Python, SQLAlchemy pass parameters in connection.execute

python

parameter-passing

sqlalchemy

best-practices

byNikita Barsukov·Jan 25, 2025

In SQLAlchemy, SQL query parameters can be executed using named placeholders in SQL statements and a parameters dictionary in connection.execute(). Here's an illustration:

query = "SELECT * FROM my_table WHERE id = :id"
params = {"id": 42}
result = engine.execute(query, params).fetchall()  # 'fetchall' - gives me all, just like a Dalmatian movie

The :id gets replaced with the actual ID from the params dictionary during query execution.

When employing sqlalchemy.sql.text() you assure both backend-neutral handling and improved security with bind parameters usage:

from sqlalchemy.sql import text

stmt = text("SELECT * FROM my_table WHERE id = :id")  
result = engine.execute(stmt, id=42).fetchall()  # fetchall(), not fetchsome() or fetchlittle(), all()

Building queries safely

While constructing SQL statements, avoid string formatting operations like sql.format(...), they are a potential gateway to SQL injection attacks. SQLAlchemy's text constructs safeguard against these attacks by segregating the query structure from the data.

Parameter passing: best practices

Incorporating parameters instead of plain values makes your code more maintainable and reusable. Modularity in your query creation improves adaptability and scalability of your application.

Power of parameterization

Parameterization goes beyond SQL safety, it is about efficiency. By utilizing SQLAlchemy's bindparams, a statement can be prepared once and executed multiple times with different values, improving performance:

stmt = text("UPDATE users SET name = :name WHERE id = :id").bindparams(name='John Doe')
for user_id in range(1, 4):
    engine.execute(stmt, id=user_id)  # watch me loop through userId's like a boss!

Efficiencies with session.execute

Adopting modularity and reusability in your code leads to improved efficiency. Consider using the stmt (statement) and res (response) for session execution, leading to better readability and maintainability:

stmt = text("SELECT * FROM employees WHERE department = :department")
for department in ['sales', 'engineering']:
    res = session.execute(stmt, {'department': department})
    for row in res:  # cruising through the rows like a seasoned rower
        print(row)

Avoiding common execution pitfalls

When parameters are involved, errors like StatementError for mismatched data types or a ProgrammingError for incorrect bindings aren't uncommon. To troubleshoot, examine your parameter names and the SQL query structure.

Future-proof your code

Account for database schema or underlying database changes by using SQL expressions abstracted by SQLAlchemy. This makes your code independent of the specifics of your current database setup, and hence more flexible and scalable.

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