{% set name = "numba" %}
{% set version = "0.58.1" %}
{% set sha256 = "487ded0633efccd9ca3a46364b40006dbdaca0f95e99b8b83e778d1195ebcbaa" %}

package:
  name: numba
  version: {{ version }}

source:
  url: https://pypi.io/packages/source/{{ name[0] }}/{{ name }}/{{ name }}-{{ version }}.tar.gz
  # url: https://github.com/numba/numba/archive/{{ version }}.tar.gz
  sha256: {{ sha256 }}

build:
  number: 0
  entry_points:
    - numba = numba.misc.numba_entry:main
  script:
    - export CC="${CC} -pthread"  # [linux]
    - export CXX="${CXX} -pthread"  # [linux]
    - {{ PYTHON }} -m pip install . --no-deps --ignore-installed -vvv
  ignore_run_exports:
    # tbb-devel triggers hard dependency on tbb, this is not the case.
    - tbb
  skip: true  # [py<38 or (python_impl == 'pypy')]

requirements:
  build:
    - python                                 # [build_platform != target_platform]
    - cross-python_{{ target_platform }}     # [build_platform != target_platform]
    - numpy                                  # [build_platform != target_platform]
    - {{ compiler('c') }}
    - {{ compiler('cxx') }}
    # llvm is needed for the headers
    - llvm-openmp  # [osx]
    - libgomp      # [linux]

  host:
    - python
    - pip
    - setuptools
    - llvmlite 0.41.*
    - numpy
    - tbb-devel 2021.6.0

  run:
    - python
    - {{ pin_compatible('llvmlite', max_pin='x.x') }}
    - {{ pin_compatible('numpy') }}
    - importlib-metadata  # [py < 39]

  run_constrained:
    - {{ pin_compatible('tbb', max_pin=None) }}
    # avoid confusion from openblas bugs
    - libopenblas !=0.3.6             # [x86_64]
    - libopenblas >=0.3.18, !=0.3.20  # [arm64]
    # CUDA 11.2 or later is required for CUDA support
    - cuda-version >=11.2
    - cudatoolkit >=11.2
    # scipy 1.0 or later
    - scipy >=1.0
    # NumPy has a hard upper limit.
    # Also NumPy 1.22.0, 1.22.1, 1.22.2 are all broken for ufuncs
    # xref: https://github.com/numba/numba/issues/7756
    - numpy >=1.22.3,<1.27
    # CUDA Python 11.6 or later
    - cuda-python >=11.6

test:
  requires:
    - pip
    # Required to test optional Numba features
    - jinja2
    - cffi
    - scipy
    # At least NumPy 1.26.0 has an issue with arctanh on glibc<=2.17.
    # ref: https://github.com/numpy/numpy/issues/25087
    - numpy !=1.26.0  # [linux and x86_64]
    - ipython
    - setuptools
    - tbb
    # Need these for AOT.
    - {{ compiler('c') }}
    - {{ compiler('cxx') }}

  imports:
    - numba
    - numba.core.annotations
    - numba.core.datamodel
    - numba.core.rewrites
    - numba.core.runtime
    - numba.core.typeconv
    - numba.core.typing
    - numba.core.unsafe
    - numba.cuda
    - numba.cuda.cudadrv
    - numba.cuda.kernels
    - numba.cuda.simulator
    - numba.cuda.simulator.cudadrv
    - numba.cuda.tests
    - numba.cuda.tests.cudadrv
    - numba.cuda.tests.cudapy
    - numba.cuda.tests.cudasim
    - numba.cuda.tests.nocuda
    - numba.experimental.jitclass
    - numba.np.ufunc
    - numba.scripts
    - numba.testing
    - numba.tests
    - numba.tests.npyufunc

about:
  home: http://numba.pydata.org
  license: BSD-2-Clause
  license_family: BSD
  license_file: LICENSE
  summary: NumPy aware dynamic Python compiler using LLVM
  description: |
    Numba is an Open Source NumPy-aware optimizing compiler for Python 
    sponsored by Anaconda, Inc. It uses the remarkable LLVM compiler 
    infrastructure to compile Python syntax to machine code."
  doc_url: http://numba.pydata.org/
  dev_url: https://github.com/numba/numba

extra:
  recipe-maintainers:
    - souravsingh
    - marcelotrevisani
    - henryiii
    - mbargull
    - jakirkham
    - step21