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1Fix the driver behind crashes, sound loss and screen glitches2Clear out junk files and repair common Windows errors3Scan for outdated or missing drivers - takes under a minuteFor handwritten SQL in a Python application using SQLAlchemy 2.x, use text() with Connection.execute() and pass values separately as bound parameters. That keeps the SQL readable and gives SQLAlchemy a chance to manage parameter handling and results. Raw SQL is a supported option, not a replacement for every Core expression or ORM query.
Run a handwritten SQL query with SQLAlchemy 2.x
This example assumes a SQLAlchemy engine is already configured for your database and an appropriate DB-API driver is installed. The tutorial uses a connection context manager, a named parameter, and result mappings:
from sqlalchemy import text
with engine.connect() as conn:
result = conn.execute(
text("SELECT x, y FROM some_table WHERE y > :y"),
{"y": 2},
)
for row in result.mappings():
print(row["x"], row["y"])The SQL template contains :y; the mapping supplies its value. SQLAlchemy and the database driver handle binding. Do not add quotes around the placeholder or build a value-bearing SQL string yourself. The connection context manager also closes the connection when the block exits. See the SQLAlchemy 2.0 tutorial on working with transactions and the DBAPI.
Keep values out of the SQL string
Use bound parameters for data values, especially values that may come from users or other untrusted sources. Do not interpolate them with f-strings, percent formatting, concatenation, or equivalent string construction:
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# Unsafe: the value becomes part of the SQL text
query = f"SELECT x, y FROM some_table WHERE y > {user_value}"
# Safer: the value is bound separately
stmt = text("SELECT x, y FROM some_table WHERE y > :y")
result = conn.execute(stmt, {"y": user_value})SQLAlchemy’s guidance is explicit: “Always use bound parameters.” This advice concerns values. A parameter placeholder is not a general way to insert a table name, column name, or sort direction; those are parts of SQL structure. If an application needs dynamic identifiers or clauses, restrict choices with an allowlist or use a library- and backend-appropriate identifier-composition mechanism. The SQLAlchemy FAQ also warns against treating inline literal rendering as an execution shortcut for untrusted input; literal_binds is mainly useful for logging or debugging and has datatype caveats. See the SQLAlchemy FAQ on SQL expressions.
Choose the SQLAlchemy interface that fits the query
SQLAlchemy offers three neighboring approaches. The right choice depends on whether you need to write exact SQL, pass SQL directly to a driver, or build a query from Python expressions.
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| Approach | SQL control and abstraction | Driver dependence | Good fit |
|---|---|---|---|
text() with Connection.execute() |
You write the SQL statement; SQLAlchemy integrates it with bound parameters, typing, and result handling. | SQLAlchemy handles parameter conventions across supported dialects. | Handwritten SQL within a SQLAlchemy application when you want SQLAlchemy-level integration. |
Connection.exec_driver_sql() |
You pass a SQL string directly to the underlying DB-API driver, with less SQLAlchemy-level handling. | More directly dependent on the driver’s parameter style and behavior. | A case that specifically requires driver-level SQL behavior. |
| Core expressions or ORM queries | You construct queries through SQLAlchemy’s expression or ORM APIs instead of writing the full statement as text. | SQLAlchemy provides more abstraction over SQL construction. | Queries built programmatically, or ORM work using mapped entities. |
SQLAlchemy documents textual SQL as supported, but describes it as the exception in ordinary day-to-day use; Core expressions and ORM constructs provide more abstraction. This is not a performance ranking. The documented distinction is about control, abstraction, parameter handling, and result integration. Read the SQLAlchemy 2.0 Core overview for Core’s role.
When direct driver SQL is different
Connection.exec_driver_sql() sends textual SQL directly to the underlying DB-API driver, bypassing SQLAlchemy’s usual text() compilation path. That can be appropriate when driver-specific behavior matters, but it also means parameter conventions may differ by driver. Do not assume a placeholder style that works with one backend will work with another.
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For ordinary handwritten statements in a SQLAlchemy application, text() is generally the more integrated starting point: it normalizes parameter passing and supports SQLAlchemy-level typing and result behavior. Use driver-direct execution only when the direct driver interface is the reason for the choice. See SQLAlchemy’s 2.1 documentation on engines and connections.
Raw SQL and ORM queries can coexist
Using SQLAlchemy does not require choosing between handwritten SQL and an ORM. A textual statement is useful when you want direct control over a statement’s SQL. For ORM querying in SQLAlchemy 2.x, construct a select() statement and execute it through a Session:
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from sqlalchemy import select
stmt = select(User).where(User.name == "Ada")
users = session.execute(stmt).scalars().all()Core expressions are another option when you want to construct SQL through Python objects rather than write the whole statement as text. Prefer these abstractions when they make query construction or ORM integration clearer; prefer text() when explicit SQL is the clearest way to express the operation. The SQLAlchemy 2.0 ORM Querying Guide documents the ORM approach.
Check the database and driver assumptions
SQLAlchemy supports dialects for several major database families, but each requires an appropriate DB-API implementation. A SQLAlchemy URL, installed driver, database backend, and parameter style all matter to the working code. The examples above use SQLAlchemy’s text() abstraction rather than claiming one driver’s placeholder syntax is universal. For the supported dialect and DB-API context, consult SQLAlchemy’s features and dialect information.
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