* Upgrade presets for CPython 3.14.6, NumPy 2.5.0, SciPy 1.18.0

Author: saudet

.github/actions/deploy-macosx/action.yml

@@ -24,7 +24,7 @@ runs:
           sudo rm -Rf /Library/Developer/CommandLineTools/SDKs/MacOSX10*
         fi
 
-        brew uninstall --force --ignore-dependencies cmake gcc gcc@7 gcc@8 gcc@9 gcc@10 gcc@11 gcc@12 gcc@13 gcc@14 little-cms2 maven openblas r
+        brew uninstall --force --ignore-dependencies cmake gcc gcc@7 gcc@8 gcc@9 gcc@10 gcc@11 gcc@12 gcc@13 gcc@14 gcc@15 gcc@16 little-cms2 maven openblas r
         brew install --overwrite boost ccache swig autoconf-archive automake libomp libtool libusb ant nasm xz pkg-config sdl2 gpg1 bison flex perl ragel binutils gradle gmp isl libmpc mpfr pcre ssdeep yajl ninja meson pkgconf
 
         FORMULAE=()

CHANGELOG.md

@@ -8,7 +8,7 @@
  * Add new `SampleOnnxMNIST` in samples for TensorRT ([pull #1742](https://github.com/bytedeco/javacpp-presets/pull/1742))
  * Fix loading issues with `libomp.dylib` and `libiomp5.dylib` for DNNL and PyTorch on Mac
  * Include `model_package_loader.h` header file in presets for PyTorch ([issue #1729](https://github.com/bytedeco/javacpp-presets/issues/1729))
- * Upgrade presets for FFmpeg 8.1.1, MKL 2026.0.0, DNNL 3.12.1, OpenBLAS 0.3.33, CUDA 13.2.1, cuDNN 9.21.1.3, NCCL 2.30.4, nvCOMP 5.2.0.10, OpenCL 3.1.1, FFTW 3.3.11, CPython 3.14.5, NumPy 2.4.6, SciPy 1.17.1, LLVM 22.1.7, PyTorch 2.12.0, TensorFlow Lite 2.21.0, TensorRT 10.16.1.11, Triton Inference Server 2.68.0, ONNX 1.21.0, ONNX Runtime 1.26.0 ([pull #1753](https://github.com/bytedeco/javacpp-presets/pull/1753)), and their dependencies
+ * Upgrade presets for FFmpeg 8.1.1, MKL 2026.0.0, DNNL 3.12.1, OpenBLAS 0.3.33, CUDA 13.2.1, cuDNN 9.21.1.3, NCCL 2.30.4, nvCOMP 5.2.0.10, OpenCL 3.1.1, FFTW 3.3.11, CPython 3.14.6, NumPy 2.5.0, SciPy 1.18.0, LLVM 22.1.7, PyTorch 2.12.0, TensorFlow Lite 2.21.0, TensorRT 10.16.1.11, Triton Inference Server 2.68.0, ONNX 1.21.0, ONNX Runtime 1.26.0 ([pull #1753](https://github.com/bytedeco/javacpp-presets/pull/1753)), and their dependencies
  * Compile classes with `parameters` bumping minimum requirements to Java SE 8 and Android 7.0 ([issue #1739](https://github.com/bytedeco/javacpp-presets/issues/1739))
 
 ### February 22, 2026 version 1.5.13

README.md

@@ -207,8 +207,8 @@ Each child module in turn relies by default on the included [`cppbuild.sh` scrip
  * FFTW 3.3.11  http://www.fftw.org/download.html
  * GSL 2.8  http://www.gnu.org/software/gsl/#downloading
  * CPython 3.14.x  https://www.python.org/downloads/
- * NumPy 2.4.x  https://github.com/numpy/numpy
- * SciPy 1.17.x  https://github.com/scipy/scipy
+ * NumPy 2.5.x  https://github.com/numpy/numpy
+ * SciPy 1.18.x  https://github.com/scipy/scipy
  * Gym 0.26.x  https://github.com/openai/gym
  * LLVM 22.1.x  http://llvm.org/releases/download.html
  * libffi 3.5.x  https://github.com/libffi/libffi

cpython/cppbuild.sh

@@ -7,8 +7,8 @@ if [[ -z "$PLATFORM" ]]; then
     exit
 fi
 
-OPENSSL=openssl-3.5.6
-CPYTHON_VERSION=3.14.5
+OPENSSL=openssl-3.5.7
+CPYTHON_VERSION=3.14.6
 download https://www.openssl.org/source/$OPENSSL.tar.gz $OPENSSL.tar.gz
 download https://www.python.org/ftp/python/$CPYTHON_VERSION/Python-$CPYTHON_VERSION.tgz Python-$CPYTHON_VERSION.tgz
 

cpython/platform/pom.xml

@@ -12,7 +12,7 @@
 
   <groupId>org.bytedeco</groupId>
   <artifactId>cpython-platform</artifactId>
-  <version>3.14.5-${project.parent.version}</version>
+  <version>3.14.6-${project.parent.version}</version>
   <name>JavaCPP Presets Platform for CPython</name>
 
   <properties>

cpython/pom.xml

@@ -11,7 +11,7 @@
 
   <groupId>org.bytedeco</groupId>
   <artifactId>cpython</artifactId>
-  <version>3.14.5-${project.parent.version}</version>
+  <version>3.14.6-${project.parent.version}</version>
   <name>JavaCPP Presets for CPython</name>
 
   <dependencies>

cpython/src/gen/java/org/bytedeco/cpython/global/python.java

@@ -191,12 +191,12 @@ There is also (independent) API version information in modsupport.h.
 /*--start constants--*/
 public static final int PY_MAJOR_VERSION =        3;
 public static final int PY_MINOR_VERSION =        14;
-public static final int PY_MICRO_VERSION =        5;
+public static final int PY_MICRO_VERSION =        6;
 public static final int PY_RELEASE_LEVEL =        PY_RELEASE_LEVEL_FINAL;
 public static final int PY_RELEASE_SERIAL =       0;
 
 /* Version as a string */
-public static final String PY_VERSION =              "3.14.5";
+public static final String PY_VERSION =              "3.14.6";
 /*--end constants--*/
 
 

numpy/README.md

@@ -9,7 +9,7 @@ Introduction
 ------------
 This directory contains the JavaCPP Presets module for:
 
- * NumPy 2.4.6  http://www.numpy.org/
+ * NumPy 2.5.0  http://www.numpy.org/
 
 Please refer to the parent README.md file for more detailed information about the JavaCPP Presets.
 
@@ -48,7 +48,7 @@ We can use [Maven 3](http://maven.apache.org/) to download and install automatic
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>numpy-platform</artifactId>
-            <version>2.4.6-1.5.14-SNAPSHOT</version>
+            <version>2.5.0-1.5.14-SNAPSHOT</version>
         </dependency>
 
         <!-- Additional dependencies to use bundled full version of MKL -->

numpy/cppbuild.sh

@@ -7,7 +7,7 @@ if [[ -z "$PLATFORM" ]]; then
     exit
 fi
 
-NUMPY_VERSION=2.4.6
+NUMPY_VERSION=2.5.0
 download https://github.com/numpy/numpy/releases/download/v$NUMPY_VERSION/numpy-$NUMPY_VERSION.tar.gz numpy-$NUMPY_VERSION.tar.gz
 
 mkdir -p $PLATFORM
@@ -85,7 +85,7 @@ fi
 export PYTHONPATH="$PYTHON_INSTALL_PATH"
 mkdir -p "$PYTHON_INSTALL_PATH"
 
-TOOLS="setuptools==67.6.1 cython==3.0.10"
+TOOLS="setuptools==67.6.1 cython==3.2.6"
 if ! $PYTHON_BIN_PATH -m pip install --target=$PYTHON_LIB_PATH $TOOLS; then
     echo "extra_link_args = -lgfortran"           >> site.cfg
     chmod +x "$CPYTHON_HOST_PATH/bin/python3.14"
@@ -128,7 +128,7 @@ case $PLATFORM in
         ;;
     linux-x86)
         # https://github.com/numpy/numpy/pull/20695
-        sedinplace 's/machine = platform.machine()/return False/g' numpy/core/setup.py
+        # sedinplace 's/machine = platform.machine()/return False/g' numpy/core/setup.py
         ATLAS=None CC="gcc -m32" "$PYTHON_BIN_PATH" -m pip install . --prefix $INSTALL_PATH --config-settings=build-dir=build
         strip $(find ../ -iname *.so)
         ;;
@@ -137,14 +137,14 @@ case $PLATFORM in
         strip $(find ../ -iname *.so)
         ;;
     macosx-*)
-        sedinplace 's/-std=c99/-w/g' numpy/distutils/ccompiler.py
+        # sedinplace 's/-std=c99/-w/g' numpy/distutils/ccompiler.py
         ATLAS=None "$PYTHON_BIN_PATH" -m pip install . --prefix $INSTALL_PATH --config-settings=build-dir=build
         # need to add RPATH so it can find MKL in cache
         for f in $(find ../ -iname *.so); do install_name_tool -add_rpath @loader_path/../../../ $f; done
         ;;
     windows-x86)
-        sedinplace '/ccompiler._default_compilers = /,+2d' numpy/distutils/ccompiler.py # don't try to use GCC
-        sedinplace 's/ltype = long_double_representation(pyod("_configtest"))/ltype = "IEEE_DOUBLE_LE"/g' numpy/core/setup_common.py
+        # sedinplace '/ccompiler._default_compilers = /,+2d' numpy/distutils/ccompiler.py # don't try to use GCC
+        # sedinplace 's/ltype = long_double_representation(pyod("_configtest"))/ltype = "IEEE_DOUBLE_LE"/g' numpy/core/setup_common.py
         ATLAS=None "$PYTHON_BIN_PATH" -m pip install . --prefix $INSTALL_PATH --config-settings=build-dir=build
         ;;
     windows-x86_64)

numpy/platform/pom.xml

@@ -12,7 +12,7 @@
 
   <groupId>org.bytedeco</groupId>
   <artifactId>numpy-platform</artifactId>
-  <version>2.4.6-${project.parent.version}</version>
+  <version>2.5.0-${project.parent.version}</version>
   <name>JavaCPP Presets Platform for NumPy</name>
 
   <properties>
@@ -28,7 +28,7 @@
     <dependency>
       <groupId>org.bytedeco</groupId>
       <artifactId>cpython-platform</artifactId>
-      <version>3.14.5-${project.parent.version}</version>
+      <version>3.14.6-${project.parent.version}</version>
     </dependency>
     <dependency>
       <groupId>${project.groupId}</groupId>