nautilus-model 0.59.0

// -------------------------------------------------------------------------------------------------
//  Copyright (C) 2015-2026 Nautech Systems Pty Ltd. All rights reserved.
//  https://nautechsystems.io
//
//  Licensed under the GNU Lesser General Public License Version 3.0 (the "License");
//  You may not use this file except in compliance with the License.
//  You may obtain a copy of the License at https://www.gnu.org/licenses/lgpl-3.0.en.html
//
//  Unless required by applicable law or agreed to in writing, software
//  distributed under the License is distributed on an "AS IS" BASIS,
//  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
//  See the License for the specific language governing permissions and
//  limitations under the License.
// -------------------------------------------------------------------------------------------------

//! Python bindings for DeFi pool profiler.

use std::str::FromStr;

use alloy_primitives::{U160, U256};
use nautilus_core::python::to_pyvalue_err;
use pyo3::{prelude::*, types::PyModule};

use crate::{
    defi::{
        Pool,
        pool_analysis::{PoolProfiler, quote::SwapQuote, size_estimator::SizeForImpactResult},
    },
    identifiers::InstrumentId,
};

#[pymethods]
#[pyo3_stub_gen::derive::gen_stub_pymethods]
impl PoolProfiler {
    #[getter]
    #[pyo3(name = "pool")]
    fn py_pool(&self) -> Pool {
        self.pool.as_ref().clone()
    }

    #[getter]
    #[pyo3(name = "instrument_id")]
    fn py_instrument_id(&self) -> InstrumentId {
        self.pool.instrument_id
    }

    #[getter]
    #[pyo3(name = "is_initialized")]
    fn py_is_initialized(&self) -> bool {
        self.is_initialized
    }

    #[getter]
    #[pyo3(name = "current_tick")]
    fn py_current_tick(&self) -> i32 {
        self.state.current_tick
    }

    #[getter]
    #[pyo3(name = "price_sqrt_ratio_x96")]
    #[gen_stub(override_return_type(type_repr = "int"))]
    fn py_price_sqrt_ratio_x96(&self, py: Python<'_>) -> PyResult<Py<PyAny>> {
        Ok(PyModule::import(py, "builtins")?
            .getattr("int")?
            .call1((self.state.price_sqrt_ratio_x96.to_string(),))?
            .unbind())
    }

    #[getter]
    #[pyo3(name = "total_amount0_deposited")]
    fn py_total_amount0_deposited(&self) -> String {
        self.analytics.total_amount0_deposited.to_string()
    }

    #[getter]
    #[pyo3(name = "total_amount1_deposited")]
    fn py_total_amount1_deposited(&self) -> String {
        self.analytics.total_amount1_deposited.to_string()
    }

    #[getter]
    #[pyo3(name = "total_amount0_collected")]
    fn py_total_amount0_collected(&self) -> String {
        self.analytics.total_amount0_collected.to_string()
    }

    #[getter]
    #[pyo3(name = "total_amount1_collected")]
    fn py_total_amount1_collected(&self) -> String {
        self.analytics.total_amount1_collected.to_string()
    }

    #[getter]
    #[pyo3(name = "protocol_fees_token0")]
    fn py_protocol_fees_token0(&self) -> String {
        self.state.protocol_fees_token0.to_string()
    }

    #[getter]
    #[pyo3(name = "protocol_fees_token1")]
    fn py_protocol_fees_token1(&self) -> String {
        self.state.protocol_fees_token1.to_string()
    }

    #[getter]
    #[pyo3(name = "fee_protocol")]
    fn py_fee_protocol(&self) -> u8 {
        self.state.fee_protocol
    }

    /// Returns the pool's active liquidity tracked by the tick map.
    ///
    /// This represents the effective liquidity available for trading at the current price.
    /// The tick map maintains this value efficiently by updating it during tick crossings
    /// as the price moves through different ranges.
    ///
    /// # Returns
    /// The active liquidity (u128) at the current tick from the tick map
    #[pyo3(name = "get_active_liquidity")]
    fn py_get_active_liquidity(&self) -> u128 {
        self.get_active_liquidity()
    }

    /// Gets the number of active ticks.
    #[pyo3(name = "get_active_tick_count")]
    fn py_get_active_tick_count(&self) -> usize {
        self.get_active_tick_count()
    }

    /// Gets the total number of ticks tracked by the tick map.
    ///
    /// Returns count of all ticks that have ever been initialized,
    /// including those that may no longer have active liquidity.
    ///
    /// # Returns
    /// Total tick count in the tick map
    #[pyo3(name = "get_total_tick_count")]
    fn py_get_total_tick_count(&self) -> usize {
        self.get_total_tick_count()
    }

    /// Gets the count of positions that are currently active.
    ///
    /// Active positions are those with liquidity > 0 and whose tick range
    /// includes the current pool tick (meaning they have tokens in the pool).
    #[pyo3(name = "get_total_active_positions")]
    fn py_get_total_active_positions(&self) -> usize {
        self.get_total_active_positions()
    }

    /// Gets the count of positions that are currently inactive.
    ///
    /// Inactive positions are those that exist but don't span the current tick,
    /// meaning their liquidity is entirely in one token or the other.
    #[pyo3(name = "get_total_inactive_positions")]
    fn py_get_total_inactive_positions(&self) -> usize {
        self.get_total_inactive_positions()
    }

    /// Estimates the total amount of token0 in the pool.
    ///
    /// Calculates token0 balance by summing:
    /// - Token0 amounts from all active liquidity positions
    /// - Accumulated trading fees (approximated from fee growth)
    /// - Protocol fees collected
    #[pyo3(name = "estimate_balance_of_token0")]
    fn py_estimate_balance_of_token0(&self) -> String {
        self.estimate_balance_of_token0().to_string()
    }

    /// Estimates the total amount of token1 in the pool.
    ///
    /// Calculates token1 balance by summing:
    /// - Token1 amounts from all active liquidity positions
    /// - Accumulated trading fees (approximated from fee growth)
    /// - Protocol fees collected
    #[pyo3(name = "estimate_balance_of_token1")]
    fn py_estimate_balance_of_token1(&self) -> String {
        self.estimate_balance_of_token1().to_string()
    }

    #[pyo3(name = "get_total_liquidity")]
    fn py_get_total_liquidity_all_positions(&self) -> String {
        self.get_total_liquidity().to_string()
    }

    /// Calculates the liquidity utilization rate for the pool.
    ///
    /// The utilization rate measures what percentage of total deployed liquidity
    /// is currently active (in-range and earning fees) at the current price tick.
    #[pyo3(name = "liquidity_utilization_rate")]
    fn py_liquidity_utilization_rate(&self) -> f64 {
        self.liquidity_utilization_rate()
    }

    /// Simulates an exact input swap (know input amount, calculate output amount).
    #[pyo3(name = "swap_exact_in")]
    fn py_swap_exact_in(
        &self,
        amount_in: &str,
        zero_for_one: bool,
        sqrt_price_limit_x96: Option<&str>,
    ) -> PyResult<SwapQuote> {
        let amount_in = U256::from_str(amount_in).map_err(to_pyvalue_err)?;
        let sqrt_price_limit = match sqrt_price_limit_x96 {
            Some(limit_str) => Some(U160::from_str(limit_str).map_err(to_pyvalue_err)?),
            None => None,
        };

        self.swap_exact_in(amount_in, zero_for_one, sqrt_price_limit)
            .map_err(to_pyvalue_err)
    }

    /// Simulates an exact output swap (know output amount, calculate required input amount).
    #[pyo3(name = "swap_exact_out")]
    fn py_swap_exact_out(
        &self,
        amount_out: &str,
        zero_for_one: bool,
        sqrt_price_limit_x96: Option<&str>,
    ) -> PyResult<SwapQuote> {
        let amount_out = U256::from_str(amount_out).map_err(to_pyvalue_err)?;
        let sqrt_price_limit = match sqrt_price_limit_x96 {
            Some(limit_str) => Some(U160::from_str(limit_str).map_err(to_pyvalue_err)?),
            None => None,
        };

        self.swap_exact_out(amount_out, zero_for_one, sqrt_price_limit)
            .map_err(to_pyvalue_err)
    }

    /// Finds the maximum trade size that produces a target slippage (including fees).
    ///
    /// Uses binary search to find the largest trade size that results in slippage
    /// at or below the target. The method iteratively simulates swaps at different
    /// sizes until it converges to the optimal size within the specified tolerance.
    ///
    /// # Returns
    /// The maximum trade size (U256) that produces the target slippage
    ///
    /// # Errors
    /// Returns error if:
    /// - Impact is zero or exceeds 100% (10000 bps)
    /// - Pool is not initialized
    /// - Swap simulations fail
    #[pyo3(name = "size_for_impact_bps")]
    fn py_size_for_impact_bps(&self, impact_bps: u32, zero_for_one: bool) -> PyResult<String> {
        self.size_for_impact_bps(impact_bps, zero_for_one)
            .map(|size| size.to_string())
            .map_err(to_pyvalue_err)
    }

    /// Finds the maximum trade size with search diagnostics.
    /// This is the detailed version of `Self.size_for_impact_bps` that returns
    /// extensive information about the search process.It is useful for debugging,
    /// monitoring, and analyzing search behavior in production.
    ///
    /// # Returns
    /// Detailed result with size and search diagnostics
    #[pyo3(name = "size_for_impact_bps_detailed")]
    fn py_size_for_impact_bps_detailed(
        &self,
        impact_bps: u32,
        zero_for_one: bool,
    ) -> PyResult<SizeForImpactResult> {
        self.size_for_impact_bps_detailed(impact_bps, zero_for_one)
            .map_err(to_pyvalue_err)
    }
}

#[cfg(test)]
mod tests {
    use std::{str::FromStr, sync::Arc};

    use alloy_primitives::{U160, address};
    use nautilus_core::UnixNanos;
    use pyo3::{
        Python,
        types::{PyAnyMethods, PyInt},
    };
    use rstest::rstest;

    use crate::defi::{
        AmmType, Blockchain, Chain, Dex, DexType, Pool, PoolIdentifier, Token,
        pool_analysis::PoolProfiler,
    };

    #[rstest]
    fn price_sqrt_ratio_x96_returns_python_int() {
        let sqrt_price_x96 = U160::from_str("79228162514264337593543950336").unwrap();
        let mut profiler = PoolProfiler::new(pool());
        profiler.initialize(sqrt_price_x96).unwrap();
        Python::initialize();

        Python::attach(|py| {
            let value = profiler.py_price_sqrt_ratio_x96(py).unwrap();
            let value = value.bind(py);

            assert!(value.is_instance_of::<PyInt>());
            assert_eq!(value.str().unwrap().to_string(), sqrt_price_x96.to_string());
        });
    }

    fn pool() -> Arc<Pool> {
        let chain = Arc::new(Chain::new(Blockchain::Ethereum, 1));
        let dex = Arc::new(Dex::new(
            (*chain).clone(),
            DexType::UniswapV3,
            "0x0000000000000000000000000000000000000fac",
            1,
            AmmType::CLAMM,
            "PoolCreated",
            "Swap",
            "Mint",
            "Burn",
            "Collect",
        ));
        let token0 = Token::new(
            chain.clone(),
            address!("0000000000000000000000000000000000000001"),
            "USD Coin".to_string(),
            "USDC".to_string(),
            6,
        );
        let token1 = Token::new(
            chain.clone(),
            address!("0000000000000000000000000000000000000002"),
            "Wrapped Ether".to_string(),
            "WETH".to_string(),
            18,
        );
        let pool_address = address!("0000000000000000000000000000000000000003");

        Arc::new(Pool::new(
            chain,
            dex,
            pool_address,
            PoolIdentifier::from_address(pool_address),
            1,
            token0,
            token1,
            Some(500),
            Some(10),
            UnixNanos::default(),
        ))
    }
}