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fast-geodist-0.4.0
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مشاهده بیشترتوضیحات
An implementation of Haversine distance calculations using Rust and PyO3
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | fast-geodist-0.4.0 |
| نام | fast-geodist |
| نسخه کتابخانه | 0.4.0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | - |
| ایمیل نویسنده | Martin Black <18327836+mblackgeo@users.noreply.github.com> |
| آدرس صفحه اصلی | - |
| آدرس اینترنتی | https://pypi.org/project/fast-geodist/ |
| مجوز | - |
# fast-geodist
[](https://pypi.org/project/fast-geodist/)
[](https://github.com/mblackgeo/fast-geodist/actions)
[](https://github.com/mblackgeo/fast-geodist/actions)
[](https://github.com/psf/black)
An implementation of the [Haversine formula](https://en.wikipedia.org/wiki/Haversine_formula) for calculating [Great Circle distance](https://en.wikipedia.org/wiki/Great-circle_distance) using Rust and [PyO3](https://github.com/PyO3/PyO3).
This package was started as an experiment for learning how to implement functions in Rust and wrap them for use in python. The Haversine Formula is implemented following [georust](https://github.com/georust/geo/blob/main/geo/src/algorithm/haversine_distance.rs), with an array-wise implementation written using [`ndarray::parallel`](https://docs.rs/ndarray/latest/ndarray/parallel/index.html). It is wrapped for python using [Maturin](https://github.com/PyO3/maturin) and integrates [`rust-numpy`](https://github.com/PyO3/rust-numpy) for array operations.
## Installation
```
pip install fast-geodist
```
## Quick start
The package provides two main entry points:
```python
import numpy as np
from fast_geodist import haversine
# input either a tuple of (lat/lon, lat/lon)
result = haversine((1, 1, 0, 0))
# or a numpy array of coordinates pairs
# useful if lots of distances need to be calculated
# will be computed in parallel
result = haversine(np.array([(1, 1, 0, 0), (2, 2, 0, 0)]))
```
## Benchmarks
The results of benchmarking show the rust implementation is **14x faster** than the python implementation. This benchmark computes distances on an array containing 1,000,000 pairs of coordinates (see [`bench.py`](/tests/bench.py)):
```
--------------------------------------------- benchmark: 2 tests ---------------------------------------------
Name (time in ms) Min Max Mean Median
--------------------------------------------------------------------------------------------------------------
test_benchmark_fast 164.0635 (1.0) 171.7663 (1.0) 168.0218 (1.0) 168.4129 (1.0)
test_benchmark_slow 2,335.4281 (14.23) 2,439.7850 (14.20) 2,395.6077 (14.26) 2,406.6356 (14.29)
--------------------------------------------------------------------------------------------------------------
```
Computed on an Intel i7-1165G7.
## Development
Prequisites:
* Python (>=3.7) and make
* [Rust toolchain](https://rustup.rs/)
After cloning the repository, the Makefile includes helpful commands for setting up a development environment, linting, formatting, testing, and benchmarking. Get started as follows:
```shell
# setup a new virtual environment
python -m venv .venv
source .venv/bin/activate
# install the development dependencies
make install
# check other available commands
make help
```
Tooling:
* Cargo and [Pytest](https://docs.pytest.org/en/6.2.x/) are used for testing the Rust and Python code respectively (see [`/tests`](/tests/)).
* Python code is linted using [flake8](https://flake8.pycqa.org/en/latest/) and formatted using [Black](https://github.com/psf/black); rust code with `cargo fmt` and `cargo clippy`.
* [pre-commit](https://pre-commit.com/) is used to run these checks locally before files are pushed to git
* The [Github Actions pipeline](.github/workflows/ci.yml) runs these checks and tests
* [Semantic-release](https://python-semantic-release.readthedocs.io/en/latest/) is used with [conventional commits](https://www.conventionalcommits.org/en/v1.0.0/) for automated releasing to PyPI
## References
As well as the excellent PyO3 documentation, the following posts helped with creation of this package:
- https://blog.yossarian.net/2020/08/02/Writing-and-publishing-a-python-module-in-rust
- https://depth-first.com/articles/2020/08/10/python-extensions-in-pure-rust-with-pyo3/
- http://saidvandeklundert.net/learn/2021-11-18-calling-rust-from-python-using-pyo3/
- https://itnext.io/how-to-bind-python-numpy-with-rust-ndarray-2efa5717ed21
نیازمندی
| مقدار | نام |
|---|---|
| - | numpy~=1.0 |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.7 | Python |
نحوه نصب
نصب پکیج whl fast-geodist-0.4.0:
pip install fast-geodist-0.4.0.whl
نصب پکیج tar.gz fast-geodist-0.4.0:
pip install fast-geodist-0.4.0.tar.gz