Azure函数V2风格编码- Http触发器和blob输出绑定

dsf9zpds 于 2023-10-22 发布在其他

关注(0)|答案(1)|浏览(151)

我有下面的代码，它在本地启动时可以无故障地运行。我输入URL，该函数通过从API检索TFL有效负载并将数据存储在blob存储中来执行其任务。此过程通过访问URL http：//localhost：7071/api/tfl_blob触发。
尽管如此，在将此代码部署到Azure平台时，部署过程不会出现任何错误消息，但函数不会出现在函数应用程序中。虽然我可以访问应用程序文件，但我在触发它时遇到了困难，当我导航到功能概述页面时，该功能明显缺失。
问题可能是什么以及如何解决？
功能代码：

import datetime
import json
import requests
import azure.functions as func
import logging
import uuid

app = func.FunctionApp()

def generate_blob_path():
    current_datetime = datetime.datetime.now()
    date_str = current_datetime.strftime('%Y-%m-%d')
    unique_id = str(uuid.uuid4())
    blob_path = f"bloboutput/{date_str}/{unique_id}.json"
    return blob_path

_blob_path = generate_blob_path()

@app.function_name(name="HttpTflBlobOut")
@app.route(route="tfl_blob")
@app.blob_output(arg_name="blob",
                 path=_blob_path,
                 connection="AzureWebJobsStorage")
def main(req: func.HttpRequest, blob: func.Out[str]) -> func.HttpResponse:
    try:
        result = requests.get('https://api.tfl.gov.uk/line/mode/tube/status',
                              headers={"content-type": "application/json", "charset": "utf-8"})

        logging.info('Python HTTP trigger function processed the API request to TFL')

        since_id = None
        timeline = json.loads(result.text)

        tflLineStatus = []
        for t in timeline:
            if since_id is None:
                since_id = t["id"]

            tflLineStatus.append({
                "linename": t["id"],
                "linestatus": t["lineStatuses"][0]["statusSeverityDescription"],
                "timestamp": t["created"]
            })

        if since_id is None:
            since_id = req.state.since_id

        ans = {
            "state": {
                since_id: since_id
            },
            "schema": {
                "tflLineStatus": {
                    "primary_key": ["linename"]
                }
            },
            "insert": {
                "tflLineStatus": tflLineStatus
            },
            "hasMore": False
        }

        logging.info('Payload is constructed')

        payload = json.dumps(ans, indent=4)
        logging.info('Payload is converted to a string')
        blob.set(payload)

        return func.HttpResponse(f"Function executed successfully", status_code=200)
    except Exception as e:
        logging.error(f"Error: {str(e)}")
        return func.HttpResponse("Internal Server Error", status_code=500)

host.json

{
  "version": "2.0",
  "logging": {
    "applicationInsights": {
      "samplingSettings": {
        "isEnabled": true,
        "excludedTypes": "Request"
      }
    }
  },
  "extensionBundle": {
    "id": "Microsoft.Azure.Functions.ExtensionBundle",
    "version": "[4.*, 5.0.0)"
  }
}

local.settings.json:

{
  "IsEncrypted": false,
  "Values": {
    "FUNCTIONS_WORKER_RUNTIME": "python",
    "AzureWebJobsFeatureFlags": "EnableWorkerIndexing",
    "AzureWebJobsStorage": <match with storage account connection string and also set on the az function>,
    "FUNCTIONS_EXTENSION_VERSION": "~4",
    "APPLICATIONINSIGHTS_CONNECTION_STRING": "<match with the function config on az>"
  },
  "ConnectionStrings": {}
}

我的期望是，我应该能够通过HTTP请求调用函数，使用以下URL格式：https://<function app name>.azurewebsites.net/api/<function name>?code=<function key>。它的表现应该与它在本地的表现相似。但是，我遇到了一个HTTP错误404，表明无法找到该页面。

Azure

来源：https://stackoverflow.com/questions/77293828/azure-function-v2-style-coding-http-trigger-and-blob-output-binding

1条答案

按热度按时间

fykwrbwg1#

*我在我的环境中尝试了你的代码。我能够运行函数代码并部署它。
编码：

import datetime
import json 
import requests 
import azure.functions as func 
import logging 
import uuid

app = func.FunctionApp()

def generate_blob_path():
    current_datetime = datetime.datetime.now()
    date_str = current_datetime.strftime('%Y-%m-%d')
    unique_id = str(uuid.uuid4())
    blob_path = f"bloboutput/{date_str}/{unique_id}.json"
    return blob_path

_blob_path = generate_blob_path()

@app.function_name(name="HttpTflBlobOut") @app.route(route="tfl_blob")
@app.blob_output(arg_name="blob",
                 path=_blob_path,
                 connection="AzureWebJobsStorage") def main(req: func.HttpRequest, blob: func.Out[str]) -> func.HttpResponse:
    try:
        result = requests.get('https://api.tfl.gov.uk/line/mode/tube/status',
                              headers={"content-type": "application/json", "charset": "utf-8"})

        logging.info('Python HTTP trigger function processed the API request to TFL')

        since_id = None
        timeline = json.loads(result.text)

        tflLineStatus = []
        for t in timeline:
            if since_id is None:
                since_id = t["id"]

            tflLineStatus.append({
                "linename": t["id"],
                "linestatus": t["lineStatuses"][0]["statusSeverityDescription"],
                "timestamp": t["created"]
            })

        if since_id is None:
            since_id = req.state.since_id

        ans = {
            "state": {
                since_id: since_id
            },
            "schema": {
                "tflLineStatus": {
                    "primary_key": ["linename"]
                }
            },
            "insert": {
                "tflLineStatus": tflLineStatus
            },
            "hasMore": False
        }

        logging.info('Payload is constructed')

        payload = json.dumps(ans, indent=4)
        logging.info('Payload is converted to a string')
        blob.set(payload)

        return func.HttpResponse(f"Function executed successfully", status_code=200)
    except Exception as e:
        logging.error(f"Error: {str(e)}")
        return func.HttpResponse("Internal Server Error", status_code=500) ```

local.settings.json：

{
  "IsEncrypted": false,
  "Values": {
    "FUNCTIONS_WORKER_RUNTIME": "python",
    "AzureWebJobsFeatureFlags": "EnableWorkerIndexing",
    "AzureWebJobsStorage": "<storage_connec_string>",
    "FUNCTIONS_EXTENSION_VERSION": "~4",
    "APPLICATIONINSIGHTS_CONNECTION_STRING": "<applicationInsights_connec_string>"
  },
  "ConnectionStrings": {}
}

requirements.txt：