##
##  python-ml.spec -- OpenPKG RPM Package Specification
##  Copyright (c) 2000-2025 OpenPKG Project <http://openpkg.org/>
##
##  Permission to use, copy, modify, and distribute this software for
##  any purpose with or without fee is hereby granted, provided that
##  the above copyright notice and this permission notice appear in all
##  copies.
##
##  THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED
##  WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
##  MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
##  IN NO EVENT SHALL THE AUTHORS AND COPYRIGHT HOLDERS AND THEIR
##  CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
##  SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
##  LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
##  USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
##  ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
##  OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
##  OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
##  SUCH DAMAGE.
##

#   package versions
%define       V_python        3.10
%define       V_keras         2.4.0
%define       V_elektronn     0.6.0
%define       V_blocks        0.2
%define       V_lasagne       20190105
%define       V_pytorch       20180221
%define       V_gensim        3.8.3
%define       V_spacy         2.3.2
%define       V_holmes        2.2.1

#   package information
Name:         python-ml
Summary:      Python Modules for Machine Learning
URL:          http://www.python.org/
Vendor:       Python Community
Packager:     OpenPKG Project
Distribution: OpenPKG Community
Class:        BASE
Group:        Language
License:      GPL
Version:      %{V_python}
Release:      20211008

#   list of sources
Source0:      https://github.com/fchollet/keras/archive/%{V_keras}.tar.gz
Source1:      https://github.com/ELEKTRONN/ELEKTRONN2/archive/v%{V_elektronn}.tar.gz
Source2:      https://github.com/mila-udem/blocks/archive/%{V_blocks}.tar.gz
Source3:      http://download.openpkg.org/components/versioned/lasagne/lasagne-%{V_lasagne}.tar.xz
Source4:      http://download.openpkg.org/components/versioned/pytorch/pytorch-%{V_pytorch}.tar.xz
Source5:      https://files.pythonhosted.org/packages/source/g/gensim/gensim-%{V_gensim}.tar.gz
Source6:      https://files.pythonhosted.org/packages/source/s/spacy/spacy-%{V_spacy}.tar.gz
Source7:      https://files.pythonhosted.org/packages/source/h/holmes-extractor/holmes-extractor-%{V_holmes}.tar.gz
Patch0:       python-ml.patch

#   build information
BuildPreReq:  OpenPKG, openpkg >= 20160101, python >= %{V_python}
PreReq:       OpenPKG, openpkg >= 20160101, python >= %{V_python}
BuildPreReq:  python-math, python-yaml
PreReq:       python-math, python-yaml

%description
    This is a set of Python extension modules for Machine Learning.

%track
    prog python-ml:keras = {
        version   = %{V_keras}
        url       = https://github.com/fchollet/keras/releases
        regex     = (__VER__)\.tar\.gz
    }
    prog python-ml:elektronn = {
        version   = %{V_elektronn}
        url       = https://github.com/ELEKTRONN/ELEKTRONN2/releases
        regex     = v(__VER__)\.tar\.gz
    }
    prog python-ml:blocks = {
        version   = %{V_blocks}
        url       = https://github.com/mila-udem/blocks/releases
        regex     = (__VER__)\.tar\.gz
    }
    prog python-ml:lasagne = {
        version   = %{V_lasagne}
        url       = http://download.openpkg.org/components/versioned/lasagne/
        regex     = lasagne-(__VER__)\.tar\.xz
    }
    prog python-ml:pytorch = {
        version   = %{V_pytorch}
        url       = http://download.openpkg.org/components/versioned/lasagne/
        regex     = pytorch-(__VER__)\.tar\.xz
    }
    prog python-ml:gensim = {
        version   = %{V_gensim}
        url       = https://pypi.python.org/pypi/gensim
        regex     = gensim-(__VER__)\.tar\.gz
    }
    prog python-ml:spacy = {
        version   = %{V_spacy}
        url       = https://pypi.python.org/pypi/spacy
        regex     = spacy-(__VER__)\.tar\.gz
    }
    prog python-ml:holmes-extractor = {
        version   = %{V_holmes}
        url       = https://pypi.python.org/pypi/holmes-extractor
        regex     = holmes-extractor-(__VER__)\.tar\.gz
    }

%prep
    %setup -q -c
    %setup -q -T -D -a 1
    %setup -q -T -D -a 2
    %setup -q -T -D -a 3
    %setup -q -T -D -a 4
    %setup -q -T -D -a 5
    %setup -q -T -D -a 6
    %setup -q -T -D -a 7
    %patch -p0

%build

%install
    export PYTHONPATH=$RPM_BUILD_ROOT%{l_prefix}/lib/python%{V_python}/site-packages
    ( cd keras-%{V_keras}
      %{l_prefix}/bin/python \
          setup.py install \
          --root=$RPM_BUILD_ROOT \
          --prefix=%{l_prefix}
    ) || exit $?
    ( cd ELEKTRONN2-%{V_elektronn}
      %{l_prefix}/bin/python \
          setup.py install \
          --root=$RPM_BUILD_ROOT \
          --prefix=%{l_prefix}
    ) || exit $?
    ( cd blocks-%{V_blocks}
      %{l_prefix}/bin/python \
          setup.py install \
          --root=$RPM_BUILD_ROOT \
          --prefix=%{l_prefix}
    ) || exit $?
    ( cd lasagne
      %{l_prefix}/bin/python \
          setup.py install \
          --root=$RPM_BUILD_ROOT \
          --prefix=%{l_prefix}
    ) || exit $?
    ( cd pytorch
      export NO_CUDA=1
      %{l_prefix}/bin/python \
          setup.py install \
          --root=$RPM_BUILD_ROOT \
          --prefix=%{l_prefix}
    ) || exit $?
    ( cd gensim-%{V_gensim}
      %{l_prefix}/bin/python \
          setup.py install \
          --root=$RPM_BUILD_ROOT \
          --prefix=%{l_prefix}
    ) || exit $?
    ( cd spacy-%{V_spacy}
      %{l_prefix}/bin/python \
          setup.py install \
          --root=$RPM_BUILD_ROOT \
          --prefix=%{l_prefix}
    ) || exit $?
    ( cd holmes-extractor-%{V_holmes}
      %{l_prefix}/bin/python \
          setup.py install \
          --root=$RPM_BUILD_ROOT \
          --prefix=%{l_prefix}
    ) || exit $?
    %{l_rpmtool} files -v -ofiles -r$RPM_BUILD_ROOT %{l_files_std}

%files -f files

%clean

