Understanding INSERT Statements in MS SQL (Azure) from Python

As a programmer, interacting with databases is an essential part of any project. When working with Microsoft SQL Server (MS SQL) databases, particularly those hosted on Azure, understanding how to execute INSERT statements efficiently is crucial. In this article, we will delve into the world of MS SQL and explore why calling INSERT statements from Python can result in errors.

Setting Up Your Environment

Before diving into the technical aspects, it’s essential to set up your development environment. You’ll need:

• A Python interpreter installed on your machine
• The pyodbc library for interacting with MS SQL databases
• An Azure account or access to a local MS SQL Server instance

Understanding the Problem

The original question highlights two scenarios where attempting to execute INSERT statements from Python results in errors. We’ll break down each scenario and explore potential solutions.

Scenario 1: Using Pure pyodbc

import pyodbc
server = 'server'
database = 'db'
username = 'user'
password = 'pswd'
driver= '{ODBC Driver 17 for SQL Server}'
cnxn = pyodbc.connect('DRIVER='+driver+';SERVER='+server+';PORT=1433;DATABASE='+database+';UID='+username+';PWD='+ password)
cursor = cnxn.cursor()

query = "SET NOCOUNT ON INSERT INTO foo ([x],[y],[z]) VALUES(1,1,1)  "

cursor.execute(query)

row = cursor.fetchone() 
while row: 
    print (row)
    row = cursor.fetchone()

In this example, the pyodbc library is used to connect to the MS SQL Server instance and execute an INSERT statement. However, the code fails with a pyodbc.ProgrammingError exception, indicating that there are no results from the query.

Scenario 2: Using SQLAlchemy, PyODBC, and Pandas

import sqlalchemy
import pyodbc
import urllib
import pandas as pd

server = 'server'
database = 'db'
username = 'user'
password = 'pswd'
driver= '{ODBC Driver 17 for SQL Server}'

params = urllib.parse.quote_plus('DRIVER='+driver+';SERVER='+server+';PORT=1433;DATABASE='+database+';UID='+username+';PWD='+ password)
engine = sqlalchemy.create_engine("mssql+pyodbc:///?odbc_connect=%s" % params)

sql = "SET NOCOUNT ON INSERT INTO foo ([x],[y],[z]) VALUES(1,1,1)"
sql_df = pd.read_sql(sql=sql, con = engine)

In this example, the sqlalchemy library is used to create a connection to the MS SQL Server instance using pyodbc. The code then attempts to execute an INSERT statement and retrieve the results. However, it fails with a ResourceClosedError exception.

The Issue: Understanding SET NOCOUNT ON

In both scenarios, the SET NOCOUNT ON statement is used to suppress the count of rows affected by the query. This statement is useful in certain situations, such as when executing bulk INSERT statements or when working with cursors that return large amounts of data.

However, when using pyodbc, sqlalchemy, or other libraries that interact with MS SQL databases, there’s an underlying issue: these libraries don’t actually see the rows affected by the query. This is because the SET NOCOUNT ON statement is a server-side setting that doesn’t affect how the client library (in this case, pyodbc, sqlalchemy, or Pandas) interacts with the database.

The Solution: Removing SET NOCOUNT ON

To resolve these issues, you should remove the SET NOCOUNT ON statement from your INSERT queries. This will allow the libraries to accurately track the number of rows affected by the query and retrieve the results correctly.

Best Practices for Handling Results

When working with MS SQL databases, it’s essential to handle the results of your queries carefully. Here are some best practices to keep in mind:

• Always remove SET NOCOUNT ON statements from your INSERT queries.
• Use the correct type of cursor (e.g., pyodbc.Cursor or sqlalchemy.engine.RowProxy) for retrieving and processing query results.
• Be aware of how libraries handle errors and exceptions, as they may behave differently than expected.

Conclusion

Calling INSERT statements in MS SQL (Azure) from Python can result in errors due to the way SET NOCOUNT ON affects how client libraries interact with the database. By removing this statement and understanding how client libraries work, you can write more efficient and effective code for interacting with your MS SQL databases.

Last modified on 2023-08-23