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    <p>If you have a list of terms and want to find rows where a field matches one of them, then you could use the in_() method:</p> <pre><code>terms = ['term1', 'term2', 'term3'] query.filter(Cls.field.in_(terms)) </code></pre> <p>If you want to do something more complex, then <code>or_()</code> and <code>and_()</code> take <code>ClauseElement</code> objects as parameters. ClauseElement and it's subclasses basically represent the SQL <a href="http://en.wikipedia.org/wiki/Abstract_syntax_tree" rel="noreferrer">AST</a> of your query. Typically you create clause elements by invoking a comparison operator on Column or InstrumentedAttribute objects:</p> <pre><code># Create the clause element clause = (users_table.columns['name'] == "something") # you can also use the shorthand users_table.c.name # The clause is a binary expression ... print(type(clause)) # &lt;class 'sqlalchemy.sql.expression._BinaryExpression'&gt; # ... that compares a column for equality with a bound value. print(type(clause.left), clause.operator, type(clause.right)) # &lt;class 'sqlalchemy.schema.Column'&gt;, &lt;built-in function eq&gt;, # &lt;class 'sqlalchemy.sql.expression._BindParamClause'&gt; # str() compiles it to SQL print(str(clause)) # users.name = ? # You can also do that with ORM attributes clause = (User.name == "something") print(str(clause)) # users.name = ? </code></pre> <p>You can handle clause elements representing your conditions like any Python objects, put them into lists, compose them into other clause elements, etc. So you can do something like this:</p> <pre><code># Collect the separate conditions to a list conditions = [] for term in terms: conditions.append(User.name == term) # Combine them with or to a BooleanClauseList condition = or_(*conditions) # Can now use the clause element as a predicate in queries query = query.filter(condition) # or to view the SQL fragment print(str(condition)) # users.name = ? OR users.name = ? OR users.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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