fastsort 0.1.1

A high-performance sorting library for NumPy arrays.

fastsort

A high-performance sorting library for NumPy arrays.

import numpy as np
from fastsort import sort, argsort

arr = np.array([3, 1, 2], dtype=np.int32)

sorted_arr = sort(arr)
# Output: array([1, 2, 3], dtype=int32)

indices = argsort(arr)
# Output: array([1, 2, 0], dtype=int32)

Only two functions are exported: sort and argsort. Both functions take an n-dimensional NumPy array as input, along with an optional axis. If the axis is None, the flattened array is sorted. The sorting is unstable and utilizes Rust's sort_unstable for parallel slices of arrays or par_sort_unstable for vectors.

You can install the package using pip install fastsort. The library is in its early stages, and while further performance optimizations may be possible, it already achieves state-of-the-art performance, particularly on larger arrays, thanks to improved resource utilization.

How to develop

• Use uv sync to install dependencies from the lock file.
• Use uv lock to update the lock file if necessary given the pinned dependencies.
• Use uv lock --upgrade to upgrade the lock file the latest valid dependencies.
• Use uv build to build the package.
• Use uv pip install --editable . to install the package.
• Use uv run pytest tests to test the local package.

During development its useful to run uv build && uv pip install --no-deps --force-reinstall --editable ., which builds and re-installs the built package.

How to benchmark

• Use uv run bench/benchmark.py to run an individual benchmark.
• Use uv run bench/experiment.py to run an experiment of multiple benchmarks.
• Use uv run bench/visualize.py to plot experiment results.

Have a look at the individual scripts to learn about the configuration options.