Slack Observer: A Slack Message Fetcher & Listener Example

This repository contains two example Python scripts that demonstrate how to interact with the Slack API to retrieve and process messages from channels.

You can use them as a base for analytics, automation, or message monitoring inside your Slack workspace.

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📜 Overview

Script	Description
fetch_slack_history.py	Fetches past (historical) messages from a specific Slack channel.
slack_socket_bot.py	Listens to new (real-time) messages posted in channels where the bot is a member.

These examples can be adapted for many use cases — such as building analytics dashboards, chat archivers, or automation tools.

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⚙️ Requirements

• Python 3.9+

• A Slack workspace where you can create and install an app

• The following libraries (already listed in requirements.txt):

  slack-sdk
  slack-bolt
  

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🚀 1. Set up your Slack App

You’ll need to create a Slack App and connect it to your workspace.

Step-by-step:

1. Go to https://api.slack.com/apps and click "Create New App".

2. Choose "From scratch", give it a name (e.g. MessageFetcherBot), and select your workspace.

3. In the sidebar, open "OAuth & Permissions" and add these Bot Token Scopes:

   channels:history
   channels:read
   chat:write
   app_mentions:read
   im:history
   im:read
   groups:history
   groups:read
   

4. Scroll down and click "Install App to Workspace". This will generate a Bot User OAuth Token (starts with xoxb-).

5. In the sidebar, go to "Socket Mode" and enable it. Then, create an App-Level Token (starts with xapp-) with the permission:

   connections:write
   

6. Copy both tokens — you’ll need them for your environment variables.

7. Finally, invite your bot to the channel you want to read messages from:

   /invite @your-bot-name
   

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🔑 2. Configure environment variables

Create a .env file or set the variables in your terminal:

export SLACK_BOT_TOKEN="xoxb-your-bot-token-here"
export SLACK_APP_TOKEN="xapp-your-app-token-here"

You can also load them from a .env file using tools like python-dotenv (optional).

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💻 3. Install dependencies

Install the required libraries from requirements.txt:

pip install -r requirements.txt

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🕓 4. Run the scripts

▶️ Fetch past messages (historical data)

Use the script fetch_slack_history.py to download messages from a specific channel:

python fetch_slack_history.py

This script retrieves messages that were already sent in the channel and prints them in the terminal. You can easily modify it to save them to a JSON or database for further analysis.

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⚡ Listen to new messages in real-time

Use slack_socket_bot.py to start a live listener that reacts to new incoming messages:

python slack_socket_bot.py

The script uses Slack Socket Mode, which keeps a live WebSocket connection open and triggers your function every time a new message arrives.

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🧩 5. Example output

------------------------------------------------------------
Channel:   C08FNQR0N3E
User:      U123456789
Message:   Hello world!
Timestamp: 1729347856.000200
------------------------------------------------------------

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🛠️ Customization ideas

Both scripts are starting points — you can easily adapt them to:

• Store messages in a database (e.g., SQLite, PostgreSQL)
• Perform sentiment analysis or keyword detection
• Build dashboards of Slack activity
• Automate responses or workflows
• Integrate Slack messages with other systems (CRM, analytics tools, etc.)

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⚠️ Notes

• Never commit your Slack tokens to a public repository. Always use environment variables.
• If your bot doesn’t receive messages, ensure it has been invited to the channel and the required scopes are set.
• Slack’s free plan limits message history — older messages may not be accessible.

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📚 References

• Slack API Documentation
• Slack Bolt for Python
• Slack Web API (slack_sdk)