How to call Microsoft SQL Server Stored Procedure from within Python using SQL Alchemy

Question

I would like to execute a Stored Procedure residing on Microsoft SQL Server using Python and SQL Alchemy.

So far I am able to connect to Microsoft SQL Server, run simple select query, assign it to a Panda Data Frame and save it to an csv file using the following code:

from sqlalchemy import create_engine
import pandas as pd
Server='Jaar'
Database='M'
Driver='ODBC Driver 17 for SQL Server'
Database_Con = f'mssql://@{Server}/{Database}?driver={Driver}'
engine=create_engine(Database_Con)
con = engine.connect()
df=pd.read_sql_query("SELECT * FROM [M].[Dim].[Accounts_t]",con)

However, I've tried unsuccessfully to do the same with a SP which takes two parameters

Furthermore, I have not been able to get this example to work: https://sql-query.dev/articles/1767

And haven't found much in the SQL Alchemy documentation that can help me.

Thanks

The SP that I want to execute is below:

USE [M]
GO

DECLARE @return_value int

EXEC    @return_value = [Reporting].[Finance_Payments_Mvmts_sp]
        @PeriodStart = 202212,
        @PeriodEnd = 202310

SELECT  'Return Value' = @return_value

GO

Answer 1

I couldn't work with SQL Alchemy and SQL Server so I finally found another Python module for accessing SQL Server called pymssql:

import pymssql
import pandas as pd
conn = pymssql.connect(server = 'Jaar', database = 'M')
cursor = conn.cursor(as_dict=True)
PeriodStart = 202212
PeriodEnd = 202310
cursor.callproc('[Reporting].[Finance_Payments_Mvmts_sp]', (PeriodStart, PeriodEnd))
(202212, 202310)
rows = []
for row in cursor:
    rows.append(row)

df = pd.DataFrame(rows)
print(df)

df.to_csv("TestOutput.csv")

Does what I need it to do which is to run a SQL Server Stored Procedure with input parameters

https://pypi.org/project/pymssql/