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Merged
vlad-perevezentsev merged 3 commits into from
Oct 20, 2026
Merged

Prepare for 1.6.0 release #200

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791143a
Finalized the CHANGELOG
vlad-perevezentsev Oct 20, 2026
a5736ac
Bump the version
vlad-perevezentsev Oct 20, 2026
140bfdf
Clarify stream changes and add gh-159 fixes to the CHANGELOG
vlad-perevezentsev Oct 20, 2026
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10 changes: 6 additions & 4 deletions CHANGELOG.md
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Expand Up @@ -4,7 +4,7 @@ All notable changes to this project will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).

# [dev] (MM/DD/YYYY)
## [1.6.0] (10/20/2026)

### Added
* Added support for `array_like` (broadcastable) `low`/`high` bounds in `randint` [gh-168](https://github.com/IntelPython/mkl_random/pull/168)
Expand All @@ -21,7 +21,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
* `uniform` with array-valued bounds may return `high` due to floating-point rounding [gh-171](https://github.com/IntelPython/mkl_random/pull/171)
* Pinned Cython in the Coverity Scan workflow so generated code stays stable between scans, and added `coverity/README.md` documenting the known Cython-boilerplate false positives and the scan review checklist [gh-164](https://github.com/IntelPython/mkl_random/pull/164)
* Sped up `randint` for power-of-two ranges at or above `INT_MAX` [gh-172](https://github.com/IntelPython/mkl_random/pull/172)
* The random streams for power-of-two `randint` ranges at or above `INT_MAX` have changed: with a fixed seed these now produce different (but equally valid) samples. All other streams are unaffected. [gh-172](https://github.com/IntelPython/mkl_random/pull/172)
* The random streams for power-of-two `randint` ranges at or above `INT_MAX` have changed: with a fixed seed these now produce different (but equally valid) samples [gh-172](https://github.com/IntelPython/mkl_random/pull/172)
* Sped up `randint` for `bool`, `uint8`, `int8`, `uint16` and `int16`; generated values are unchanged [gh-172](https://github.com/IntelPython/mkl_random/pull/172)
* Raised the minimum build-time `Cython` requirement to `3.1.0`, the first release providing the `freethreading_compatible` directive [gh-159](https://github.com/IntelPython/mkl_random/pull/159)
* Extended the `memcpy`-based fast path of `shuffle` to multi-dimensional `ndarray` inputs whose first-axis items are contiguous, which is also much faster than the previous buffered path [gh-159](https://github.com/IntelPython/mkl_random/pull/159)
Expand All @@ -31,7 +31,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
* Replaced the `mklrand_py_helper.h` shim with `cpython.bytes` cimports and dropped the no-op `__future__` import, since the project requires Python 3.10+ [gh-192](https://github.com/IntelPython/mkl_random/pull/192)
* `negative_binomial` now rejects `p == 0`, which MKL does not support, with a `ValueError`; the documented range of `p` is `(0, 1]` [gh-195](https://github.com/IntelPython/mkl_random/pull/195)
* `poisson`, `negative_binomial`, `geometric` and `logseries` now reject `NaN` parameters with a `ValueError`, as NumPy does, instead of passing them to MKL [gh-195](https://github.com/IntelPython/mkl_random/pull/195)
* `geometric` samples are now one larger than before for every `p`, so results for a fixed seed change; `geometric(p) - 1` reproduces the old values. All other streams are unaffected [gh-196](https://github.com/IntelPython/mkl_random/pull/196)
* `geometric` samples are now one larger than before for every `p` whose result fits in `int32`, so results for a fixed seed change; `geometric(p) - 1` reproduces the old values for them [gh-196](https://github.com/IntelPython/mkl_random/pull/196)

### Fixed
* Fixed `poisson` with a scalar `lam == 0` returning uninitialized memory as random values, since MKL requires `lam > 0`. The same applied to array-valued `lam` with `method="PTPE"`. Both now return zeros, as the default array path and NumPy already did [gh-195](https://github.com/IntelPython/mkl_random/pull/195)
Expand All @@ -49,6 +49,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
* Fixed `multinomial` under-filling large outputs by decrementing its chunk counter by elements instead of draws [gh-172](https://github.com/IntelPython/mkl_random/pull/172)
* Fixed a memory leak in `set_state`, which leaked the previous MKL stream on every call [gh-159](https://github.com/IntelPython/mkl_random/pull/159)
* Fixed a memory leak in `logseries`, which leaked a temporary buffer on every call [gh-159](https://github.com/IntelPython/mkl_random/pull/159)
* Fixed `set_state` replacing the generator state before raising `ValueError` when the buffer does not match the algorithm name; the state is now left unchanged [gh-159](https://github.com/IntelPython/mkl_random/pull/159)
* Fixed `get_state` writing past its buffer when another thread reseeded the generator with a different `brng` at the same time, and a deadlock when a `seed` value or a `shuffle` element called back into the same generator [gh-159](https://github.com/IntelPython/mkl_random/pull/159)
* Fixed `randint` with scalar bounds above `INT_MAX`, `tomaxint` and `bytes` returning uninitialized data for `WH`, `MCG31`, `R250` and `MRG32K3A`, which lack `viRngUniformBits` support [gh-175](https://github.com/IntelPython/mkl_random/pull/175)
* Fixed 64-bit integer generation returning zeros or crashing with `PHILOX4X32X10` and `ARS5` for requests of `2**30` elements or more [gh-175](https://github.com/IntelPython/mkl_random/pull/175)
* Fixed `randint_untyped` raising `OverflowError` for bounds outside the C `long` range, e.g. `2**40` on Windows [gh-176](https://github.com/IntelPython/mkl_random/pull/176)
Expand All @@ -57,7 +59,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
* Fixed the `tomaxint` example, which compared against the Python 2 `sys.maxint` [gh-192](https://github.com/IntelPython/mkl_random/pull/192)
* Fixed the remaining Python 2 references in the `random_sample`, `random_integers` and `randint` docstrings and in the `zipf` implementation comment: the `<type '...'>` reprs, `np.int` and `sys.maxint` [gh-192](https://github.com/IntelPython/mkl_random/pull/192)
* Fixed the `random_integers` docstring, which described the result as `numpy.int_` rather than a C `long`, documented the wrong scalar return type, and passed a float `size` that no longer works [gh-192](https://github.com/IntelPython/mkl_random/pull/192)
* Fixed `geometric` returning the number of failures before the first success instead of the number of trials, which contradicted its own docstring and NumPy. The support now starts at `1`, `P(1)` is `p` and the mean is `1 / p` [gh-196](https://github.com/IntelPython/mkl_random/pull/196)
* Fixed `geometric` returning the number of failures before the first success instead of the number of trials, which contradicted its own docstring and NumPy. The support now starts at `1`, `P(1)` is `p` and the mean is `1 / p`. The samples are still `int32`, unlike NumPy's `int64`, and overflow for very small `p` [gh-196](https://github.com/IntelPython/mkl_random/pull/196)

### Removed
* Removed the `python-gil` constraint from the conda recipes, which pinned `mkl_random` to GIL-enabled Python 3.14 builds [gh-159](https://github.com/IntelPython/mkl_random/pull/159)
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2 changes: 1 addition & 1 deletion docs/source/conf.py
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Expand Up @@ -9,7 +9,7 @@
project = "mkl_random"
copyright = "2017-2026, Intel Corp."
author = "Intel Corp."
release = "1.6.0dev0"
release = "1.6.0"

@antonwolfy antonwolfy Oct 20, 2026

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Nit, could be a follow-up: the version is kept by hand both here and in mkl_random/_version.py. meson.build already reads _version.py; conf.py could do the same, so future version bumps only touch one file.

@vlad-perevezentsev vlad-perevezentsev Oct 20, 2026 •
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Added a Fixed entry for the two gh-159 bugs that also affect GIL-enabled builds: the get_state buffer overflow when racing a reseed with another brng, and the re-entrancy deadlocks in seed/shuffle. The lock serialization of size=None draws, multinomial, multinormal_cholesky etc. only matters on free-threaded builds: 1.5.0 always ran with the GIL, so those calls were already serialized, and that part is covered by the free-threading entry.

Your nit will be done in the follow-up PR after the release


# -- General configuration ---------------------------------------------------
# https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration
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2 changes: 1 addition & 1 deletion mkl_random/_version.py
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@@ -1 +1 @@
__version__ = "1.6.0dev0"
__version__ = "1.6.0"
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