Metadata-Version: 2.4
Name: quantalytics
Version: 0.1.2
Summary: Modern quantitative analysis library for portfolio analytics, charts, and reports
Author: Tyler Patterson
License: MIT License
        
        Copyright (c) 2025 Tyler
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
        
Project-URL: Homepage, https://github.com/pattertj/quantalytics
Project-URL: Issues, https://github.com/pattertj/quantalytics/issues
Keywords: analytics,charts,finance,metrics,quantitative,reporting,statistics,visualization
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Topic :: Office/Business :: Financial :: Investment
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: jinja2>=3.1
Requires-Dist: matplotlib>=3.6
Requires-Dist: numpy>=1.23
Requires-Dist: pandas>=1.5
Requires-Dist: plotly>=5.15
Requires-Dist: scipy>=1.9
Dynamic: license-file

# Quantalytics

Quantalytics is a fast, modern Python library for generating quantitative performance metrics, interactive charts, and publication-ready reports. It is designed for strategy researchers, portfolio managers, and data scientists who want an ergonomic toolchain without the overhead of large monolithic frameworks.

## Features

- **Descriptive Stats** – Grab skew, kurtosis, total return, and CAGR via the lightweight `qa.stats` helpers.
- **Performance Metrics** – Compute Sharpe, Sortino, Calmar, max drawdown, annualized returns/volatility, and more in a single call.
- **Interactive Visuals** – Build Plotly-based charts for cumulative returns, rolling volatility, and drawdown analysis with sensible defaults.
- **Beautiful Reports** – Produce responsive HTML tear sheets with configurable sections, ready to export to PDF.
- **Composable API** – Small, well-typed functions that play nicely with pandas Series/DataFrames.
- **Production Ready Packaging** – Standards-based `pyproject.toml`, semantic versioning, and optional CLI hooks for release automation.

## Installation

```bash
pip install quantalytics
```

## Quickstart

```python
import pandas as pd
import quantalytics as qa

returns = pd.Series(
    [0.01, 0.02, -0.005, 0.015, -0.01, 0.03],
    index=pd.date_range("2024-01-01", periods=6, freq="B"),
)

summary = qa.metrics.performance_summary(returns)
print(summary.sharpe, summary.calmar)

fig = qa.charts.cumulative_returns_chart(returns)
fig.show()
```

## Documentation

Full tutorials and API references live on our Docusaurus site: [https://pattertj.github.io/quantalytics/](https://pattertj.github.io/quantalytics/). Start with the introduction, then dive into the stats, metrics, charts, or reports guides as needed.

## License

MIT License. See [LICENSE](LICENSE).
