Blockchain-Network-Analysis
所属分类：以太坊
开发工具：Jupyter Notebook
文件大小：4992KB
下载次数：0
上传日期：2022-12-14 00:39:06
上 传 者：
sh-1993
说明： 区块链网络分析：去中心化银行的比较研究
(Blockchain Network Analysis: A Comparative Study of Decentralized Banks)
文件列表:
Code (0, 2022-12-14)
Code\analysis.ipynb (399845, 2022-12-14)
Code\extract_feature.py (5409, 2022-12-14)
Code\logs (0, 2022-12-14)
Code\logs\LQTY.txt (809, 2022-12-14)
Code\query_tx.ipynb (16192, 2022-12-14)
Code\utils (0, 2022-12-14)
Code\utils\__pycache__ (0, 2022-12-14)
Code\utils\__pycache__\cp_test.cpython-38.pyc (1810, 2022-12-14)
Code\utils\__pycache__\network_fea.cpython-38.pyc (1871, 2022-12-14)
Code\utils\cp_test.py (2050, 2022-12-14)
Code\utils\network_fea.py (2750, 2022-12-14)
Data (0, 2022-12-14)
Data\processedData (0, 2022-12-14)
Data\processedData\AAVE_2022-07-13 (0, 2022-12-14)
Data\processedData\AAVE_2022-07-13\02_network_fea.csv (187610, 2022-12-14)
Data\processedData\AAVE_2022-07-13\03_core_address.csv (18373, 2022-12-14)
Data\processedData\COMP_2022-07-13 (0, 2022-12-14)
Data\processedData\COMP_2022-07-13\02_network_fea.csv (223363, 2022-12-14)
Data\processedData\COMP_2022-07-13\03_core_address.csv (48304, 2022-12-14)
Data\processedData\Dai_2022-07-13 (0, 2022-12-14)
Data\processedData\Dai_2022-07-13\02_network_fea.csv (284510, 2022-12-14)
Data\processedData\Dai_2022-07-13\03_core_address.csv (65461, 2022-12-14)
Data\processedData\LQTY_2022-07-13 (0, 2022-12-14)
Data\processedData\LQTY_2022-07-13\.ipynb_checkpoints (0, 2022-12-14)
Data\processedData\LQTY_2022-07-13\.ipynb_checkpoints\03_core_address-checkpoint.csv (5448, 2022-12-14)
Data\processedData\LQTY_2022-07-13\02_network_fea.csv (135522, 2022-12-14)
Data\processedData\LQTY_2022-07-13\03_core_address.csv (304758, 2022-12-14)
Data\processedData\LQTY_2022-07-13\04_correlation.csv (504, 2022-12-14)
Data\processedData\LUSD_2022-07-13 (0, 2022-12-14)
Data\processedData\LUSD_2022-07-13\02_network_fea.csv (127675, 2022-12-14)
Data\processedData\LUSD_2022-07-13\03_core_address.csv (3194, 2022-12-14)
Data\processedData\LUSD_2022-07-13\04_correlation.csv (496, 2022-12-14)
Figure (0, 2022-12-14)
Figure\.DS_Store (8196, 2022-12-14)
... ...
# Blockchain Network Analysis
## Project information
**The Portfolio for [Blockchain Network Analysis: A Comparative Study of Decentralized Banks](https://arxiv.org/abs/2212.05632)**
- Paper accepted by [SAI Computing Conference 2023](https://saiconference.com/Computing)
- by **[Yufan Zhang](https://yufanz.xyz/), Zichao Chen, Yutong Sun, Yulin Liu\*, and [Luyao Zhang](http://scholars.duke.edu/person/luyao.zhang)\***
The flow chart of the blockchain network analysis methodology
## Repository structure
This repository includes the supplementary resources, data, and code.
*The Structure is generated by the [ASCII Tree Generator](https://ascii-tree-generator.com/)
```
.
├── Code
│ ├── analysis.ipynb
│ ├── extract_feature.py
│ ├── query_tx.ipynb
│ └── utils
│ ├── cp_test.py
│ └── network_fea.py
├── Data
│ ├── processedData
│ │ ├── AAVE_2022-07-13
│ │ ├── COMP_2022-07-13
│ │ ├── Dai_2022-07-13
│ │ ├── LQTY_2022-07-13
│ │ └── LUSD_2022-07-13
│ └── queriedData
│ ├── AAVE_2022-07-13.csv
│ ├── COMP_2022-07-13.csv
│ ├── Dai_2022-07-13.csv
│ ├── LQTY_2022-07-13.csv
│ └── LUSD_2022-07-13.csv
├── Figure
│ ├── AAVE_2020-10-02-2022-07-12
│ ├── BoxPlots
│ ├── COMP_2020-03-06-2022-07-12
│ ├── Dai_2019-11-18-2022-07-12
│ ├── LQTY_2021-04-05-2022-07-12
│ └── LUSD_2021-04-05-2022-07-12
├── README.md
└── requirements.txt
```
### Data
| Token Name | Queried Data (need to download by yourself) | Processed Data |
|------------|---------------------------------------------|----------------------------------------|
| AAVE | ./Data/queriedData/AAVE_2022-07-13.csv | ./Data/processedData/AAVE_2022-07-13/* |
| COMP | ./Data/queriedData/COMP_2022-07-13.csv | ./Data/processedData/COMP_2022-07-13/* |
| Dai | ./Data/queriedData/Dai_2022-07-13.csv | ./Data/processedData/Dai_2022-07-13/* |
| LQTY | ./Data/queriedData/LQTY_2022-07-13.csv | ./Data/processedData/LQTY_2022-07-13/* |
| LUSD | ./Data/queriedData/LUSD_2022-07-13.csv | ./Data/processedData/LUSD_2022-07-13/* |
### Code
| Content | File |
|-------------------------------------------------|------------------------------|
| Query the transaction data in Kaggle kernel | ./Code/query_tx.ipynb |
| Extract the network features | ./Code/extract_feature.ipynb |
| Analysis the features and perform visualization | ./Code/analysis.py |
## How to use
**Contract address**
| Token | Protocol | Contract Address | Start Date |
|-------|---------------------------------------|--------------------------------------------|------------|
| LUSD | [Liquity](https://www.liquity.org/) | 0x5f***805A4E8be255a32880FDeC7F6728C6568bA0 | 2021-04-05 |
| LQTY | [Liquity](https://www.liquity.org/) | 0x6DEA81C8171D0bA574754EF6F8b412F2Ed88c54D | 2021-04-05 |
| AAVE | [Aave](https://aave.com/) | 0x7Fc66500c84A76Ad7e9c93437bFc5Ac33E2DDaE9 | 2020-10-02 |
| COMP | [Compound](https://compound.finance/) | 0xc00e94Cb662C3520282E6f5717214004A7f26888 | 2020-03-04 |
| Dai | [MakerDAO](https://makerdao.com/) | 0x6B175474E89094C44Da***b954EedeAC495271d0F | 2019-11-13 |
1. Create a [conda](https://docs.conda.io/en/latest/) environment with Python>=3.8
```bash
conda create --name bna python=3.8
conda activate bna
```
2. Install required packages
```bash
pip install -r requirements.txt
```
3. Query token transaction records via [Kaggle Integration of BigQuery](https://www.kaggle.com/datasets/bigquery/ethereum-blockchain)
- Since the data is too big to commit to the GitHub, query by yourself by running this Kaggle notebook: [https://www.kaggle.com/bruceyufanzhang/query-defi-token-transaction-records](https://www.kaggle.com/bruceyufanzhang/query-defi-token-transaction-records) (The same code can be found at [./Code/query_tx.ipynb](./Code/query_tx.ipynb))
- Download the queried CSV files and put them file under `./Data/queriedData`
- **Note**: You must use Kaggle to run the notebook. It won't work elsewhere.
4. Extract network features and the core-periphery test results
```bash
cd ./Code
nohup python extract_feature.py --token-name LQTY >> ./logs/LQTY.txt
nohup python extract_feature.py --token-name LUSD >> ./logs/LUSD.txt
nohup python extract_feature.py --token-name AAVE >> ./logs/AAVE.txt
nohup python extract_feature.py --token-name COMP >> ./logs/COMP.txt
nohup python extract_feature.py --token-name Dai >> ./logs/Dai.txt
```
- **Note**: If you are using ssh, you might need to use `nohup` to run the Python since it might takes **hours** for the [core-periphery test](https://github.com/skojaku/core-periphery-detection).
- The output data will be saved to `./Data/processedData/{token_name}_{data_collected_date}/`
5. Register a [infura project](https://infura.io/) for Ethereum API use, and remember the ENDPOINTS
- The infura ENDPOINTS will be used to detect whether an address is CA or EOA, through [Web3.py](https://web3py.readthedocs.io/en/stable/quickstart.html)
6. Run `analysis.ipynb` and get the visualization results
- The output figures will be saved to `./Figure/{token_name}_{start_date}_{end_date}`
## Acknowledgements
Code derived and reshaped from: [BNS](https://github.com/Blockchain-Network-Studies/BNS)
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