Sad Tux - Windows bias detected
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

Detected Bias Types
windows_first
missing_linux_example
windows_tools
Summary
The documentation page demonstrates a Windows bias by referencing Windows-specific tools and patterns (such as 'command prompt', backslash path separators, and lack of Linux/MacOS terminal instructions). There are no explicit Linux or cross-platform instructions for running scripts or handling file paths, and all examples assume a Windows environment.
Recommendations
  • Provide equivalent instructions for Linux and MacOS, such as using 'terminal' instead of 'command prompt', and show relevant shell commands.
  • Use platform-agnostic path handling in code examples (e.g., os.path.join instead of hardcoded backslashes).
  • Show both Windows and Linux/MacOS commands for installing dependencies and running scripts.
  • Explicitly mention that the scripts are cross-platform and note any platform-specific considerations.
  • Include screenshots or terminal output from Linux/MacOS environments where appropriate.
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Scan History

Date Scan Status Result
2026-01-14 00:00 #250 in_progress Clean Clean
2026-01-13 00:00 #246 completed Clean Clean
2026-01-11 00:00 #240 completed Clean Clean
2026-01-10 00:00 #237 completed Clean Clean
2026-01-09 00:34 #234 completed Clean Clean
2026-01-08 00:53 #231 completed Clean Clean
2026-01-06 18:15 #225 cancelled Clean Clean
2025-08-17 00:01 #83 cancelled Clean Clean
2025-07-13 21:37 #48 completed Clean Clean
2025-07-09 13:09 #3 cancelled Clean Clean
2025-07-08 04:23 #2 cancelled Biased Biased

Flagged Code Snippets

    import os
    import string
    import json
    import uuid
    import avro.schema
    
    from azure.storage.blob import ContainerClient, BlobClient
    from avro.datafile import DataFileReader, DataFileWriter
    from avro.io import DatumReader, DatumWriter
    
    
    def processBlob2(filename):
        reader = DataFileReader(open(filename, 'rb'), DatumReader())
        dict = {}
        for reading in reader:
            parsed_json = json.loads(reading["Body"])
            if not 'id' in parsed_json:
                return
            if not parsed_json['id'] in dict:
                list = []
                dict[parsed_json['id']] = list
            else:
                list = dict[parsed_json['id']]
                list.append(parsed_json)
        reader.close()
        for device in dict.keys():
            filename = os.getcwd() + '\\' + str(device) + '.csv'
            deviceFile = open(filename, "a")
            for r in dict[device]:
                deviceFile.write(", ".join([str(r[x]) for x in r.keys()])+'\n')
    
    def startProcessing():
        print('Processor started using path: ' + os.getcwd())
        # Create a blob container client.
        container = ContainerClient.from_connection_string("AZURE STORAGE CONNECTION STRING", container_name="BLOB CONTAINER NAME")
        blob_list = container.list_blobs() # List all the blobs in the container.
        for blob in blob_list:
            # Content_length == 508 is an empty file, so process only content_length > 508 (skip empty files).        
            if blob.size > 508:
                print('Downloaded a non empty blob: ' + blob.name)
                # Create a blob client for the blob.
                blob_client = ContainerClient.get_blob_client(container, blob=blob.name)
                # Construct a file name based on the blob name.
                cleanName = str.replace(blob.name, '/', '_')
                cleanName = os.getcwd() + '\\' + cleanName 
                with open(cleanName, "wb+") as my_file: # Open the file to write. Create it if it doesn't exist. 
                    my_file.write(blob_client.download_blob().readall()) # Write blob contents into the file.
                processBlob2(cleanName) # Convert the file into a CSV file.
                os.remove(cleanName) # Remove the original downloaded file.
                # Delete the blob from the container after it's read.
                container.delete_blob(blob.name)
    
    startProcessing()