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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. 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 - 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.
    • 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!