Merge pull request #61 from IntelPython/upd_wheel_description

README.md

@@ -10,6 +10,22 @@ as a stand-alone package. It can be installed into conda environment using
 
 ---
 
+To install mkl_fft Pypi package please use following command:
+
+```
+   python -m pip install --i https://pypi.anaconda.org/intel/simple -extra-index-url https://pypi.org/simple mkl_fft
+```
+
+If command above installs NumPy package from the Pypi, please use following command to install Intel optimized NumPy wheel package from Anaconda Cloud:
+
+```
+   python -m pip install --i https://pypi.anaconda.org/intel/simple -extra-index-url https://pypi.org/simple mkl_fft numpy==<numpy_version>
+```
+
+Where `<numpy_version>` should be the latest version from https://anaconda.org/intel/numpy
+
+---
+
 Since MKL FFT supports performing discrete Fourier transforms over non-contiguously laid out arrays, MKL can be directly
 used on any well-behaved floating point array with no internal overlaps for both in-place and not in-place transforms of 
 arrays in single and double floating point precision.

conda-recipe/meta.yaml

@@ -1,5 +1,5 @@
 {% set version = "1.3.0" %}
-{% set buildnumber = 0 %}
+{% set buildnumber = 1 %}
 
 package:
     name: mkl_fft

setup.py

@@ -30,6 +30,9 @@
 with io.open('mkl_fft/_version.py', 'rt', encoding='utf8') as f:
     version = re.search(r'__version__ = \'(.*?)\'', f.read()).group(1)
 
+with open("README.md", "r", encoding="utf-8") as file:
+    long_description = file.read()
+
 VERSION = version
 
 CLASSIFIERS = """\
@@ -77,15 +80,16 @@ def setup_package():
         maintainer = "Intel Corp.",
         maintainer_email = "scripting@intel.com",
         description = "MKL-based FFT transforms for NumPy arrays",
-        long_description = """NumPy-based implementation of Fast Fourier Transform using Intel (R) Math Kernel Library. 1D and ND, complex and real transforms, in-place and not-in-place on single and double precision arrays""",
+        long_description = long_description,
+        long_description_content_type="text/markdown",
         url = "http://github.com/IntelPython/mkl_fft",
         author = "Intel Corporation",
         download_url = "http://github.com/IntelPython/mkl_fft",
         license = 'BSD',
         classifiers = [_f for _f in CLASSIFIERS.split('\n') if _f],
         platforms = ["Windows", "Linux", "Mac OS-X"],
         test_suite = 'nose.collector',
-        python_requires = '>=3.5',
+        python_requires = '>=3.6',
         install_requires = ['numpy >=1.16'],
         configuration = configuration
     )