SQL Expressions

How do I render SQL expressions as strings, possibly with bound parameters inlined?

The “stringification” of a SQLAlchemy Core statement object or expression fragment, as well as that of an ORM Query object, in the majority of simple cases is as simple as using the str() builtin function, as below when use it with the print function (note the Python print function also calls str() automatically if we don’t use it explicitly):

>>> from sqlalchemy import table, column, select
>>> t = table('my_table', column('x'))
>>> statement = select([t])
>>> print(str(statement))
SELECT my_table.x
FROM my_table

The str() builtin, or an equivalent, can be invoked on ORM Query object as well as any statement such as that of select(), insert() etc. and also any expression fragment, such as:

>>> from sqlalchemy import column
>>> print(column('x') == 'some value')
x = :x_1

Stringifying for Specific Databases

A complication arises when the statement or fragment we are stringifying contains elements that have a database-specific string format, or when it contains elements that are only available within a certain kind of database. In these cases, we might get a stringified statement that is not in the correct syntax for the database we are targeting, or the operation may raise a UnsupportedCompilationError exception. In these cases, it is necessary that we stringify the statement using the ClauseElement.compile() method, while passing along an Engine or Dialect object that represents the target database. Such as below, if we have a MySQL database engine, we can stringify a statement in terms of the MySQL dialect:

from sqlalchemy import create_engine

engine = create_engine("mysql+pymysql://scott:tiger@localhost/test")

More directly, without building up an Engine object we can instantiate a Dialect object directly, as below where we use a PostgreSQL dialect:

from sqlalchemy.dialects import postgresql

When given an ORM Query object, in order to get at the ClauseElement.compile() method we only need access the Query.statement accessor first:

statement = query.statement

Rendering Bound Parameters Inline


Never use this technique with string content received from untrusted input, such as from web forms or other user-input applications. SQLAlchemy’s facilities to coerce Python values into direct SQL string values are not secure against untrusted input and do not validate the type of data being passed. Always use bound parameters when programmatically invoking non-DDL SQL statements against a relational database.

The above forms will render the SQL statement as it is passed to the Python DBAPI, which includes that bound parameters are not rendered inline. SQLAlchemy normally does not stringify bound parameters, as this is handled appropriately by the Python DBAPI, not to mention bypassing bound parameters is probably the most widely exploited security hole in modern web applications. SQLAlchemy has limited ability to do this stringification in certain circumstances such as that of emitting DDL. In order to access this functionality one can use the literal_binds flag, passed to compile_kwargs:

from sqlalchemy.sql import table, column, select

t = table('t', column('x'))

s = select([t]).where(t.c.x == 5)

# **do not use** with untrusted input!!!
print(s.compile(compile_kwargs={"literal_binds": True}))

The above approach has the caveats that it is only supported for basic types, such as ints and strings, and furthermore if a bindparam() without a pre-set value is used directly, it won’t be able to stringify that either.

This functionality is provided mainly for logging or debugging purposes, where having the raw sql string of a query may prove useful. Note that the dialect parameter should also passed to the ClauseElement.compile() method to render the query that will be sent to the database.

To support inline literal rendering for types not supported, implement a TypeDecorator for the target type which includes a TypeDecorator.process_literal_param() method:

from sqlalchemy import TypeDecorator, Integer

class MyFancyType(TypeDecorator):
    impl = Integer

    def process_literal_param(self, value, dialect):
        return "my_fancy_formatting(%s)" % value

from sqlalchemy import Table, Column, MetaData

tab = Table('mytable', MetaData(), Column('x', MyFancyType()))

stmt = tab.select().where(tab.c.x > 5)
print(stmt.compile(compile_kwargs={"literal_binds": True}))

producing output like:

SELECT mytable.x
FROM mytable
WHERE mytable.x > my_fancy_formatting(5)

Why are percent signs being doubled up when stringifying SQL statements?

Many DBAPI implementations make use of the pyformat or format paramstyle, which necessarily involve percent signs in their syntax. Most DBAPIs that do this expect percent signs used for other reasons to be doubled up (i.e. escaped) in the string form of the statements used, e.g.:

SELECT a, b FROM some_table WHERE a = %s AND c = %s AND num %% modulus = 0

When SQL statements are passed to the underlying DBAPI by SQLAlchemy, substitution of bound parameters works in the same way as the Python string interpolation operator %, and in many cases the DBAPI actually uses this operator directly. Above, the substitution of bound parameters would then look like:

SELECT a, b FROM some_table WHERE a = 5 AND c = 10 AND num % modulus = 0

The default compilers for databases like PostgreSQL (default DBAPI is psycopg2) and MySQL (default DBAPI is mysqlclient) will have this percent sign escaping behavior:

>>> from sqlalchemy import table, column
>>> from sqlalchemy.dialects import postgresql
>>> t = table("my_table", column("value % one"), column("value % two"))
>>> print(t.select().compile(dialect=postgresql.dialect()))
SELECT my_table."value %% one", my_table."value %% two"
FROM my_table

When such a dialect is being used, if non-DBAPI statements are desired that don’t include bound parameter symbols, one quick way to remove the percent signs is to simply substitute in an empty set of parameters using Python’s % operator directly:

>>> strstmt = str(t.select().compile(dialect=postgresql.dialect()))
>>> print(strstmt % ())
SELECT my_table."value % one", my_table."value % two"
FROM my_table

The other is to set a different parameter style on the dialect being used; all Dialect implementations accept a parameter paramstyle which will cause the compiler for that dialect to use the given parameter style. Below, the very common named parameter style is set within the dialect used for the compilation so that percent signs are no longer significant in the compiled form of SQL, and will no longer be escaped:

>>> print(t.select().compile(dialect=postgresql.dialect(paramstyle="named")))
SELECT my_table."value % one", my_table."value % two"
FROM my_table

I’m using op() to generate a custom operator and my parenthesis are not coming out correctly

The Operators.op() method allows one to create a custom database operator otherwise not known by SQLAlchemy:

>>> print(column('q').op('->')(column('p')))
q -> p

However, when using it on the right side of a compound expression, it doesn’t generate parenthesis as we expect:

>>> print((column('q1') + column('q2')).op('->')(column('p')))
q1 + q2 -> p

Where above, we probably want (q1 + q2) -> p.

The solution to this case is to set the precedence of the operator, using the Operators.op.precedence parameter, to a high number, where 100 is the maximum value, and the highest number used by any SQLAlchemy operator is currently 15:

>>> print((column('q1') + column('q2')).op('->', precedence=100)(column('p')))
(q1 + q2) -> p

We can also usually force parenthesization around a binary expression (e.g. an expression that has left/right operands and an operator) using the ColumnElement.self_group() method:

>>> print((column('q1') + column('q2')).self_group().op('->')(column('p')))
(q1 + q2) -> p

Why are the parentheses rules like this?

A lot of databases barf when there are excessive parenthesis or when parenthesis are in unusual places they doesn’t expect, so SQLAlchemy does not generate parenthesis based on groupings, it uses operator precedence and if the operator is known to be associative, so that parenthesis are generated minimally. Otherwise, an expression like:

column('a') & column('b') & column('c') & column('d')

would produce:

(((a AND b) AND c) AND d)

which is fine but would probably annoy people (and be reported as a bug). In other cases, it leads to things that are more likely to confuse databases or at the very least readability, such as:

column('q', ARRAY(Integer, dimensions=2))[5][6]

would produce:


There are also some edge cases where we get things like "(x) = 7" and databases really don’t like that either. So parenthesization doesn’t naively parenthesize, it uses operator precedence and associativity to determine groupings.

For Operators.op(), the value of precedence defaults to zero.

What if we defaulted the value of Operators.op.precedence to 100, e.g. the highest? Then this expression makes more parenthesis, but is otherwise OK, that is, these two are equivalent:

>>> print((column('q') - column('y')).op('+', precedence=100)(column('z')))
(q - y) + z
>>> print((column('q') - column('y')).op('+')(column('z')))
q - y + z

but these two are not:

>>> print(column('q') - column('y').op('+', precedence=100)(column('z')))
q - y + z
>>> print(column('q') - column('y').op('+')(column('z')))
q - (y + z)

For now, it’s not clear that as long as we are doing parenthesization based on operator precedence and associativity, if there is really a way to parenthesize automatically for a generic operator with no precedence given that is going to work in all cases, because sometimes you want a custom op to have a lower precedence than the other operators and sometimes you want it to be higher.

It is possible that maybe if the “binary” expression above forced the use of the self_group() method when op() is called, making the assumption that a compound expression on the left side can always be parenthesized harmlessly. Perhaps this change can be made at some point, however for the time being keeping the parenthesization rules more internally consistent seems to be the safer approach.