Visualization Techniques for Tracking Carbon Credit Trading Pathways and Identifying Potential Arbitrage Activities
A method for visual analysis of token transaction data on the blockchain to quickly identify suspicious transactions.
Please follow the steps below to install and configure this project :
STEP 1:
git clone https://github.com/peculab/TrackingCarbon.git
STEP 2: Setup virtual environment and install dependencies using pip install -r requirements.txt
STEP 3: Replace the credentials in the .env file with your own API_KEYS
🎞️Video demonstration: Visualization Techniques for Tracking Carbon Credit Trading Pathways
Here are instructions on how to use this project.
Obtaining Multi-layer Historical Transaction Data for a Wallet:
-
Copy the wallet address(es) you want to track and paste them into the INITIAL_ADDRESSES in the main function on line 84 of the file
data_collection.py.
-
Modify the
MAX_DEPTH
parameter in the .env file according to the maximum number of layers you want to track. -
Adjust the
TX_COUNT_THRESHOLD
in .env to set the number of transactions per layer you want to track ( Note: If no limit is set, the process may take several hours). -
Run the script:
py data_collection.py
- Obtain the CSV file.
Obtaining Single-layer Historical Transaction Data for a Wallet:
- Directly download the transaction data from Etherscan.
- Replace 'path/to/your/csvfile.csv' in the file_path variable with the path to your CSV file containing the transaction data. This can be found in the main function on line 7 of the file graph.py.
- Run the application:
python graph.py
- Open a web browser and navigate to the address in the command line (usually http://127.0.0.1:8050/) to view the dashboard.