---
# System prepended metadata

title: Inline Top Degen Trending Bot

---

# Inline Top Degen Trending Bot

The EVM Degen Trending Bot [EDTB] is a Telegram bot that provides real-time updates on the top trending tokens on the Ethereum network. The bot is designed for use in group chats and channels and can handle multiple groups or channels.

To use the bot, an admin must first add the bot to the group or channel. Once the bot is added, the admin can click on the /start command to initiate the bot. The bot will then automatically post a message in the group with the details of the top trending tokens on the Ethereum network. The message will be updated in real-time based on the latest data in the bot's database.

We have a dedicated bot for each EVM network that is designed to only display information on tokens that satisfy the predefined criteria for that particular network. Therefore, the bot will exclusively provide information on tokens that meet the specified requirements for the specific network it is assigned to.


 The message will contain the following details for each token:

- Token Name (with a direct link to Dexscreener)
- Liquidity
- Volume
- ROI
- FDV (Marketcap)

The user can pin the message if they want to. The message will also include a link to Dexscreener for each token, allowing users to access more detailed information on the token.

Sample Message


| #   | Token             | Liquidity | Volume     | ROI    | FDV      |
| --- | ----------------- | --------- | ----------| ------ | -------- |
| 1   | Dog Face  | 1,249     | $1.0M     | 6,754% | $14.3M   |
| 2   | DNAI              | 733       | $308K     | 3,891% | $10.4M   |
| 3   | Momo Face         | 663       | $145K     | 355%   | $3.3M    |
| 4   | Tetsuya Inu       | 614       | $120K     | 626%   | $2.2M    |
| 5   | BAIB              | 576       | $136K     | 1,684% | $8.0M    |
| 6   | Amogus       | 568       | $374K     | 1,440% | $10.4M   |
| 7   | KEK AI     | 420       | $151K     | 660%   | $37.4M   |
| 8   | The Final Chapter         | 411       | $289K     | 30.34% | $4.4M    |
| 9   | CleverBot | 377       | $111K     | 282%   | $8.1M    |
| 10  | Decentracat  | 292 | $108K     | 25.13% | $4.7M    |
| 11  | BILL              | 270       | $177K     | 1,033% | $2.2M    |




## Backend

### Tools Required

- **Python:** This is the primary programming language used to build the bot and backend functionality.
- **Dexscreener API:** This is the API used to pull data on Ethereum pairs that meet the filter criteria specified.
- **Requests Library:** This Python library is used to make HTTP requests to the Dexscreener API and retrieve the JSON data.
- **Database Management System:** A database management system (DBMS) is needed to store the data retrieved from the Dexscreener API. This can be a relational database management system (such as MySQL, PostgreSQL, or Oracle) or a NoSQL database (such as MongoDB or Cassandra).
- **Python Database Libraries:** A Python library that allows the script to connect and manipulate the database. This includes libraries such as SQLAlchemy, PyMySQL, or pymongo.
- **Telegram Bot API:** This API is used to send messages to the Telegram group or channel.
- **Python Telegram Bot Library:** This is a Python wrapper for the Telegram Bot API that simplifies the process of sending messages to Telegram.
- **Cron Job Scheduler:** A cron job scheduler is used to run the Python script periodically to retrieve the latest data from the Dexscreener API and update the Telegram message.





### Workflow

1. **Python script pulls data from Dexscreener API:**

    - The script uses the Python requests library to make a GET request to the Dexscreener API endpoint.
    - The request includes query parameters that filter the results by Ethereum pairs with the specified criteria (24-hour volume, number of transactions, FDV, etc.).
    - The response from the API is in JSON format, containing data for each Ethereum pair that meets the filter criteria.

2. **Python script extracts relevant data from API response:**

    - The script parses the JSON response from the API and extracts the relevant data for each pair, such as the pair's name, liquidity, volume, ROI, and market cap.
    - The extracted data is organized into a Python dictionary or other data structure that can be easily stored in a database.

3. **Python script stores data in a database:**

    - The script uses a Python database library (such as SQLAlchemy or PyMySQL) to connect to a database server.
    - The extracted data is then inserted into a table in the database, with each row representing one Ethereum pair that meets the filter criteria.

4. **Python script sends message to Telegram group or channel:**

    - The script uses the Python Telegram Bot API library to send a message to the specified Telegram group or channel.
    - The message includes the latest data for the top trending tokens based on the filter criteria, as well as links to Dexscreener for each pair.

5. **Cron job periodically triggers the Python script:**

    - The Python script is run periodically (using a cron job) to ensure that the latest data is always available in the database and the Telegram message is always up to date.
    - The interval for the cron job can be adjusted depending on how often you want the data to be updated and how frequently the Dexscreener API data is refreshed.



## This is an example of someone who has an inline bot that features a single message which updates itself automatically.



![](https://i.imgur.com/uyn5bSl.png)
https://t.me/callbombeth




