带有 python 和 aws lambda 的无服务器框架

Question

当我从另一个文件导入一个函数并进行部署时，它不起作用。 它给我：错误 500 内部服务器错误。 python 要求工作正常，因为 hello 函数没有给我错误。但是 getPrediction 效果不佳

在离线模式下一切正常。

我的 handler.js

try:
    import unzip_requirements
except ImportError:
    pass

import json
import numpy
import scipy
from predictions.make_prediction import make_prediction

def hello(event, context):

    response = {"statusCode": 200, "body": {mod.__name__: mod.__version__ for mod in (numpy, scipy)}}
    return response 

def getPrediction(event, context):
    hola = make_prediction([1,2,3,4,5,6,7])
    response = {"statusCode": 200, "body": json.dumps(hola.tolist())}
    return response 

我的 serverless.yml

service: enno-searcher
frameworkVersion: '3'

provider:
  name: aws
  runtime: python3.7
  timeout: 29

plugins:
  - serverless-offline
  - serverless-python-requirements

package:
 patterns:
   - '!node_modules/**'
   - '!Lib/**'
   - '!README.md'
   - '!build/**'
   - '!__pycache__/**'
   - '!Include/**'

custom:
  pythonRequirements:
    dockerizePip: true
    zip: true

functions:
  hello:
    handler: handler.hello
    events:
      - httpApi:
          path: /
          method: get
  getPrediction:
    handler: handler.getPrediction
    events:
      - httpApi:
          path: /get-prediction
          method: get

我试过改变我导入外部函数的方式，但它总是给我同样的错误。也许我做错了

我也试过不从其他文件导入函数。我试过将代码从 make_prediction 带到 getPrediction，但它一直给我一个错误。

Answer 1

我已经设法用无服务器框架解决了我的问题。经过多次测试，这就是我的文件“handler.py”和我的“serverless.yml”的保留方式

无服务器.yml

service: enno-searcher
frameworkVersion: '3'

provider:
  name: aws
  runtime: python3.7
  timeout: 29
  httpApi:
    cors: true

package:
  patterns:
   - '!node_modules/**'
   - '!Lib/**'
   - '!README.md'
   - '!build/**'
   - '!__pycache__/**'
   - '!Include/**'

functions:
  hello:
    handler: handler.hello
    events:
      - httpApi:
          path: /
          method: get
  test:
    handler: handler.test
    events:
      - httpApi:
          path: /test
          method: get
  getprediction:
    handler: handler.getPrediction
    events:
      - httpApi:
          path: /get-prediction
          method: get

plugins:
  - serverless-offline
  - serverless-python-requirements

custom:
  pythonRequirements:
    dockerizePip: non-linux
    zip: true

处理程序.py

try:
    import unzip_requirements
except ImportError:
    pass

import json

def hello(event, context):
    response = {
        "statusCode": 200,
        'headers': {
            'Access-Control-Allow-Origin': '*',
            "Access-Control-Allow-Credentials": True
        },
        "body": 'Searcher Backend v0.0.1'}
    return response

def test(event, context):
    from predictions.make_prediction import make_prediction
    hola = make_prediction([1,2,3,4,5,6,7])
    response = {
        "statusCode": 200,
        'headers': {
            'Access-Control-Allow-Origin': '*',
            "Access-Control-Allow-Credentials": True
        },
        "body": json.dumps(
        hola.tolist()
    )}
    return response 

def getPrediction(event, context):
    try:
        from predictions.make_prediction import make_prediction
        inputPrediction = event['queryStringParameters']['prediction']
        prediction = make_prediction(eval(inputPrediction))
        response = {
            "statusCode": 200,
            'headers': {
                'Access-Control-Allow-Origin': '*',
                "Access-Control-Allow-Credentials": True
            },
            "body": json.dumps(
            prediction.tolist()
        )}
        return response
    
    except KeyError as e:
        error_message = f'Faltan los parametros requeridos: {e}'
        response = {
            'statusCode': 400,
            'headers': {
                'Access-Control-Allow-Origin': '*',
                "Access-Control-Allow-Credentials": True
            },
            'body': json.dumps({'error': error_message})
        }
        return response
    
    except Exception as e:
        # Captura cualquier otra excepción y devuelve un mensaje de error genérico
        error_message = f'Se produjo un error al procesar la solicitud: {e}'
        response = {
            'statusCode': 500,
            'headers': {
                'Access-Control-Allow-Origin': '*',
                "Access-Control-Allow-Credentials": True
            },
            'body': json.dumps({'error': error_message})
        }
        return response

这样，我已经成功地从其他文件导入功能了。通过在每个函数中导入它，我设法控制了错误。我还添加了 try 和 except 来进一步处理错误。我还在 API 中添加了 cors。

此外，我还添加了更多函数（我没有放在这里），其结构与“getPrediction”函数相同。他们对我来说都很完美。