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// -------------------------------------------------------------------------------------------------
// 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.
// -------------------------------------------------------------------------------------------------
use std::collections::BTreeMap;
#[allow(unused_imports)] // Used in template pattern for returns conversion
use nautilus_core::UnixNanos;
use pyo3::prelude::*;
use crate::{statistic::PortfolioStatistic, statistics::win_rate::WinRate};
#[pymethods]
#[pyo3_stub_gen::derive::gen_stub_pymethods]
impl WinRate {
/// Calculates the win rate of a trading strategy based on realized PnLs.
///
/// Win rate is the percentage of profitable trades out of total trades:
/// `Count(Trades with PnL > 0) / Total Trades`
///
/// Returns a value between 0.0 and 1.0, where 1.0 represents 100% winning trades.
///
/// Note: While a high win rate is desirable, it should be considered alongside
/// average win/loss sizes and profit factor for complete system evaluation.
///
/// # References
///
/// - Standard trading performance metric across the industry
/// - Tharp, V. K. (1998). *Trade Your Way to Financial Freedom*. McGraw-Hill.
/// - Kaufman, P. J. (2013). *Trading Systems and Methods* (5th ed.). Wiley.
#[new]
fn py_new() -> Self {
Self {}
}
fn __repr__(&self) -> String {
self.to_string()
}
#[getter]
#[pyo3(name = "name")]
fn py_name(&self) -> String {
self.name()
}
#[pyo3(name = "calculate_from_realized_pnls")]
#[expect(clippy::needless_pass_by_value)]
fn py_calculate_from_realized_pnls(&mut self, realized_pnls: Vec<f64>) -> Option<f64> {
self.calculate_from_realized_pnls(&realized_pnls)
}
#[pyo3(name = "calculate_from_returns")]
#[allow(unused_variables)] // Pattern preserved for consistency across statistics
fn py_calculate_from_returns(&mut self, _returns: BTreeMap<u64, f64>) -> Option<f64> {
None
}
#[pyo3(name = "calculate_from_positions")]
fn py_calculate_from_positions(&mut self, _positions: Vec<Py<PyAny>>) -> Option<f64> {
None
}
}