fastgpx

An experimental Python library for parsing GPX files fast.

# Get the total length of the tracks in a GPX file:
import fastgpx

gpx = fastgpx.load("example.gpx")
print(f'{gpx.length_2d()} m')

# Iterate over GPX file:
import fastgpx

gpx = fastgpx.load("example.gpx")
for track in gpx.tracks:
    print(f'Track: {track.name}')
    print(f'Distance: {track.length_2d()} m')
    time_bounds = track.time_bounds()
    if not time_bounds.is_empty():
        print(f'Time: {time_bounds.start_time} - {time_bounds.end_time}')
    for segment in track.segments:
        for point in segment.points:
            print(f'Point: {point.latitude}, {point.longitude}')

import fastgpx

locations = [
    fastgpx.LatLong(64, 10),
    fastgpx.LatLong(66, 11),
]
encoded = fastgpx.polyline.encode(locations, precision=6)

decoded = fastgpx.polyline.decode(encoded, precision=6)

Documentation

Requirements

• Python 3.12+ (Tested with 3.12, 3.13, 3.14)
• C++23 Compiler (For building fastgpx)

Windows

• Tested with MSVC 17.12.4+ and Clang-cl 19+.

Linux (Tested on Ubuntu)

• C++23 compatible runtime (GCC libstdc++ 14+ or Clang libc++ 18.1+)

GPX/XML Performance (Background)

This library came out of the need to extract information from many GPX files fast.

gpxpy is the most popular GPX library for Python. It is very versatile in manipulating GPX files.

However in benchmarking it doesn't perform well.

gpxpy docs says (at time of writing) that it uses lxml is available because it is faster than "minidom" (etree).

When benchmarking that was not the case. It appear that the stdlib XML library has gotten much better since gpxpy was created.

Reference: Open ticket on making etree default: https://github.com/tkrajina/gpxpy/issues/248

fastgpx is not intended as a replacement for gpxpy. It mainly focuses on extracting GPX data fast for performance critical tasks. For the few functionalities that does overlap with gpxpy compatible method calls has been added so that one can quickly swap between fastgpx and gpxy.

Benchmarks

Test machine: AMD Ryzen 7 5800X, 32 GB memory, Windows 11, and WSL2 Ubuntu 24.04 on the same machine. Python 3.12, fastgpx 0.8.0, gpxpy 1.6.2, lxml 6.1.3, polyline 2.0.4.

Total track length

Total track length of gpx/2024 Great Roadtrip (24 files, 330k points), in seconds per pass. Lower is better.

gpxpy's and fastgpx's lengths differ by 0.08%, because they use different distance formulas.

Polyline encoding

Encoding every segment of the same files, in seconds per pass. Both timings include loading the files with fastgpx.

Reproducing

uv run --group benchmarks benchmarks/benchmark_gpx.py
uv run --group benchmarks benchmarks/benchmark_polyline.py

benchmark_gpx.py prints each method's time per pass as "Average"; gpxpy runs once. benchmark_polyline.py prints the total for 10 passes, so divide it by 10 to compare with the table.

Detailed performance notes are in benchmarks/README.md.