Metadata-Version: 2.1
Name: qformatpy
Version: 1.0.2
Summary: Simple to use fixed-point library.
Keywords: DSP,Fixed-point,Signal-Processing,Qformat
Author-Email: Eric Macedo <ericsmacedo@gmail.com>
Classifier: Programming Language :: Python :: 3
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: Operating System :: OS Independent
Project-URL: Documentation, https://qformatpy.readthedocs.io/en/latest/
Project-URL: Source Code, https://github.com/ericsmacedo/qformatpy
Requires-Python: <4.0,>=3.10.0
Requires-Dist: numba>=0.61.2
Requires-Dist: numpy
Description-Content-Type: text/markdown


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# Easy-to-use fixed-point library

**qformatpy** is a lightweight Python library for converting numbers to fixed-point format using the ARM-style Qm.n notation. It is designed to be simple, readable, and easy to integrate into simulation, modeling, or hardware verification pipelines.

The library provides a single function, `qformat`, that lets you control integer and fractional precision, signedness, rounding behavior, and overflow handling — all without the complexity of a full fixed-point arithmetic suite.

Whether you're developing embedded systems, DSP algorithms, or just need fast fixed-point conversion, **qformatpy** keeps things straightforward.

To get started, check the example of a [fixed-point integrator](docs/example_int/example_int.md) implemented
using the library.

- [Documentation](https://qformatpy.readthedocs.io/en/latest/)
- [PyPI](https://pypi.org/project/qformatpy/)
- [Sources](https://github.com/ericsmacedo/qformatpy)
- [Issues](https://github.com/ericsmacedo/qformatpy/issues)

## Features

- **Support for Numba**
  Optimized with optional [Numba](https://numba.pydata.org/) acceleration for fast, JIT-compiled conversions.

- **Native NumPy Array Support**
  Seamlessly handles `numpy.ndarray` inputs for efficient batch processing.

- **Flexible Rounding Modes**
  Choose from 9 rounding modes, including truncation, ceiling, rounding to nearest (with tie-breaking), and more.

- **Customizable Overflow Handling**
  Select between wraparound, saturation, or error-on-overflow behavior.

- **Signed and Unsigned Formats**
  Easily switch between signed and unsigned representations using the `signed` parameter.

- **Consistent Q-Format Notation**
  Follows ARM-style Qm.n notation for compatibility with DSP and embedded tools.

- **Well-Suited for Embedded and DSP Simulation**
  Ideal for preparing and validating fixed-point behavior before deploying to hardware.

## Installation

Installing it is pretty easy:

```bash
pip install qformatpy
```
