nautilus_analysis/python/
mod.rs

1// -------------------------------------------------------------------------------------------------
2//  Copyright (C) 2015-2025 Nautech Systems Pty Ltd. All rights reserved.
3//  https://nautechsystems.io
4//
5//  Licensed under the GNU Lesser General Public License Version 3.0 (the "License");
6//  You may not use this file except in compliance with the License.
7//  You may obtain a copy of the License at https://www.gnu.org/licenses/lgpl-3.0.en.html
8//
9//  Unless required by applicable law or agreed to in writing, software
10//  distributed under the License is distributed on an "AS IS" BASIS,
11//  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12//  See the License for the specific language governing permissions and
13//  limitations under the License.
14// -------------------------------------------------------------------------------------------------
15
16//! Python bindings from [PyO3](https://pyo3.rs).
17
18pub mod analyzer;
19pub mod statistics;
20
21use pyo3::{prelude::*, pymodule};
22
23/// Initializes the Python `analysis` module.
24///
25/// Adds the `PortfolioAnalyzer` class and all portfolio statistics.
26///
27/// # Errors
28///
29/// Returns a Python exception if adding any class fails.
30#[pymodule]
31pub fn analysis(_: Python<'_>, m: &Bound<'_, PyModule>) -> PyResult<()> {
32    m.add_class::<crate::analyzer::PortfolioAnalyzer>()?;
33
34    // Statistics - Returns-based
35    m.add_class::<crate::statistics::returns_avg::ReturnsAverage>()?;
36    m.add_class::<crate::statistics::returns_avg_loss::ReturnsAverageLoss>()?;
37    m.add_class::<crate::statistics::returns_avg_win::ReturnsAverageWin>()?;
38    m.add_class::<crate::statistics::returns_volatility::ReturnsVolatility>()?;
39    m.add_class::<crate::statistics::sharpe_ratio::SharpeRatio>()?;
40    m.add_class::<crate::statistics::sortino_ratio::SortinoRatio>()?;
41    m.add_class::<crate::statistics::profit_factor::ProfitFactor>()?;
42    m.add_class::<crate::statistics::risk_return_ratio::RiskReturnRatio>()?;
43
44    // Statistics - PnL-based
45    m.add_class::<crate::statistics::win_rate::WinRate>()?;
46    m.add_class::<crate::statistics::expectancy::Expectancy>()?;
47    m.add_class::<crate::statistics::winner_avg::AvgWinner>()?;
48    m.add_class::<crate::statistics::winner_max::MaxWinner>()?;
49    m.add_class::<crate::statistics::winner_min::MinWinner>()?;
50    m.add_class::<crate::statistics::loser_avg::AvgLoser>()?;
51    m.add_class::<crate::statistics::loser_max::MaxLoser>()?;
52    m.add_class::<crate::statistics::loser_min::MinLoser>()?;
53
54    // Statistics - Position-based
55    m.add_class::<crate::statistics::long_ratio::LongRatio>()?;
56
57    Ok(())
58}
nautilus_analysis/python/mod.rs

nautilus_analysis/python/
mod.rs
