A high-performance, in-place Radix Sort library for Dart and Flutter.
Fast. Efficient. Low-level sorting for number-intensive applications.
About • Features • Installation • Usage • Benchmarks • Contributing • License
Welcome to Radix Plus — a blazing-fast, in-place sorting library for Dart and Flutter.
Radix Plus provides a set of highly optimized, stable sorting algorithms that can be significantly faster than List.sort() for specific data types, especially large lists of numbers (int, double, and BigInt). It uses low-level byte manipulation to achieve top-tier performance, making it ideal for data-intensive applications, scientific computing, and real-time data processing.
- Multi-Type Support: Sorts
List<int>,List<double>, andList<BigInt>. - Stable Sort: Preserves the relative order of equal elements.
- Unified Integer API: A single function,
radixSortInt, handles both signed and unsigned integers. - Comprehensive Float Support:
radixSortDoublecorrectly handles positive/negative values, infinities, and zero.
- Parallel Sorting:
radixSortParallelUnsignedleverages multiple CPU cores using Isolates to sort very large lists even faster. - Memory Efficiency: Includes a buffer pooling mechanism (
reuseBuffer: true) to minimize GC pressure during frequent sorting tasks. - Zero-Copy Operations: Works directly on
TypedDatalists (Int32List,Float64List, etc.) to avoid unnecessary memory copies. - Adaptive Algorithms: Uses hybrid strategies (like switching to insertion sort for small sub-lists) for optimal performance across different data sizes.
-
Add this to your package's
pubspec.yamlfile:dependencies: radix_Plus: ^1.0.3 # Replace with the latest version
-
Install it from your terminal:
dart pub get
or
flutter pub get
Import the library and call the appropriate sorting function.
import 'package:radix_Plus/radix_Plus.dart';
// Sort a list of signed integers
final numbers = [40, -1, 900, -10, 0, 5];
radixSortInt(numbers); // Automatically handles signed integers
print(numbers); // [-10, -1, 0, 5, 40, 900]Use radixSortInt for both signed and unsigned integer lists.
// Sort a list of signed integers (ascending)
final signedNumbers = [40, -1, 900, -10, 0, 5];
radixSortInt(signedNumbers, ascending: true);
print(signedNumbers); // [-10, -1, 0, 5, 40, 900]
// Sort a list of unsigned integers (descending)
final unsignedNumbers = [40, 1, 900, 10, 5];
radixSortInt(unsignedNumbers, signed: false, ascending: false);
print(unsignedNumbers); // [900, 40, 10, 5, 1]Use radixSortDouble for List<double>.
final doubleNumbers = [10.5, -1.2, 900.0, -10.0, 0.0];
radixSortDouble(doubleNumbers);
print(doubleNumbers); // [-10.0, -1.2, 0.0, 10.5, 900.0]Use radixSortBigInt for List<BigInt>.
final bigIntNumbers = [
BigInt.parse('100000000000000000000'),
BigInt.from(-100),
BigInt.parse('-200000000000000000000'),
BigInt.zero,
];
radixSortBigInt(bigIntNumbers);
print(bigIntNumbers);For very large lists, radixSortParallelUnsigned can provide a significant speed boost.
Note: Parallel sorting is not available on the Web platform.
// A large list of numbers
final largeList = List.generate(1000000, (i) => 999999 - i);
// Sort it in parallel across multiple isolates
await radixSortParallelUnsigned(largeList);
print(largeList.first); // 0
print(largeList.last); // 999999Performance is the core feature of Radix Plus. Our algorithms are consistently faster than the standard List.sort() for large numerical datasets, often by a significant margin.
To ensure accuracy, the results below are the average of 10 separate benchmark runs on a standard development machine AMD Ryzen™ 7 5800H, each sorting a list of 1,000,000 random elements.
| Method | Average Time (ms) | Speedup vs. List.sort() |
|---|---|---|
List.sort() |
~1628 | 1.0x |
radixSortInt |
~288 | ~5.6x faster |
Typed lists (Int32List, Uint32List) achieve even better performance due to optimized memory layout.
| Method | Average Time (ms) | Speedup vs. List.sort() |
|---|---|---|
List.sort() |
~1347 | 1.0x |
radixSortInt32 |
~210 | ~6.4x faster |
| Method | Average Time (ms) | Speedup vs. List.sort() |
|---|---|---|
List.sort() |
~1344 | 1.0x |
radixSortUint32 |
~191 | ~7.0x faster |
Supports both List<double> and optimized Float64List, including correct handling of NaN values.
| Method | Average Time (ms) | Speedup vs. List.sort() |
|---|---|---|
List.sort() |
~2471 | 1.0x |
radixSortDouble |
~571 | ~4.3x faster |
| Method | Average Time (ms) | Speedup vs. List.sort() |
|---|---|---|
List.sort() |
~1493 | 1.0x |
radixSortFloat64 |
~387 | ~3.9x faster |
radixSortFloat64WithNaN |
~311 | ~4.8x faster |
Efficient sorting for arbitrary-precision integers.
| Method | Average Time (ms) | Speedup vs. List.sort() |
|---|---|---|
List.sort() |
~6454 | 1.0x |
radixSortBigInt |
~1092 | ~5.9x faster |
radixSortBigIntWithRange |
~6654 | ~0.97x |
ℹ️
radixSortBigIntWithRangeis optimized for specific range-based scenarios, not general-purpose sorting.
Leverages Dart Isolates to unlock massive speedups on multi-core CPUs.
| Method | Average Time (ms) | Speedup vs. List.sort() |
|---|---|---|
List.sort() (Standard int) |
~1628 | 1.0x |
radixSortParallelUnsigned |
~29 | ~56.5x faster |
radixSortParallelSigned |
~31 | ~52.2x faster |
| Technology | Description |
|---|---|
| 🧠 Dart | dart.dev — The core language for the library. |
| ⚡ Isolates | dart:isolate — Used for parallel sorting to leverage multiple CPU cores. |
| 💾 TypedData | dart:typed_data — Used for low-level, efficient memory manipulation. |
| 🧪 benchmark_harness | A framework for creating and running performance benchmarks. |
Contributions are welcome! Here’s how to get started:
- Fork the repository.
- Create a new branch:
git checkout -b feature/YourFeature - Commit your changes:
git commit -m "Add amazing feature" - Push to your branch:
git push origin feature/YourFeature - Open a pull request.
💡 Please read our Contributing Guidelines and open an issue first for major feature ideas or changes.
This project is licensed under the GPL-V3.0 License. See the LICENSE file for full details.
Made with ❤️ by MostafaSensei106
