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<div class="section" id="remarks-on-adaptation-and-typecasting">
<h1>Remarks on Adaptation and Typecasting<a class="headerlink" href="#remarks-on-adaptation-and-typecasting" title="Permalink to this headline">¶</a></h1>
<p>Both PostgreSQL and Python have the concept of data types, but there
are of course differences between the two type systems. Therefore PyGreSQL
needs to adapt Python objects to the representation required by PostgreSQL
when passing values as query parameters, and it needs to typecast the
representation of PostgreSQL data types returned by database queries to
Python objects. Here are some explanations about how this works in
detail in case you want to better understand or change the default
behavior of PyGreSQL.</p>
<div class="section" id="supported-data-types">
<h2>Supported data types<a class="headerlink" href="#supported-data-types" title="Permalink to this headline">¶</a></h2>
<p>The following automatic data type conversions are supported by PyGreSQL
out of the box. If you need other automatic type conversions or want to
change the default conversions, you can achieve this by using the methods
explained in the next two sections.</p>
<table border="1" class="docutils">
<colgroup>
<col width="65%" />
<col width="35%" />
</colgroup>
<thead valign="bottom">
<tr class="row-odd"><th class="head">PostgreSQL</th>
<th class="head">Python</th>
</tr>
</thead>
<tbody valign="top">
<tr class="row-even"><td>char, bpchar, name, text, varchar</td>
<td>str</td>
</tr>
<tr class="row-odd"><td>bool</td>
<td>bool</td>
</tr>
<tr class="row-even"><td>bytea</td>
<td>bytes</td>
</tr>
<tr class="row-odd"><td>int2, int4, int8, oid, serial</td>
<td>int <a class="footnote-reference" href="#int8" id="id1">[1]</a></td>
</tr>
<tr class="row-even"><td>int2vector</td>
<td>list of int</td>
</tr>
<tr class="row-odd"><td>float4, float8</td>
<td>float</td>
</tr>
<tr class="row-even"><td>numeric, money</td>
<td>Decimal</td>
</tr>
<tr class="row-odd"><td>date</td>
<td>datetime.date</td>
</tr>
<tr class="row-even"><td>time, timetz</td>
<td>datetime.time</td>
</tr>
<tr class="row-odd"><td>timestamp, timestamptz</td>
<td>datetime.datetime</td>
</tr>
<tr class="row-even"><td>interval</td>
<td>datetime.timedelta</td>
</tr>
<tr class="row-odd"><td>hstore</td>
<td>dict</td>
</tr>
<tr class="row-even"><td>json, jsonb</td>
<td>list or dict</td>
</tr>
<tr class="row-odd"><td>uuid</td>
<td>uuid.UUID</td>
</tr>
<tr class="row-even"><td>array</td>
<td>list <a class="footnote-reference" href="#array" id="id2">[2]</a></td>
</tr>
<tr class="row-odd"><td>record</td>
<td>tuple</td>
</tr>
</tbody>
</table>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p>Elements of arrays and records will also be converted accordingly.</p>
<table class="docutils footnote" frame="void" id="int8" rules="none">
<colgroup><col class="label" /><col /></colgroup>
<tbody valign="top">
<tr><td class="label"><a class="fn-backref" href="#id1">[1]</a></td><td>int8 is converted to long in Python 2</td></tr>
</tbody>
</table>
<table class="last docutils footnote" frame="void" id="array" rules="none">
<colgroup><col class="label" /><col /></colgroup>
<tbody valign="top">
<tr><td class="label"><a class="fn-backref" href="#id2">[2]</a></td><td>The first element of the array will always be the first element
of the Python list, no matter what the lower bound of the PostgreSQL
array is. The information about the start index of the array (which is
usually 1 in PostgreSQL, but can also be different from 1) is ignored
and gets lost in the conversion to the Python list. If you need that
information, you can request it separately with the <cite>array_lower()</cite>
function provided by PostgreSQL.</td></tr>
</tbody>
</table>
</div>
</div>
<div class="section" id="adaptation-of-parameters">
<h2>Adaptation of parameters<a class="headerlink" href="#adaptation-of-parameters" title="Permalink to this headline">¶</a></h2>
<p>When you use the higher level methods of the classic <a class="reference internal" href="index.html#module-pg" title="pg"><code class="xref py py-mod docutils literal"><span class="pre">pg</span></code></a> module like
<a class="reference internal" href="db_wrapper.html#pg.DB.insert" title="pg.DB.insert"><code class="xref py py-meth docutils literal"><span class="pre">DB.insert()</span></code></a> or <a class="reference internal" href="db_wrapper.html#pg.DB.update" title="pg.DB.update"><code class="xref py py-meth docutils literal"><span class="pre">DB.update()</span></code></a>, you don’t need to care about
adaptation of parameters, since all of this is happening automatically behind
the scenes. You only need to consider this issue when creating SQL commands
manually and sending them to the database using the <a class="reference internal" href="db_wrapper.html#pg.DB.query" title="pg.DB.query"><code class="xref py py-meth docutils literal"><span class="pre">DB.query()</span></code></a> method.</p>
<p>Imagine you have created a user login form that stores the login name as
<em>login</em> and the password as <em>passwd</em> and you now want to get the user
data for that user. You may be tempted to execute a query like this:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">db</span> <span class="o">=</span> <span class="n">pg</span><span class="o">.</span><span class="n">DB</span><span class="p">(</span><span class="o">...</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">sql</span> <span class="o">=</span> <span class="s">"SELECT * FROM user_table WHERE login = '%s' AND passwd = '%s'"</span>
<span class="gp">>>> </span><span class="n">db</span><span class="o">.</span><span class="n">query</span><span class="p">(</span><span class="n">sql</span> <span class="o">%</span> <span class="p">(</span><span class="n">login</span><span class="p">,</span> <span class="n">passwd</span><span class="p">))</span><span class="o">.</span><span class="n">getresult</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span>
</pre></div>
</div>
<p>This seems to work at a first glance, but you will notice an error as soon as
you try to use a login name containing a single quote. Even worse, this error
can be exploited through a so called “SQL injection”, where an attacker inserts
malicious SQL statements into the query that you never intended to be executed.
For instance, with a login name something like <code class="docutils literal"><span class="pre">'</span> <span class="pre">OR</span> <span class="pre">''='</span></code> the user could
easily log in and see the user data of another user in the database.</p>
<p>One solution for this problem would be to clean your input from “dangerous”
characters like the single quote, but this is tedious and it is likely that
you overlook something or break the application e.g. for users with names
like “D’Arcy”. A better solution is to use the escaping functions provided
by PostgreSQL which are available as methods on the <a class="reference internal" href="db_wrapper.html#pg.DB" title="pg.DB"><code class="xref py py-class docutils literal"><span class="pre">DB</span></code></a> object:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">login</span> <span class="o">=</span> <span class="s">"D'Arcy"</span>
<span class="gp">>>> </span><span class="n">db</span><span class="o">.</span><span class="n">escape_string</span><span class="p">(</span><span class="n">login</span><span class="p">)</span>
<span class="go">"D''Arcy"</span>
</pre></div>
</div>
<p>As you see, <a class="reference internal" href="db_wrapper.html#pg.DB.escape_string" title="pg.DB.escape_string"><code class="xref py py-meth docutils literal"><span class="pre">DB.escape_string()</span></code></a> has doubled the single quote which is
the right thing to do in SQL. However, there are better ways of passing
parameters to the query, without having to manually escape them. If you
pass the parameters as positional arguments to <a class="reference internal" href="db_wrapper.html#pg.DB.query" title="pg.DB.query"><code class="xref py py-meth docutils literal"><span class="pre">DB.query()</span></code></a>, then
PyGreSQL will send them to the database separately, without the need for
quoting them inside the SQL command, and without the problems inherent with
that process. In this case you must put placeholders of the form <code class="docutils literal"><span class="pre">$1</span></code>,
<code class="docutils literal"><span class="pre">$2</span></code> etc. in the SQL command in place of the parameters that should go there.
For instance:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">sql</span> <span class="o">=</span> <span class="s">"SELECT * FROM user_table WHERE login = $1 AND passwd = $2"</span>
<span class="gp">>>> </span><span class="n">db</span><span class="o">.</span><span class="n">query</span><span class="p">(</span><span class="n">sql</span><span class="p">,</span> <span class="n">login</span><span class="p">,</span> <span class="n">passwd</span><span class="p">)</span><span class="o">.</span><span class="n">getresult</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span>
</pre></div>
</div>
<p>That’s much better. So please always keep the following warning in mind:</p>
<div class="admonition warning">
<p class="first admonition-title">Warning</p>
<p class="last">Remember to <strong>never</strong> insert parameters directly into your queries using
the <code class="docutils literal"><span class="pre">%</span></code> operator. Always pass the parameters separately.</p>
</div>
<p>If you like the <code class="docutils literal"><span class="pre">%</span></code> format specifications of Python better than the
placeholders used by PostgreSQL, there is still a way to use them, via the
<a class="reference internal" href="db_wrapper.html#pg.DB.query_formatted" title="pg.DB.query_formatted"><code class="xref py py-meth docutils literal"><span class="pre">DB.query_formatted()</span></code></a> method:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">sql</span> <span class="o">=</span> <span class="s">"SELECT * FROM user_table WHERE login = %s AND passwd = %s"</span>
<span class="gp">>>> </span><span class="n">db</span><span class="o">.</span><span class="n">query_formatted</span><span class="p">(</span><span class="n">sql</span><span class="p">,</span> <span class="p">(</span><span class="n">login</span><span class="p">,</span> <span class="n">passwd</span><span class="p">))</span><span class="o">.</span><span class="n">getresult</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span>
</pre></div>
</div>
<p>Note that we need to pass the parameters not as positional arguments here,
but as a single tuple. Also note again that we did not use the <code class="docutils literal"><span class="pre">%</span></code>
operator of Python to format the SQL string, we just used the <code class="docutils literal"><span class="pre">%s</span></code> format
specifications of Python and let PyGreSQL care about the formatting.
Even better, you can also pass the parameters as a dictionary if you use
the <a class="reference internal" href="db_wrapper.html#pg.DB.query_formatted" title="pg.DB.query_formatted"><code class="xref py py-meth docutils literal"><span class="pre">DB.query_formatted()</span></code></a> method:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">sql</span> <span class="o">=</span> <span class="s">"""SELECT * FROM user_table</span>
<span class="gp">... </span><span class="s"> WHERE login = %(login)s AND passwd = %(passwd)s"""</span>
<span class="gp">>>> </span><span class="n">parameters</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">(</span><span class="n">login</span><span class="o">=</span><span class="n">login</span><span class="p">,</span> <span class="n">passwd</span><span class="o">=</span><span class="n">passwd</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">db</span><span class="o">.</span><span class="n">query_formatted</span><span class="p">(</span><span class="n">sql</span><span class="p">,</span> <span class="n">parameters</span><span class="p">)</span><span class="o">.</span><span class="n">getresult</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span>
</pre></div>
</div>
<p>Here is another example:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">sql</span> <span class="o">=</span> <span class="s">"SELECT 'Hello, ' || %s || '!'"</span>
<span class="gp">>>> </span><span class="n">db</span><span class="o">.</span><span class="n">query_formatted</span><span class="p">(</span><span class="n">sql</span><span class="p">,</span> <span class="p">(</span><span class="n">login</span><span class="p">,))</span><span class="o">.</span><span class="n">getresult</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span>
</pre></div>
</div>
<p>You would think that the following even simpler example should work, too:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">sql</span> <span class="o">=</span> <span class="s">"SELECT %s"</span>
<span class="gp">>>> </span><span class="n">db</span><span class="o">.</span><span class="n">query_formatted</span><span class="p">(</span><span class="n">sql</span><span class="p">,</span> <span class="p">(</span><span class="n">login</span><span class="p">,))</span><span class="o">.</span><span class="n">getresult</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span>
<span class="go">ProgrammingError: Could not determine data type of parameter $1</span>
</pre></div>
</div>
<p>The issue here is that <a class="reference internal" href="db_wrapper.html#pg.DB.query_formatted" title="pg.DB.query_formatted"><code class="xref py py-meth docutils literal"><span class="pre">DB.query_formatted()</span></code></a> by default still uses
PostgreSQL parameters, transforming the Python style <code class="docutils literal"><span class="pre">%s</span></code> placeholder
into a <code class="docutils literal"><span class="pre">$1</span></code> placeholder, and sending the login name separately from
the query. In the query we looked at before, the concatenation with other
strings made it clear that it should be interpreted as a string. This simple
query however does not give PostgreSQL a clue what data type the <code class="docutils literal"><span class="pre">$1</span></code>
placeholder stands for.</p>
<p>This is different when you are embedding the login name directly into the
query instead of passing it as parameter to PostgreSQL. You can achieve this
by setting the <em>inline</em> parameter of <a class="reference internal" href="db_wrapper.html#pg.DB.query_formatted" title="pg.DB.query_formatted"><code class="xref py py-meth docutils literal"><span class="pre">DB.query_formatted()</span></code></a>, like so:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">sql</span> <span class="o">=</span> <span class="s">"SELECT %s"</span>
<span class="gp">>>> </span><span class="n">db</span><span class="o">.</span><span class="n">query_formatted</span><span class="p">(</span><span class="n">sql</span><span class="p">,</span> <span class="p">(</span><span class="n">login</span><span class="p">,),</span> <span class="n">inline</span><span class="o">=</span><span class="k">True</span><span class="p">)</span><span class="o">.</span><span class="n">getresult</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span>
</pre></div>
</div>
<p>Another way of making this query work while still sending the parameters
separately is to simply cast the parameter values:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">sql</span> <span class="o">=</span> <span class="s">"SELECT %s::text"</span>
<span class="gp">>>> </span><span class="n">db</span><span class="o">.</span><span class="n">query_formatted</span><span class="p">(</span><span class="n">sql</span><span class="p">,</span> <span class="p">(</span><span class="n">login</span><span class="p">,),</span> <span class="n">inline</span><span class="o">=</span><span class="k">False</span><span class="p">)</span><span class="o">.</span><span class="n">getresult</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span>
</pre></div>
</div>
<p>In real world examples you will rarely have to cast your parameters like that,
since in an INSERT statement or a WHERE clause comparing the parameter to a
table column the data type will be clear from the context.</p>
<p>When binding the parameters to a query, PyGreSQL does not only adapt the basic
types like <code class="docutils literal"><span class="pre">int</span></code>, <code class="docutils literal"><span class="pre">float</span></code>, <code class="docutils literal"><span class="pre">bool</span></code> and <code class="docutils literal"><span class="pre">str</span></code>, but also tries to make
sense of Python lists and tuples.</p>
<p>Lists are adapted as PostgreSQL arrays:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">params</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">(</span><span class="n">array</span><span class="o">=</span><span class="p">[[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">],[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">]])</span>
<span class="gp">>>> </span><span class="n">db</span><span class="o">.</span><span class="n">query_formatted</span><span class="p">(</span><span class="s">"SELECT %(array)s::int[]"</span><span class="p">,</span> <span class="n">params</span><span class="p">)</span><span class="o">.</span><span class="n">getresult</span><span class="p">()[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
<span class="go">[[1, 2], [3, 4]]</span>
</pre></div>
</div>
<p>Note that again we only need to cast the array parameter or use inline
parameters because this simple query does not provide enough context.
Also note that the query gives the value back as Python lists again. This
is achieved by the typecasting mechanism explained in the next section.</p>
<p>Tuples are adapted as PostgreSQL composite types. If you use inline paramters,
they can also be used with the <code class="docutils literal"><span class="pre">IN</span></code> syntax.</p>
<p>Let’s think of a more real world example again where we create a table with a
composite type in PostgreSQL:</p>
<div class="highlight-sql"><div class="highlight"><pre><span class="k">CREATE</span> <span class="k">TABLE</span> <span class="n">on_hand</span> <span class="p">(</span>
<span class="n">item</span> <span class="n">inventory_item</span><span class="p">,</span>
<span class="k">count</span> <span class="nb">integer</span><span class="p">)</span>
</pre></div>
</div>
<p>We assume the composite type <code class="docutils literal"><span class="pre">inventory_item</span></code> has been created like this:</p>
<div class="highlight-sql"><div class="highlight"><pre><span class="k">CREATE</span> <span class="k">TYPE</span> <span class="n">inventory_item</span> <span class="k">AS</span> <span class="p">(</span>
<span class="n">name</span> <span class="nb">text</span><span class="p">,</span>
<span class="n">supplier_id</span> <span class="nb">integer</span><span class="p">,</span>
<span class="n">price</span> <span class="nb">numeric</span><span class="p">)</span>
</pre></div>
</div>
<p>In Python we can use a named tuple as an equivalent to this PostgreSQL type:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="kn">from</span> <span class="nn">collections</span> <span class="k">import</span> <span class="n">namedtuple</span>
<span class="gp">>>> </span><span class="n">inventory_item</span> <span class="o">=</span> <span class="n">namedtuple</span><span class="p">(</span>
<span class="gp">... </span> <span class="s">'inventory_item'</span><span class="p">,</span> <span class="p">[</span><span class="s">'name'</span><span class="p">,</span> <span class="s">'supplier_id'</span><span class="p">,</span> <span class="s">'price'</span><span class="p">])</span>
</pre></div>
</div>
<p>Using the automatic adaptation of Python tuples, an item can now be
inserted into the database and then read back as follows:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">db</span><span class="o">.</span><span class="n">query_formatted</span><span class="p">(</span><span class="s">"INSERT INTO on_hand VALUES (%(item)s, %(count)s)"</span><span class="p">,</span>
<span class="gp">... </span> <span class="nb">dict</span><span class="p">(</span><span class="n">item</span><span class="o">=</span><span class="n">inventory_item</span><span class="p">(</span><span class="s">'fuzzy dice'</span><span class="p">,</span> <span class="mi">42</span><span class="p">,</span> <span class="mf">1.99</span><span class="p">),</span> <span class="n">count</span><span class="o">=</span><span class="mi">1000</span><span class="p">))</span>
<span class="gp">>>> </span><span class="n">db</span><span class="o">.</span><span class="n">query</span><span class="p">(</span><span class="s">"SELECT * FROM on_hand"</span><span class="p">)</span><span class="o">.</span><span class="n">getresult</span><span class="p">()[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
<span class="go">Row(item=inventory_item(name='fuzzy dice', supplier_id=42,</span>
<span class="go"> price=Decimal('1.99')), count=1000)</span>
</pre></div>
</div>
<p>The <a class="reference internal" href="db_wrapper.html#pg.DB.insert" title="pg.DB.insert"><code class="xref py py-meth docutils literal"><span class="pre">DB.insert()</span></code></a> method provides a simpler way to achieve the same:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">row</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">(</span><span class="n">item</span><span class="o">=</span><span class="n">inventory_item</span><span class="p">(</span><span class="s">'fuzzy dice'</span><span class="p">,</span> <span class="mi">42</span><span class="p">,</span> <span class="mf">1.99</span><span class="p">),</span> <span class="n">count</span><span class="o">=</span><span class="mi">1000</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">db</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="s">'on_hand'</span><span class="p">,</span> <span class="n">row</span><span class="p">)</span>
<span class="go">{'count': 1000, 'item': inventory_item(name='fuzzy dice',</span>
<span class="go"> supplier_id=42, price=Decimal('1.99'))}</span>
</pre></div>
</div>
<p>However, we may not want to use named tuples, but custom Python classes
to hold our values, like this one:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="k">class</span> <span class="nc">InventoryItem</span><span class="p">:</span>
<span class="gp">...</span>
<span class="gp">... </span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">supplier_id</span><span class="p">,</span> <span class="n">price</span><span class="p">):</span>
<span class="gp">... </span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="n">name</span>
<span class="gp">... </span> <span class="bp">self</span><span class="o">.</span><span class="n">supplier_id</span> <span class="o">=</span> <span class="n">supplier_id</span>
<span class="gp">... </span> <span class="bp">self</span><span class="o">.</span><span class="n">price</span> <span class="o">=</span> <span class="n">price</span>
<span class="gp">...</span>
<span class="gp">... </span> <span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="gp">... </span> <span class="k">return</span> <span class="s">'%s (from %s, at $%s)'</span> <span class="o">%</span> <span class="p">(</span>
<span class="gp">... </span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">supplier_id</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">price</span><span class="p">)</span>
</pre></div>
</div>
<p>But when we try to insert an instance of this class in the same way, we
will get an error. This is because PyGreSQL tries to pass the string
representation of the object as a parameter to PostgreSQL, but this is just a
human readable string and not useful for PostgreSQL to build a composite type.
However, it is possible to make such custom classes adapt themselves to
PostgreSQL by adding a “magic” method with the name <code class="docutils literal"><span class="pre">__pg_str__</span></code>, like so:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="k">class</span> <span class="nc">InventoryItem</span><span class="p">:</span>
<span class="gp">...</span>
<span class="gp">... </span> <span class="o">...</span>
<span class="gp">...</span>
<span class="gp">... </span> <span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="gp">... </span> <span class="k">return</span> <span class="s">'%s (from %s, at $%s)'</span> <span class="o">%</span> <span class="p">(</span>
<span class="gp">... </span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">supplier_id</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">price</span><span class="p">)</span>
<span class="gp">...</span>
<span class="gp">... </span> <span class="k">def</span> <span class="nf">__pg_str__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">typ</span><span class="p">):</span>
<span class="gp">... </span> <span class="k">return</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">supplier_id</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">price</span><span class="p">)</span>
</pre></div>
</div>
<p>Now you can insert class instances the same way as you insert named tuples.
You can even make these objects adapt to different types in different ways:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="k">class</span> <span class="nc">InventoryItem</span><span class="p">:</span>
<span class="gp">...</span>
<span class="gp">... </span> <span class="o">...</span>
<span class="gp">...</span>
<span class="gp">... </span> <span class="k">def</span> <span class="nf">__pg_str__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">typ</span><span class="p">):</span>
<span class="gp">... </span> <span class="k">if</span> <span class="n">typ</span> <span class="o">==</span> <span class="s">'text'</span><span class="p">:</span>
<span class="gp">... </span> <span class="k">return</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
<span class="gp">... </span> <span class="k">return</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">supplier_id</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">price</span><span class="p">)</span>
<span class="gp">...</span>
<span class="gp">>>> </span><span class="n">db</span><span class="o">.</span><span class="n">query</span><span class="p">(</span><span class="s">"ALTER TABLE on_hand ADD COLUMN remark varchar"</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">item</span><span class="o">=</span><span class="n">InventoryItem</span><span class="p">(</span><span class="s">'fuzzy dice'</span><span class="p">,</span> <span class="mi">42</span><span class="p">,</span> <span class="mf">1.99</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">row</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">(</span><span class="n">item</span><span class="o">=</span><span class="n">item</span><span class="p">,</span> <span class="n">remark</span><span class="o">=</span><span class="n">item</span><span class="p">,</span> <span class="n">count</span><span class="o">=</span><span class="mi">1000</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">db</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="s">'on_hand'</span><span class="p">,</span> <span class="n">row</span><span class="p">)</span>
<span class="go">{'count': 1000, 'item': inventory_item(name='fuzzy dice',</span>
<span class="go"> supplier_id=42, price=Decimal('1.99')),</span>
<span class="go"> 'remark': 'fuzzy dice (from 42, at $1.99)'}</span>
</pre></div>
</div>
<p>There is also another “magic” method <code class="docutils literal"><span class="pre">__pg_repr__</span></code> which does not take the
<em>typ</em> parameter. That method is used instead of <code class="docutils literal"><span class="pre">__pg_str__</span></code> when passing
parameters inline. You must be more careful when using <code class="docutils literal"><span class="pre">__pg_repr__</span></code>,
because it must return a properly escaped string that can be put literally
inside the SQL. The only exception is when you return a tuple or list,
because these will be adapted and properly escaped by PyGreSQL again.</p>
</div>
<div class="section" id="typecasting-to-python">
<h2>Typecasting to Python<a class="headerlink" href="#typecasting-to-python" title="Permalink to this headline">¶</a></h2>
<p>As you noticed, PyGreSQL automatically converted the PostgreSQL data to
suitable Python objects when returning values via the <a class="reference internal" href="db_wrapper.html#pg.DB.get" title="pg.DB.get"><code class="xref py py-meth docutils literal"><span class="pre">DB.get()</span></code></a>,
<a class="reference internal" href="query.html#pg.Query.getresult" title="pg.Query.getresult"><code class="xref py py-meth docutils literal"><span class="pre">Query.getresult()</span></code></a> and similar methods. This is done by the use
of built-in typecast functions.</p>
<p>If you want to use different typecast functions or add your own if no
built-in typecast function is available, then this is possible using
the <a class="reference internal" href="module.html#pg.set_typecast" title="pg.set_typecast"><code class="xref py py-func docutils literal"><span class="pre">set_typecast()</span></code></a> function. With the <a class="reference internal" href="module.html#pg.get_typecast" title="pg.get_typecast"><code class="xref py py-func docutils literal"><span class="pre">get_typecast()</span></code></a> function
you can check which function is currently set. If no typecast function
is set, then PyGreSQL will return the raw strings from the database.</p>
<p>For instance, you will find that PyGreSQL uses the normal <code class="docutils literal"><span class="pre">int</span></code> function
to cast PostgreSQL <code class="docutils literal"><span class="pre">int4</span></code> type values to Python:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">pg</span><span class="o">.</span><span class="n">get_typecast</span><span class="p">(</span><span class="s">'int4'</span><span class="p">)</span>
<span class="go">int</span>
</pre></div>
</div>
<p>In the classic PyGreSQL module, the typecasting for these basic types is
always done internally by the C extension module for performance reasons.
We can set a different typecast function for <code class="docutils literal"><span class="pre">int4</span></code>, but it will not
become effective, the C module continues to use its internal typecasting.</p>
<p>However, we can add new typecast functions for the database types that are
not supported by the C modul. Fore example, we can create a typecast function
that casts items of the composite PostgreSQL type used as example in the
previous section to instances of the corresponding Python class.</p>
<p>To do this, at first we get the default typecast function that PyGreSQL has
created for the current <a class="reference internal" href="db_wrapper.html#pg.DB" title="pg.DB"><code class="xref py py-class docutils literal"><span class="pre">DB</span></code></a> connection. This default function casts
composite types to named tuples, as we have seen in the section before.
We can grab it from the <a class="reference internal" href="db_wrapper.html#pg.DB.dbtypes" title="pg.DB.dbtypes"><code class="xref py py-attr docutils literal"><span class="pre">DB.dbtypes</span></code></a> object as follows:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">cast_tuple</span> <span class="o">=</span> <span class="n">db</span><span class="o">.</span><span class="n">dbtypes</span><span class="o">.</span><span class="n">get_typecast</span><span class="p">(</span><span class="s">'inventory_item'</span><span class="p">)</span>
</pre></div>
</div>
<p>Now we can create a new typecast function that converts the tuple to
an instance of our custom class:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">cast_item</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">value</span><span class="p">:</span> <span class="n">InventoryItem</span><span class="p">(</span><span class="o">*</span><span class="n">cast_tuple</span><span class="p">(</span><span class="n">value</span><span class="p">))</span>
</pre></div>
</div>
<p>Finally, we set this typecast function, either globally with
<a class="reference internal" href="module.html#pg.set_typecast" title="pg.set_typecast"><code class="xref py py-func docutils literal"><span class="pre">set_typecast()</span></code></a>, or locally for the current connection like this:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">db</span><span class="o">.</span><span class="n">dbtypes</span><span class="o">.</span><span class="n">set_typecast</span><span class="p">(</span><span class="s">'inventory_item'</span><span class="p">,</span> <span class="n">cast_item</span><span class="p">)</span>
</pre></div>
</div>
<p>Now we can get instances of our custom class directly from the database:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">item</span> <span class="o">=</span> <span class="n">db</span><span class="o">.</span><span class="n">query</span><span class="p">(</span><span class="s">"SELECT * FROM on_hand"</span><span class="p">)</span><span class="o">.</span><span class="n">getresult</span><span class="p">()[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
<span class="gp">>>> </span><span class="nb">str</span><span class="p">(</span><span class="n">item</span><span class="p">)</span>
<span class="go">'fuzzy dice (from 42, at $1.99)'</span>
</pre></div>
</div>
<p>Note that some of the typecast functions used by the C module are configurable
with separate module level functions, such as <a class="reference internal" href="module.html#pg.set_decimal" title="pg.set_decimal"><code class="xref py py-meth docutils literal"><span class="pre">set_decimal()</span></code></a>,
<a class="reference internal" href="module.html#pg.set_bool" title="pg.set_bool"><code class="xref py py-meth docutils literal"><span class="pre">set_bool()</span></code></a> or <a class="reference internal" href="module.html#pg.set_jsondecode" title="pg.set_jsondecode"><code class="xref py py-meth docutils literal"><span class="pre">set_jsondecode()</span></code></a>. You need to use these instead of
<a class="reference internal" href="module.html#pg.set_typecast" title="pg.set_typecast"><code class="xref py py-meth docutils literal"><span class="pre">set_typecast()</span></code></a> if you want to change the behavior of the C module.</p>
<p>Also note that after changing global typecast functions with
<a class="reference internal" href="module.html#pg.set_typecast" title="pg.set_typecast"><code class="xref py py-meth docutils literal"><span class="pre">set_typecast()</span></code></a>, you may need to run <code class="docutils literal"><span class="pre">db.dbtypes.reset_typecast()</span></code>
to make these changes effective on connections that were already open.</p>
<p>As one last example, let us try to typecast the geometric data type <code class="docutils literal"><span class="pre">circle</span></code>
of PostgreSQL into a <a class="reference external" href="http://www.sympy.org">SymPy</a> <code class="docutils literal"><span class="pre">Circle</span></code> object. Let’s
assume we have created and populated a table with two circles, like so:</p>
<div class="highlight-sql"><div class="highlight"><pre><span class="k">CREATE</span> <span class="k">TABLE</span> <span class="n">circle</span> <span class="p">(</span>
<span class="n">name</span> <span class="nb">varchar</span><span class="p">(</span><span class="mi">8</span><span class="p">)</span> <span class="k">primary</span> <span class="k">key</span><span class="p">,</span> <span class="n">circle</span> <span class="n">circle</span><span class="p">);</span>
<span class="k">INSERT</span> <span class="k">INTO</span> <span class="n">circle</span> <span class="k">VALUES</span> <span class="p">(</span><span class="s1">'C1'</span><span class="p">,</span> <span class="s1">'<(2, 3), 3>'</span><span class="p">);</span>
<span class="k">INSERT</span> <span class="k">INTO</span> <span class="n">circle</span> <span class="k">VALUES</span> <span class="p">(</span><span class="s1">'C2'</span><span class="p">,</span> <span class="s1">'<(1, -1), 4>'</span><span class="p">);</span>
</pre></div>
</div>
<p>With PostgreSQL we can easily calculate that these two circles overlap:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">q</span> <span class="o">=</span> <span class="n">db</span><span class="o">.</span><span class="n">query</span><span class="p">(</span><span class="s">"""SELECT c1.circle && c2.circle</span>
<span class="gp">... </span><span class="s"> FROM circle c1, circle c2</span>
<span class="gp">... </span><span class="s"> WHERE c1.name = 'C1' AND c2.name = 'C2'"""</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">q</span><span class="o">.</span><span class="n">getresult</span><span class="p">()[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
<span class="go">True</span>
</pre></div>
</div>
<p>However, calculating the intersection points between the two circles using the
<code class="docutils literal"><span class="pre">#</span></code> operator does not work (at least not as of PostgreSQL version 9.5).
So let’ resort to SymPy to find out. To ease importing circles from
PostgreSQL to SymPy, we create and register the following typecast function:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="kn">from</span> <span class="nn">sympy</span> <span class="k">import</span> <span class="n">Point</span><span class="p">,</span> <span class="n">Circle</span>
<span class="go">>>></span>
<span class="gp">>>> </span><span class="k">def</span> <span class="nf">cast_circle</span><span class="p">(</span><span class="n">s</span><span class="p">):</span>
<span class="gp">... </span> <span class="n">p</span><span class="p">,</span> <span class="n">r</span> <span class="o">=</span> <span class="n">s</span><span class="p">[</span><span class="mi">1</span><span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s">','</span><span class="p">)</span>
<span class="gp">... </span> <span class="n">p</span> <span class="o">=</span> <span class="n">p</span><span class="p">[</span><span class="mi">1</span><span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s">','</span><span class="p">)</span>
<span class="gp">... </span> <span class="k">return</span> <span class="n">Circle</span><span class="p">(</span><span class="n">Point</span><span class="p">(</span><span class="nb">float</span><span class="p">(</span><span class="n">p</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="nb">float</span><span class="p">(</span><span class="n">p</span><span class="p">[</span><span class="mi">1</span><span class="p">])),</span> <span class="nb">float</span><span class="p">(</span><span class="n">r</span><span class="p">))</span>
<span class="gp">...</span>
<span class="gp">>>> </span><span class="n">pg</span><span class="o">.</span><span class="n">set_typecast</span><span class="p">(</span><span class="s">'circle'</span><span class="p">,</span> <span class="n">cast_circle</span><span class="p">)</span>
</pre></div>
</div>
<p>Now we can import the circles in the table into Python simply using:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">circle</span> <span class="o">=</span> <span class="n">db</span><span class="o">.</span><span class="n">get_as_dict</span><span class="p">(</span><span class="s">'circle'</span><span class="p">,</span> <span class="n">scalar</span><span class="o">=</span><span class="k">True</span><span class="p">)</span>
</pre></div>
</div>
<p>The result is a dictionary mapping circle names to SymPy <code class="docutils literal"><span class="pre">Circle</span></code> objects.
We can verify that the circles have been imported correctly:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">circle</span><span class="p">[</span><span class="s">'C1'</span><span class="p">]</span>
<span class="go">Circle(Point(2, 3), 3.0)</span>
<span class="gp">>>> </span><span class="n">circle</span><span class="p">[</span><span class="s">'C2'</span><span class="p">]</span>
<span class="go">Circle(Point(1, -1), 4.0)</span>
</pre></div>
</div>
<p>Finally we can find the exact intersection points with SymPy:</p>
<div class="highlight-default"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">circle</span><span class="p">[</span><span class="s">'C1'</span><span class="p">]</span><span class="o">.</span><span class="n">intersection</span><span class="p">(</span><span class="n">circle</span><span class="p">[</span><span class="s">'C2'</span><span class="p">])</span>
<span class="go">[Point(29/17 + 64564173230121*sqrt(17)/100000000000000,</span>
<span class="go"> -80705216537651*sqrt(17)/500000000000000 + 31/17),</span>
<span class="go"> Point(-64564173230121*sqrt(17)/100000000000000 + 29/17,</span>
<span class="go"> 80705216537651*sqrt(17)/500000000000000 + 31/17)]</span>
</pre></div>
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