Fast Google Polyline Encoding and Decoding
Installation
pip install pypolyline
Supported Python Versions
- Python 3.9
- Python 3.10
- Python 3.11
- Python 3.12
- Python 3.13
Supported Platforms
- Linux (
manylinux*
-compatible, x86_64 and aarch64) - macOS (x86_64 and arm64)
- Windows 64-bit
Usage
Coordinates must be in (Longitude, Latitude
) order
from pypolyline.cutil import encode_coordinates, decode_polyline
coords = [
[52.64125, 23.70162],
[52.64938, 23.70154],
[52.64957, 23.68546],
[52.64122, 23.68549],
[52.64125, 23.70162]
]
polyline = encode_coordinates(coords, 5)
decoded_coords = decode_polyline(polyline, 5)
Error Handling
Failure to encode coordinates, or to decode a supplied Polyline, will raise a RuntimeError
containing information about the invalid input.
How it Works
FFI and a Rust binary
Is It Fast
…Yes.
You can verify this by installing the polyline
package, then running benchmarks.py
, a calibrated benchmark using cProfile
.
On an M2 MBP, The pure-Python test runs in ~2500 ms, the Flexpolyline benchmark runs in ~1500 ms and The Rust + Cython benchmark runs in around 80 ms (30 x and 17.5 x faster, respectively).
License
The Blue Oak Model Licence 1.0.0
Citing Pypolyline
If Pypolyline has been significant in your research, and you would like to acknowledge the project in your academic publication, we suggest citing it as follows (example in APA style, 7th edition):
Hügel, S. (2021). Pypolyline (Version X.Y.Z) [Computer software]. https://doi.org/10.5281/zenodo.5774925
In Bibtex format:
@software{Hugel_Pypolyline_2021,
author = {Hügel, Stephan},
doi = {10.5281/zenodo.5774925},
license = {MIT},
month = {12},
title = {{Pypolyline}},
url = {https://github.com/urschrei/simplification},
version = {X.Y.Z},
year = {2021}
}