SQLAlchemy 2.0 Documentation
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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")
print(statement.compile(engine))
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
print(statement.compile(dialect=postgresql.dialect()))
Note that any dialect can be assembled using create_engine()
itself
with a dummy URL and then accessing the Engine.dialect
attribute,
such as if we wanted a dialect object for psycopg2:
e = create_engine("postgresql+psycopg2://")
psycopg2_dialect = e.dialect
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
print(statement.compile(someengine))
Rendering Bound Parameters Inline¶
Warning
Never use these techniques 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}))
# to render for a specific dialect
print(s.compile(dialect=dialect, compile_kwargs={"literal_binds": True}))
# or if you have an Engine, pass as first argument
print(s.compile(some_engine, compile_kwargs={"literal_binds": True}))
This functionality is provided mainly for logging or debugging purposes, where having the raw sql string of a query may prove useful.
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.
Methods of stringifying all parameters unconditionally are detailed below.
Tip
The reason SQLAlchemy does not support full stringification of all datatypes is threefold:
This is a functionality that is already supported by the DBAPI in use when the DBAPI is used normally. The SQLAlchemy project cannot be tasked with duplicating this functionality for every datatype for all backends, as this is redundant work which also incurs significant testing and ongoing support overhead.
Stringifying with bound parameters inlined for specific databases suggests a usage that is actually passing these fully stringified statements onto the database for execution. This is unnecessary and insecure, and SQLAlchemy does not want to encourage this use in any way.
The area of rendering literal values is the most likely area for security issues to be reported. SQLAlchemy tries to keep the area of safe parameter stringification an issue for the DBAPI drivers as much as possible where the specifics for each DBAPI can be handled appropriately and securely.
As SQLAlchemy intentionally does not support full stringification of literal
values, techniques to do so within specific debugging scenarios include the
following. As an example, we will use the PostgreSQL UUID
datatype:
import uuid
from sqlalchemy import Column
from sqlalchemy import create_engine
from sqlalchemy import Integer
from sqlalchemy import select
from sqlalchemy.dialects.postgresql import UUID
from sqlalchemy.orm import declarative_base
Base = declarative_base()
class A(Base):
__tablename__ = "a"
id = Column(Integer, primary_key=True)
data = Column(UUID)
stmt = select(A).where(A.data == uuid.uuid4())
Given the above model and statement which will compare a column to a single UUID value, options for stringifying this statement with inline values include:
Some DBAPIs such as psycopg2 support helper functions like mogrify() which provide access to their literal-rendering functionality. To use such features, render the SQL string without using
literal_binds
and pass the parameters separately via theSQLCompiler.params
accessor:e = create_engine("postgresql+psycopg2://scott:tiger@localhost/test") with e.connect() as conn: cursor = conn.connection.cursor() compiled = stmt.compile(e) print(cursor.mogrify(str(compiled), compiled.params))
The above code will produce psycopg2’s raw bytestring:
b"SELECT a.id, a.data \nFROM a \nWHERE a.data = 'a511b0fc-76da-4c47-a4b4-716a8189b7ac'::uuid"
Render the
SQLCompiler.params
directly into the statement, using the appropriate paramstyle of the target DBAPI. For example, the psycopg2 DBAPI uses the namedpyformat
style. The meaning ofrender_postcompile
will be discussed in the next section. WARNING this is NOT secure, do NOT use untrusted input:e = create_engine("postgresql+psycopg2://") # will use pyformat style, i.e. %(paramname)s for param compiled = stmt.compile(e, compile_kwargs={"render_postcompile": True}) print(str(compiled) % compiled.params)
This will produce a non-working string, that nonetheless is suitable for debugging:
SELECT a.id, a.data FROM a WHERE a.data = 9eec1209-50b4-4253-b74b-f82461ed80c1
Another example using a positional paramstyle such as
qmark
, we can render our above statement in terms of SQLite by also using theSQLCompiler.positiontup
collection in conjunction withSQLCompiler.params
, in order to retrieve the parameters in their positional order for the statement as compiled:import re e = create_engine("sqlite+pysqlite://") # will use qmark style, i.e. ? for param compiled = stmt.compile(e, compile_kwargs={"render_postcompile": True}) # params in positional order params = (repr(compiled.params[name]) for name in compiled.positiontup) print(re.sub(r"\?", lambda m: next(params), str(compiled)))
The above snippet prints:
SELECT a.id, a.data FROM a WHERE a.data = UUID('1bd70375-db17-4d8c-94f1-fc2ef3aada26')
Use the Custom SQL Constructs and Compilation Extension extension to render
BindParameter
objects in a custom way when a user-defined flag is present. This flag is sent through thecompile_kwargs
dictionary like any other flag:from sqlalchemy.ext.compiler import compiles from sqlalchemy.sql.expression import BindParameter @compiles(BindParameter) def _render_literal_bindparam(element, compiler, use_my_literal_recipe=False, **kw): if not use_my_literal_recipe: # use normal bindparam processing return compiler.visit_bindparam(element, **kw) # if use_my_literal_recipe was passed to compiler_kwargs, # render the value directly return repr(element.value) e = create_engine("postgresql+psycopg2://") print(stmt.compile(e, compile_kwargs={"use_my_literal_recipe": True}))
The above recipe will print:
SELECT a.id, a.data FROM a WHERE a.data = UUID('47b154cd-36b2-42ae-9718-888629ab9857')
For type-specific stringification that’s built into a model or a statement, the
TypeDecorator
class may be used to provide custom stringification of any datatype using theTypeDecorator.process_literal_param()
method:from sqlalchemy import TypeDecorator class UUIDStringify(TypeDecorator): impl = UUID def process_literal_param(self, value, dialect): return repr(value)
The above datatype needs to be used either explicitly within the model or locally within the statement using
type_coerce()
, such asfrom sqlalchemy import type_coerce stmt = select(A).where(type_coerce(A.data, UUIDStringify) == uuid.uuid4()) print(stmt.compile(e, compile_kwargs={"literal_binds": True}))
Again printing the same form:
SELECT a.id, a.data FROM a WHERE a.data = UUID('47b154cd-36b2-42ae-9718-888629ab9857')
Rendering “POSTCOMPILE” Parameters as Bound Parameters¶
SQLAlchemy includes a variant on a bound parameter known as
BindParameter.expanding
, which is a “late evaluated” parameter
that is rendered in an intermediary state when a SQL construct is compiled,
which is then further processed at statement execution time when the actual
known values are passed. “Expanding” parameters are used for
ColumnOperators.in_()
expressions by default so that the SQL
string can be safely cached independently of the actual lists of values
being passed to a particular invocation of ColumnOperators.in_()
:
>>> stmt = select(A).where(A.id.in_([1, 2, 3]))
To render the IN clause with real bound parameter symbols, use the
render_postcompile=True
flag with ClauseElement.compile()
:
>>> e = create_engine("postgresql+psycopg2://")
>>> print(stmt.compile(e, compile_kwargs={"render_postcompile": True}))
SELECT a.id, a.data
FROM a
WHERE a.id IN (%(id_1_1)s, %(id_1_2)s, %(id_1_3)s)
The literal_binds
flag, described in the previous section regarding
rendering of bound parameters, automatically sets render_postcompile
to
True, so for a statement with simple ints/strings, these can be stringified
directly:
# render_postcompile is implied by literal_binds
>>> print(stmt.compile(e, compile_kwargs={"literal_binds": True}))
SELECT a.id, a.data
FROM a
WHERE a.id IN (1, 2, 3)
The SQLCompiler.params
and SQLCompiler.positiontup
are
also compatible with render_postcompile
, so that
the previous recipes for rendering inline bound parameters will work here
in the same way, such as SQLite’s positional form:
>>> u1, u2, u3 = uuid.uuid4(), uuid.uuid4(), uuid.uuid4()
>>> stmt = select(A).where(A.data.in_([u1, u2, u3]))
>>> import re
>>> e = create_engine("sqlite+pysqlite://")
>>> compiled = stmt.compile(e, compile_kwargs={"render_postcompile": True})
>>> params = (repr(compiled.params[name]) for name in compiled.positiontup)
>>> print(re.sub(r"\?", lambda m: next(params), str(compiled)))
SELECT a.id, a.data
FROM a
WHERE a.data IN (UUID('aa1944d6-9a5a-45d5-b8da-0ba1ef0a4f38'), UUID('a81920e6-15e2-4392-8a3c-d775ffa9ccd2'), UUID('b5574cdb-ff9b-49a3-be52-dbc89f087bfa'))
Warning
Remember, all of the above code recipes which stringify literal values, bypassing the use of bound parameters when sending statements to the database, are only to be used when:
the use is debugging purposes only
the string is not to be passed to a live production database
only with local, trusted input
The above recipes for stringification of literal values are not secure in any way and should never be used against production databases.
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:
((q[5])[6])
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.
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