Shopping Bot

A Telegram bot for managing shopping lists with SQLite persistence.

Features

• Add items to shopping list
• Remove items by ID
• View current list
• Clear entire list
• Persistent storage using SQLite
• Multi-chat support with optional access control

Commands

• /help - Display available commands
• /add <item> - Add an item to the shopping list
• /remove <id> - Remove an item by its ID
• /show - Display the current shopping list
• /clear - Clear the entire shopping list

Ordinary messages also support concise input:

• a <item> - Add an item
• r <id> - Remove an item
• s - Show the list

Legacy /add and /remove responses include a hint for the equivalent concise form.

Deployment

Kubernetes

Pushes to main build the container in Forgejo Actions, publish it to registry.pjw.lol/pawel/shopping-bot, and deploy the immutable image digest using the manifests in deploy/. The cluster must provide the shopping-bot-secret application secret and registry-pull image pull secret in the default namespace.

Using Docker Compose

1. Clone the repository
2. Copy .env.example to .env and configure:

   cp .env.example .env
   

3. Edit .env and set your bot token:

   BOT_TOKEN=your_bot_token_from_botfather
   

4. (Optional) Set allowed chat IDs for access control:

   ALLOWED_CHAT_IDS=123456789,-987654321
   

5. Build and run:

   docker-compose up -d
   

Using Docker

Build the image:

docker build -t shopping-bot .

Run the container:

docker run -d \
  --name shopping-bot \
  -e BOT_TOKEN=your_bot_token \
  -e ALLOWED_CHAT_IDS=123456789,-987654321 \
  -v shopping-bot-data:/data \
  shopping-bot

Local Development

1. Install Rust
2. Set environment variables:

   export BOT_TOKEN=your_bot_token
   export ALLOWED_CHAT_IDS=123456789,-987654321  # Optional
   

3. Run the bot:

   cargo run
   

Environment Variables

• BOT_TOKEN (required): Your Telegram bot token from @BotFather
• ALLOWED_CHAT_IDS (optional): Comma-separated list of allowed chat IDs. Leave empty to allow all chats.
• RUST_LOG (optional): Log level (error, warn, info, debug, trace)

Data Storage

• In Docker: Data is stored in /data/shopping_list.db (persisted via volume)
• Local development: Data is stored in /tmp/shopping_list.db