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    <p>SQLAlchemy generates a tree structure from your filter predicates, appending each leaf on as appropriate and putting the result in <code>Query._criterion</code>. You can explore this with the <code>get_children()</code> method of various <code>ClauseElement</code> and <code>ColumnElement</code> classes. </p> <p>For <code>Model.foo == 6</code> you'll end up with something like this:</p> <pre><code> Model.foo == 6 | _BinaryExpression / \ / \ / \ Column('foo', Integer(), _BindParamClause(u'%(168261004 foo)s', ...) 6, type_=Integer()) </code></pre> <p>If you were to &amp; together two predicates, like <code>(Model.foo == 6) &amp; (Model.name == 'a name')</code> or by chaining <code>filter</code> calls, you'd get a <code>BooleanClauseList</code> with two <code>_BinaryExpression</code> children. This means you can't hard code a simple expression to reliably return the values you want but instead have to traverse the predicate tree.</p> <p>The <code>traverse</code> function from <code>sqlalchemy.sql.visitors</code> does just that, relying on a dictionary of special names that relate each Element's <code>__visit_name__</code> attribute to a processing function. This is a breadth-first traversal, which as you can see is appropriate for the example below; there's also a depth-first version available.</p> <p>The following function shows how to generate a list of column-parameter pairs from a given query. I adapted it from <a href="http://hg.sqlalchemy.org/sqlalchemy/file/b1573376f29c/examples/beaker_caching/caching_query.py#l248)" rel="noreferrer">the Beaker caching example</a>:</p> <pre><code> def extract_cols_params(query): if query._criterion is None: return [] c, v = [], [] def visit_bindparam(bind): value = query._params.get(bind.key, bind.value) if callable(value): value = value() v.append(value) def visit_column(col): c.append('%s.%s' % (col.table.name, col.name)) visitors.traverse(query._criterion, # our predicate tree {}, # kwargs for the iterator used by # the traversal; undeeded. {'bindparam': visit_bindparam, # for _BindParamClauses 'column' : visit_column}) # for Columns return zip(c, v) &gt;&gt;&gt; extract_cols_params(Session.query(Model).filter((Model.foo == 6) ).filter(Model.name == 'a name')) [('models.foo', 6), ('models.name', 'a name')] </code></pre>
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Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

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