Metadata-Version: 2.1
Name: pynanoflann
Version: 0.0.9
Summary: Python nanoflann wrapper
Author-Email: =?utf-8?q?Dag_W=C3=A4stberg?= <dwastberg@gmail.com>, u1234x1234 <u1234x1234@gmail.com>
License: BSD-2-Clause
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: C++
Requires-Python: >=3.8
Requires-Dist: numpy
Requires-Dist: scikit-learn; extra == "sklearn"
Requires-Dist: pytest; extra == "test"
Requires-Dist: pytest-cov; extra == "test"
Requires-Dist: codecov; extra == "test"
Requires-Dist: contexttimer; extra == "test"
Requires-Dist: tabulate; extra == "test"
Requires-Dist: scikit-learn; extra == "test"
Requires-Dist: pandas; extra == "benchmark"
Requires-Dist: seaborn; extra == "benchmark"
Requires-Dist: contexttimer; extra == "benchmark"
Requires-Dist: matplotlib; extra == "benchmark"
Requires-Dist: scikit-learn; extra == "benchmark"
Provides-Extra: sklearn
Provides-Extra: test
Provides-Extra: benchmark
Description-Content-Type: text/markdown

# pynanoflann

This is a fork of [a fork](https://github.com/dwastberg/pynanoflann) of [the unofficial python wrapper](https://github.com/u1234x1234/pynanoflann) to the [nanoflann](https://github.com/jlblancoc/nanoflann) library.

The nanoflann implementation of [k-d tree](https://en.wikipedia.org/wiki/K-d_tree) provides one of the best performance for many k-nearest neighbour problems.

The main distinguishing feature of this fork is that it's installable from pip.

# Install

```
pip install pynanoflann
```

*Corin Wagen, 2025*
