Top 10 Ethereum NFTs with Dune Analytics API

You can find the complete guide on the Dune blog here.

This python script integrates with the Dune Analytics API to retrieve data about the top 10 NFT collections by volume within a specified date range. It prompts the user to input the start and end dates for the query, loads the DUNE API key from a .env file, and runs the query using the dune_client library. It then displays the results DataFrame and creates visualizations using Seaborn for better data representation.

You can find the sql query that this script runs in SQL QUERY/query_sql.sql file.

The flowchart below outlines the process of the Python script designed to retrieve and display Ethereum NFT data from Dune, starting from loading the API key to graphing the trading volumes.

Dependencies

To run the script src/script.py, you need to install the following dependencies:

Python Packages

• dune-client: A Python client library for interacting with the Dune Analytics API.

  • Installation: pip install dune-client

• dotenv: Loads environment variables from a .env file.

  • Installation: pip install python-dotenv

• seaborn: Python visualization library based on matplotlib.

  • Installation: pip install seaborn

• matplotlib: Python plotting library.

  • Installation: pip install matplotlib

• pandas: Data manipulation and analysis library.

  • Installation: pip install pandas

Additional Requirements

• Dune API Key: You need to obtain an API key from Dune Analytics and store it in Dune API Key/dune-api-key.env file.

Once you have installed the above dependencies and obtained your Dune API key, you can run the script successfully.

Components of the Script

Loading DUNE API Key

• The load_dune_api_key() function loads the DUNE API key from a .env file using the load_dotenv function from the dotenv library.

Creating DuneClient Instance

• The get_dune_client(api_key) function creates and returns a DuneClient instance using the provided API key.

Running DUNE Query

• The run_dune_query(client, query_id, start_date, end_date) function runs a DUNE query to retrieve data within the specified date range. It constructs the query using QueryBase and QueryParameter objects from the dune_client library.

User Input for Date Range

• The get_user_input() function prompts the user to input the start and end dates for the query. It validates the input format and ensures that the end date is after the start date.

Main Function

• The main() function serves as the entry point of the script. It orchestrates the execution of other functions, including loading the API key, creating the DuneClient instance, getting user input, running the query, displaying the results DataFrame, and creating visualizations.

Visualizations

• The script uses Seaborn to create two visualizations:
  1. A horizontal bar plot showing the top 10 NFT collections by USD volume.
  2. A horizontal bar plot showing the top 10 NFT collections by ETH volume.

Running the Script

• To run the script, execute it using a Python interpreter. Follow the prompts to input the start and end dates for the query.
• Ensure that the required libraries (dune_client, dotenv, seaborn, matplotlib) are installed in your Python environment.
• The result of the DUNE query is saved into a csv file in Results/results.csv.