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README.md

Webhooks in ArcGIS Enterprise + the ArcGIS API for python + Slack

The following sample can be used as a guide to create an end to end workflow that integrates ArcGIS Enterprise with Slack. The scripts and applications were written for the purpose of prototyping.

Scenario

As an administrator, I want to be notified any time an item is incorrectly shared to the public. If an item is shared publicly, I want to examine that item's properties to ensure that it meets our organization standards (complete tags, description, completeness score, thumbnail etc.). If it does not meet our standards, notify me in slack and allow me to respond and manage that item within slack.

Demo components:

Slack bot:

How to deploy

View our webinar (link coming soon), to see how we put this all together.

Step One: Install and configure ArcGIS Enterprise

Webhooks were introduced as part of ArcGIS Enterprise 10.7. You will need to have this installed, and have administrative access in order to continue with these steps.

Step Two: Clone this repository

All of the samples you will need are included in this repository. Make a local copy of this repository in your environment.

Step Three: Configure webhook receiver

You need to begin by configuring a webhook receiver that will write payloads to a local textfile. We used our Java receiver sample.

Once you have configured your webhook receiver, go ahead and create your webhook with your desired trigger events.

Step Four: Python Scripts

Python 3 will come installed with your ArcGIS Enterprise deployment.

  1. Use this to install the arcgis package
  2. There are also a number of packages that need to be installed which can be found in requirements.txt You can quickly install these packages using the python package manager pip: pip install -r requirements.txt
  3. file_listener.py Using the python library watchdog, we monitor the directory where the payloads are being written to. Any time this file is written to/updated, this script will call our main function. You can copy this script to your workspace.
  4. admin_assistant.py This is our main script, and it contains two functions:
slackBot()

The script will parse through the textfile containing the payloads, extract the events and relevant information, and determine what operation was performed. If an item was shared to everyone, the script will then call into portal to examine the item's properties. If the item's properties do not meet the requirements you have defined in the script, the slack API is used to send a message to the administrator. You can alter this script to automatically update the missing properties, and bypass this slack component.

To send a message via Slack, you will need to create a slack application. We followed this great tutorial to familiarize ourselves with the Slack Event API, and creating an application: https://github.com/slackapi/Slack-Python-Onboarding-Tutorial/blob/master/README.md#pythonboarding-bot

responseHandler()

The second function handles the response received in Slack (see the slack bot .gif above). Using the tags given in the response, the item is updated accordingly. This component requires creating a node.js application that is listening to the slack channel (see below). 5. config.py The parameters needed to run this script have been externalized in the config file. After you have cloned this repository, and moved these files into your workspace, you will need to update these variables with the appropriate values.

Step Five: Slack bot with node.js

  1. Install Node.js You will need to have node installed in order to open a web socket that can listen to responses in Slack. You can follow the steps documented here to install Node.js in your workspace.

  2. Install bot.kit This application uses Botkit to create the chat bot.

  3. Copy the slackBot.js file into your node workspace. This application opens a web socket to listen for messages directed at your slack bot. When a message is sent, the application will write the response to a text file so that it can be picked up and processed by the responseHandler() function.

  4. Deploy the application using node The slackBot.js should be running in the background to allow it to pick up messages sent to the bot in slack. These will be written to the response.txt that is in the same directory as the webhookPayload.txt file.

The bot was given the skill to respond with "Adding tags". You can further customize this application to add new skills. For more information, please see the following resources and tutorials for creating a chat bot with the bot.kit :