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new file: d/dask/dask-0.17.0-Py-3.6.eb new file: d/decorator/decorator-4.2.1-Py-3.6.eb modified: n/networkx/networkx-1.11-Python-2.7.13.eb new file: n/networkx/networkx-2.1-Py-3.6.eb new file: p/Pillow/Pillow-5.0.0-Py-3.6.eb new file: p/PyWavelets/PyWavelets-0.5.2-Py-3.6.eb modified: s/Score-P/Score-P-3.1-intel-2017a.eb modified: s/scikit-image/scikit-image-0.13.1-Py-3.6.eb new file: t/toolz/toolz-0.9.0-Py-3.6.eb deleted: n/networkx/networkx-1.11-Py-3.6.eb deleted: s/scikit-image/.scikit-image-0.13.1-Py-3.6.eb.swp
39 lines
1.1 KiB
Plaintext
39 lines
1.1 KiB
Plaintext
# IT4Innovations 2018
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easyblock = 'PythonPackage'
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name = 'scikit-image'
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version = '0.13.1'
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homepage = 'http://scikit-learn.org/stable/index.html'
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description = """Scikit-learn integrates machine learning algorithms in the tightly-knit scientific Python world,
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building upon numpy, scipy, and matplotlib. As a machine-learning module,
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it provides versatile tools for data mining and analysis in any field of science and engineering.
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It strives to be simple and efficient, accessible to everybody, and reusable in various contexts."""
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toolchain = {'name': 'Py', 'version': '3.6'}
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source_urls = [PYPI_SOURCE]
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sources = [SOURCE_TAR_GZ]
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dependencies = [
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('matplotlib', '2.1.1'),
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('numpy', '1.13.3'),
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('scipy', '1.0.0'),
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('six', '1.11.0'),
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('networkx', '2.1'),
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('Pillow', '5.0.0'),
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('dask', '0.17.0'),
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('toolz', '0.9.0'),
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('PyWavelets', '0.5.2'),
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]
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options = {'modulename': 'skimage'}
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sanity_check_paths = {
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'files': [],
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'dirs': ['lib/python3.6/site-packages/scikit_image-%(version)s-py3.6-linux-x86_64.egg'],
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}
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moduleclass = 'python'
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