def get_inference()

in container_images/batch_image/inference.py [0:0]

• 26 lines of code
• 4 McCabe index (conditional complexity)

def get_inference(inputBucket, fileName, region):
    s3 = boto3.client('s3')
    inputFilePath = '/tmp/'+fileName
    inferenceFilePath = '/tmp/'+fileName.split('.')[0]+'_out.csv'
    # Download file from S3
    try:
        s3.download_file(inputBucket, INPUT_PREFIX+fileName, inputFilePath)

    except ClientError as e:
        logMessage(fileName, "Error retrieving file from S3 using `download_fileobj`" + str(e), LOGTYPE_DEBUG)

    # Process file
    try:
        inference = resnet_pipeline(inputFilePath, fileName)
        print("inference from resnet_pipeline as below:")
        print(inference)
        with open(inferenceFilePath, "w") as ff:
            ff.write(inference)

    except Exception as e:
        logMessage(fileName, "Error processing file " + str(e), LOGTYPE_DEBUG)

    # Upload processed file to S3
    try:
        endTime = datetime.now()
        with open(inferenceFilePath, 'rb') as file:
            s3.upload_fileobj(
                file,
                inputBucket,
                'output/'+endTime.strftime("%m-%d-%Y-%H:%M:%S.%f")[:-3]+'-'+fileName.split('.')[0]+'.csv'
                )

    except ClientError as e:
        logMessage(fileName, "Can't upload to S3 using `upload_fileobj`" + str(e), LOGTYPE_DEBUG)