TwoCrypto C++ Modular

High-performance C++ implementation of Curve's TwoCrypto AMM pool for simulation and parameter grid search.

Two Main Use Cases

1. C++ Pool Parity Validation

Verify C++ pool math matches Vyper reference. Generate test data, run C++ variants (double/float), compare against Vyper.

# Check math parity
uv run python/benchmark_math/main.py

# Generate benchmark data
uv run python/benchmark_pool/generate_data.py --pools 3 --trades 20 --seed 42

# Run C++ variants and Vyper, compare results
uv run python/benchmark_pool/run_full_benchmark.py --n-cpp 8 --n-py 1

2. Arbitrage Grid Search

Run parameter sweeps over historical candle data to evaluate pool configurations. Optionally replay historical CoWSwap trades.

Get data first:

• Candles: https://github.com/heswithme/FX-1-Minute-Data (put in python/arb_sim/trade_data/)
• CoWSwap trades (optional): https://github.com/heswithme/cowswap-trades-fetch

Run grid search:

# 1. Generate pool parameter grid
uv run python/arb_sim/generate_pools_nd.py

# 2. Run simulation
uv run python/arb_sim/arb_sim.py --real double --dustswapfreq 600 -n 10

# 3. Plot results
uv run python/arb_sim/plot_heatmap.py --metrics apy,apy_net,vp,tvl_growth,total_notional_coin0,n_rebalances,trades,donations,tw_avg_pool_fee,avg_rel_price_diff,avg_imbalance,tw_real_slippage_5pct --ncol 5

With CoWSwap replay (add --cow):

uv run python/arb_sim/arb_sim.py --real double --dustswapfreq 600 -n 10 --cow

One-liner:

uv run python/arb_sim/generate_pools_nd.py && uv run python/arb_sim/arb_sim.py --real double --dustswapfreq 600 -n 10 && uv run python/arb_sim/plot_heatmap.py --metrics apy,apy_net,vp,tvl_growth,total_notional_coin0,n_rebalances,trades,donations,tw_avg_pool_fee,avg_rel_price_diff,avg_imbalance,tw_real_slippage_5pct --ncol 5

Cluster sweep (orchestration + analysis):

# 1. Generate N-dimensional pool grid
uv run python/arb_sim/generate_pools_nd.py

# 2. Run cluster sweep (streams one blade)
uv run python/arb_sim/cluster_orchestration/orchestrate.py --pools python/arb_sim/run_data/pool_config.json --stream-blade blade-a5

# 3. Plot optimized N-d heatmaps from merged results
uv run python/arb_sim/plot_heatmap_nd_opt.py --metrics apy_masked,apy,apy_net,apy_xcp,apy_xcp_net,vp,tvl_growth,total_notional_coin0,n_rebalances,trades,donations,tw_avg_pool_fee,avg_rel_price_diff,avg_imbalance,tw_real_slippage_5pct --ncol 4 --arb python/arb_sim/cluster_orchestration/results/cluster_sweep_latest.json --pricethr 50

# 4. Enumerate local maxima for a metric
uv run python/arb_sim/find_local_maxima_orjson.py --arb python/arb_sim/cluster_orchestration/results/cluster_sweep_latest.json --metric apy_masked --local --top 100 --enumerate --pricethr 50

# 5. Rank grid points by multiple metrics (rank aggregation)
uv run --with orjson python/arb_sim/find_ranked_maxima.py \
  --arb python/arb_sim/cluster_orchestration/results/cluster_sweep_latest.json \
  --desc-metrics apy_net --asc-metrics avg_rel_price_diff,tw_real_slippage_5pct \
  --weights apy_net=1 --top 20

Key CLI Flags

Flag	Description
--real double/float/longdouble	Numeric precision
-n N	Thread count
--n-candles N	Limit candles processed
--dustswapfreq S	Idle tick frequency (seconds)
--cow	Enable CoWSwap trade replay
--save-actions	Record all trades for replay
--detailed-log	Per-candle state output
--disable-slippage-probes	Skip slippage probe sampling

Requirements

• C++17 compiler, CMake, Boost (json)
• Python 3.10+, uv
• For Vyper validation: titanoboa

git submodule update --init --recursive

Build

cmake -B cpp_modular/build cpp_modular -DCMAKE_BUILD_TYPE=Release
cmake --build cpp_modular/build -j

Repository Structure

cpp_modular/          # C++ pool implementation and harness
python/
  arb_sim/            # Grid search simulator
    trade_data/       # Candle data (btcusd/, ethusd/, etc.)
    run_data/         # Output: pool_config.json, arb_run_*.json
  benchmark_pool/     # Parity validation tools
  vyper_pool/         # Vyper runner via titanoboa
contracts/twocrypto-ng/  # Vyper reference (submodule)

Outputs

Results written to:

• python/arb_sim/run_data/ - grid search results
• python/benchmark_pool/data/results/ - parity benchmark results

Both directories are gitignored.