AWS Lambda 在 lambda 调用中削减我的有效负载

Question

我用一个奇怪的问题困扰了我一整天。 我正在尝试发送以 base64 编码的 .docx 文件文档，最初，我认为 AWS Api 网关正在削减我的主体请求，但通过 awscli 直接调用我检查 lambda 正在削减主体有效负载的一部分。 让我演示给你看：

这是我的 lambda function 的片段：

def lambda_handler(event, context):
    if event["httpMethod"] == "GET":
        return {
            'statusCode': 200,
            'body': json.dumps('Hello from PDFTron! Please send base64 doc to use this Lambda function!')
        }

    elif event["httpMethod"] == "POST":
        try:
            output_path    = "/tmp/"
            body           = json.loads(str(event["body"])) # <--- the error is thrown here
            base64str      = body["file"]["data"]
            filename       = body["file"]["filename"]
            base64_bytes   = base64decode(base64str)
            input_filename = filename.split('.')[0] + "docx"

你能检查lambda_function.py中的完整文件吗

好的，现在我尝试使用以下命令行通过 awscli 调用我的 function：

aws lambda invoke \
  --profile lab \
  --region us-east-1 \
  --function-name pdf_sign \
  --cli-binary-format raw-in-base64-out \
  --log-type Tail \
  --query 'LogResult' \
  --output text \
  --payload file://payload.json response.json | base64 -d

payload.json

并收到错误：

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'}}}
[ERROR] Runtime.MarshalError: Unable to marshal response: Object of type KeyError is not JSON serializable
Traceback (most recent call last):END RequestId: a26b93bd-bcf2-4072-99da-29ffcc3bc350
REPORT RequestId: a26b93bd-bcf2-4072-99da-29ffcc3bc350  Duration: 11.92 ms      Billed Duration: 12 ms  Memory Size: 1024 MB    Max Memory Used: 93 MB

当我在我的代码上添加调试（打印命令）时，我可以检查有效载荷是否被切割，并且在日志错误中包含我的有效载荷的最后部分（例如RX4GAGN1c3RvbVhtbC9pdGVtMS54bWxQSwUGAAAAABEAEQBdBAAAQn8GAAAA'}}} 。

阅读关于 lambda 配额和限制的 aws 文档，我们可以看到调用负载限制为 6MB，与我的负载大小 (232kb) 有很大不同

资源	配额
调用负载（请求和响应）	请求和响应（同步）各 6 MB； 256 KB（异步）

资料来源： https://docs.aws.amazon.com/lambda/latest/dg/gettingstarted-limits.html

我真的认为我正在做所有事情，遵守规则，这里有人可以告诉我并帮助我，我哪里出错或误解了？

我希望我的请求的有效负载正确到达我的 python function。

Answer 1

您如何在 Lambda function 中记录event ？

似乎问题出在这一行： body = json.loads(str(event["body"]))

您正在使用 CLI 并且基于文档，事件将作为字符串发送。 所以需要JSON先解析事件object。

            output_path    = "/tmp/"
            e = json.loads(event)
            body           = str(e["body"])
            base64str      = body["file"]["data"]
            filename       = body["file"]["filename"]
            base64_bytes   = base64decode(base64str)
            input_filename = filename.split('.')[0] + "docx"