Punks Analysis

Distribution of CryptoPunks over time (blue: oldest -> orange: newest)

Summary

This repository contains Python code written to investigate the distribution of CryptoPunks over time. It uses web3py to interact with an Ethereum node via Infura and collects all claim, transfer and sale logs broadcasted from the CryptoPunks smart contract, which is then parsed and cleaned.

The data is used to determine how the Punks NFTs are distributed across addresses. I graph Lorenz Curves and calculate Gini Coefficients to quantify the degree of inequality.

For a more comprehensive discussion of CryptoPunks, my results and some limitations of the investigation, I did a write-up on my website.

Usage

The repository already includes a set of logs (under the data directory prefixed with event_) which may be used to analyze other aspects of the CryptoPunks market. The graphs are in the figures directory.

What follows is instructions to gather, clean and graph the data from scratch.

Firstly, clone the project and install the requirements.

emilio@MPB:~$ git clone https://github.com/emilioziniades/punks-analysis
emilio@MPB:~$ cd punks-analysis
emilio@MPB:~$ pip install -r requirements.txt

Next, you will also need to get an auth key from Infura. Head over to their website, create an account if you do not have one, go to your dashboard, create a new project and go to the project settings. We want the 'Project ID'. punks-analysis reads this Project ID from the WEB3_INFURA_PROJECT_ID environment variable. Either manually create a new environment variable via the command line

emilio@MBP:~$ export WEB3_INFURA_PROJECT_ID=abcdef123456...

or create a file named .env in the code directory and include this line

/code/.env:

WEB3_INFURA_PROJECT_ID=abcdef124567

Now that you have the relevant auth key, you should also delete the data and figures directories.

emilio@MBP:~/punks-analysis$ rm -rf data && rm -rf figures

Now you, you can run main.py and the data will be fetched, cleaned, parsed and graphed.

NOTE: This project requires Python version 3.9.10.

emilio@MBP:~/punks-analysis$ python3 ./code/main.py

You should see progress messages in the terminal output. This process may take anywhere from 10 minutes to 30 minutes. Results are stored in the data and figures directories.

Contributing

If you identify any bugs, please feel free to open an issue or submit a pull request if you are willing to fix it.

Since this is a research project, I am not really looking to implement any new features. Having said that, it would be pretty trivial to adapt this project to fetch logs from any smart contract. If you're interested in doing this, let me know and I would gladly assist.