Telegram Bot

This project is a Telegram bot developed using Golang and PostgreSQL. The bot saves all messages sent in a chat and stores messages that contain a specific filter word in a separate table.

Setup and Usage

Starting the Services

1. Add your telegram bot token:

   • Go to docker-compose.yml and on 52nd line you will see the following: "TELEGRAM_BOT_TOKEN=TELEGRAM_TOKEN"
   • Replace "TELEGRAM_TOKEN" with your token.

2. Start all services:

   docker-compose up

   This command will pull the necessary images from Docker Hub and start all services.

   The database is at port 5435.

3. Send commands to the bot:

   • The bot has the following username: @message_filtering2_bot (https://t.me/message_filtering2_bot)
   • /start: The bot will respond with a welcome message.
   • /filter + word: The bot will save the word and filter messages by it.
   • Any other message will be saved to one of the tables, depending on whether it contains the filter word or not.

Checking the Database

1. Connect to the db-psql container:

   docker exec -it telegram_bot-db-psql-1 psql -U postgres

   2. Check available databases and connect to the telegram_records database:

      \l
      \c telegram_records
      

   3. Select all unfiltered and filtered messages and exit psql shell:

      SELECT * FROM messages;
      SELECT * FROM filtered_messages;
      \q
      

Stopping All Services

docker-compose down

Development Decisions

1. Project Structure: The project is split into three main directories:

   • init Directory: Contains the main.go file which connects to a database and initialises MessageHandler and MessagesDB structures as well as the Telegram bot.
   • handlers Directory: Contains functions for processing incoming messages and commands.
   • storage Directory: Works with the database.

2. Handler and Storage Functions:

   • Handler functions are encapsulated within the MessageHandler structure. This allows shared variables such as messagesDB (for database operations) and filterWord (for filtering messages) to be easily accessed and managed.
   • Storage functions belong to the MessagesDB structure, to ensure that sql database can be accessed from the functions.

3. Docker Compose:

   • Docker compose is used and separate container is created to make migrations to the database