How to avoid slack command timeout error?

问题:

I am working with slack command (python code is running behind this), it works fine, but this gives error

This slash command experienced a problem: 'Timeout was reached' (error detail provided only to team owning command).

How to avoid this ?

回答1:

According to the Slack slash command documentation, you need to respond within 3000ms (three seconds). If your command takes longer then you get the Timeout was reached error. Your code obviously won't stop running, but the user won't get any response to their command.

Three seconds is fine for a quick thing where your command has instant access to data, but might not be long enough if you're calling out to external APIs or doing something complicated. If you do need to take longer, then see the Delayed responses and multiple responses section of the documentation:

1. Validate the request is okay.
2. Return a 200 response immediately, maybe something along the lines of {'text': 'ok, got that'}
3. Go and perform the actual action you want to do.
4. In the original request, you get passed a unique response_url parameter. Make a POST request to that URL with your follow-up message:
   • Content-type needs to be application/json
   • With the body as a JSON-encoded message: {'text': 'all done :)'}
   • you can return ephemeral or in-channel responses, and add attachments the same as the immediate approach

According to the docs, "you can respond to a user commands up to 5 times within 30 minutes of the user's invocation".

回答2:

I too was facing this error frequently:

"Darn – that slash command didn't work (error message: Timeout was reached). Manage the command at slash-command"

I was writing a Slack slash-command "bot" on AWS Lambda that sometimes needed to perform slow operations (invoking other external APIs etc). The Lambda function would take greater than 3 seconds in some cases causing the Timeout was reached error from Slack.

I found @rcoup's excellent answer here and applied it in the context of AWS Lambda. The error doesn't appear any more.

I did this with two separate Lambda functions. One is a "dispatcher" or "receptionist" that greets the incoming Slack slash command with a "200 OK" and returns the simple "Ok, got that" type of message to the user. The other is the actual "worker" Lambda function that starts the long-ish operation asynchronously and posts the result of that operation to the Slack response_url later.

This is the dispatcher/receptionist Lambda function:

def lambda_handler(event, context):
    req_body = event['body']

    try:
        retval = {}

        # the param_map contains the 'response_url' that the worker will need to post back to later
        param_map = _formparams_to_dict(req_body)
        # command_list is a sequence of strings in the slash command such as "slashcommand weather pune"
        command_list = param_map['text'].split('+')

        # publish SNS message to delegate the actual work to worker lambda function
        message = {
            "param_map": param_map,
            "command_list": command_list
        }

        sns_response = sns_client.publish(
            TopicArn=MY_SNS_TOPIC_ARN,
            Message=json.dumps({'default': json.dumps(message)}),
            MessageStructure='json'
        )

        retval['text'] = "Ok, working on your slash command ..."
    except Exception as e:
        retval['text'] = '[ERROR] {}'.format(str(e))

    return retval


def _formparams_to_dict(req_body):
    """ Converts the incoming form_params from Slack into a dictionary. """
    retval = {}
    for val in req_body.split('&'):
        k, v = val.split('=')
        retval[k] = v
    return retval

As you can see from the above, I didn't invoke the worker Lambda Function directly from the dispatcher (though this is possible). I chose to use AWS SNS to publish a message that the worker receives and processes.

Based on this StackOverflow answer, this is the better approach as it's non-blocking (asynchronous) and scalable. Also it was easier to use SNS to decouple the two functions in the context of AWS Lambda, direct invocation is trickier for this use-case.

Finally, here's how I consume the SNS event in my worker Lambda Function:

def lambda_handler(event, context):
    message = json.loads(event['Records'][0]['Sns']['Message'])
    param_map = message['param_map']
    response_url = param_map['response_url']

    command_list = message['command_list']
    main_command = command_list[0].lower()

    # process the command as you need to and finally post results to `response_url`

回答3:

After dealing with this issue myself and having my Flask app hosted on Heroku I found that the simplest solution was to use threading. I followed the example from here: https://blog.miguelgrinberg.com/post/the-flask-mega-tutorial-part-xi-email-support

from threading import Thread

def backgroundworker(somedata,response_url):

    # your task

    payload = {"text":"your task is complete",
                "username": "bot"}

    requests.post(response_url,data=json.dumps(payload))    

@app.route('/appmethodaddress',methods=['POST','GET'])
def receptionist():

    response_url = request.form.get("response_url")

    somedata = {}

    thr = Thread(target=backgroundworker, args=[somedata,response_url])
    thr.start()

    return jsonify(message= "working on your request")  

All the slow heavy work is performed by the backgroundworker() function. My slack command points to https://myappaddress.com/appmethodaddress where the receptionist() function takes the response_url of the received Slack message and passes it alongside any other optional data to the backgroundworker(). As the process is now split it simply returns the "working on your request" message to your Slack channel pretty much instantly and upon completion backgroundworker() sends the second message "your task is complete".

回答4:

Create thread to do major part of work and return response to slack. You can also return a response when thread will complete.