2

我正在自动化 AWS Textract 流程，其中文件使用应用程序（我已经完成）上传到 S3，触发 lambda 函数，将表单提取为 CSV，并将其保存在同一个存储桶中。

我从图像中所有文本的 Textract 公式开始，结果是一个 .txt 文件。下面是我的代码：

def InvokeTextract(bucketName, documentKey):
    print('Loading InvokeTextract')
    # Call Amazon Textract
    response = textract.detect_document_text(
        Document={
            'S3Object': {
                'Bucket': bucketName,
                'Name': documentKey
            }
        })

    Textractoutput = ''

    # Print detected text
    for item in response['Blocks']:
        if item['BlockType'] == 'LINE':
            Textractoutput += item['Text'] + '\n'

    return Textractoutput

def writeOutputToS3Bucket(textractData, bucketName, createdS3Document):
    print('Loading writeOutputToS3Bucket')
    generateFilePath = os.path.splitext(createdS3Document)[0] + '.txt'
    s3.put_object(Body=textractData, Bucket=bucketName, Key=generateFilePath)
    print('Generated ' + generateFilePath)


def lambda_handler(event, context):
    # Get the object from the event and show its content type
    bucket = event['Records'][0]['s3']['bucket']['name']
    key = urllib.parse.unquote_plus(event['Records'][0]['s3']['object']['key'], encoding='utf-8')
    try:
        Textractoutput = InvokeTextract(bucket, key)
        writeOutputToS3Bucket(Textractoutput, bucket, key)

        return 'Processed'

这工作很好，但如果我想获得键值对，这没有帮助。所以，我尝试对 CSV 使用另一个代码。从我的本地驱动器，我能够做到这一点。以下是我的部分代码：

import trp #Local Module
import csv

doc = Document(response) #from TRP

with open('aws_doc.csv', mode='w') as aws_field_file:
    field_write = csv.writer(aws_field_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
    field_write.writerow(["Key", "Value"])

    for page in doc.pages:
        for field in page.form.fields:
            # This will write it as your <key>, <value>
            field_write.writerow([field.key, field.value])

但是当我尝试使用 Lambda 进行编码时，我没有得到结果（即我的存储桶中的 CSV 文件）。我阅读了它，发现我需要创建一个 tmp 文件，但这有点不清楚。我使用下面的代码：

def lambda_handler(event, context):
    # Get the object from the event and show its content type
    bucketName = event['Records'][0]['s3']['bucket']['name']
    documentKey = urllib.parse.unquote_plus(event['Records'][0]['s3']['object']['key'], encoding='utf-8')

    #S3 client
    s3 = boto3.resource('s3')

    # Amazon Textract client
    textract = boto3.client('textract')

    # Get AWS Textract Response for Forms
    response = textract.analyze_document(
        Document={
            'S3Object': {
                'Bucket': bucketName,
                'Name': documentKey
            }
        },
        FeatureTypes = ["FORMS"])

    # Using custom trp module
    doc = Document(response)

    import csv 

    temp_csv_file = csv.writer(open("/tmp/csv_file.csv", "w+"))
    temp_csv_file.writerow(["Key", "Value"])

    for page in doc.pages:
        for field in page.form.fields:
            # This will write it as your <key>, <value>
            temp_csv_file.writerow([field.key, field.value])

    bucketName.upload_file('/tmp/csv_file.csv', 'textractData.csv')

我的代码正确吗？我错过了那里的一步吗？

4

2 回答 2

0

除非您需要创建临时文件，否则请尝试此操作。

s3.put_object(Body='contents', Bucket='bucket-name', Key='outputTextFileName')

通过如下实现使其工作：

def writeCSV(csvData):
    body = StringIO() #because s3 require bytes or file like obj
    writer = csv.writer(body)
    for item in csvData:
        writer.writerow(item)
    csvS3 = body.getvalue()
    return csvS3

contents = writeCSV('provide csv data')
s3.put_object(Body=contents, Bucket='bucket-name', Key='outputTextFileName')
  • S3 必须使用之前定义s3 = boto3.client('s3')
  • Bucket 必须与 lambda 函数存在于同一区域
于 2019-11-05T09:59:04.237 回答
0

代替

bucketName.upload_file('/tmp/csv_file.csv', 'textractData.csv')

尝试

s3.upload_file('/tmp/csv_file.csv', bucketName, 'textractData.csv')
于 2019-10-09T13:09:11.660 回答