pandas/sqlalchemy/pyodbc: Result object does not return rows from stored proc when UPDATE statement appears before SELECT

问题

I'm using SQL Server 2014, pandas 0.23.4, sqlalchemy 1.2.11, pyodbc 4.0.24, and Python 3.7.0. I have a very simple stored procedure that performs an UPDATE on a table and then a SELECT on it:

CREATE PROCEDURE my_proc_1
    @v2     INT
AS
BEGIN
    UPDATE my_table_1 
    SET v2 = @v2 
    ;

    SELECT * from my_table_1
    ;
END 
GO

This runs fine in MS SQL Server Management Studio. However, when I try to invoke it via Python using this code:

import pandas as pd
from sqlalchemy import create_engine

if __name__ == "__main__":
    conn_str = 'mssql+pyodbc://@MODEL_TESTING'
    engine = create_engine(conn_str)
    with engine.connect() as conn:
        df = pd.read_sql_query("EXEC my_proc_1 33", conn)
        print(df)

I get the following error:

sqlalchemy.exc.ResourceClosedError: This result object does not return rows. It has been closed automatically.

(Please let me know if you want full stack trace, I will update if so)

When I remove the UPDATE from the stored proc, the code runs and the results are returned. Note also that selecting from a table other than the one being updated does not make a difference, I get the same error. Any help is much appreciated.

回答1:

The issue is that the UPDATE statement is returning a row count, which is a scalar value, and the rows returned by the SELECT statement are "stuck" behind the row count where pyodbc cannot "see" them (without additional machinations).

It is considered a best practice to ensure that our stored procedures always start with a SET NOCOUNT ON; statement to suppress the returning of row count values from DML statements (UPDATE, DELETE, etc.) and allow the stored procedure to just return the rows from the SELECT statement.

来源：https://stackoverflow.com/questions/53819199/pandas-sqlalchemy-pyodbc-result-object-does-not-return-rows-from-stored-proc-wh

标签

python

sql-server

pandas

sqlalchemy

pyodbc