UniswapPy: Uniswap V2 / V3 Analytics with Python

This package contains python re-factors of both original Uniswap V2 and V3 pairing codes, and can be utilized for the purpose of analysing and modelling its behavior for DeFi.

🔗 SPDX-Anchor: anchorregistry.ai/AR-2026-M86pm5A

📘 Official Textbook

Looking for a structured, graduate-level walkthrough of DeFiPy and DeFi analytics?

DeFiPy: Python SDK for On-Chain Analytics is the official companion textbook for this project.
It covers:

• AMM math and invariants (Uniswap V2 & V3, Balancer, Stableswap)
• On-chain analytics and pool/event decoding
• Python workflows for DeFi modeling and simulation
• Agent-based architectures and risk pipelines built on DeFiPy

👉 Buy on Amazon: https://www.amazon.com/dp/B0G3RV5QRB

📝 Docs

Visit DeFiPy docs for full documentation

🔍 Install

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

or

> pip install UniswapPy

Uniswap V2

• See test notebook for basic usage and tutorial on Uniswap V2 math

from uniswappy import *

user_nm = 'user'
eth_amount = 1000
tkn_amount = 100000

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

factory = UniswapFactory("ETH pool factory", "0x2")
lp = factory.deploy(exchg_data)

Join().apply(lp, user_nm, eth_amount, tkn_amount)
lp.summary()

OUTPUT:

Exchange ETH-TKN (LP)
Reserves: ETH = 1000, TKN = 100000
Liquidity: 10000.0

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

OUTPUT:

Exchange ETH-TKN (LP)
Reserves: 990.1284196560293, TKN = 101000
Liquidity: 10000.0

Uniswap V3

• See test notebook for basic usage and tutorial on Uniswap V3 math

from uniswappy import *

user_nm = 'user'
eth_amount = 1000
tkn_amount = 100000

eth = ERC20("ETH", "0x09")
tkn = ERC20("TKN", "0x111")

exchg_data = UniswapExchangeData(tkn0 = eth, tkn1 = tkn, symbol="LP", 
                                   address="0x011", version = 'V3', 
                                   tick_spacing = tick_spacing, 
                                   fee = fee)

factory = UniswapFactory("ETH pool factory", "0x2")
lp = factory.deploy(exchg_data)

out_v3 = Join().apply(lp, user_nm, eth_amount, tkn_amount, lwr_tick, upr_tick)
lp.summary()

OUTPUT:

Exchange ETH-TKN (LP)
Reserves: ETH = 1000, TKN = 100000
Liquidity: 10000.0

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

OUTPUT:

Exchange ETH-TKN (LP)
Real Reserves: ETH = 990.1284196560293, TKN = 101000
Liquidity: 10000.0

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; see article How to Simulate a Uniswap V3 Order Book in Python

If you find this package helpful, please leave a ⭐!

Testing

Run the full test suite from the repo root:

> python -m pytest python/test/ -v

Tests cover V2 and V3 functionality including:

• Process: join, swap, deposit, withdraw, add/remove liquidity
• CPT index: rebase index token, settlement LP token, round-trip identity
• Quotes: LP token pricing and reserve queries
• Analytics: impermanent loss calculations
• V3: mint, swap, LP quote, settlement, and rebase with tick ranges

Requirements

> pip install pytest

License

Licensed under the Apache License, Version 2.0.
See LICENSE and NOTICE for details.
Portions of this project may include code from third-party projects under compatible open-source licenses.