data row.  The first uses array indexes like <code>row[0]</code>. The second uses loop target variables that take each row tuple's values.</p>

  <p>Run the file:</p>

<pre><strong>python rowfactory.py</strong></pre>

  <p>Both access methods gives the same results.</p>

  <p>To use a rowfactory function, edit <code>rowfactory.py</code> and
  add this code at the bottom:</p>

<pre>
<strong>print('Rowfactory:')
cur.execute("select deptno, dname from dept")
cur.rowfactory = collections.namedtuple("MyClass", ["DeptNumber", "DeptName"])

rows = cur.fetchall()
for row in rows:
    print(row.DeptNumber, "->", row.DeptName)
</strong></pre>

      <p>This uses the Python factory function
      <code>namedtuple()</code> to create a subclass of tuple that allows access to the elements via indexes or the given field names.</p>

      <p>The <code>print()</code> function shows the use of the new
      named tuple fields.  This coding style can help reduce coding
      errors.</p>

      <p>Run the script again:</p>

<pre><strong>python rowfactory.py</strong></pre>


  <p>The output results are the same.</p>

</li>
</ul>

<h2><a name="subclass">9. Subclassing connections and cursors</a></h2>

  <p>Subclassing enables application to "hook" connection and cursor
  creation.  This can be used to alter or log connection and execution
  parameters, and to extend python-oracledb functionality. <em>Documentation link for
further reading: <a
  href="https://python-oracledb.readthedocs.io/en/latest/user_guide/tracing.html#application-tracing"
  >Application Tracing</a></em>.</p>

  <ul>
    <li><h4>9.1 Subclassing connections</h4>

  <p>Review the code contained in <code>subclass.py</code>:</p>

  <pre>
import oracledb
import db_config

class MyConnection(oracledb.Connection):

    def __init__(self):
        print("Connecting to database")
        return super(MyConnection, self).__init__(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)

con = MyConnection()
cur = con.cursor()

cur.execute("select count(*) from emp where deptno = :bv", (10,))
count, = cur.fetchone()
print("Number of rows:", count)
</pre>

  <p>This creates a new class "MyConnection" that inherits from the python-oracledb Connection class.  The <code>__init__</code> method is
  invoked when an instance of the new class is created.  It prints a message and calls the base class, passing the connection credentials.</p>

  <p>In the "normal" application, the application code:</p>

  <pre>con = MyConnection()</pre>

  <p>does not need to supply any credentials, as they are embedded in the
  custom subclass. All the python-oracledb methods such as <code>cursor()</code> are
  available, as shown by the query.</p>

  <p>Run the file:</p>

<pre><strong>python subclass.py</strong></pre>

  <p>The query executes successfully.</p>

    </li>

    <li><h4>9.2 Subclassing cursors</h4>

      <p>Edit <code>subclass.py</code> and extend the
      <code>cursor()</code> method with a new MyCursor class:</p>

<pre>
import oracledb
import db_config

class MyConnection(oracledb.Connection):

    def __init__(self):
        print("Connecting to database")
        return super(MyConnection, self).__init__(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)

<strong>    def cursor(self):
        return MyCursor(self)

class MyCursor(oracledb.Cursor):

   def execute(self, statement, args):
       print("Executing:", statement)
       print("Arguments:")
       for argIndex, arg in enumerate(args):
           print("  Bind", argIndex + 1, "has value", repr(arg))
           return super(MyCursor, self).execute(statement, args)

   def fetchone(self):
       print("Fetchone()")
       return super(MyCursor, self).fetchone()</strong>

con = MyConnection()
cur = con.cursor()

cur.execute("select count(*) from emp where deptno = :bv", (10,))
count, = cur.fetchone()
print("Number of rows:", count)
</pre>

<p>When the application gets a cursor from the
<code>MyConnection</code> class, the new <code>cursor()</code> method returns an instance of our new <code>MyCursor</code> class.</p>

<p>The "application" query code remains unchanged.  The new <code>execute()</code> and <code>fetchone()</code> methods of the <code>MyCursor</code> class get invoked.  They do some logging and invoke the parent methods to do the actual statement execution.</p>

<p>To confirm this, run the file again:</p>

<pre><strong>python subclass.py</strong></pre>

    </li>

</ul>

<h2> <a name="thick">10. Python-oracledb Thick mode</a></h2>
<p>All the above examples use python-oracledb in <em>thin</em> mode, but there are certain features which are only available in the <em>thick</em> mode of the python-oracledb driver. The upcoming sections  show some of these.  Note that you can also run all the earlier examples in thick mode by just changing the import line in examples from <code>import db_config</code> to <code>import db_config_thick as db_config</code>.</p>

<p>The following sections assume you have installed the tutorial schema as shown at the <a href="#preface" >tutorial start</a>.</p>

<ul>
        <li>
          <h4> 10.1 Review the Oracle Client library path</h4>

          <p>You additionally need to make Oracle Client libraries available.  Follow the documentation on <a href="https://python-oracledb.readthedocs.io/en/latest/user_guide/installation.html" >Installing python-oracledb</a>.</p>

          <p>When you have installed Oracle Client libraries, review the library path settings in <code>db_config_thick.py</code> file. If python-oracledb cannot locate Oracle Client libraries, then your applications will fail with an error like "<em>DPI-1047: Cannot locate a 64-bit Oracle Client library</em>". For our examples, we are using Oracle Instant Client libraries.</p>

<pre>
# On Linux, this must be None.
# Instead, the Oracle environment must be set before Python starts.
instant_client_dir = None

# On Windows, if your database is on the same machine, comment these lines out
# and let instant_client_dir be None.  Otherwise, set this to your Instant
# Client directory.  Note the use of the raw string r"...", which allows backslashes to
# be used as directory separators.
if platform.system() == &quot;Windows&quot;:
    instant_client_dir = r"C:\Oracle\instantclient_19_14"

# On macOS (Intel x86) set the directory to your Instant Client directory
if platform.system() == &quot;Darwin&quot;:
    instant_client_dir = os.environ.get("HOME")+"/Downloads/instantclient_19_8"

# You must always call init_oracle_client() to use thick mode
oracledb.init_oracle_client(lib_dir=instant_client_dir)</pre>

 <p> <strong>Important! </strong>Calling the <code>init_oracle_client()</code> function enables the thick mode of python-oracledb. Once python-oracledb is in thick mode, you cannot return to thin mode without removing calls to <code>init_oracle_client()</code> and restarting the application.</p>
 <p>Edit <code>db_config_thick.py</code> and set <code>instant_client_dir</code> to <code>None</code> or to a valid path according to the following notes:</p>

          <ul>
            <li>

              <p>If you are on  macOS (Intel x86) or Windows, and you have installed Oracle Instant Client libraries because your database is on a remote machine, then set <code>instant_client_dir</code> to the path of the Instant Client libraries.</p>
            </li>

            <li>

            <p>If you are on Windows and have a local database installed, then comment out the two Windows lines, so that <code>instant_client_dir</code> remains <code>None</code>.</p>

            </li>

            <li>

            <p>In all other cases (including Linux with Oracle Instant Client), make sure that <code>instant_client_dir</code> is set to <code>None</code>.  In these cases you must make sure that the Oracle libraries from Instant Client or your ORACLE_HOME are in your system library search path before you start Python. On Linux, the path can be configured with <em>ldconfig</em> or with the <em>LD_LIBRARY_PATH</em> environment variable.</p>
           </li>
         </ul>
</li>
<li><h4 id="thickconfig">10.2 Review the configuration files for thick mode</h4>

          <p>Review <code>db_config_thick.py</code>   (thick mode), and <code>db_config.sql</code> files in the <code>tutorial</code> directory.  These are included in other Python and SQL files for setting up the database connection.</p>

          <p>Edit <code>db_config_thick.py</code> file and change the default values to match the connection information for your environment.  Alternatively, you can set the given environment variables in your terminal window. For example, the default username is "<em>pythondemo</em>" unless the environment variable "<em>PYTHON_USER</em>" contains a different username. The default connection string is for the '<em>orclpdb</em>' database service on the same machine as Python. In Python Database API terminology, the connection string parameter is called the "data source name" or "dsn".  Using environment variables is convenient because you will not be asked to re-enter the password when you run scripts:</p>

<pre>
user = os.environ.get("PYTHON_USER", "pythondemo")

dsn = os.environ.get("PYTHON_CONNECT_STRING", "localhost/orclpdb")

pw = os.environ.get("PYTHON_PASSWORD")
if pw is None:
    pw = getpass.getpass("Enter password for %s: " % user)
</pre>

<p>Also, change the default username and connection string in the SQL configuration file <code>db_config.sql</code>:</p>

<pre>
-- Default database username
def user = "pythondemo"

-- Default database connection string
def connect_string = "localhost/orclpdb"

-- Prompt for the password
accept pw char prompt 'Enter database password for &amp;user: ' hide
</pre>


          <p>The tutorial instructions may need adjusting, depending on how you have set up your environment.</p>
  </li>
</ul>

<p>The following sections are specific to the python-oracledb thick modes in this release of python-oracledb.</p>

 <h2><a name = "scrollable">11. Scrollable cursors</a></h2>

    <p>Scrollable cursors enable python-oracledb thick mode applications to move backwards as well as forwards in query results. They can be used to skip rows as well as move to a particular row.</p>
    <ul>
    <li><h4>11.1 Working with scrollable cursors</h4>
    <p>Review the code contained in <code>query_scroll.py</code>:</p>

    <pre>
import oracledb
import db_config_thick as db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)
cur = con.cursor(<strong>scrollable=True</strong>)

cur.execute("select * from dept order by deptno")

cur.scroll(2, mode="absolute")  # go to second row
print(cur.fetchone())

cur.scroll(-1)                    # go back one row
print(cur.fetchone())
</pre>

    <p>Run the script in a terminal window:</p>

  <pre><strong>python query_scroll.py</strong></pre>

    <p>Edit <code>query_scroll.py</code> and experiment with different
    scroll options and orders, such as:</p>

    <pre>cur.scroll(1)  # go to next row
print(cur.fetchone())

cur.scroll(mode="first")  # go to first row
print(cur.fetchone())</pre>

    <p>Try some scroll options that go beyond the number of rows in the resultset.</p>
</li>
</ul>

<h2><a name="bindnamedobj">12. Binding named objects</a></h2>

  <p>Python-oracledb's thick mode can fetch and bind named object types such as Oracle's Spatial Data Objects (SDO).</p>

  <p>The  SDO definition includes the following attributes:</p>

<pre>
 Name                                      Null?    Type
 ----------------------------------------- -------- ----------------------------
 SDO_GTYPE                                          NUMBER
 SDO_SRID                                           NUMBER
 SDO_POINT                                          MDSYS.SDO_POINT_TYPE
 SDO_ELEM_INFO                                      MDSYS.SDO_ELEM_INFO_ARRAY
 SDO_ORDINATES                                      MDSYS.SDO_ORDINATE_ARRAY
</pre>
<ul>
    <li><h4>12.1 How to bind named objects</h4>
  <p>Review the code contained in <code>bind_sdo.py</code>:</p>

<pre>
import oracledb
import db_config_thick as db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)
cur = con.cursor()

# Create table
cur.execute("""begin
                 execute immediate 'drop table testgeometry';
                 exception when others then
                   if sqlcode &lt;&gt; -942 then
                     raise;
                   end if;
               end;""")
cur.execute("""create table testgeometry (
               id number(9) not null,
               geometry MDSYS.SDO_GEOMETRY not null)""")

# Create and populate Oracle objects
type_obj = con.<strong>gettype</strong>("MDSYS.SDO_GEOMETRY")
element_info_type_obj = con.<strong>gettype</strong>("MDSYS.SDO_ELEM_INFO_ARRAY")
ordinate_type_obj = con.<strong>gettype</strong>("MDSYS.SDO_ORDINATE_ARRAY")
obj = type_obj.<strong>newobject()</strong>
obj.SDO_GTYPE = 2003
obj.SDO_ELEM_INFO = element_info_type_obj.<strong>newobject()</strong>
obj.SDO_ELEM_INFO.<strong>extend</strong>([1, 1003, 3])
obj.SDO_ORDINATES = ordinate_type_obj.<strong>newobject()</strong>
obj.SDO_ORDINATES.<strong>extend</strong>([1, 1, 5, 7])
print("Created object", obj)

# Add a new row
print("Adding row to table...")
cur.execute("insert into testgeometry values (1, :objbv)", objbv = obj)
print("Row added!")

# Query the row
print("Querying row just inserted...")
cur.execute("select id, geometry from testgeometry");
for row in cur:
    print(row)</pre>
<p>This uses <code>gettype()</code> to get the database types of the SDO and its object attributes. The <code>newobject()</code> calls create Python representations of those objects. The python object atributes are then set.  Oracle VARRAY types such as SDO_ELEM_INFO_ARRAY are set with <code>extend()</code>.</p>

<p>Run the file:</p>

<pre><strong>python bind_sdo.py</strong></pre>

<p>The new SDO is shown as an object, similar to </p>

<pre>(1, &lt;oracledb.Object MDSYS.SDO_GEOMETRY at 0x104a76230&gt;)</pre>

<p>To show the attribute values, edit the query code section at
the end of the file.  Add a new method that traverses the object. The file below the existing comment "<code># (Change below here)</code>")
should look like:</p>

<pre>
# (Change below here)

# Define a function to dump the contents of an Oracle object
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, "}")

# Query the row
print("Querying row just inserted...")
cur.execute("select id, geometry from testgeometry")
for id, obj in cur:
    print("Id: ", id)
    dumpobject(obj)</pre>

<p>Run the file again:</p>

<pre><strong>python bind_sdo.py</strong></pre>

<p>This shows</p>
<pre>
Querying row just inserted...
Id:  1
   {
    SDO_GTYPE : 2003
    SDO_SRID : None
    SDO_POINT : None
    SDO_ELEM_INFO :
       [
         1
         1003
         3
       ]
    SDO_ORDINATES :
       [
         1
         1
         5
         7
       ]
   }
</pre>

<p>To explore further, try setting the SDO attribute SDO_POINT, which is of type SDO_POINT_TYPE.</p>

<p>The <code>gettype()</code> and <code>newobject()</code> methods can also be used to bind PL/SQL Records and Collections.</p>

<p>Before deciding to use objects, review your performance goals because working with scalar values can be faster.</p>
   </li>
</ul>

<h2><a name="typehandlers">13. Input and Output Type Handlers with named objects</a></h2>
<p>Named objects can only be used in python-oracledb's thick mode. <em>Documentation links for further reading: <a
href="https://python-oracledb.readthedocs.io/en/latest/user_guide/sql_execution.html#changing-fetched-data-types-with-output-type-handlers"
>Changing Fetched Data Types with Output Type Handlers</a> and <a
href="https://python-oracledb.readthedocs.io/en/latest/user_guide/bind.html#changing-bind-data-types-using-an-input-type-handler"
>Changing Bind Data Types using an Input Type Handler</a></em>.</p>
<ul>
<li>
  <h4>13.1 Input type handlers with named objects</h4>
<p>Input type handlers for named objects can enable applications to change how data is bound to the individual attributes of the named objects. Review the code contained in <code>type_input_named_obj.py</code>, which is similar to the final <code>bind_sdo.py</code> from section 12.1, with the
    addition of a new class and converter (shown in bold):</p>
<pre>
import oracledb
import db_config_thick as db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)
cur = con.cursor()

# Create table
cur.execute("""begin
                 execute immediate 'drop table testgeometry';
                 exception when others then
                   if sqlcode &lt;&gt; -942 then
                     raise;
                   end if;
               end;""")
cur.execute("""create table testgeometry (
               id number(9) not null,
               geometry MDSYS.SDO_GEOMETRY not null)""")

<strong># Create a Python class for an SDO
class mySDO(object):
    def __init__(self, gtype, elemInfo, ordinates):
        self.gtype = gtype
        self.elemInfo = elemInfo
        self.ordinates = ordinates</strong>

# Get Oracle type information
obj_type = con.gettype("MDSYS.SDO_GEOMETRY")
element_info_type_obj = con.gettype("MDSYS.SDO_ELEM_INFO_ARRAY")
ordinate_type_obj = con.gettype("MDSYS.SDO_ORDINATE_ARRAY")

# Convert a Python object to MDSYS.SDO_GEOMETRY
<strong>def SDOInConverter(value):
    obj = obj_type.newobject()
    obj.SDO_GTYPE = value.gtype
    obj.SDO_ELEM_INFO = element_info_type_obj.newobject()
    obj.SDO_ELEM_INFO.extend(value.elemInfo)
    obj.SDO_ORDINATES = ordinate_type_obj.newobject()
    obj.SDO_ORDINATES.extend(value.ordinates)
    return obj

def SDOInputTypeHandler(cursor, value, numElements):
    if isinstance(value, mySDO):
        return cursor.var(oracledb.OBJECT, arraysize=numElements,
                inconverter=SDOInConverter, typename=obj_type.name)</strong>

sdo = mySDO(2003, [1, 1003, 3], [1, 1, 5, 7])  # Python object
<strong>cur.inputtypehandler = SDOInputTypeHandler</strong>
cur.execute("insert into testgeometry values (:1, :2)", (1, sdo))

# Define a function to dump the contents of an Oracle object
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, "}")

# Query the row
print("Querying row just inserted...")
cur.execute("select id, geometry from testgeometry")
for (id, obj) in cur:
    print("Id: ", id)
    dumpobject(obj)
</pre>
<p>The mapping between Python and Oracle objects is handled in <code>SDOInConverter</code> which uses the python-oracledb <code>newobject()</code> and <code>extend()</code> methods to create an Oracle object from the Python object values. The <code>SDOInConverter</code> method is called by the input type handler
<code>SDOInputTypeHandler</code> whenever an instance of
<code>mySDO</code> is inserted with the cursor.</p>

<p>To confirm the behavior, run the file:</p>

<pre><strong>python type_input_named_obj.py</strong></pre>
<p> This will show</p>
<pre>Querying row just inserted...
Id:  1
   {
    SDO_GTYPE : 2003.0
    SDO_SRID : None
    SDO_POINT : None
    SDO_ELEM_INFO :
       [
         1.0
         1003.0
         3.0
       ]
    SDO_ORDINATES :
       [
         1.0
         1.0
         5.0
         7.0
       ]
   }</pre></li>
</ul>

<ul>
<li>
  <h4>13.2 Output type handlers with named objects</h4>
<p>Output type handlers enable applications to extract the data from  database named objects into a user-defined Python object (defined by the <code>mySDO</code> class here). Review the code contained in <code>type_output_named_obj.py</code> with the output converter function shown in bold:</p>
<pre>
import oracledb
import db_config_thick as db_config

con = oracledb.connect(user=db_config.user,
                       password=db_config.pw, dsn=db_config.dsn)
cur = con.cursor()

# Create table
cur.execute("""begin
                 execute immediate 'drop table testgeometry';
                 exception when others then
                   if sqlcode &lt;&gt; -942 then
                     raise;
                   end if;
               end;""")
cur.execute("""create table testgeometry (
               id number(9) not null,
               geometry MDSYS.SDO_GEOMETRY not null)""")

# Create a Python class for an SDO
class mySDO(object):
    def __init__(self, gtype, elemInfo, ordinates):
        self.gtype = gtype
        self.elemInfo = elemInfo
        self.ordinates = ordinates

# Get Oracle type information
obj_type = con.gettype("MDSYS.SDO_GEOMETRY")
element_info_type_obj = con.gettype("MDSYS.SDO_ELEM_INFO_ARRAY")
ordinate_type_obj = con.gettype("MDSYS.SDO_ORDINATE_ARRAY")

# Convert a Python object to MDSYS.SDO_GEOMETRY
def SDOInConverter(value):
    obj = obj_type.newobject()
    obj.SDO_GTYPE = value.gtype
    obj.SDO_ELEM_INFO = element_info_type_obj.newobject()
    obj.SDO_ELEM_INFO.extend(value.elemInfo)
    obj.SDO_ORDINATES = ordinate_type_obj.newobject()
    obj.SDO_ORDINATES.extend(value.ordinates)
    return obj

def SDOInputTypeHandler(cursor, value, numElements):
    if isinstance(value, mySDO):
        return cursor.var(oracledb.OBJECT, arraysize=numElements,
                          inconverter=SDOInConverter, typename=obj_type.name)

# Convert a MDSYS.SDO_GEOMETRY DB Object to Python object
<strong>def SDOOutConverter(DBobj):
    return mySDO(int(DBobj.SDO_GTYPE), DBobj.SDO_ELEM_INFO.aslist(),
                 DBobj.SDO_ORDINATES.aslist())</strong>

<strong>def SDOOutputTypeHandler(cursor, name, default_type, size, precision,
                         scale):
    if default_type == oracledb.DB_TYPE_OBJECT:
        return cursor.var(obj_type, arraysize=cursor.arraysize,
                          outconverter=SDOOutConverter)</strong>

sdo = mySDO(2003, [1, 1003, 3], [1, 1, 5, 7])  # Python object
cur.inputtypehandler = SDOInputTypeHandler
cur.execute("insert into testgeometry values (:1, :2)", (1, sdo))
cur.outputtypehandler = SDOOutputTypeHandler

# Query the SDO Table row
print("Querying the Spatial Data Object(SDO) Table using the Output Type Handler...")
print("----------------------------------------------------------------------------")
cur.execute("select id, geometry from testgeometry")
for (id, obj) in cur:
    print("SDO ID:", id)
    print("SDO GYTPE:", obj.gtype)
    print("SDO ELEMINFO:", obj.elemInfo)
    print("SDO_ORDINATES:", obj.ordinates)</pre>
<p>Note that the Input Type Handler and the InConverter functions are the same as the previous example. </p>
<p>The mapping between the Python and Oracle objects is handled in <code>SDOOutConverter</code>. The <code>SDOOutConverter</code> method is called by the output type handler
  <code>SDOOutputTypeHandler</code> whenever  data of the named object (<code>MDSYS.SDOGEOMETRY</code> in this case) is selected with the cursor and needs to be converted to a user-defined Python object (<code>mySDO</code> object in this case).</p>

<p>To confirm the behavior, run the file:</p>

<pre><strong>python type_output_named_obj.py</strong></pre>
<p> This will show</p>
<pre>Querying the Spatial Data Object(SDO) Table using the Output Type Handler...
----------------------------------------------------------------------------
SDO ID: 1
SDO GYTPE: 2003
SDO ELEMINFO: [1.0, 1003.0, 3.0]
SDO_ORDINATES: [1.0, 1.0, 5.0, 7.0]</pre></li>
</ul>

<h2><a name="aq">14. Advanced Queuing</a></h2>

<p>Oracle Advanced Queuing (AQ) APIs usable in python-oracledb thick mode allow messages to be passed between applications. <em>Documentation link for further reading: <a
href="https://python-oracledb.readthedocs.io/en/latest/user_guide/aq.html" >Oracle Advanced Queuing (AQ)</a></em>.</p>

  <ul>
    <li>
    <h4>14.1 Message passing with Oracle Advanced Queuing</h4>

    <p>Review <code>aq.py</code>:</p>

<pre>
import oracledb
import decimal
import db_config_thick as db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)
cur = con.cursor()

BOOK_TYPE_NAME = "UDT_BOOK"
QUEUE_NAME = "BOOKS"
QUEUE_TABLE_NAME = "BOOK_QUEUE_TABLE"

# Cleanup
cur.execute(
    """begin
         dbms_aqadm.stop_queue('""" + QUEUE_NAME + """');
         dbms_aqadm.drop_queue('""" + QUEUE_NAME + """');
         dbms_aqadm.drop_queue_table('""" + QUEUE_TABLE_NAME + """');
         execute immediate 'drop type """ + BOOK_TYPE_NAME + """';
         exception when others then
           if sqlcode &lt;&gt; -24010 then
             raise;
           end if;
       end;""")

# Create a type
print("Creating books type UDT_BOOK...")
cur.execute("""
        create type %s as object (
            title varchar2(100),
            authors varchar2(100),
            price number(5,2)
        );""" % BOOK_TYPE_NAME)

# Create queue table and queue and start the queue
print("Creating queue table...")
cur.callproc("dbms_aqadm.create_queue_table",
        (QUEUE_TABLE_NAME, BOOK_TYPE_NAME))
cur.callproc("dbms_aqadm.create_queue", (QUEUE_NAME, QUEUE_TABLE_NAME))
cur.callproc("dbms_aqadm.start_queue", (QUEUE_NAME,))

books_type = con.gettype(BOOK_TYPE_NAME)
queue = con.queue(QUEUE_NAME, booksType)

# Enqueue a few messages
print("Enqueuing messages...")

BOOK_DATA = [
    ("The Fellowship of the Ring", "Tolkien, J.R.R.", decimal.Decimal("10.99")),
    ("Harry Potter and the Philosopher's Stone", "Rowling, J.K.",
            decimal.Decimal("7.99"))
]

for title, authors, price in BOOK_DATA:
    book = books_type.newobject()
    book.TITLE = title
    book.AUTHORS = authors
    book.PRICE = price
    print(title)
    queue.enqone(con.msgproperties(payload=book))
    con.commit()

# Dequeue the messages
print("\nDequeuing messages...")
queue.deqoptions.wait = oracledb.DEQ_NO_WAIT
while True:
    props = queue.deqone()
    if not props:
        break
    print(props.payload.TITLE)
    con.commit()

print("\nDone.")
</pre>

<p>This file sets up Advanced Queuing using Oracle's DBMS_AQADM
package.  The queue is used for passing Oracle UDT_BOOK objects. The file uses AQ interface features enhanced in python-oracledb v1.0.</p>

<p>Run the file:</p>

<pre><strong>python aq.py</strong></pre>

<p>The output shows messages being queued and dequeued.</p>

<p>To experiment, split the code into three files: one to create and
start the queue and two other files to queue and dequeue messages.
Experiment with running the queue and dequeue files concurrently in
separate terminal windows.</p>

<p>Try removing the <code>commit()</code> call in
<code>aq-dequeue.py</code>.  Now run <code>aq-enqueue.py</code> once
and then <code>aq-dequeue.py</code> several times.  The same messages
will be available each time you try to dequeue them.</p>

<p>Change <code>aq-dequeue.py</code> to commit in a separate
transaction by changing the "visibility" setting:</p>

<pre>
queue.deqoptions.visibility = oracledb.DEQ_IMMEDIATE
</pre>

<p>This gives the same behavior as the original code.</p>

<p>Now change the options of enqueued messages so that they expire from the
queue if they have not been dequeued after four seconds:</p>

<pre>
queue.enqone(con.msgproperties(payload=book, expiration=4))
</pre>

<p>Now run <code>aq-enqueue.py</code> and wait four seconds before you
run <code>aq-dequeue.py</code>.  There should be no messages to
dequeue. </p>

<p>If you are stuck, please look in the <code>solutions</code> directory at the <code>aq-dequeue.py</code>, <code>aq-enqueue.py</code> and <code>aq-queuestart.py</code> files.</p>

</li>
</ul>

<h2><a name="soda">15. Simple Oracle Document Access (SODA)</a></h2>

  <p>Simple Oracle Document Access (SODA) is a set of NoSQL-style APIs.
  Documents can be inserted, queried, and retrieved from Oracle Database.  By default, documents are JSON strings.  SODA APIs exist in many languages. It is usable in python-oracledb's thick mode. <i>Documentation link for further reading: <a
  href="https://python-oracledb.readthedocs.io/en/latest/user_guide/soda.html" >Simple Oracle Document Access (SODA)</a></i>.</p>

  <ul>

    <li>
      <h4>15.1 Inserting JSON Documents</h4>

      <p>Review <code>soda.py</code> :</p>

<pre>
import oracledb
import db_config_thick as db_config

con = oracledb.connect(user=db_config.user, password=db_config.pw, dsn=db_config.dsn)

soda = con.getSodaDatabase()

# Explicit metadata is used for maximum version portability
metadata = {
               "keyColumn": {
                   "name":"ID"
               },
               "contentColumn": {
                   "name": "JSON_DOCUMENT",
                   "sqlType": "BLOB"
               },
               "versionColumn": {
                   "name": "VERSION",
                   "method": "UUID"
               },
               "lastModifiedColumn": {
                   "name": "LAST_MODIFIED"
               },
               "creationTimeColumn": {
                   "name": "CREATED_ON"
               }
           }

collection = soda.createCollection("friends", metadata)

content = {'name': 'Jared', 'age': 35, 'address': {'city': 'Melbourne'}}

doc = collection.insertOneAndGet(content)
key = doc.key

doc = collection.find().key(key).getOne()
content = doc.getContent()
print('Retrieved SODA document dictionary is:')
print(content)</pre>

      <p><code>soda.createCollection()</code> will create a new collection, or open an existing collection, if the name is already in use. (Due to a change in the default "<em>sqlType</em>" storage for Oracle Database 21c, the metadata is explicitly stated to use a BLOB column. This lets the example run with different client and database versions).</p>

      <p><code>insertOneAndGet()</code> inserts the content of a document into the database and returns a SODA Document Object.
This allows access to metadata such as the document key. By default, document keys are automatically generated.</p>

      <p>The <code>find()</code> method is used to begin an operation that will act upon documents in the collection.</p>

      <p><code>content</code> is a dictionary.  You can also get a JSON string by calling <code>doc.getContentAsString()</code>.</p>

      <p>Run the file:</p>

<pre><strong>python soda.py</strong></pre>

      <p>The output shows the content of the new document.</p>

    </li>

    <li>
      <h4>15.2 Searching SODA Documents</h4>

      <p>Extend <code>soda.py</code> to insert some more documents and perform a find filter operation:</p>

<pre>
my_docs = [
    {'name': 'Gerald', 'age': 21, 'address': {'city': 'London'}},
    {'name': 'David', 'age': 28, 'address': {'city': 'Melbourne'}},
    {'name': 'Shawn', 'age': 20, 'address': {'city': 'San Francisco'}}
]
collection.insertMany(my_docs)

filter_spec = { "address.city": "Melbourne" }
my_documents = collection.find().filter(filter_spec).getDocuments()

print('Melbourne people:')
for doc in my_documents:
    print(doc.getContent()["name"])
</pre>

      <p>Run the script again:</p>

      <pre><strong>python soda.py</strong></pre>

      <p>The find operation filters the collection and returns documents where the city is Melbourne.  Note the
 <code>insertMany()</code> method is currently in preview.</p>

      <p>SODA supports query by example (QBE) with an extensive set of
      operators.  Extend <code>soda.py</code> with a QBE to find
      documents where the age is less than 25:</p>

<pre>
filter_spec = {'age': {'$lt': 25}}
my_documents = collection.find().filter(filter_spec).getDocuments()

print('Young people:')
for doc in my_documents:
    print(doc.getContent()["name"])
</pre>

<p>Running the script displays the names.</p>

    </li>
  </ul>

  <h2><a name="summary">Summary</a></h2>
  <p>In this tutorial, you have learned how to: </p>
  <ul>
    <li>Install the python-oracledb driver and use thin and thick modes</li>
    <li>Create and work with connections</li>
    <li>Use python-oracledb's connection pooling and Database Resident Connection Pooling</li>
    <li>Execute queries and fetch data</li>
    <li>Use bind variables</li>
    <li>Use PL/SQL stored functions and procedures</li>
    <li>Extend python-oracledb classes</li>
    <li>Use scrollable cursors</li>
    <li>Work with named objects</li>
    <li>Use Oracle Advanced Queuing</li>
    <li>Use the SODA document store API</li>
  </ul>

  <p>For further reading, see the <a
  href="https://python-oracledb.readthedocs.io/en/latest/index.html" >python-oracledb documentation</a>.</p>

  <h2><a name="primer">Appendix: Python Primer</a></h2>

  <p>Python is a dynamically typed scripting language. It is most often used to run command-line scripts but is also used for web applications and web services.</p>

  <h4>Running Python</h4>

<p> You can either:</p>

  <ul>

    <li><p>Create a file of Python commands, such as
      <code>myfile.py</code>.  This can be run with:</p>
      <pre><strong>python myfile.py</strong></pre></li>

    <li><p>Alternatively run the Python interpreter by executing the <code>python</code> command in a terminal, and then interactively enter commands. Use <strong>Ctrl-D</strong> to exit back to the operating system prompt.</p></li>

</ul>

    <p>On some machines, you may need to run the <code>python3</code> command instead of <code>python</code>. </p>
    <p>When you run scripts, Python automatically creates bytecode versions of them in a folder called <code>__pycache__</code>.
    These improve the performance of scripts that are run multiple times. They are automatically recreated if the source file changes.</p>

    <h4>Indentation</h4>

    <p> Whitespace indentation is significant in Python.  When copying examples, use the same column alignment as shown. The samples in this tutorial use spaces, not tabs. </p>

    <p>The following indentation prints 'done' once after the loop has completed:</p>

<pre>
for i in range(5):
    print(i)
print('done')
</pre>

    <p>But this indentation prints 'done' in each iteration:</p>

<pre>
for i in range(5):
    print(i)
    print('done')
</pre>

<h4>Strings</h4>

<p> Python strings can be enclosed in
    single or double quotes:</p>

  <pre>'A string constant'
&quot;another constant&quot;</pre>
  <p>Multi line strings use a triple-quote syntax:</p>
  <pre>&quot;&quot;&quot;
SELECT *
FROM EMP
&quot;&quot;&quot;</pre>

    <h4>Variables</h4>

<p> Variables do not need types declared:</p>
  <pre>count = 1
ename = 'Arnie'</pre>

    <h4>Comments</h4>

<p> Comments can be single line:</p>
  <pre># a short comment</pre>
  <p>Or they can be multi-line using the triple-quote token to create a string that does nothing:</p>
  <pre>&quot;&quot;&quot;
a longer
comment
&quot;&quot;&quot;
</pre>

    <h4>Printing</h4>

<p> Strings and variables can be displayed with a <code>print()</code> function:</p>
  <pre>print('Hello, World!')
print('Value:', count)</pre>

    <h4>Data Structures</h4>

    <p>Associative arrays are called 'dictionaries':</p>
    <pre>a2 = {'PI':3.1415, 'E':2.7182}</pre>
    <p>Ordered arrays are called 'lists':</p>
    <pre>a3 = [101, 4, 67]</pre>
    <p>Lists can be accessed via indexes.</p>
    <pre>
print(a3[0])
print(a3[-1])
print(a3[1:3])
</pre>

  <p>Tuples are like lists but cannot be changed once they are
  created. They are created with parentheses:</p>

  <pre>a4 = (3, 7, 10)</pre>

  <p>Individual values in a tuple can be assigned to variables like:</p>

  <pre>v1, v2, v3 = a4</pre>

  <p>Now the variable v1 contains 3, the variable v2 contains 7 and the variable v3 contains 10.</p>

  <p>The value in a single entry tuple like "<code>(13,)</code>"can be
  assigned to a variable by putting a comma after the variable name
  like:</p>

  <pre>v1, = (13,)</pre>

  <p>If the assignment is:</p>

  <pre>v1 = (13,)</pre>

  <p>then <code>v1</code> will contain the whole tuple "<code>(13,)</code>"</p>

    <h4>Objects</h4>

<p>Everything in Python is an object. As an example, given the of the list <code>a3</code> above, the <code>append()</code> method can be used to add a value to the list.</p>

  <pre>a3.append(23)</pre>
  <p>Now <code>a3</code> contains <code>[101, 4, 67, 23]</code></p>

<h4>Flow Control</h4>

<p> Code flow can be controlled with tests and loops. The
<code>if</code>/<code>elif</code>/<code>else</code> statements look like:</p>

<pre>
if v == 2 or v == 4:
    print('Even')
elif v == 1 or v == 3:
    print('Odd')
else:
    print('Unknown number')
</pre>

<p>This also shows how the clauses are delimited with colons, and each sub-block of code is indented.</p>

<h4>Loops</h4>

  <p>A traditional loop is:</p>
  <pre>for i in range(10):
    print(i)</pre>

  <p>This prints the numbers from 0 to 9. The value of <code>i</code>
    is incremented in each iteration. </p>

  <p>The '<code>for</code>' command can also be used to iterate over lists and tuples:</p>

 <pre>
a5 = ['Aa', 'Bb', 'Cc']
for v in a5:
    print(v)
</pre>

<p>This sets <code>v</code> to each element of the list
<code>a5</code> in turn.</p>

<h4>Functions</h4>

<p> A function may be defined as:</p>

<pre>
def myfunc(p1, p2):
    &quot;Function documentation: add two numbers&quot;
    print(p1, p2)
    return p1 + p2</pre>

<p>Functions may or may not return values. This function could be called using:</p>

<pre>v3 = myfunc(1, 3)</pre>

<p>Function calls must appear after their function definition.</p>

<p>Functions are also objects and have attributes. The inbuilt
<code>__doc__</code> attribute can be used to find the function description:</p>

  <pre>print(myfunc.__doc__)</pre>

<h4>Modules</h4>

<p> Sub-files can be included in Python scripts with an import statement.</p>
  <pre>import os
import sys</pre>
  <p>Many predefined modules exist, such as the os and the sys modules.</p>


<h2><a name="resources">Resources</a></h2>

<ul>
  <li><a href="https://docs.python.org/3/" >Python Documentation</a></li>
  <li><a href="http://python-oracledb.readthedocs.io/en/latest/index.html" >Python python-oracledb Documentation</a></li>
    <li><a href="https://github.com/oracle/python-oracledb/tree/main/samples" >Python-oracledb Source Code Repository Samples</a></li>
</ul>

<div class="footer"></div>

<hr/>
<h2>License</h2>
<p>Copyright &copy; 2017, 2022, Oracle and/or its affiliates. </p>

<p>This software is dual-licensed to you under the Universal Permissive License
(UPL) 1.0 as shown at https://oss.oracle.com/licenses/upl and Apache License
2.0 as shown at http://www.apache.org/licenses/LICENSE-2.0. You may choose
either license. </p>
<p>If you elect to accept the software under the Apache License, Version 2.0,
the following applies: </p>
<p>Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at </p>
<p>
   https://www.apache.org/licenses/LICENSE-2.0
 </p>
<p>Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. </p>

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