v1.1.0: extend binary matrix to CPython 3.10/3.11/3.13 on Linux and Windows

- Linux x86_64: add cp310, cp311, cp313 (.so), built in conda-forge envs.
- Windows AMD64: add cp310, cp311, cp313 (.pyd), built with MSVC v14.50.
- All eight binaries verified to produce identical numerical output.
- README compatibility table + build provenance updated.
- macOS still deferred.

CHANGELOG.md

@@ -9,6 +9,32 @@ release `MAJOR.MINOR.PATCH` increments
 - `MINOR` on backwards-compatible feature additions,
 - `PATCH` on backwards-compatible bug fixes.
 
+## [1.1.0] - 2026-05-10
+
+Binary matrix expanded to four CPython versions on both supported
+platforms.
+
+### Added
+
+- Pre-compiled Linux x86_64 binaries for **CPython 3.10, 3.11, 3.13**
+  (`sem_core12.cpython-3{10,11,13}-x86_64-linux-gnu.so`).  Built in
+  isolated conda-forge environments with conda-forge gcc, same
+  OpenMP and optimisation flags as the cp312 binary.
+- Pre-compiled Windows AMD64 binaries for **CPython 3.10, 3.11, 3.13**
+  (`sem_core12.cp3{10,11,13}-win_amd64.pyd`).  Built with MSVC v14.50
+  against the matching CPython installed via `winget`.
+
+### Verified
+
+- All eight binaries (4 Linux + 4 Windows) produce identical numerical
+  output for the same fixed-seed input on `batch_max_similarity`.
+
+### Compatibility notes
+
+- macOS is still not provided in this release.  Contact
+  `sales@sevana.biz` if you need a macOS build.
+- numpy requirement unchanged: `numpy >= 1.23`.
+
 ## [1.0.0] - 2026-05-09
 
 First public release.

README.md

@@ -6,70 +6,53 @@ install time.
 
 ## What is this for?
 
-`sem_cython12` is a small, focused toolbox of fast C-level routines
+For an introduction to SEM (Similarity Energy Model) and how
-exposed through a thin numpy wrapper.  It is not a general-purpose
+`sem_cython12` fits in, see:
-numerical library; it accelerates three specific jobs that are
-awkward or slow to do in pure numpy once `N` reaches the thousands:
 
-1. **Similarity / distance over batches of vectors.**  Full
+- [`docs/SEM_Overview.md`](./docs/SEM_Overview.md) — non-internal
-   pairwise distance matrices, nearest-neighbour distances, and
+  introduction to SEM, what it does, and how this library fits in.
-   kernel-based `[0, 1]` similarity scores of a query set against
+- [`docs/SEM_Mathematical_Apparatus.md`](./docs/SEM_Mathematical_Apparatus.md)
-   one or many reference sets.  Useful for nearest-neighbour
+  — capabilities-level description of the operators and engines
-   search, kernel-density-style scoring, and "how close is each
+  exposed by the library.
-   query to this concept?" lookups.
-2. **Multi-objective ("best-tradeoff") filtering of score matrices.**
-   Given a matrix of `N` candidates × `k` criteria, select the
-   rows on the Pareto frontier, isolate rows that only spike on a
-   single criterion, and recover the rows that contribute
-   meaningfully across several criteria - candidates a naive
-   sum-of-scores ranker would miss.
-3. **An incremental aggregation primitive** for streaming
-   clustering / frontier-expansion algorithms: a fused bulk update
-   that, given `F` running summaries (centre + radius) and `A`
-   new contributions, produces all `F·A` updated summaries in one
-   parallel pass.
-
-The kernels release the GIL, scale near-linearly to ~8 OpenMP
-threads on commodity x86, and operate on shared-memory numpy
-arrays with no inter-process serialisation.  The Python wrapper
-handles contiguous-float64 casting and degrades loudly (via
-`available()` / `backend()` plus `RuntimeError`) when the compiled
-extension cannot load on the host - there is no slow pure-Python
-fallback path.
-
-The [`demos/`](./demos/) directory contains three runnable
-end-to-end examples (Iris boundary discovery, parameter-free
-anomaly detection, multi-criteria candidate selection) that
-exercise these three jobs against well-known baselines.
 
 ## Contents
 
-- `sem_cython12/sem_core12.cpython-312-x86_64-linux-gnu.so` -
+- `sem_cython12/sem_core12.cpython-3{10,11,12,13}-x86_64-linux-gnu.so` -
-  compiled extension (Linux, CPython 3.12, x86_64).
+  compiled extensions (Linux, x86_64) for CPython 3.10 / 3.11 / 3.12 / 3.13.
-- `sem_cython12/sem_core12.cp312-win_amd64.pyd` -
+- `sem_cython12/sem_core12.cp3{10,11,12,13}-win_amd64.pyd` -
-  compiled extension (Windows, CPython 3.12, AMD64).
+  compiled extensions (Windows, AMD64) for CPython 3.10 / 3.11 / 3.12 / 3.13.
 - `sem_cython12/wrapper.py` - Python API.
 - `sem_cython12/__init__.py` - package entry.
 
+Python's import system selects the correct binary for the running
+interpreter automatically — install the whole package and the right
+`.so` / `.pyd` is picked up by ABI tag.
+
 ## Compatibility
 
-| Platform        | Architecture | Python    | Runtime requirements        |
+| Platform        | Architecture | Python                 | Runtime requirements        |
-|-----------------|--------------|-----------|-----------------------------|
+|-----------------|--------------|------------------------|-----------------------------|
-| Linux           | x86_64       | CPython 3.12 | glibc >= 2.31, libgomp   |
+| Linux           | x86_64       | CPython 3.10/3.11/3.12/3.13 | glibc >= 2.31, libgomp   |
-| Windows 10/11   | AMD64        | CPython 3.12 | vcomp (ships with Windows) |
+| Windows 10/11   | AMD64        | CPython 3.10/3.11/3.12/3.13 | vcomp (ships with Windows) |
-| macOS           | -            | -         | not provided (contact sales@sevana.biz) |
+| macOS           | -            | -                      | not provided (contact sales@sevana.biz) |
 
 Single Python dependency: `numpy >= 1.23` (see `requirements.txt`).
 
 ## How the binaries were built
 
-- **Linux (`*.so`)**: gcc 13.3, OpenMP via `libgomp`, flags
+- **Linux (`*.so`), cp312**: system gcc 13.3 on Ubuntu, OpenMP via
-  `-O3 -ffast-math -march=native -fopenmp`.
+  `libgomp`, flags `-O3 -ffast-math -march=native -fopenmp`.
-- **Windows (`*.pyd`)**: MSVC v14.50 (Visual Studio Build Tools 2026),
+- **Linux (`*.so`), cp310 / cp311 / cp313**: conda-forge gcc inside
-  OpenMP via `vcomp`, flags `/O2 /openmp`.
+  isolated `python=3.10/3.11/3.13` envs (clean, system-Python-free
+  build), same OpenMP and optimisation flags.
+- **Windows (`*.pyd`), all four versions**: MSVC v14.50 (Visual Studio
+  Build Tools 2026), OpenMP via `vcomp`, flags `/O2 /openmp`. Each
+  built against the matching CPython interpreter installed via
+  `winget`.
 
-Both binaries target CPython 3.12 (cp312) ABI.  No other Python
+All eight binaries pass the same numerical smoke test
-version is supported in this release.
+(`batch_max_similarity` over fixed-seed data) and produce identical
+output to within float64 round-off.
 
 ## Install
 
@@ -147,15 +130,6 @@ internally cast to contiguous `float64`.  Outputs are numpy arrays.
 
 See the wrapper docstrings for exact semantics of each function.
 
-## Documentation
-
-- [`docs/SEM_Overview.md`](./docs/SEM_Overview.md) — non-internal
-  introduction to SEM (Similarity Energy Model), what it does, and
-  how the `sem_cython12` library fits in.
-- [`docs/SEM_Mathematical_Apparatus.md`](./docs/SEM_Mathematical_Apparatus.md)
-  — capabilities-level description of the operators and engines
-  exposed by the library.
-
 ## Demos
 
 Three runnable demos live in [`demos/`](./demos/):