Slack Consolidate: a slackbot built with Python and Supabase

2022-08-09

15 minute read

Supabase is a platform-as-a-service built on top of PostgreSQL and many other amazing open-source tools. It’s a fantastic option to create data-intensive apps and tooling. Taking advantage of the community-made Python SDK and Slack's Python SDK, you can automate tasks and build apps for several use cases.

Prerequisites

Before we dive in, let’s look at some prerequisites you'll need:

  • Supabase Client
    • The SDK only supports Python > 3.7. You can download a supported Python version from here. pip install supabase
  • Python dotenv to handle API keys without exposing them in the code
    • This is optional, but it will avoid issues of package dependencies and version conflicts. pip install python-dotenv
  • Slack SDK for Python
    • This is needed to create the Slack bot pip install slack-sdk

Creating the App in Slack

Now, it is time to create the bot in Slack and get the API Keys (after granting the required scopes)

https://api.slack.com/apps

Green arrow pointing to the ‘Create New App’ button.

Then, select to create an app from a manifest (this will already set the required permissions) for the app:

Green arrow pointing to the option ‘From an app manifest’ inside the “Create an app” menu.

Select the Slack workspace to deploy:

The picture shows a dropdown UI with Supabase selected as the workspace.

Manifest.yaml


_30
display_information:
_30
name: SlackConsolidate
_30
features:
_30
bot_user:
_30
display_name: SlackConsolidate
_30
always_online: false
_30
oauth_config:
_30
scopes:
_30
user:
_30
- channels:history
_30
- channels:read
_30
- channels:write
_30
- chat:write
_30
- links:read
_30
- users:read
_30
- groups:history
_30
- groups:read
_30
- mpim:history
_30
- im:history
_30
bot:
_30
- channels:history
_30
- channels:read
_30
- links:read
_30
- chat:write.public
_30
- chat:write
_30
- channels:join
_30
settings:
_30
org_deploy_enabled: false
_30
socket_mode_enabled: false
_30
token_rotation_enabled: false

Enter the manifest above when asked:

The picture shows the place where you have to paste the manifest file included in the repo.

Then, confirm to create the bot:

You can see a summary screen to confirm the creation of the bot and the scopes assigned.

Granting access to the bot:

Install the app on the workspace:

The picture shows the button to Install the App to the Slack Workspace.

Inviting the bot to the channels, it will post messages on:

The command to invite the bot is below:

/invite @SlackConsolidate

The picture shows the command /invite @Slackbot in the channel #team-support.

Now, we are done with Slack for now. Let's create some buffer tables in Supabase.

Creating Tables in Supabase

Create an account here (if you don't have one yet).

We will be using Supabase's database and the Python client Libraries. First, we will create one table to store the channels that are being watched and where they are going to send the message which works analogously to a multiplexer circuit. Since you may want to watch several channels but split them into a smaller buffer e.g VIP / Enterprise, etc.

Go to the SQL Editor and run this:


_18
CREATE TABLE slack_channels (
_18
id SERIAL PRIMARY KEY,
_18
channel text,
_18
channel_id text,
_18
p_level text DEFAULT ''::text NOT NULL,
_18
dest_channel text,
_18
dest_channel_id text,
_18
private int DEFAULT '0'::int NOT NULL
_18
);
_18
_18
CREATE TABLE slack_watcher (
_18
channel_name text,
_18
channel_id text NOT NULL,
_18
message text,
_18
ts timestamp with time zone NOT NULL,
_18
ts_ms text NOT NULL,
_18
CONSTRAINT pk_slackwatcher PRIMARY KEY (channel_id, ts, ts_ms)
_18
);

Adding channels to the watch list and setting the destination channel:

You may want to call conversations.list to dump all the channels and channel IDs into a CSV file, then use it to populate the table slack_channels. You can also manually get the data, but copying the links to messages in the channels:

After right-clicking a message in Slack, you can see the option to select the link.

Slack links have the following format:

https://ORGANIZATION.slack.com/archives/ channel_id/pmessage_id


Organization: subdomain used in Slack

Channel ID: It is the string that you'll need to enter in slack channels as the channel id e.g C0000ABC02DE

The name of the channel is not needed. But it is recommended to set, it so you can filter and find this information later on if needed. You can ignore everything else when setting the table for slack_channels

Examples of adding data to the channel's list:

Method 1:

Using Supabase UI (easier):

The green arrow points to insert row button inside Supabase.

Then, enter the information as needed:

The picture shows the UI in Supabase to insert a new row to the database table.

Method 2:

Go to SQL Editor and run insert commands:

Inserting a public channel named #support-channel to be monitored:


_10
insert into slack_channels
_10
(channel, channel_id, p_level, dest_channel, dest_channel_id, private)
_10
values
_10
('support-channel', 'C0000ABC02DE', 'Support msgs', 'all_them_messages', 'C0000ABC02DF', 0);

Inserting a private channel named #support-enterprise to be monitored:


_11
insert into slack_channels
_11
(channel, channel_id, p_level, dest_channel, dest_channel_id, private)
_11
values
_11
(
_11
'support-enterprise',
_11
'C0000ABC02DC',
_11
'Enterprise Support msgs',
_11
'all_them_messages',
_11
'C0000ABC02DF',
_11
1
_11
);

Notes:

p_level is an optional message that will be included in with the message e.g VIP customer.

private is an integer field that should be set to 1 if the channel has a 🔒padlock before the name (not a public channel).

channel_id is the source channel ID and dest_channel_id is the ID of the channel where the bot will post the message.

Setting up the environment File:

You need to get the supabase URL and API keys from here:

https://supabase.com/dashboard/project/_/settings/api

The picture illustrates where to get the URL and the service key to setup the environment variables.

Slack environment variables:

Then, copy the bot and person API Tokens for the bot:

The picture has arrows pointing to the tokens that will be used as environment variables from Slack.

Now, you have everything needed to set up the environment file. Please note that Slack ORG is the subdomain of your slack organization i.e supabase for supabase.slack.com

The environment file:


_10
SUPABASE_URL=https://XXXX.supabase.co
_10
SUPABASE_KEY=eyJhbGc_SUP4N4CH0_IkpXVCJ9.SUPAKEY_*
_10
SLACK_TOKEN=xoxp-Slack_PERSON_TOKEN
_10
SLACK_BOT_TOKEN=xoxb-Slack_BOT_TOKEN
_10
SLACK_ORG=slack_sub_domain

Now, we can run the bot:

It works in a similar fashion to Arduino / PIC processors of an infinity loop looking for new data and performing tasks.


_155
import time
_155
import logging
_155
from slack_sdk import WebClient
_155
from slack_sdk.errors import SlackApiError
_155
from supabase import create_client, Client
_155
from datetime import datetime
_155
from dotenv import dotenv_values
_155
logger = logging.getLogger(__name__)
_155
config = dotenv_values(".env")
_155
bot_client = WebClient(token=config['SLACK_BOT_TOKEN'])
_155
client = WebClient(token=config['SLACK_TOKEN'])
_155
SUPABASE_URL=config['SUPABASE_URL']
_155
SUPABASE_KEY=config['SUPABASE_KEY']
_155
supabase: Client = create_client(SUPABASE_URL, SUPABASE_KEY)
_155
SLACK_ORG = config['SLACK_ORG']
_155
SLACK_ORG_LINK = f"https://{SLACK_ORG}.slack.com/archives/"
_155
############
_155
# Config:
_155
############
_155
# 1.4 seconds should be the minimum to avoid passing Slack API limits.
_155
# https://api.slack.com/docs/rate-limits#tier_t3
_155
POOLING_DELAY = 1.4
_155
# Check if new channels were added each hour.
_155
SCAN_CHANNELS_DELAY = 3600.0
_155
BUFFER_SIZE = 20
_155
_155
class SlackChannel:
_155
def __init__(self, id, name, p_level, dest_channel_id, dest_channel, private):
_155
"""_summary_
_155
_155
Args:
_155
id (str): Slack channel ID from the source channel
_155
name (str): Name of the source channel (used in logging)
_155
p_level (str): (Optional message) added when posting
_155
dest_channel_id (str): Slack channel ID for the destination channel
_155
dest_channel (str): Name of the destination channel (used in logging)
_155
private (int): Integer to check if the channel is private (private==1) or public channel
_155
Returns:
_155
SlackChannel: object
_155
"""
_155
self.id = id
_155
self.name = name
_155
self.p_level = p_level
_155
self.dest_channel = dest_channel
_155
self.dest_channel_id = dest_channel_id
_155
self.private = private
_155
_155
def setup():
_155
"""_summary_
_155
Fetches the list of channels from Supabase and returns them in a dict()
_155
Returns:
_155
dict: Dictionary with SlackChannel objects.
_155
"""
_155
channels = dict()
_155
data = supabase.from_("slack_channels").select("channel_id, channel, p_level, dest_channel, dest_channel_id, private").execute().data
_155
data_dic = data
_155
for row in data_dic:
_155
channels[row['channel_id']] = SlackChannel(id = row['channel_id'],
_155
name = row['channel'],
_155
p_level = row['p_level'],
_155
dest_channel = row['dest_channel'],
_155
dest_channel_id = row['dest_channel_id'],
_155
private = row['private'])
_155
return channels
_155
_155
def post(src_channel, link, message):
_155
"""_summary_
_155
Post a message from a source channel into the destination channel
_155
Args:
_155
src_channel (SlackChannel): SlackChannel object
_155
link (_type_): The link of the message in slack
_155
message (_type_): _description_
_155
_155
Returns:
_155
_type_: _description_
_155
"""
_155
try:
_155
aux_text = ""
_155
if src_channel.private != 1:
_155
aux_text = ("Message on <#"+src_channel.id+
_155
">. "+src_channel.p_level+" \n"+link)
_155
else:
_155
aux_text = ("Message on <#"+src_channel.id+
_155
">."+src_channel.p_level+" \n"+message+" \n"+link)
_155
result = bot_client.chat_postMessage(
_155
channel= src_channel.dest_channel_id,
_155
text=aux_text
_155
)
_155
logger.info(result)
_155
except SlackApiError as e:
_155
logger.error(f"Error posting message: {e}")
_155
_155
def ts_to_strtime(ts):
_155
"""_summary_
_155
Converts the UNIX time in timestamp to ISO format.
_155
Args:
_155
ts (int): TS datetime
_155
_155
Returns:
_155
str: ISO format datetime string for compatibility with Postgres.
_155
"""
_155
aux_ts = int(ts)
_155
return str(datetime.utcfromtimestamp(aux_ts).isoformat())
_155
_155
def loop_through_channels(channels):
_155
"""_summary_
_155
Loop through the channels and post messages on postgres if they aren't cached.
_155
Args:
_155
channels (dict): dict() with SlackChannel objects
_155
"""
_155
for channel_id in channels:
_155
channel = channels[channel_id]
_155
conversation_history = []
_155
try:
_155
result = client.conversations_history(channel=channel.id, limit = BUFFER_SIZE)
_155
conversation_history = result["messages"]
_155
logger.info("{} messages found in {}".format(len(conversation_history), id))
_155
except SlackApiError as e:
_155
logger.error("Error creating conversation: {}".format(e))
_155
for message in conversation_history:
_155
try:
_155
msg_dic = dict()
_155
msg_dic['channel_name'] = channel.name
_155
msg_dic['channel_id'] = channel.id
_155
aux_msg = "<@"+message['user']+"> wrote: \n"
_155
msg_dic['message'] = aux_msg + message['text']
_155
ts_aux = message['ts'].split(".")
_155
msg_dic['ts'] = ts_to_strtime(ts_aux[0])
_155
msg_dic['ts_ms'] = ts_aux[1]
_155
supabase.table("slack_watcher").insert(msg_dic).execute()
_155
auxint = ts_aux[0]+ts_aux[1]
_155
auxint = auxint.replace(".","")
_155
link = SLACK_ORG_LINK+channel.id+"/p"+auxint
_155
post(channel, link, msg_dic['message'])
_155
except Exception as e:
_155
pass
_155
time.sleep(POOLING_DELAY)
_155
_155
def main():
_155
"""_summary_
_155
Main loop to infinitely keep pooling data from channels and posting on Slack.
_155
It also checks for new channels every hour.
_155
"""
_155
channels = setup()
_155
start = time.time()
_155
while True:
_155
end = time.time()
_155
if ((end - start) > SCAN_CHANNELS_DELAY):
_155
start = time.time()
_155
channels = setup()
_155
else:
_155
loop_through_channels(channels)
_155
_155
if __name__ == '__main__':
_155
main()

Of course, we aren't doing a proper Python example if we don't make a test notebook available:

Open in Colab

Conclusion

Using Supabase and Slack SDK, it is very easy to create a bot that consolidates data according to the rules set. It just takes some steps to get started with the Python SDK and you can even run a demo directly in Google Colab.

If you have any questions please reach out via Twitter or join our Discord.

More Python and Supabase resources

Share this article

Build in a weekend, scale to millions