This page contains Windows bias

About This Page

This page is part of the Azure documentation. It contains code examples and configuration instructions for working with Azure services.

Bias Analysis

Bias Types:
⚠️ windows_first
⚠️ windows_tools
⚠️ missing_linux_example
Summary:
The documentation page demonstrates a bias towards Windows environments by exclusively referencing Windows tools (ODBC Driver 17 for SQL Server, Azure Data Studio), using Windows-style connection strings, and omitting any Linux-specific instructions or troubleshooting. There are no examples or notes for Linux users regarding driver installation, connection string differences, or alternative tools. The documentation assumes the reader is using Windows, which may hinder Linux users attempting the same workflow.
Recommendations:
  • Add explicit instructions for installing ODBC Driver 17 for SQL Server on Linux (e.g., Ubuntu, CentOS), including relevant package manager commands.
  • Mention that Azure Data Studio is cross-platform and provide download/installation links for Linux and macOS.
  • Provide Linux-specific connection string examples, noting any differences in driver naming or path syntax.
  • Include troubleshooting tips for common Linux issues (e.g., driver not found, permissions).
  • Clarify that the workflow is supported on both Windows and Linux, and ensure parity in setup and execution steps.
  • If any steps are Windows-only, clearly label them and offer Linux alternatives where possible.
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Scan History

Date Scan ID Status Bias Status
2025-08-17 00:01 #83 in_progress ✅ Clean
2025-07-13 21:37 #48 completed ❌ Biased
2025-07-09 13:09 #3 cancelled ✅ Clean
2025-07-08 04:23 #2 cancelled ❌ Biased

Flagged Code Snippets

import pyodbc server = '' # SQL Server IP address username = '' # SQL Server username password = '' # SQL Server password # Connect to the master DB to create the new onnx database connection_string = "Driver={ODBC Driver 17 for SQL Server};Server=" + server + ";Database=master;UID=" + username + ";PWD=" + password + ";" conn = pyodbc.connect(connection_string, autocommit=True) cursor = conn.cursor() database = 'onnx' query = 'DROP DATABASE IF EXISTS ' + database cursor.execute(query) conn.commit() # Create onnx database query = 'CREATE DATABASE ' + database cursor.execute(query) conn.commit() # Connect to onnx database db_connection_string = "Driver={ODBC Driver 17 for SQL Server};Server=" + server + ";Database=" + database + ";UID=" + username + ";PWD=" + password + ";" conn = pyodbc.connect(db_connection_string, autocommit=True) cursor = conn.cursor() table_name = 'models' # Drop the table if it exists query = f'drop table if exists {table_name}' cursor.execute(query) conn.commit() # Create the model table query = f'create table {table_name} ( ' \ f'[id] [int] IDENTITY(1,1) NOT NULL, ' \ f'[data] [varbinary](max) NULL, ' \ f'[description] varchar(1000))' cursor.execute(query) conn.commit() # Insert the ONNX model into the models table query = f"insert into {table_name} ([description], [data]) values ('Onnx Model',?)" model_bits = onnx_model.SerializeToString() insert_params = (pyodbc.Binary(model_bits)) cursor.execute(query, insert_params) conn.commit()
import sqlalchemy from sqlalchemy import create_engine import urllib db_connection_string = "Driver={ODBC Driver 17 for SQL Server};Server=" + server + ";Database=" + database + ";UID=" + username + ";PWD=" + password + ";" conn = pyodbc.connect(db_connection_string) cursor = conn.cursor() features_table_name = 'features' # Drop the table if it exists query = f'drop table if exists {features_table_name}' cursor.execute(query) conn.commit() # Create the features table query = \ f'create table {features_table_name} ( ' \ f' [CRIM] float, ' \ f' [ZN] float, ' \ f' [INDUS] float, ' \ f' [CHAS] float, ' \ f' [NOX] float, ' \ f' [RM] float, ' \ f' [AGE] float, ' \ f' [DIS] float, ' \ f' [RAD] float, ' \ f' [TAX] float, ' \ f' [PTRATIO] float, ' \ f' [B] float, ' \ f' [LSTAT] float, ' \ f' [id] int)' cursor.execute(query) conn.commit() target_table_name = 'target' # Create the target table query = \ f'create table {target_table_name} ( ' \ f' [MEDV] float, ' \ f' [id] int)' x_train['id'] = range(1, len(x_train)+1) y_train['id'] = range(1, len(y_train)+1) print(x_train.head()) print(y_train.head())
db_connection_string = 'mssql+pyodbc://' + username + ':' + password + '@' + server + '/' + database + '?driver=ODBC+Driver+17+for+SQL+Server' sql_engine = sqlalchemy.create_engine(db_connection_string) x_train.to_sql(features_table_name, sql_engine, if_exists='append', index=False) y_train.to_sql(target_table_name, sql_engine, if_exists='append', index=False)