Changelog

All notable changes to arrayops will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

Unreleased

Planned

[1.0.0] - 2025-01-01

Added

  • Production-ready 1.0.0 release

  • API stability guarantees documented (see API_STABILITY.md)

  • Comprehensive security documentation

  • Migration guide from 0.x to 1.0.0 (see MIGRATION.md)

  • Deprecation tracking and migration plans (see DEPRECATION_NOTES.md)

Changed

  • Development status updated from “Alpha” to “Production/Stable”

  • Improved error messages for better debugging

  • Enhanced documentation across all modules

Documentation

  • Added comprehensive API stability documentation

  • Created migration guide for upgrading from 0.x versions

  • Documented deprecation warnings and migration plans

  • Updated security documentation with detailed guarantees

  • Enhanced README with 1.0.0 release information

Testing

  • Maintained 100% test coverage (Python and Rust)

  • Comprehensive integration tests for large datasets

  • Security test suite covering input validation, DoS resistance, and overflow handling

  • Performance regression tests to ensure optimizations are maintained

Code Quality

  • Comprehensive code review completed

  • Unsafe code audit completed (only dead code uses unsafe, well-documented)

  • API stability review completed

  • Thread safety verified for parallel operations

  • Memory safety verified through Rust’s type system

Security

  • Security review completed

  • Buffer access patterns verified safe (using PyO3 safe APIs)

  • Input validation comprehensive and tested

  • Error handling secure (no information leakage)

Technical Details

  • PyO3 0.24 with extension-module feature

  • Rust 2021 edition

  • Python 3.8+ support

  • Optional parallel execution support (via parallel feature)

  • SIMD optimization infrastructure (via simd feature)

Notes

  • No breaking changes from 0.4.x to 1.0.0

  • All 0.4.x code should work unchanged

  • See MIGRATION.md for migration guidance

  • See API_STABILITY.md for API stability guarantees

0.3.0 - 2024-01-XX

Added

  • Statistical Operations (6 functions)

    • mean(arr) -> float - Arithmetic mean calculation

      • Always returns float, even for integer arrays

      • ~50x faster than computing mean in pure Python

    • min(arr) -> scalar - Minimum value

      • Returns type matching array element type

      • ~30x faster than Python’s built-in min() for large arrays

    • max(arr) -> scalar - Maximum value

      • Returns type matching array element type

      • ~30x faster than Python’s built-in max() for large arrays

    • std(arr) -> float - Population standard deviation

      • Uses formula: sqrt(sum((x - mean)^2) / n)

      • ~40x faster than computing std in pure Python

    • var(arr) -> float - Population variance

      • Uses formula: sum((x - mean)^2) / n

      • ~40x faster than computing variance in pure Python

    • median(arr) -> scalar - Median value

      • For even-length arrays, returns lower median

      • Returns type matching array element type

      • ~20x faster than computing median in pure Python

  • Element-wise Operations (4 functions)

    • add(arr1, arr2) -> array - Element-wise addition

      • Requires arrays of same length

      • Returns new array (preserves input type)

      • ~30x faster than Python loops

    • multiply(arr1, arr2) -> array - Element-wise multiplication

      • Requires arrays of same length

      • Returns new array (preserves input type)

      • ~30x faster than Python loops

    • clip(arr, min_val, max_val) -> None - In-place clipping to range

      • Modifies array elements to be within [min_val, max_val]

      • ~25x faster than Python loops

    • normalize(arr) -> None - In-place normalization to [0, 1]

      • Uses min-max normalization: (x - min) / (max - min)

      • Requires non-empty array with min != max

      • ~25x faster than computing normalization in pure Python

  • Array Manipulation (3 functions)

    • reverse(arr) -> None - In-place reversal of array elements

      • Uses standard reversal algorithm

      • ~30x faster than Python’s arr.reverse() for large arrays

    • sort(arr) -> None - In-place sorting (ascending order)

      • Uses Rust’s stable sort algorithm

      • ~10x faster than Python’s arr.sort() for large arrays

    • unique(arr) -> array - Return unique elements (sorted)

      • Returns new array with unique elements in sorted order

      • Preserves input type (NumPy if NumPy input, array.array otherwise)

      • ~20x faster than Python’s list(set(arr)) for large arrays

  • All new operations support array.array, numpy.ndarray (1D, contiguous), and memoryview inputs

  • Comprehensive test coverage for all new functions (50+ new tests)

  • Complete API documentation and examples for all new functions

Testing

  • Added 50+ comprehensive tests for Phase 4 functions

  • Tests cover all numeric types, edge cases, error conditions, and NumPy inputs

  • 100% code coverage maintained for all new code

Documentation

  • Updated API reference with complete documentation for all 13 new functions

  • Added practical examples for statistical, element-wise, and array manipulation operations

  • Updated README with Phase 4 features

  • Updated ROADMAP to mark Phase 4 as completed

0.2.0 - 2024-01-XX

Added

  • map(arr, fn) -> array.array - Apply function to each element, return new array

    • Supports Python callables (lambda, functions)

    • Type preservation (input type determines output type)

    • ~20x faster than Python list comprehensions

  • map_inplace(arr, fn) -> None - Apply function in-place

    • Modify array elements without allocation

    • Same callable support as map

    • ~15x faster than Python loops

  • filter(arr, predicate) -> array.array - Return new array with filtered elements

    • Support for Python callable predicates

    • Preserve original array type

    • Handle empty results gracefully

    • ~15x faster than Python list comprehensions

  • reduce(arr, fn, initial=None) -> Any - Fold array with binary function

    • Support for Python callables

    • Optional initial value

    • Type inference for return value

    • ~25x faster than Python functools.reduce

Performance

  • All new operations provide significant speedups over pure Python

  • Zero-copy buffer access maintained for all operations

  • Memory-efficient in-place operations available

Documentation

  • Updated API reference with new operations

  • Added examples for map, filter, and reduce operations

  • Updated README with usage examples

  • Added comprehensive examples in documentation

Testing

  • 75 comprehensive tests (up from 45)

  • 30 new tests for Phase 1 operations

  • 100% code coverage maintained

  • Tests cover all numeric types, edge cases, and error conditions

Technical Details

  • Python callable support via PyO3

  • Type-safe conversions between Python and Rust types

  • Comprehensive error handling and validation

0.1.0 - 2024-01-XX

Added

  • Initial release of arrayops

  • sum() function for computing sum of array elements

    • Supports all numeric array types (b, B, h, H, i, I, l, L, f, d)

    • Returns int for integer arrays, float for float arrays

    • Handles empty arrays gracefully (returns 0)

  • scale() function for in-place array scaling

    • Supports all numeric array types

    • Modifies arrays in-place (no allocation)

    • Handles empty arrays gracefully

  • Zero-copy buffer access via Python buffer protocol

  • Type stubs for mypy type checking

  • Comprehensive test suite with 100% coverage

  • Full documentation

Performance

  • sum() operation: ~100x faster than Python’s built-in sum() for large arrays

  • scale() operation: ~50x faster than Python loops for large arrays

  • Zero memory overhead for operations

Documentation

  • README with quick start guide

  • API reference

  • Examples and use cases

  • Design document

  • Roadmap

Testing

  • 100% code coverage (Python and Rust)

  • Tests for all numeric types

  • Edge case testing (empty arrays, single elements)

  • Error handling tests

  • Performance tests

Technical Details

  • Built with PyO3 for Python-Rust interop

  • Uses maturin for packaging

  • Supports Python 3.8+

  • Requires Rust 1.70+

Types of Changes

  • Added for new features

  • Changed for changes in existing functionality

  • Deprecated for soon-to-be removed features

  • Removed for now removed features

  • Fixed for any bug fixes

  • Security for vulnerability fixes