libxrk 0.6.0

Library for reading AIM XRK files from AIM automotive data loggers

libxrk

A Python library for reading AIM XRK and XRZ files from AIM automotive data loggers.

Features

• Read AIM XRK files (raw data logs)
• Read AIM XRZ files (zlib-compressed XRK files)
• Parse track data and telemetry channels
• GPS coordinate conversion and lap detection
• High-performance Cython implementation
• Supports Python 3.10 - 3.14

Installation

Install from PyPI

pip install libxrk

Install from Source

Prerequisites

On Ubuntu/Debian:

sudo apt install build-essential python3-dev

Install with Poetry

poetry install

The Cython extension will be automatically compiled during installation.

Usage

from libxrk import aim_xrk

# Read an XRK file
log = aim_xrk('path/to/file.xrk')

# Read an XRZ file (automatically decompressed)
log = aim_xrk('path/to/file.xrz')

# Access channels (each channel is a PyArrow table with 'timecodes' and value columns)
for channel_name, channel_table in log.channels.items():
    print(f"{channel_name}: {channel_table.num_rows} samples")

# Get all channels merged into a single PyArrow table
# (handles different sample rates with interpolation/forward-fill)
merged_table = log.get_channels_as_table()
print(merged_table.column_names)

# Convert to pandas DataFrame
df = merged_table.to_pandas()

# Access laps (PyArrow table with 'num', 'start_time', 'end_time' columns)
print(f"Laps: {log.laps.num_rows}")
for i in range(log.laps.num_rows):
    lap_num = log.laps.column("num")[i].as_py()
    start = log.laps.column("start_time")[i].as_py()
    end = log.laps.column("end_time")[i].as_py()
    print(f"Lap {lap_num}: {start} - {end}")

# Access metadata
print(log.metadata)

Filtering and Resampling

from libxrk import aim_xrk

log = aim_xrk('session.xrk')

# Select specific channels
gps_log = log.select_channels(['GPS Latitude', 'GPS Longitude', 'GPS Speed'])

# Filter to a time range (milliseconds, inclusive start, exclusive end)
segment = log.filter_by_time_range(60000, 120000)

# Filter to a specific lap
lap5 = log.filter_by_lap(5)

# Combine filtering and channel selection
lap5_gps = log.filter_by_lap(5, channel_names=['GPS Latitude', 'GPS Longitude'])

# Resample all channels to match a reference channel's timebase
aligned = log.resample_to_channel('GPS Speed')

# Resample to a custom timebase
import pyarrow as pa
target = pa.array(range(0, 100000, 100), type=pa.int64())  # 10 Hz
resampled = log.resample_to_timecodes(target)

# Chain operations for analysis workflows
df = (log
    .filter_by_lap(5)
    .select_channels(['Engine RPM', 'GPS Speed'])
    .resample_to_channel('GPS Speed')
    .get_channels_as_table()
    .to_pandas())

All filtering and resampling methods return new LogFile instances (immutable pattern), enabling method chaining for complex analysis workflows.

Development

Quick Check

# Run all quality checks (format check, type check, tests)
poetry run poe check

Code Formatting

This project uses Black for code formatting.

# Format all Python files
poetry run black .

Type Checking

This project uses mypy for static type checking.

# Run type checker on all Python files
poetry run mypy .

Running Tests

This project uses pytest for testing.

# Run all tests
poetry run pytest

# Run tests with verbose output
poetry run pytest -v

# Run specific test file
poetry run pytest tests/test_xrk_loading.py

# Run tests with coverage
poetry run pytest --cov=libxrk

Testing with Pyodide (WebAssembly)

You can test the library in a WebAssembly environment using Pyodide. This requires Node.js to be installed.

# Build and run tests in Pyodide (installs Emscripten SDK to build/emsdk if needed)
poetry run poe pyodide-test

Note: Pyodide tests run automatically in CI via GitHub Actions.

Building

# Build CPython wheel and sdist
poetry build

# Build all wheels (CPython, Pyodide/WebAssembly, and sdist)
poetry run poe build-all

Clean Build

# Clean all build artifacts and rebuild
rm -rf build/ dist/ src/libxrk/*.so && poetry install

Testing

The project includes end-to-end tests that validate XRK and XRZ file loading and parsing.

Test files are located in tests/test_data/ and include real XRK and XRZ files for validation.

Credits

This project incorporates code from TrackDataAnalysis by Scott Smith, used under the MIT License.

License

MIT License - See LICENSE file for details.