# This file created by conda-build 3.18.11
# meta.yaml template originally from:
# /tmp/build/80754af9/rsync-recipes/numpy-1.17.4-python_3.7-blas_impl_mkl-on-linux_64, last modified Mon Nov 25 14:36:58 2019
# ------------------------------------------------

package:
    name: numpy
    version: 1.17.4
build:
    string: py37hc1035e2_0
requirements:
    build:
        - _libgcc_mutex 0.1 main
        - binutils_impl_linux-64 2.31.1 h6176602_1
        - binutils_linux-64 2.31.1 h6176602_8
        - gcc_impl_linux-64 7.3.0 habb00fd_1
        - gcc_linux-64 7.3.0 h553295d_8
        - gfortran_impl_linux-64 7.3.0 hdf63c60_1
        - gfortran_linux-64 7.3.0 h553295d_8
        - libgcc-ng 9.1.0 hdf63c60_0
        - libgfortran-ng 7.3.0 hdf63c60_0
        - libstdcxx-ng 9.1.0 hdf63c60_0
    host:
        - _libgcc_mutex 0.1 main
        - blas 1.0 mkl
        - ca-certificates 2019.10.16 0
        - intel-openmp 2019.4 243
        - libedit 3.1.20181209 hc058e9b_0
        - libffi 3.2.1 hd88cf55_4
        - libgcc-ng 9.1.0 hdf63c60_0
        - libgfortran-ng 7.3.0 hdf63c60_0
        - libstdcxx-ng 9.1.0 hdf63c60_0
        - mkl 2019.4 243
        - mkl-devel 2019.4 243
        - mkl-include 2019.4 243
        - ncurses 6.1 he6710b0_1
        - openssl 1.1.1d h7b6447c_3
        - python 3.7.5 h0371630_0
        - readline 7.0 h7b6447c_5
        - sqlite 3.30.1 h7b6447c_0
        - tk 8.6.8 hbc83047_0
        - xz 5.2.4 h14c3975_4
        - zlib 1.2.11 h7b6447c_3
    run:
        - blas 1.0 mkl
        - libgcc-ng >=7.3.0
        - libgfortran-ng >=7,<8.0a0
        - mkl >=2019.4,<2020.0a0
        - mkl-service >=2,<3.0a0
        - mkl_fft
        - mkl_random
        - numpy-base 1.17.4.*
        - python >=3.7,<3.8.0a0
test:
    commands:
        - f2py -h
        - python -c "import numpy; numpy.show_config()"
    imports:
        - numpy
        - numpy.linalg.lapack_lite
    requires:
        - gcc_linux-64 7.3.0.*
        - gfortran_linux-64 7.3.0.*
        - pytest
    script: numpy_test.py
about:
    description: 'NumPy is the fundamental package needed for scientific computing
        with Python.

        '
    dev_source_url: https://github.com/numpy/numpy/tree/master/doc
    dev_url: https://github.com/numpy/numpy
    doc_url: https://docs.scipy.org/doc/numpy-1.17.4/reference/
    home: http://numpy.scipy.org/
    license: BSD 3-Clause
    summary: Array processing for numbers, strings, records, and objects.
extra:
    copy_test_source_files: true
    final: true
