possible for example to debug query execution results
          using <literal>plpy.debug(rv)</literal>.
         </para>
        </listitem>
       </varlistentry>
      </variablelist>
     </para>

     <para>
      The result object can be modified.
     </para>

     <para>
      Note that calling <literal>plpy.execute</literal> will cause the entire
      result set to be read into memory.  Only use that function when you are
      sure that the result set will be relatively small.  If you don't want to
      risk excessive memory usage when fetching large results,
      use <literal>plpy.cursor</literal> rather
      than <literal>plpy.execute</literal>.
     </para>
    </listitem>
   </varlistentry>

   <varlistentry>
    <term><literal>plpy.<function>prepare</function>(<replaceable>query</replaceable> [, <replaceable>argtypes</replaceable>])</literal></term>
    <term><literal>plpy.<function>execute</function>(<replaceable>plan</replaceable> [, <replaceable>arguments</replaceable> [, <replaceable>limit</replaceable>]])</literal></term>
    <listitem>
     <para>
      <indexterm><primary>preparing a query</primary><secondary>in PL/Python</secondary></indexterm>
      <function>plpy.prepare</function> prepares the execution plan for a
      query.  It is called with a query string and a list of parameter types,
      if you have parameter references in the query.  For example:
<programlisting>
plan = plpy.prepare("SELECT last_name FROM my_users WHERE first_name = $1", ["text"])
</programlisting>
      <literal>text</literal> is the type of the variable you will be passing
      for <literal>$1</literal>.  The second argument is optional if you don't
      want to pass any parameters to the query.
     </para>
     <para>
      After preparing a statement, you use a variant of the
      function <function>plpy.execute</function> to run it:
<programlisting>
rv = plpy.execute(plan, ["name"], 5)
</programlisting>
      Pass the plan as the first argument (instead of the query string), and a
      list of values to substitute into the query as the second argument.  The
      second argument is optional if the query does not expect any parameters.
      The third argument is the optional row limit as before.
     </para>

     <para>
      Alternatively, you can call the <function>execute</function> method on
      the plan object:
<programlisting>
rv = plan.execute(["name"], 5)
</programlisting>
     </para>

     <para>
      Query parameters and result row fields are converted between PostgreSQL
      and Python data types as described in <xref linkend="plpython-data"/>.
     </para>

     <para>
      When you prepare a plan using the PL/Python module it is automatically
      saved.  Read the SPI documentation (<xref linkend="spi"/>) for a
      description of what this means.  In order to make effective use of this
      across function calls one needs to use one of the persistent storage
      dictionaries <literal>SD</literal> or <literal>GD</literal> (see
      <xref linkend="plpython-sharing"/>). For example:
<programlisting>
CREATE FUNCTION usesavedplan() RETURNS trigger AS $$
    if "plan" in SD:
        plan = SD["plan"]
    else:
        plan = plpy.prepare("SELECT 1")
        SD["plan"] = plan
    # rest of function
$$ LANGUAGE plpython3u;
</programlisting>
     </para>
    </listitem>
   </varlistentry>

   <varlistentry>
    <term><literal>plpy.<function>cursor</function>(<replaceable>query</replaceable>)</literal></term>
    <term><literal>plpy.<function>cursor</function>(<replaceable>plan</replaceable> [, <replaceable>arguments</replaceable>])</literal></term>
    <listitem>
     <para>
      The <literal>plpy.cursor</literal> function accepts the same arguments
      as <literal>plpy.execute</literal> (except for the row limit) and returns
      a cursor object, which allows you to process large result sets in smaller
      chunks.  As with <literal>plpy.execute</literal>, either a query string
      or