UniswapPy 1.2.0

Uniswap Analytics with Python

UniswapPy: Uniswap Analytics with Python

This package is a python re-factor of the original Uniswap V2 pairing code and can be utilized for the purpose of analysing and modelling its behavior for DeFi

Docs

Visit docs for full documentation with walk-through tutorials

Installation

> git clone https://github.com/defipy-devs/uniswappy
> pip install .

or

> pip install UniswapPy

Basic Usage

• See test notebook for basic usage

from uniswappy.erc import ERC20
from uniswappy.cpt.factory import UniswapFactory
from uniswappy.utils.data import UniswapExchangeData

user_nm = 'user_intro'
eth_amount = 1000
dai_amount = 1000000

dai = ERC20("DAI", "0x111")
eth = ERC20("ETH", "0x09")
exchg_data = UniswapExchangeData(tkn0 = eth, tkn1 = dai, symbol="LP", 
address="0x011")

factory = UniswapFactory("ETH pool factory", "0x2")
lp = factory.deploy(exchg_data)
lp.add_liquidity("user0", eth_amount, dai_amount, eth_amount, dai_amount)
lp.summary()

OUTPUT:

Exchange ETH-DAI (LP)
Reserves: ETH = 1000, DAI = 1000000
Liquidity: 31622.776601683792

from uniswappy.process.swap import Swap

out = Swap().apply(lp, dai, user_nm, 1000)
lp.summary()

OUTPUT:

Exchange ETH-DAI (LP)
Reserves: ETH = 999.00399301896, DAI = 1001000
Liquidity: 31622.776601683792

0x Quant Terminal

This application utilizes the 0x API to produce a mock Uniswap pool which allows end-users to stress test the limitations of a Uniswap pool setup using live price feeds from 0x API; for backend setup, see notebook

Click dashboard.defipy.org for live link; for more detail see README

Run application locally

> bokeh serve --show python/application/quant_terminal/bokeh_server.py

Special Features

• Abstracted Actions: Obfuscation is removed from standard Uniswap action events to help streamline analysis and lower line count; see article How to Handle Uniswap Withdrawals like an OG, and Setup your Uniswap Deposits like a Baller
• Indexing: Can calculate settlment LP token amounts given token amounts and vice versa; see article The Uniswap Indexing Problem
• Simulation: Can simulate trading using Geometric Brownian Motion (GBM) process, or feed in actual raw price data to analyze behavior; see article How to Simulate a Liquidity Pool for Decentralized Finance
• Randomized Events: Token amount and time delta models to simulate possible trading behavior
• Analytical Tools: Basic yeild calculators and risk tools to assist in analyzing outcomes