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  <h1>Python and Oracle Database Tutorial: Scripting for the Future</h1>

  <img src="resources/community-py-200.png" alt="Python cx_Oracle logo" />

  <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>
      </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 Scrollable cursors</li>
        <li>3.5 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>
        <li>4.4 Binding named objects</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="#aq">Advanced Queuing</a>
      <ul>
        <li>10.1 Message passing with Oracle Advanced Queuing</li>
      </ul>
    </li>
    <li><a href="#soda">Simple Oracle Document Access (SODA)</a>
      <ul>
        <li>11.1 Inserting JSON Documents</li>
        <li>11.2 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>

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

  <p>This tutorial is an introduction to using Python with Oracle Database.  It
  contains beginner and advanced material.  Sections can be done in any order.
  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
  cx_Oracle interface provides the Python API to access Oracle Database.</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://cx-oracle.readthedocs.org/en/latest/index.html" >cx_Oracle
  documention</a>. </p>

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

  <h3><a name="architecture">cx_Oracle Architecture</a></h3>

  <p>Python programs call cx_Oracle functions. Internally cx_Oracle dynamically
  loads Oracle Client libraries to access Oracle Database. The database can be
  on the same machine as Python, or it can be remote. If the database is local,
  the client libraries from the Oracle Database software installation can be
  used.</p>

  <img src="resources/cx_Oracle_arch.png" alt="Python cx_Oracle architecture" width=800/>


  <h2><a name="preface">Setup</a></h2>

  <ul>

    <li>
      <h4>Install software</h4>

      <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>


      <p>For this tutorial, you will need <a href="https://www.python.org/"
      >Python</a> 3.6 (or later), <a href="https://pypi.org/project/cx-Oracle/"
      >cx_Oracle</a> 7.3 (or later), and access to Oracle Database.</p>

      <p>The Advanced Queuing section requires Python cx_Oracle to be using
      Oracle client libraries 12.2 or later.  The SODA section requires Oracle
      Database 18 or later, and Python cx_Oracle must be using Oracle libraries
      from 18.5, or later.</p>

      </li>


      <li>
        <h4>Download the tutorial scripts</h4>

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

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

      </li>

      <li><h4>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, review the grants created in
          <code>samples/tutorial/sql/create_user.sql</code>.  Then open a terminal
          window, change to the <code>samples/tutorial/sql</code> directory, and
          run the <code>create_user.sql</code> script as the SYSTEM user, for
          example:</p>

<pre>
cd samples/tutorial/sql
sqlplus -l system/systempassword@localhost/orclpdb1 @create_user
</pre>

          <p>The example above connects as the SYSTEM user.  The connection
          string is "localhost/orclpdb1", meaning use the database service
          "orclpdb1" running on localhost (the computer you are running SQL*Plus
          on). Substitute values for your environment.  If you are using Oracle
          Autonomous Database, use the ADMIN user instead of SYSTEM.</p>

         <p>When the tutorial is finished, the <code>drop_user.sql</code> script
         in the same directory can be used to remove the tutorial user.</p>

      </li>

      <li><h4>Install the sample tables</h4>

          <p>Once you have a database user, then you can create the tutorial
          tables by running a command like this, using your values for the
          tutorial username, password and connection string:</p>

<pre>
sqlplus -l pythonhol/welcome@localhost/orclpdb1 @setup_tables
</pre>

        </li>

        <li><h4>Start the Database Resident Connection Pool (DRCP)</h4>

          <p>If you want to try the DRCP examples in section 2, start the DRCP
          pool.  (The pool is already started in Oracle Autonomous Database).</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 you may need to do this in the container database, not a pluggable database.</p>

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

          <p>Review <code>db_config.py</code> and <code>db_config.sql</code> in
          the <code>tutorial</code> directory.  These are included in other
          Python and SQL files. </p>

          <p>Edit <code>db_config.py</code> and change the default values to
          match the connection information for your environment.  Alternatively
          you can set the given envionment variables in your terminal
          window. For example, the default username is "pythonhol" unless the
          envionment variable "PYTHON_USER" contains a different username.  The
          default connection string is for the 'orclpdb1' 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 envionment 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", "pythonhol")

dsn = os.environ.get("PYTHON_CONNECT_STRING", "localhost/orclpdb1")

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*Plus
configuration file <code>db_config.sql</code>:</p>

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

-- Default database connection string
def connect_string = "localhost/orclpdb1"

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


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

        <li>
          <h4>Review the Instant Client library path</h4>

          <p>Review the Oracle Client library path settings in
          <code>db_config.py</code>.  If cx_Oracle cannot locate Oracle Client
          libraries, then your applications will fail with an error like
          "DPI-1047: Cannot locate a 64-bit Oracle Client library".</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"..."  so backslashes can
# be used as directory separators.
if sys.platform.startswith("win"):
    instant_client_dir = r"c:\oracle\instantclient_19_10"

# On macOS (Intel x86) set the directory to your Instant Client directory
if sys.platform.startswith("darwin"):
    instant_client_dir = os.environ.get("HOME")+"/Downloads/instantclient_19_8"

# This can be called at most once per process.
if instant_client_dir is not None:
    cx_Oracle.init_oracle_client(lib_dir=instant_client_dir)
</pre>

          <p>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 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 ldconfig or with the
              LD_LIBRARY_PATH environment variables.</p>

            </li>

          </ul>

        </li>
  </ul>

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

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

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

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

          <p>The cx_Oracle 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 <code>connect()</code> method is passed the username, the
          password and the connection string that you configured in the
          db_config.py module. In this case, 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>orclpdb1</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>cx_Oracle also supports "external authentication", which allows
          connections without needing usernames and passwords to be embedded in
          the code. Authentication would then instead be performed by, for
          example, LDAP or Oracle Wallets.</p>

        </li>

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

          <p>There are no statement terminators or begin/end keywords
          or braces to indicate blocks of code.</p>

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

          <pre>
import cx_Oracle
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, 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. <i>Check your indentation is
          correct before running each example.  Make sure to indent
          all statement blocks equally.</i> <b>Note 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 cx_Oracle
import db_config

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

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

          <pre>
import cx_Oracle
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, 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><i>Make sure the <code>print(row)</code> line is indented.  This lab uses spaces, not tabs.</i></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> 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 cx_Oracle 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 cx_Oracle
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, 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 cx_Oracle
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, db_config.dsn)

print(cx_Oracle.version)</pre>

          <p>Run the script:</p>

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

          <p>This gives the version of the cx_Oracle interface.</p>

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

          <pre>
import cx_Oracle
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, db_config.dsn)

print(cx_Oracle.version)
<strong>print("Database version:", con.version)
print("Client version:", cx_Oracle.clientversion())</strong>
</pre>

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

          <pre>
7.1.0
Database version: 19.3.0.0.0
Client version: (19, 8, 0, 0, 0)
</pre>

          <p>Note the client version is a tuple.</p>

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

        </li>

      </ul>

    <h2><a name="pooling">2. Connection Pooling</a></h2>

      <p>Connection pooling is important for performance in when multi-threaded
      applications frequently connect and disconnect from the database. Pooling
      also gives the best support for Oracle high availability features.
      <i>Documentation link for further reading: <a
      href="https://cx-oracle.readthedocs.io/en/latest/user_guide/connection_handling.html#connection-pooling"
      >Connection Pooling</a></i>.</p>

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

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

pool = cx_Oracle.<strong>SessionPool</strong>(db_config.user, db_config.pw, db_config.dsn,
                             min = 2, max = 5, increment = 1, threaded = True,
                             getmode = cx_Oracle.SPOOL_ATTRVAL_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>SessionPool()</code> function creates a pool of
          Oracle connections for the user.  Connections in the pool can
          be used by cx_Oracle 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 1 new connection
          will be created at a time.  The pool can shrink back to the
          minimum size of 2 when 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 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, cx_Oracle 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 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 cx_Oracle
import threading
import db_config

pool = cx_Oracle.SessionPool(db_config.user, db_config.pw, db_config.dsn,
                             min = 2, max = 5, increment = 1, threaded = True,
                             getmode = cx_Oracle.SPOOL_ATTRVAL_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>cx_Oracle.SPOOL_ATTRVAL_NOWAIT</code>.  When <code>numberOfThreads</code>
exceeds the maximum size of the pool, the <code>acquire()</code> call will now
generate an error such as "ORA-24459: OCISessionGet() timed out waiting for pool
to create new connections".  </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.  This 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 cx_Oracle 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.
  cx_Oracle connection pools reduce these costs by keeping database server
  processes open, but every cx_Oracle connection pool will requires its own set
  of database server processes, even if they are not doing database work: these
  idle server processes consumes database host resources.  Below right is a
  diagram with DRCP.  Scripts and Python processes can share database servers
  from a precreated 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 cx_Oracle's connection pooling.
  However, if the database host memory is large enough, then the default,
  'dedicated' server process model is generally recommended.  This can be with
  or without a cx_Oracle 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>

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

  <pre>
import cx_Oracle
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, db_config.dsn + "<strong>:pooled</strong>",
                        cclass=&quot;PYTHONHOL&quot;, purity=cx_Oracle.ATTR_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 "PYTHONHOL" is also
  passed into the <code>connect()</code> method to allow grouping of database
  servers to applications.  Note 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>ATTR_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>ATTR_PURITY_NEW</code> to force creation of a new
  session. This reduces overall scalability but prevents applications
  mis-using session information.</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 cx_Oracle's connection pooling.</p>

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

pool = cx_Oracle.SessionPool(db_config.user, db_config.pw, db_config.dsn <strong>+ ":pooled"</strong>,
                             min = 2, max = 5, increment = 1, threaded = True,
                             getmode = cx_Oracle.SPOOL_ATTRVAL_WAIT)

def Query():
    con = pool.acquire(<strong>cclass = "PYTHONHOL", purity = cx_Oracle.ATTR_PURITY_SELF</strong>)
    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>Review <strong>drcp_query.sql</strong> and set the connection string to
      your database.  Then open a new a terminal window and invoke SQL*Plus:</p>

      <pre><strong>sqlplus /nolog @drcp_query.sql</strong></pre>

      <p>This will prompt for the SYSTEM password and the database connection
      string.  With Pluggable databases, you will need to connect to the
      container database.  Note that with ADB, this view does not contain
      rows, so running this script is not useful.</p>

      <p>For other 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>To see the pool configuration you can query DBA_CPOOL_INFO.</p>
    </li>

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

      <p>To explore the behaviors of cx_Oracle connection pooling and DRCP pooling futher,
      you could try changing the purity to
      <code>cx_Oracle.ATTR_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.  <i>Documentation link for further reading: <a
  href="https://cx-oracle.readthedocs.io/en/latest/user_guide/sql_execution.html"
  >SQL Queries</a></i>.</p>

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

  <p>There are a number of 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 cx_Oracle
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, 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 cx_Oracle
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, 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 cx_Oracle
import db_config

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

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

  <p>The <code>fetchmany()</code> method returns a list of tuples. By
  default the number of rows 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 Scrollable cursors</h4>

    <p>Scrollable cursors enable the application 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>

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

    <pre>
import cx_Oracle
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, db_config.dsn)
cur = con.cursor(scrollable = True)

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>

  <li><h4>3.5 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 both 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>First, create a table with a large number of rows.
  Review <code>query_arraysize.sql</code>:</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;
/
show errors

commit;
</pre>

    <p>In a terminal window run the script as:</p>

    <pre><strong>sqlplus /nolog @query_arraysize.sql</strong></pre>

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

<pre>
import cx_Oracle
import time
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, 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
    prefetchrows and arraysize 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
    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 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.
  <i>Documentation link for further reading: <a
  href="https://cx-oracle.readthedocs.io/en/latest/user_guide/bind.html" >Using
  Bind Variables</a></i>.</p>

  <ul>

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

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

<pre>
import cx_Oracle
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, 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>cx_Oracle uses Oracle Database's Statement Cache.  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>In your applications you would set the statement cache size to the
      number of unique statements commonly executed.</p>

    </li>

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

  <p>Review the code in <code>bind_insert.sql </code> creating a table
  for inserting data:</p>

<pre>
create table mytab (id number, data varchar2(20), constraint my_pk primary key (id));
</pre>

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

  <pre><strong>sqlplus /nolog @bind_insert.sql</strong></pre>

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

<pre>
import cx_Oracle
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, 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.</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 it will always show the same number of
      rows in the table.</p>

    </li>

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

      <p>The Batcherrors 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 cx_Oracle
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, 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 (PYTHONHOL.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, cx_Oracle will roll back an uncommitted transaction. If you want to commit results, you can use:</p>

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

      <p>To force cx_Oracle to roll back, use:</p>

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

</li>

<li><h4>4.4 Binding named objects</h4>

  <p>cx_Oracle can fetch and bind named object types such as Oracle's
  Spatial Data Objects (SDO).</p>

  <p>In a terminal window, start SQL*Plus using the lab credentials and connection string, such as:</p>

  <pre>
sqlplus -l pythonhol/welcome@localhost/orclpdb1
</pre>

  <p>Use the SQL*Plus DESCRIBE command to look at the SDO definition:</p>

  <pre>
desc MDSYS.SDO_GEOMETRY
</pre>

  <p>It contains various attributes and methods.  The top level description is:</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>

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

<pre>
import cx_Oracle
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, 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
typeObj = con.<strong>gettype</strong>("MDSYS.SDO_GEOMETRY")
elementInfoTypeObj = con.<strong>gettype</strong>("MDSYS.SDO_ELEM_INFO_ARRAY")
ordinateTypeObj = con.<strong>gettype</strong>("MDSYS.SDO_ORDINATE_ARRAY")
obj = typeObj.<strong>newobject()</strong>
obj.SDO_GTYPE = 2003
obj.SDO_ELEM_INFO = elementInfoTypeObj.<strong>newobject()</strong>
obj.SDO_ELEM_INFO.<strong>extend</strong>([1, 1003, 3])
obj.SDO_ORDINATES = ordinateTypeObj.<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;cx_Oracle.Object MDSYS.SDO_GEOMETRY at 0x104a76230&gt;)</pre>

<p>To show the attribute values, edit the 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, cx_Oracle.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, cx_Oracle.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="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.  <i>Documentation link
  for further reading: <a
  href="https://cx-oracle.readthedocs.io/en/latest/user_guide/plsql_execution.html"
  >PL/SQL Execution</a></i>.</p>

  <ul>
    <li><h4>5.1 PL/SQL functions</h4>

      <p>Review <code>plsql_func.sql</code> which creates a PL/SQL
      stored function <code>myfunc()</code> to insert a row into a new
      table named <b>ptab</b> and return double the inserted
      value:</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>Run the script using: </p>

      <pre><strong>sqlplus /nolog @plsql_func.sql</strong></pre>

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

<pre>
import cx_Oracle
import db_config

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

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

      <p>This uses <code>callfunc()</code> to execute the function.
      The second parameter is the type of the returned value. It should be one
      of the types supported by cx_Oracle or one of the type constants defined
      by cx_Oracle (such as cx_Oracle.NUMBER). 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>Review <code>plsql_proc.sql</code> which creates a PL/SQL procedure
<code>myproc()</code> to accept two parameters. The second parameter
contains an OUT return value. </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>Run the script with:</p>

<pre><strong>sqlplus /nolog @plsql_proc.sql</strong></pre>

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

<pre>
import cx_Oracle
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, 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. <i>Documentation links for further reading: <a
href="https://cx-oracle.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://cx-oracle.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></i>.</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
      string 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 cx_Oracle
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, 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 == cx_Oracle.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
      maxium 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 cx_Oracle
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, 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 cx_Oracle
<strong>import decimal</strong>
import db_config

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

<strong>def ReturnNumbersAsDecimal(cursor, name, defaultType, size, precision, scale):
    if defaultType == cx_Oracle.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>Although the code demonstrates the use of outconverter, in this
      particular case, the variable can be created simply by using the
      following code to replace the outputtypehandler function defined
      above:</p>

<pre>
def ReturnNumbersAsDecimal(cursor, name, defaultType, size, precision, scale):
    if defaultType == cx_Oracle.NUMBER:
        return cursor.var(decimal.Decimal, arraysize = cursor.arraysize)
</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>, which is similar to the
      final <code>bind_sdo.py</code> from section 4.4, with the
      addition of a new class and converter (shown in bold):</p>

<pre>
import cx_Oracle
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, 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

# Get Oracle type information
objType = con.gettype("MDSYS.SDO_GEOMETRY")
elementInfoTypeObj = con.gettype("MDSYS.SDO_ELEM_INFO_ARRAY")
ordinateTypeObj = con.gettype("MDSYS.SDO_ORDINATE_ARRAY")

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

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

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))</strong>

# 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, cx_Oracle.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, cx_Oracle.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>In the new file, a Python class <code>mySDO</code> is defined,
which has attributes corresponding to each Oracle MDSYS.SDO_GEOMETRY
attribute.

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

<pre>
sdo = mySDO(2003, [1, 1003, 3], [1, 1, 5, 7])</pre>

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

<pre>cur.execute("insert into testgeometry values (:1, :2)", (1, sdo))</pre>

<p>The mapping between Python and Oracle objects is handled in
<code>SDOInConverter</code> which uses the cx_Oracle
<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.py</strong></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. <i>Documentation link
  for further reading: <a
  href="https://cx-oracle.readthedocs.io/en/latest/user_guide/lob_data.html"
  >Using CLOB and BLOB Data</a></i>.</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 cx_Oracle
import db_config

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

print("Inserting data...")
cur.execute("truncate table testclobs")
longString = ""
for i in range(5):
    char = chr(ord('A') + i)
    longString += 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 cx_Oracle 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 cx_Oracle
import db_config

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

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

<strong>def OutputTypeHandler(cursor, name, defaultType, size, precision, scale):
    if defaultType == cx_Oracle.CLOB:
        return cursor.var(cx_Oracle.LONG_STRING, arraysize = cursor.arraysize)

con.outputtypehandler = OutputTypeHandler</strong>

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>The OutputTypeHandler causes cx_Oracle 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 cx_Oracle
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, 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 which take the values of each row
  tuple.</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 cx_Oracle functionality. <i>Documentation link for
  further reading: <a
  href="https://cx-oracle.readthedocs.io/en/latest/user_guide/tracing_sql.html"
  >Tracing SQL and PL/SQL Statements</a></i>.</p>

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

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

  <pre>
import cx_Oracle
import db_config

class MyConnection(cx_Oracle.Connection):

    def __init__(self):
        print("Connecting to database")
        return super(MyConnection, self).__init__(db_config.user, db_config.pw, 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
  cx_Oracle 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 cx_Oracle 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 cx_Oracle
import db_config

class MyConnection(cx_Oracle.Connection):

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

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

class MyCursor(cx_Oracle.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="aq">10. Advanced Queuing</a></h2>

<p>Oracle Advanced Queuing (AQ) allows messages to be passed between
applications. <i>Documentation link for further reading: <a
href="https://cx-oracle.readthedocs.io/en/latest/user_guide/aq.html" >Oracle
Advanced Queuing (AQ)</a></i>.</p>

  <ul>
    <li><h4>10.1 Message passing with Oracle Advanced Queuing</h4>

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

<pre>
import cx_Oracle
import decimal
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, 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,))

booksType = 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 = booksType.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 = cx_Oracle.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 cx_Oracle 7.2.</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 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 = cx_Oracle.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, 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">11. 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. <i>Documentation link for further reading: <a
  href="https://cx-oracle.readthedocs.io/en/latest/user_guide/soda.html" >Simple
  Oracle Document Access (SODA)</a></i>.</p>

  <ul>

    <li><h4>11.1 Inserting JSON Documents</h4>

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

<pre>
import cx_Oracle
import db_config

con = cx_Oracle.connect(db_config.user, db_config.pw, 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 "sqlType" 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 meta data 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>11.2 Searching SODA Documents</h4>

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

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

filterSpec = { "address.city": "Melbourne" }
myDocuments = collection.find().filter(filterSpec).getDocuments()

print('Melbourne people:')
for doc in myDocuments:
    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>
filterSpec = {'age': {'$lt': 25}}
myDocuments = collection.find().filter(filterSpec).getDocuments()

print('Young people:')
for doc in myDocuments:
    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>Create connections</li>
    <li>Use cx_Oracle 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 cx_Oracle classes</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://cx-oracle.readthedocs.io/en/latest/index.html" >cx_Oracle
  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>When you run scripts, Python automatically creates bytecode
    versions of them in a folder called <code>__pycache__</code>.
    These improve 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 lab 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 are either single line:</p>
  <pre># a short comment</pre>
  <p>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://cx-oracle.readthedocs.io/en/latest/index.html" >Python cx_Oracle Documentation</a></li>
  <li><a href="https://github.com/oracle/python-cx_Oracle" >Python cx_Oracle Source Code Repository</a></li>
</ul>

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