How to build a Crypto Price Change Signal Bot on Telegram

This bot fetches real-time trading data from Bitquery and sends alerts on significant token price changes. For pre-aggregated price data with OHLC, consider using our Crypto Price API. The bot is built using the python-telegram-bot library to handle interactions with Telegram users and aiohttp for making asynchronous API requests.

Github Repository Link is available here

Tutorial Video

Components

1. Libraries and Dependencies

   • re, asyncio, json, logging, aiohttp, os: For general utilities, asynchronous handling, JSON parsing, and logging.
   • Telegram Libraries (telegram, ApplicationBuilder, etc.): For Telegram bot interaction.
   • datetime: For time manipulation in API requests.

2. Configuration and Constants

   • BOT_TOKEN: The Telegram bot token from the BotFather. Get it from here
   • OAUTH_TOKEN: The authorization token for the Bitquery API. Check out the steps on how to get it here
   • logging.basicConfig: Configures logging to track bot operations and potential errors.

3. Helper Functions

   • split_text(text, max_length)

     • Purpose: Splits long messages into smaller chunks to avoid Telegram's message length limit (4096 characters).
     • Parameters:
       • text (str): Message to be split.
       • max_length (int): Character limit.
     • Returns: List of text parts.

   • send_long_message(update, context, long_message, max_message_length=4000)

     • Purpose: Sends long messages in parts to avoid Telegram’s message length limit.
     • Parameters:
       • update, context (Telegram update and context).
       • long_message (str): Message content.
       • max_message_length (default=4000).
     • Operation: Handles RetryAfter exceptions if Telegram’s flood control limit is reached, retrying after a delay.

4. Core Functions

   • send_query_and_process(update, context)

     • Purpose: Sends GraphQL query to Bitquery API, retrieves data, processes, and sends alerts.
     • Operation:
       • Creates a query with specified variables.
       • Sends a POST request to Bitquery.
       • Processes the response to calculate price changes over different timeframes (5 minutes and 1 hour).
       • Sorts and formats the data, then sends it to Telegram using send_long_message.

   • calculate_percentage_change(start_price, end_price)

     • Purpose: Calculates and formats the percentage change between two prices.
     • Parameters:
       • start_price, end_price (float): Starting and ending prices.
     • Returns: Formatted string showing percentage change with symbols (📈 or 📉).

   • format_message(data)

     • Purpose: Formats the retrieved data for user-friendly display in Telegram.
     • Parameters:
       • data (dict): JSON data from Bitquery API.
     • Operation:
       • Iterates over the trading data items.
       • Formats each data point with trade and volume information, using fallback values if data is missing.
       • Adds a "Trade Now" link for easy access to trading.

5. Global Flag

   • is_task_running: A global flag to prevent multiple instances of send_query_and_process from running concurrently, which could lead to excessive API calls or repeated messages.

6. Command Handlers

   • start_regular_requests(update, context)

     • Purpose: Starts a recurring task to fetch data every 30 minutes.
     • Operation:
       • Checks if a task is already running (using is_task_running).
       • Sets up a loop to call send_query_and_process every 30 minutes.

   • start(update, context)

     • Purpose: Command handler for /start. Triggers start_regular_requests to begin data polling.
     • Usage: Users send /start to the bot to start receiving regular updates.

7. Main Execution Block

   • Purpose: Initializes the Telegram bot using ApplicationBuilder and starts polling for incoming /start commands.

How to Run

1. Clone the Repository

   git clone https://github.com/bitquery/Price-Change-Signal-Telegram-Bot.git

2. Set up virtual environment

   python3 -m venv venv
   source venv/bin/activate  # For Windows: venv\Scripts\activate

3. Install Dependencies

   pip install -r requirements.txt

4. Run the bot

   python bot.py

That's it for this tutorial. Happy coding, happy trading!