Adaptive stable sorting for large Python integer lists
Project description
BielSort
Early release software: the public API is stable for the 0.1 series, while performance heuristics may continue to evolve before 1.0.
BielSort is an adaptive, stable sorting library for CPython. It specializes in
large list[int] workloads while preserving Python-compatible behavior through
Timsort fallbacks.
The native core selects among:
- stable counting sort for large, dense signed 64-bit integer ranges;
- stable LSD radix sort with 11-bit digits for other signed 64-bit integers;
- CPython's Timsort for small, nearly monotonic, non-integer, arbitrary-size
integer,
key=, andreverse=workloads.
It provides separate APIs to compete fairly with both sorted() and
list.sort().
Status
- Development stage: beta (
0.1.0) - Runtime: CPython 3.9+
- Native language: C
- Fast path: exact Python integers in signed 64-bit range
- Fallback: Python-compatible stable sorting
- License: MIT
- CI: CPython 3.9-3.14 on Linux, Windows, and macOS
- Wheels: Linux x86-64, Windows x86/x64, and macOS Intel/Apple Silicon
Installation
Install the stable release from PyPI:
python -m pip install bielsort==0.1.0
The package has no runtime dependencies.
From the project directory:
python -m pip install .
For development:
python -m pip install -e .
python -m unittest discover -s tests -v
Usage
from bielsort import sort, sort_in_place
numbers = [8, -4, 10, 3, -4]
# Like sorted(): returns a new list.
ordered = sort(numbers)
# Like list.sort(): mutates the list and returns None.
sort_in_place(numbers)
key= and reverse= are supported and deliberately use the Timsort fallback:
records = [{"score": 8}, {"score": 3}]
ordered = sort(records, key=lambda item: item["score"], reverse=True)
The diagnostic APIs expose the selected strategy:
from bielsort import (
sort_in_place_with_strategy,
sort_with_strategy,
)
ordered, strategy = sort_with_strategy([3, 1, 2] * 10_000)
print(strategy)
The earlier biel_sort* names remain compatibility aliases for the 0.1
series. New code should use the four sort* names shown above.
Complexity
For n elements, numeric range k, and p varying radix digits:
| Strategy | Time | Additional memory |
|---|---|---|
| Native counting | Θ(n + k) |
Θ(n + k) |
| Native radix | Θ(pn), 1 <= p <= 6 |
Θ(n) |
| Timsort fallback | best Θ(n), worst Θ(n log n) |
O(n) |
For signed 64-bit integers, p is bounded by six and does not grow with n.
Local benchmark snapshot
Median of five executions on the original Linux development machine with one million elements:
| Input | sorted() |
Biel new | Gain | .sort() |
Biel in-place | Gain |
|---|---|---|---|---|---|---|
| dense range | 0.20259 s | 0.04713 s | 4.30x | 0.18953 s | 0.03203 s | 5.92x |
| random int32 | 0.24079 s | 0.05009 s | 4.81x | 0.23666 s | 0.03796 s | 6.23x |
| random int64 | 0.26314 s | 0.07535 s | 3.49x | 0.26081 s | 0.06028 s | 4.33x |
| 1024-bit integers | 0.33237 s | 0.33417 s | 0.99x | 0.30962 s | 0.31676 s | 0.98x |
| nearly sorted | 0.01691 s | 0.01730 s | 0.98x | 0.01139 s | 0.01097 s | 1.04x |
These numbers are not universal guarantees. See
benchmarks/README.md for the benchmark policy and
reproduction commands. The versioned
2026-07-30 Linux report
also records peak memory and NumPy comparisons. A separate
Counting Sort optimization report
records the measured 36%-45% peak-memory reduction.
Scope and limitations
- The accelerated path currently supports exact
intobjects in signed 64-bit range. - Floats, strings, subclasses, mixed types, huge integers,
key=, andreverse=use Timsort. - The project is CPython-specific because its native module uses the CPython C API.
- Prebuilt wheels currently target Linux x86-64, Windows x86/x64, and macOS Intel/Apple Silicon. Other platforms may need to build from source and are not yet part of the validated compatibility matrix.
bielsortis the canonical import. The olderbielsort_nativeimport remains available for compatibility.- Counting and radix paths allocate native buffers proportional to input size.
- BielSort is a hybrid implementation based on established sorting techniques; it should not be presented as a newly invented sorting theory.
Development
- Contributing guide
- Architecture
- Security policy
- Roadmap
- Changelog
- Release guide
- TestPyPI release candidate
- Benchmark results
- Counting Sort memory optimization
License
Copyright (c) 2026 Gabriel Fernandes Farah Elias.
BielSort is distributed under the MIT License.
Português
O BielSort é uma biblioteca de ordenação estável e adaptativa para CPython. Ela acelera listas grandes de inteiros usando Counting Sort ou Radix Sort em C e recorre ao Timsort nos casos em que o algoritmo padrão é mais adequado.
A primeira versão pública estável é a 0.1.0, distribuída sob a licença MIT.
A compilação e os testes de wheels foram validados no CI para CPython 3.9 até
3.14 em Linux, Windows, macOS Intel e macOS Apple Silicon.
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