Python - Pyodbc Says 'record Inserted', But SSMS Says No Record Inserted

May 22, 2025 by ADMIN 73 views

**Python - pyodbc says 'record inserted', but SSMS says no record inserted**

Introduction

When working with databases using Python and the pyodbc library, it's not uncommon to encounter issues that can be frustrating to resolve. One such issue is when pyodbc reports that a record has been inserted, but the SQL Server Management Studio (SSMS) shows no record inserted. In this article, we'll explore the possible reasons behind this discrepancy and provide solutions to help you resolve the issue.

Understanding the Problem

The problem arises when there's a mismatch between the data being inserted using pyodbc and the data being displayed in SSMS. This can happen due to various reasons such as:

Data type mismatch: When the data types of the columns in the SQL Server table and the data being inserted using pyodbc are different, it can lead to this issue.
Auto-incrementing ID: When the ID column in the SQL Server table is set to auto-increment, pyodbc might not be able to retrieve the newly inserted ID, leading to the discrepancy.
Transaction issues: If the transaction is not committed or rolled back properly, it can cause the issue.

Possible Causes

1. Data Type Mismatch

When the data types of the columns in the SQL Server table and the data being inserted using pyodbc are different, it can lead to this issue. For example, if the column in the SQL Server table is defined as int, but the data being inserted using pyodbc is a float, it can cause the issue.

Solution

To resolve this issue, ensure that the data types of the columns in the SQL Server table and the data being inserted using pyodbc are the same. You can use the pyodbc library's cursor.execute() method to execute a SQL query that checks the data type of the column.

import pyodbc
conn = pyodbc.connect("Driver={SQL Server Native Client 11.0};"
"Server=DESKTOP-NLPIRC6\MSSQLSERVER02;"
"Database=myDatabase;"
"Trusted_Connection=yes;")
cursor = conn.cursor()
cursor.execute("SELECT DATA_TYPE FROM INFORMATION_SCHEMA.COLUMNS WHERE TABLE_NAME = 'myTable' AND COLUMN_NAME = 'myColumn'")
data_type = cursor.fetchone()[0]
print(data_type)

2. Auto-incrementing ID

When the ID column in the SQL Server table is set to auto-increment, pyodbc might not be able to retrieve the newly inserted ID, leading to the discrepancy.

Solution

To resolve this issue, you can use the pyodbc library's cursor.execute() method to execute a SQL query that retrieves the newly inserted ID.

import pyodbc
conn = pyodbc.connect("Driver={SQL Server Native Client 11.0};"
"Server=DESKTOP-NLPIRC6\MSSQLSERVER02;"
"Database=myDatabase;"
"Trusted_Connection=yes;")
cursor = conn.cursor()

cursor.execute("INSERT INTO myTable (myColumn) VALUES ('myValue')")

cursor.execute("SELECT SCOPE_IDENTITY()")
new_id = cursor.fetchone()[0]
print(new_id)

3. Transaction Issues

If the transaction is not committed or rolled back properly, it can cause the issue.

Solution

To resolve this issue, ensure that the transaction is committed or rolled back properly. You can use the pyodbc library's cursor.commit() method to commit the transaction.

import pyodbc
conn = pyodbc.connect("Driver={SQL Server Native Client 11.0};"
"Server=DESKTOP-NLPIRC6\MSSQLSERVER02;"
"Database=myDatabase;"
"Trusted_Connection=yes;")
cursor = conn.cursor()
try:
# Insert a record
cursor.execute("INSERT INTO myTable (myColumn) VALUES ('myValue')")
# Commit the transaction
conn.commit()

except Exception as e:
# Roll back the transaction if an error occurs
conn.rollback()
print(e)

Conclusion

In conclusion, the issue of pyodbc reporting that a record has been inserted, but SSMS showing no record inserted, can be caused by various reasons such as data type mismatch, auto-incrementing ID, and transaction issues. By understanding the possible causes and using the solutions provided in this article, you can resolve the issue and ensure that your data is inserted correctly using pyodbc.

Best Practices

To avoid this issue in the future, follow these best practices:

Use the correct data types: Ensure that the data types of the columns in the SQL Server table and the data being inserted using pyodbc are the same.
Use auto-incrementing ID correctly: If the ID column in the SQL Server table is set to auto-increment, ensure that you use the pyodbc library's cursor.execute() method to execute a SQL query that retrieves the newly inserted ID.
Commit or roll back transactions properly: Ensure that the transaction is committed or rolled back properly to avoid any issues.

Introduction

In our previous article, we discussed the issue of pyodbc reporting that a record has been inserted, but SSMS showing no record inserted. We explored the possible causes of this issue and provided solutions to help you resolve it. In this article, we'll answer some frequently asked questions related to this issue.

Q: What are the common causes of this issue?

A: The common causes of this issue are:

Data type mismatch: When the data types of the columns in the SQL Server table and the data being inserted using pyodbc are different.
Auto-incrementing ID: When the ID column in the SQL Server table is set to auto-increment, pyodbc might not be able to retrieve the newly inserted ID.
Transaction issues: If the transaction is not committed or rolled back properly.

Q: How can I resolve the data type mismatch issue?

A: To resolve the data type mismatch issue, ensure that the data types of the columns in the SQL Server table and the data being inserted using pyodbc are the same. You can use the pyodbc library's cursor.execute() method to execute a SQL query that checks the data type of the column.

import pyodbc
conn = pyodbc.connect("Driver={SQL Server Native Client 11.0};"
"Server=DESKTOP-NLPIRC6\MSSQLSERVER02;"
"Database=myDatabase;"
"Trusted_Connection=yes;")
cursor = conn.cursor()

cursor.execute("SELECT DATA_TYPE FROM INFORMATION_SCHEMA.COLUMNS WHERE TABLE_NAME = 'myTable' AND COLUMN_NAME = 'myColumn'")
data_type = cursor.fetchone()[0]
print(data_type)

Q: How can I retrieve the newly inserted ID when the ID column is set to auto-increment?

A: To retrieve the newly inserted ID when the ID column is set to auto-increment, you can use the pyodbc library's cursor.execute() method to execute a SQL query that retrieves the newly inserted ID.

import pyodbc
conn = pyodbc.connect("Driver={SQL Server Native Client 11.0};"
"Server=DESKTOP-NLPIRC6\MSSQLSERVER02;"
"Database=myDatabase;"
"Trusted_Connection=yes;")
cursor = conn.cursor()

cursor.execute("INSERT INTO myTable (myColumn) VALUES ('myValue')")

cursor.execute("SELECT SCOPE_IDENTITY()")
new_id = cursor.fetchone()[0]
print(new_id)

Q: How can I commit or roll back transactions properly?

A: To commit or roll back transactions properly, ensure that you use the pyodbc library's cursor.commit() method to commit the transaction or the pyodbc library's cursor.rollback() method to roll back the transaction.

import pyodbc
conn = pyodbc.connect("Driver={SQL Server Native Client 11.0};"
"Server=DESKTOP-NLPIRC6\MSSQLSERVER02;"
"Database=myDatabase;"
"Trusted_Connection=yes;")
cursor = conn.cursor()
try:
# Insert a record
cursor.execute("INSERT INTO myTable (myColumn) VALUES ('myValue')")
# Commit the transaction
conn.commit()

except Exception as e:
# Roll back the transaction if an error occurs
conn.rollback()
print(e)

Q: What are the best practices to avoid this issue?

A: To avoid this issue in the future, follow these best practices:

Use the correct data types: Ensure that the data types of the columns in the SQL Server table and the data being inserted using pyodbc are the same.
Use auto-incrementing ID correctly: If the ID column in the SQL Server table is set to auto-increment, ensure that you use the pyodbc library's cursor.execute() method to execute a SQL query that retrieves the newly inserted ID.
Commit or roll back transactions properly: Ensure that the transaction is committed or rolled back properly to avoid any issues.