def handler()

in main/src/training-build/training-build.py [0:0]
61 lines of code
13 McCabe index (conditional complexity)

def handler(event, context):
    trainId = event['trainId']
    trainInfo = trainConfigurationClient.getTraining(trainId)
    embeddingName = trainInfo['embeddingName']
    embeddingInfo = trainConfigurationClient.getEmbeddingInfo(embeddingName)
    filterDict={}
    if ('filterBucket' in trainInfo) and ('filterKey' in trainInfo):
        if (len(trainInfo['filterBucket'])>0) and (len(trainInfo['filterKey'])>0):
            filterBucket = trainInfo['filterBucket']
            filterKey = trainInfo['filterKey']
            fileObject = s3c.get_object(Bucket=filterBucket, Key=filterKey)
            text = fileObject['Body'].read().decode('utf-8')
            lines = text.splitlines()
            for line in lines:
                filterDict[line]=True
    filterCount = len(filterDict)
    print("Filter contains {} entries".format(filterCount))
    plateList = imageClient.listCompatiblePlates(embeddingInfo['inputWidth'], embeddingInfo['inputHeight'], embeddingInfo['inputDepth'], embeddingInfo['inputChannels'])
    filterCount=0
    unlabeledCount=0
    labelCount=0
    trainPrefixList=[]
    for i, pi in enumerate(plateList):
        plateId = pi['plateId']
        print("Processing plate {} {} of {}".format(plateId, i, len(plateList)))
        imageList = imageClient.getImagesByPlateId(plateId)
        imageListCount=len(imageList)
        print("Image list has {} entries".format(imageListCount))
        for imageItem in imageList:
            image = imageItem['Item']
            imageId = image['imageId']
            if imageId in filterDict:
                filterCount+=1
            else:
                if ('trainCategory' in image) and ('trainLabel' in image):
                    if (image['trainCategory']=='moa') and (len(image['trainLabel'])>0):
                        prefixKey = bp.getTrainPrefixKey(embeddingName, plateId, imageId)
                        trainPrefixList.append(prefixKey)
                        labelCount+=1
                    else:
                        unlabeledCount+=1
                else:
                    unlabeledCount+=1
    print("Train prefix list has {} entries".format(len(trainPrefixList)))
    print("labelCount={} filterCount={} unlabeldCount={}".format(labelCount, filterCount, unlabeledCount))
    trainPrefixArtifactPath = bp.getTrainImageListArtifactPath(trainId)
    trainPrefixStringList = "\n".join(trainPrefixList) + "\n"
    trainPrefixStringListBytes = bytes(trainPrefixStringList, encoding='utf-8')
    s3c.put_object(Body=trainPrefixStringListBytes, Bucket=BUCKET, Key=trainPrefixArtifactPath)
    akey = "s3key#" + trainPrefixArtifactPath
    artifact = {
        "contextId": trainId,
        "trainId": trainId,
        "artifact": akey
    }
    artifactClient.createArtifact(artifact)
    response = {
        "statusCode": 200,
        "body": "success"
    }
    return response