optimal-sizing (Python)

A chain-agnostic mathematical library for profit-maximizing AMM trade sizing across heterogeneous liquidity curves.

optimal-sizing computes exact profit-maximizing trade sizes for constant-product (Uniswap v2), StableSwap (Curve v1), concentrated liquidity (Uniswap v3), Balancer, Velodrome/Aerodrome, Discretized Liquidity Book (DLMM), Curve CryptoSwap v2, and DODO PMM pools with explicit mathematical guarantee tiers.

Installation

pip install optimal-sizing

Quickstart

from decimal import Decimal
from sizing_py import PyCpmm, PyVelodromeStable, portfolio_optimize

# 1. Single pool sizing
cpmm = PyCpmm(Decimal("1000000"), Decimal("1000000"), Decimal("0.997"))
res = cpmm.optimal_size(reference_price=Decimal("0.95"), fixed_cost=Decimal("10"))
print(f"Optimal delta: {res.optimal_delta}, Expected profit: {res.expected_profit} ({res.guarantee_tier})")

# 2. Multi-pool joint portfolio allocation under hard budget constraint
velo = PyVelodromeStable(Decimal("2000000"), Decimal("2000000"), Decimal("0.9995"))
portfolio = portfolio_optimize(
    total_capital_budget=Decimal("50000"),
    opportunities=[
        {"id": "uniswap_v2", "pool": cpmm, "reference_price": Decimal("0.95")},
        {"id": "aerodrome", "pool": velo, "reference_price": Decimal("0.95")},
    ],
)
print(f"Total capital used: {portfolio.total_capital_used}, Profit: {portfolio.total_expected_profit}")
for pos in portfolio.allocations:
    print(f" - {pos.id}: allocated {pos.allocated_size}, profit {pos.expected_profit}")

Supported Curve Families

License

Released under the MIT License. Copyright (c) 2026 Christley OLUBELA (Xtley001).