HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept
{
"count": 53420,
"next": "https://ports.macports.org/api/v1/ports/?format=api&ordering=updated_at&page=153",
"previous": "https://ports.macports.org/api/v1/ports/?format=api&ordering=updated_at&page=151",
"results": [
{
"name": "py39-sentencepiece",
"portdir": "python/py-sentencepiece",
"version": "0.2.0",
"license": "Apache-2",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/google/sentencepiece",
"description": "Python wrapper for sentencepiece",
"long_description": "SentencePiece is an unsupervised text tokenizer and detokenizer mainly for Neural Network-based text generation systems where the vocabulary size is predetermined prior to the neural model training. SentencePiece implements subword units (e.g., byte-pair-encoding (BPE) [Sennrich et al.]) and unigram language model [Kudo.]) with the extension of direct training from raw sentences. SentencePiece allows us to make a purely end-to-end system that does not depend on language-specific pre/postprocessing.",
"active": false,
"categories": [
"textproc",
"python"
],
"maintainers": [],
"variants": [
"universal"
],
"dependencies": [
{
"type": "build",
"ports": [
"py39-build",
"py39-installer",
"clang-16",
"pkgconfig",
"py39-setuptools",
"py39-wheel"
]
},
{
"type": "lib",
"ports": [
"protobuf3-cpp",
"python39",
"sentencepiece"
]
},
{
"type": "test",
"ports": [
"py39-pytest"
]
}
],
"depends_on": [
{
"type": "run",
"ports": [
"py39-allennlp",
"py39-sentence-transformers",
"py39-bpemb"
]
}
]
},
{
"name": "py35-wasabi",
"portdir": "python/py-wasabi",
"version": "0.10.1",
"license": "MIT",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/ines/wasabi",
"description": "A lightweight console printing and formatting toolkit",
"long_description": "A lightweight console printing and formatting toolkit",
"active": false,
"categories": [
"python"
],
"maintainers": [
{
"name": "jonesc",
"github": "cjones051073",
"ports_count": 232
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py35-setuptools",
"clang-14"
]
},
{
"type": "lib",
"ports": [
"python35"
]
}
],
"depends_on": []
},
{
"name": "py27-wasabi",
"portdir": "python/py-wasabi",
"version": "0.10.1",
"license": "MIT",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/ines/wasabi",
"description": "A lightweight console printing and formatting toolkit",
"long_description": "A lightweight console printing and formatting toolkit",
"active": false,
"categories": [
"python"
],
"maintainers": [
{
"name": "jonesc",
"github": "cjones051073",
"ports_count": 232
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py27-setuptools",
"clang-14"
]
},
{
"type": "lib",
"ports": [
"python27"
]
}
],
"depends_on": []
},
{
"name": "py37-wasabi",
"portdir": "python/py-wasabi",
"version": "1.1.2",
"license": "MIT",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/ines/wasabi",
"description": "A lightweight console printing and formatting toolkit",
"long_description": "A lightweight console printing and formatting toolkit",
"active": false,
"categories": [
"python"
],
"maintainers": [
{
"name": "jonesc",
"github": "cjones051073",
"ports_count": 232
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py37-setuptools",
"py37-wheel",
"py37-build",
"py37-installer",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"python37"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py37-spaCy",
"py37-thinc"
]
},
{
"type": "run",
"ports": [
"py37-unidic"
]
}
]
},
{
"name": "py36-wasabi",
"portdir": "python/py-wasabi",
"version": "0.10.1",
"license": "MIT",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/ines/wasabi",
"description": "A lightweight console printing and formatting toolkit",
"long_description": "A lightweight console printing and formatting toolkit",
"active": false,
"categories": [
"python"
],
"maintainers": [
{
"name": "jonesc",
"github": "cjones051073",
"ports_count": 232
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py36-setuptools",
"clang-14"
]
},
{
"type": "lib",
"ports": [
"python36"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py36-spaCy",
"py36-thinc"
]
}
]
},
{
"name": "py38-wasabi",
"portdir": "python/py-wasabi",
"version": "1.1.2",
"license": "MIT",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/ines/wasabi",
"description": "A lightweight console printing and formatting toolkit",
"long_description": "A lightweight console printing and formatting toolkit",
"active": false,
"categories": [
"python"
],
"maintainers": [
{
"name": "jonesc",
"github": "cjones051073",
"ports_count": 232
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py38-setuptools",
"py38-wheel",
"py38-build",
"py38-installer",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"python38"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py38-spaCy",
"py38-thinc"
]
},
{
"type": "run",
"ports": [
"py38-unidic"
]
}
]
},
{
"name": "py39-wasabi",
"portdir": "python/py-wasabi",
"version": "1.1.2",
"license": "MIT",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/ines/wasabi",
"description": "A lightweight console printing and formatting toolkit",
"long_description": "A lightweight console printing and formatting toolkit",
"active": false,
"categories": [
"python"
],
"maintainers": [
{
"name": "jonesc",
"github": "cjones051073",
"ports_count": 232
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py39-setuptools",
"py39-wheel",
"py39-build",
"py39-installer",
"clang-18"
]
},
{
"type": "lib",
"ports": [
"python39"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py39-thinc",
"py39-spaCy"
]
},
{
"type": "run",
"ports": [
"py39-unidic"
]
}
]
},
{
"name": "py38-soxr",
"portdir": "python/py-soxr",
"version": "0.3.7",
"license": "LGPL-2.1+",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/dofuuz/python-soxr",
"description": "High quality, one-dimensional sample-rate conversion library for Python",
"long_description": "High quality, one-dimensional sample-rate conversion library for Python",
"active": false,
"categories": [
"audio",
"python"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py38-installer",
"clang-16",
"py38-cython",
"py38-setuptools",
"py38-setuptools_scm",
"py38-wheel",
"py38-build"
]
},
{
"type": "lib",
"ports": [
"python38"
]
},
{
"type": "run",
"ports": [
"py38-numpy"
]
},
{
"type": "test",
"ports": [
"py38-pytest"
]
}
],
"depends_on": [
{
"type": "run",
"ports": [
"py38-librosa"
]
}
]
},
{
"name": "py39-soxr",
"portdir": "python/py-soxr",
"version": "0.5.0.post1",
"license": "LGPL-2.1+",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/dofuuz/python-soxr",
"description": "High quality, one-dimensional sample-rate conversion library for Python",
"long_description": "High quality, one-dimensional sample-rate conversion library for Python",
"active": false,
"categories": [
"audio",
"python"
],
"maintainers": [],
"variants": [
"universal"
],
"dependencies": [
{
"type": "build",
"ports": [
"py39-scikit-build-core",
"py39-nanobind",
"py39-setuptools",
"py39-setuptools_scm",
"py39-typing_extensions",
"py39-wheel",
"py39-build",
"py39-installer",
"clang-17"
]
},
{
"type": "lib",
"ports": [
"python39"
]
},
{
"type": "run",
"ports": [
"py39-numpy"
]
},
{
"type": "test",
"ports": [
"py39-pytest"
]
}
],
"depends_on": [
{
"type": "run",
"ports": [
"py39-librosa"
]
}
]
},
{
"name": "py36-scikit-learn",
"portdir": "python/py-scikit-learn",
"version": "0.24.2",
"license": "BSD",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://scikit-learn.org/",
"description": "Easy-to-use and general-purpose machine learning in Python",
"long_description": "Scikit-learn integrates machine learning algorithms in the tightly-knit scientific Python world, building upon numpy, scipy, and matplotlib. As a machine-learning module, it provides versatile tools for data mining and analysis in any field of science and engineering.",
"active": false,
"categories": [
"science",
"python"
],
"maintainers": [
{
"name": "stromnov",
"github": "stromnov",
"ports_count": 2946
}
],
"variants": [
"universal"
],
"dependencies": [
{
"type": "build",
"ports": [
"py36-cython",
"py36-setuptools",
"clang-14"
]
},
{
"type": "lib",
"ports": [
"py36-numpy",
"libomp",
"py36-threadpoolctl",
"py36-scipy",
"python36",
"py36-joblib"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py36-astroML",
"py36-eli5",
"py36-tpot",
"py36-word2vec",
"py36-barnaba",
"py36-chainer"
]
}
]
},
{
"name": "py39-scikit-learn",
"portdir": "python/py-scikit-learn",
"version": "1.6.1",
"license": "BSD",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://scikit-learn.org/",
"description": "Easy-to-use and general-purpose machine learning in Python",
"long_description": "Scikit-learn integrates machine learning algorithms in the tightly-knit scientific Python world, building upon numpy, scipy, and matplotlib. As a machine-learning module, it provides versatile tools for data mining and analysis in any field of science and engineering.",
"active": false,
"categories": [
"science",
"python"
],
"maintainers": [
{
"name": "stromnov",
"github": "stromnov",
"ports_count": 2946
}
],
"variants": [
"universal"
],
"dependencies": [
{
"type": "build",
"ports": [
"py39-cython",
"py39-build",
"py39-installer",
"py39-meson-python",
"clang-18"
]
},
{
"type": "lib",
"ports": [
"libomp",
"py39-threadpoolctl",
"python39",
"py39-joblib",
"py39-numpy",
"py39-scipy"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py39-mapclassify",
"py39-astroML",
"py39-beancount-import",
"py39-hdbscan",
"py39-barnaba",
"py39-eli5",
"py39-tpot",
"py39-mlxtend"
]
},
{
"type": "run",
"ports": [
"py39-esda",
"py39-segregation",
"py39-xraylarch",
"py39-transformers",
"py39-spreg",
"py39-libpysal",
"py39-spopt",
"py39-allennlp",
"py39-photomosaic",
"py39-sentence-transformers",
"py39-seqeval",
"py39-umap-learn",
"py39-pmdarima",
"py39-librosa"
]
}
]
},
{
"name": "py35-scikit-learn",
"portdir": "python/py-scikit-learn",
"version": "0.22.2.post1",
"license": "BSD",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://scikit-learn.org/",
"description": "Easy-to-use and general-purpose machine learning in Python",
"long_description": "Scikit-learn integrates machine learning algorithms in the tightly-knit scientific Python world, building upon numpy, scipy, and matplotlib. As a machine-learning module, it provides versatile tools for data mining and analysis in any field of science and engineering.",
"active": false,
"categories": [
"science",
"python"
],
"maintainers": [
{
"name": "stromnov",
"github": "stromnov",
"ports_count": 2946
}
],
"variants": [
"universal"
],
"dependencies": [
{
"type": "build",
"ports": [
"py35-cython",
"py35-setuptools",
"clang-14"
]
},
{
"type": "lib",
"ports": [
"py35-numpy",
"libomp",
"py35-scipy",
"python35",
"py35-joblib"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py35-astroML",
"py35-eli5",
"py35-tpot",
"py35-word2vec",
"py35-chainer"
]
}
]
},
{
"name": "py27-scikit-learn",
"portdir": "python/py-scikit-learn",
"version": "0.20.4",
"license": "BSD",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://scikit-learn.org/",
"description": "Easy-to-use and general-purpose machine learning in Python",
"long_description": "Scikit-learn integrates machine learning algorithms in the tightly-knit scientific Python world, building upon numpy, scipy, and matplotlib. As a machine-learning module, it provides versatile tools for data mining and analysis in any field of science and engineering.",
"active": false,
"categories": [
"science",
"python"
],
"maintainers": [
{
"name": "stromnov",
"github": "stromnov",
"ports_count": 2946
}
],
"variants": [
"universal"
],
"dependencies": [
{
"type": "build",
"ports": [
"py27-cython",
"py27-setuptools",
"clang-14"
]
},
{
"type": "lib",
"ports": [
"python27",
"py27-numpy",
"py27-scipy"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py27-astroML",
"py27-tpot",
"py27-barnaba",
"py27-chainer"
]
}
]
},
{
"name": "py37-scikit-learn",
"portdir": "python/py-scikit-learn",
"version": "1.0.2",
"license": "BSD",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://scikit-learn.org/",
"description": "Easy-to-use and general-purpose machine learning in Python",
"long_description": "Scikit-learn integrates machine learning algorithms in the tightly-knit scientific Python world, building upon numpy, scipy, and matplotlib. As a machine-learning module, it provides versatile tools for data mining and analysis in any field of science and engineering.",
"active": false,
"categories": [
"science",
"python"
],
"maintainers": [
{
"name": "stromnov",
"github": "stromnov",
"ports_count": 2946
}
],
"variants": [
"universal"
],
"dependencies": [
{
"type": "build",
"ports": [
"py37-cython",
"py37-setuptools",
"clang-14"
]
},
{
"type": "lib",
"ports": [
"py37-numpy",
"libomp",
"py37-threadpoolctl",
"py37-scipy",
"python37",
"py37-joblib"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py37-barnaba",
"py37-eli5",
"py37-hdbscan",
"py37-beancount-import",
"py37-tpot",
"py37-astroML",
"py37-mapclassify"
]
},
{
"type": "run",
"ports": [
"py37-umap-learn",
"py37-xraylarch",
"py37-seqeval",
"py37-librosa",
"py37-photomosaic",
"py37-pmdarima"
]
}
]
},
{
"name": "py38-scikit-learn",
"portdir": "python/py-scikit-learn",
"version": "1.3.2",
"license": "BSD",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://scikit-learn.org/",
"description": "Easy-to-use and general-purpose machine learning in Python",
"long_description": "Scikit-learn integrates machine learning algorithms in the tightly-knit scientific Python world, building upon numpy, scipy, and matplotlib. As a machine-learning module, it provides versatile tools for data mining and analysis in any field of science and engineering.",
"active": false,
"categories": [
"science",
"python"
],
"maintainers": [
{
"name": "stromnov",
"github": "stromnov",
"ports_count": 2946
}
],
"variants": [
"universal"
],
"dependencies": [
{
"type": "build",
"ports": [
"py38-cython",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"py38-joblib",
"py38-numpy",
"libomp",
"py38-threadpoolctl",
"py38-scipy",
"python38"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py38-tpot",
"py38-barnaba",
"py38-astroML",
"py38-beancount-import",
"py38-mapclassify",
"py38-hdbscan",
"py38-eli5"
]
},
{
"type": "run",
"ports": [
"py38-transformers",
"py38-xraylarch",
"py38-librosa",
"py38-pmdarima",
"py38-umap-learn",
"py38-seqeval",
"py38-allennlp",
"py38-photomosaic",
"py38-sentence-transformers"
]
}
]
},
{
"name": "py39-imaplib2",
"portdir": "python/py-imaplib2",
"version": "3.6",
"license": "MIT",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/jazzband/imaplib2/",
"description": "A threaded Python IMAP4 client.",
"long_description": "A threaded Python IMAP4 client.",
"active": false,
"categories": [
"devel",
"mail",
"python"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py39-setuptools",
"py39-wheel",
"py39-build",
"py39-installer",
"clang-17"
]
},
{
"type": "lib",
"ports": [
"python39"
]
}
],
"depends_on": []
},
{
"name": "py38-imaplib2",
"portdir": "python/py-imaplib2",
"version": "3.6",
"license": "MIT",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/jazzband/imaplib2/",
"description": "A threaded Python IMAP4 client.",
"long_description": "A threaded Python IMAP4 client.",
"active": false,
"categories": [
"devel",
"mail",
"python"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py38-setuptools",
"py38-wheel",
"py38-build",
"py38-installer",
"clang-17"
]
},
{
"type": "lib",
"ports": [
"python38"
]
}
],
"depends_on": []
},
{
"name": "py37-imaplib2",
"portdir": "python/py-imaplib2",
"version": "3.6",
"license": "MIT",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/jazzband/imaplib2/",
"description": "A threaded Python IMAP4 client.",
"long_description": "A threaded Python IMAP4 client.",
"active": false,
"categories": [
"devel",
"mail",
"python"
],
"maintainers": [
{
"name": "kirill",
"github": "catap",
"ports_count": 120
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py37-setuptools",
"clang-15"
]
},
{
"type": "lib",
"ports": [
"python37"
]
}
],
"depends_on": []
},
{
"name": "py27-rfc6555",
"portdir": "python/py-rfc6555",
"version": "0.1.0",
"license": "Apache-2",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/sethmlarson/rfc6555",
"description": "Python implementation of RFC 6555.",
"long_description": "Python implementation of the Happy Eyeballs Algorithm described in RFC 6555. Provided with a single file and dead-simple API to allow easy vendoring and integration into other projects.",
"active": false,
"categories": [
"devel",
"python"
],
"maintainers": [
{
"name": "kirill",
"github": "catap",
"ports_count": 120
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-9.0",
"py27-setuptools"
]
},
{
"type": "lib",
"ports": [
"python27",
"py27-selectors2"
]
}
],
"depends_on": []
},
{
"name": "py39-rfc6555",
"portdir": "python/py-rfc6555",
"version": "0.1.0",
"license": "Apache-2",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/sethmlarson/rfc6555",
"description": "Python implementation of RFC 6555.",
"long_description": "Python implementation of the Happy Eyeballs Algorithm described in RFC 6555. Provided with a single file and dead-simple API to allow easy vendoring and integration into other projects.",
"active": false,
"categories": [
"devel",
"python"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py39-setuptools",
"py39-wheel",
"py39-build",
"py39-installer",
"clang-17"
]
},
{
"type": "lib",
"ports": [
"python39"
]
}
],
"depends_on": []
},
{
"name": "py38-rfc6555",
"portdir": "python/py-rfc6555",
"version": "0.1.0",
"license": "Apache-2",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/sethmlarson/rfc6555",
"description": "Python implementation of RFC 6555.",
"long_description": "Python implementation of the Happy Eyeballs Algorithm described in RFC 6555. Provided with a single file and dead-simple API to allow easy vendoring and integration into other projects.",
"active": false,
"categories": [
"devel",
"python"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py38-setuptools",
"py38-wheel",
"py38-build",
"py38-installer",
"clang-17"
]
},
{
"type": "lib",
"ports": [
"python38"
]
}
],
"depends_on": []
},
{
"name": "py27-jdcal",
"portdir": "python/py-jdcal",
"version": "1.4.1",
"license": "BSD",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/phn/jdcal",
"description": "Julian dates from proleptic Gregorian and Julian calendars",
"long_description": "Julian dates from proleptic Gregorian and Julian calendars",
"active": false,
"categories": [
"devel",
"python"
],
"maintainers": [
{
"name": "stromnov",
"github": "stromnov",
"ports_count": 2946
}
],
"variants": [
"universal"
],
"dependencies": [
{
"type": "build",
"ports": [
"clang-9.0",
"py27-setuptools"
]
},
{
"type": "lib",
"ports": [
"python27"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py27-openpyxl"
]
}
]
},
{
"name": "py38-jdcal",
"portdir": "python/py-jdcal",
"version": "1.4.1",
"license": "BSD",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/phn/jdcal",
"description": "Julian dates from proleptic Gregorian and Julian calendars",
"long_description": "Julian dates from proleptic Gregorian and Julian calendars",
"active": false,
"categories": [
"devel",
"python"
],
"maintainers": [
{
"name": "stromnov",
"github": "stromnov",
"ports_count": 2946
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py38-setuptools",
"py38-wheel",
"py38-build",
"py38-installer",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"python38"
]
}
],
"depends_on": []
},
{
"name": "py39-jdcal",
"portdir": "python/py-jdcal",
"version": "1.4.1",
"license": "BSD",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/phn/jdcal",
"description": "Julian dates from proleptic Gregorian and Julian calendars",
"long_description": "Julian dates from proleptic Gregorian and Julian calendars",
"active": false,
"categories": [
"devel",
"python"
],
"maintainers": [
{
"name": "stromnov",
"github": "stromnov",
"ports_count": 2946
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py39-setuptools",
"py39-wheel",
"py39-build",
"py39-installer",
"clang-17"
]
},
{
"type": "lib",
"ports": [
"python39"
]
}
],
"depends_on": []
},
{
"name": "py36-jdcal",
"portdir": "python/py-jdcal",
"version": "1.4.1",
"license": "BSD",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/phn/jdcal",
"description": "Julian dates from proleptic Gregorian and Julian calendars",
"long_description": "Julian dates from proleptic Gregorian and Julian calendars",
"active": false,
"categories": [
"devel",
"python"
],
"maintainers": [
{
"name": "stromnov",
"github": "stromnov",
"ports_count": 2946
}
],
"variants": [
"universal"
],
"dependencies": [
{
"type": "build",
"ports": [
"clang-9.0",
"py36-setuptools"
]
},
{
"type": "lib",
"ports": [
"python36"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py36-openpyxl"
]
}
]
},
{
"name": "py35-jdcal",
"portdir": "python/py-jdcal",
"version": "1.4.1",
"license": "BSD",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/phn/jdcal",
"description": "Julian dates from proleptic Gregorian and Julian calendars",
"long_description": "Julian dates from proleptic Gregorian and Julian calendars",
"active": false,
"categories": [
"devel",
"python"
],
"maintainers": [
{
"name": "stromnov",
"github": "stromnov",
"ports_count": 2946
}
],
"variants": [
"universal"
],
"dependencies": [
{
"type": "build",
"ports": [
"clang-9.0",
"py35-setuptools"
]
},
{
"type": "lib",
"ports": [
"python35"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py35-openpyxl"
]
}
]
},
{
"name": "py37-jdcal",
"portdir": "python/py-jdcal",
"version": "1.4.1",
"license": "BSD",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/phn/jdcal",
"description": "Julian dates from proleptic Gregorian and Julian calendars",
"long_description": "Julian dates from proleptic Gregorian and Julian calendars",
"active": false,
"categories": [
"devel",
"python"
],
"maintainers": [
{
"name": "stromnov",
"github": "stromnov",
"ports_count": 2946
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py37-setuptools",
"py37-wheel",
"py37-build",
"py37-installer",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"python37"
]
}
],
"depends_on": []
},
{
"name": "py37-librosa",
"portdir": "python/py-librosa",
"version": "0.8.0",
"license": "ISC",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/librosa/librosa",
"description": "A python package for music and audio analysis.",
"long_description": "A python package for music and audio analysis.",
"active": false,
"categories": [
"audio",
"python"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py37-setuptools",
"clang-14"
]
},
{
"type": "lib",
"ports": [
"python37"
]
},
{
"type": "run",
"ports": [
"py37-decorator",
"py37-joblib",
"py37-matplotlib",
"py37-numba",
"py37-numpy",
"py37-pooch",
"py37-resampy",
"py37-scipy",
"py37-six",
"py37-soundfile",
"py37-threadpoolctl",
"py37-scikit-learn",
"py37-audioread",
"py37-contextlib2"
]
},
{
"type": "test",
"ports": [
"py37-pytest",
"py37-pytest-mpl",
"py37-samplerate"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py37-magenta"
]
},
{
"type": "run",
"ports": [
"py37-note-seq",
"py37-magenta"
]
}
]
},
{
"name": "py38-librosa",
"portdir": "python/py-librosa",
"version": "0.10.1",
"license": "ISC",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/librosa/librosa",
"description": "A python package for music and audio analysis.",
"long_description": "A python package for music and audio analysis.",
"active": false,
"categories": [
"audio",
"python"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py38-setuptools",
"py38-wheel",
"py38-build",
"py38-installer",
"clang-16"
]
},
{
"type": "lib",
"ports": [
"python38"
]
},
{
"type": "run",
"ports": [
"py38-numba",
"py38-numpy",
"py38-pooch",
"py38-scikit-learn",
"py38-scipy",
"py38-soundfile",
"py38-lazy_loader",
"py38-soxr",
"py38-typing_extensions",
"py38-audioread",
"py38-decorator",
"py38-joblib",
"py38-matplotlib",
"py38-msgpack"
]
},
{
"type": "test",
"ports": [
"py38-pytest",
"py38-pytest-mpl",
"py38-resampy",
"py38-samplerate",
"py38-types-decorator"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py38-magenta"
]
},
{
"type": "run",
"ports": [
"py38-magenta",
"py38-note-seq"
]
}
]
},
{
"name": "py39-librosa",
"portdir": "python/py-librosa",
"version": "0.11.0",
"license": "ISC",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/librosa/librosa",
"description": "A python package for music and audio analysis.",
"long_description": "A python package for music and audio analysis.",
"active": false,
"categories": [
"audio",
"python"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py39-setuptools",
"py39-wheel",
"py39-build",
"py39-installer",
"clang-17"
]
},
{
"type": "lib",
"ports": [
"python39"
]
},
{
"type": "run",
"ports": [
"py39-numba",
"py39-numpy",
"py39-pooch",
"py39-scikit-learn",
"py39-scipy",
"py39-soundfile",
"py39-typing_extensions",
"py39-soxr",
"py39-lazy_loader",
"py39-audioread",
"py39-decorator",
"py39-joblib",
"py39-matplotlib",
"py39-msgpack"
]
},
{
"type": "test",
"ports": [
"py39-packaging",
"py39-pytest",
"py39-pytest-mpl",
"py39-resampy",
"py39-samplerate",
"py39-types-decorator"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py39-magenta"
]
},
{
"type": "run",
"ports": [
"py39-magenta",
"py39-note-seq"
]
}
]
},
{
"name": "py27-smart_open",
"portdir": "python/py-smart_open",
"version": "1.10.1",
"license": "MIT",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/RaRe-Technologies/smart_open",
"description": "Utils for streaming large files (S3, HDFS, gzip, bz2...)",
"long_description": "Utils for streaming large files (S3, HDFS, gzip, bz2...)",
"active": false,
"categories": [
"textproc",
"python"
],
"maintainers": [
{
"name": "stromnov",
"github": "stromnov",
"ports_count": 2946
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-9.0",
"py27-setuptools"
]
},
{
"type": "lib",
"ports": [
"python27",
"py27-boto3",
"py27-bz2file",
"py27-requests"
]
}
],
"depends_on": []
},
{
"name": "py39-smart_open",
"portdir": "python/py-smart_open",
"version": "7.3.0.post1",
"license": "MIT",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/piskvorky/smart_open",
"description": "Utils for streaming large files (S3, HDFS, gzip, bz2...)",
"long_description": "Utils for streaming large files (S3, HDFS, gzip, bz2...)",
"active": false,
"categories": [
"textproc",
"python"
],
"maintainers": [
{
"name": "stromnov",
"github": "stromnov",
"ports_count": 2946
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-18",
"py39-build",
"py39-installer",
"py39-setuptools",
"py39-setuptools_scm",
"py39-wheel"
]
},
{
"type": "lib",
"ports": [
"py39-wrapt",
"python39"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py39-gensim",
"py39-mp-api"
]
}
]
},
{
"name": "py36-smart_open",
"portdir": "python/py-smart_open",
"version": "5.2.1",
"license": "MIT",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/RaRe-Technologies/smart_open",
"description": "Utils for streaming large files (S3, HDFS, gzip, bz2...)",
"long_description": "Utils for streaming large files (S3, HDFS, gzip, bz2...)",
"active": false,
"categories": [
"textproc",
"python"
],
"maintainers": [
{
"name": "stromnov",
"github": "stromnov",
"ports_count": 2946
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-9.0",
"py36-setuptools"
]
},
{
"type": "lib",
"ports": [
"python36"
]
}
],
"depends_on": []
},
{
"name": "py35-smart_open",
"portdir": "python/py-smart_open",
"version": "1.10.1",
"license": "MIT",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/RaRe-Technologies/smart_open",
"description": "Utils for streaming large files (S3, HDFS, gzip, bz2...)",
"long_description": "Utils for streaming large files (S3, HDFS, gzip, bz2...)",
"active": false,
"categories": [
"textproc",
"python"
],
"maintainers": [
{
"name": "stromnov",
"github": "stromnov",
"ports_count": 2946
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-9.0",
"py35-setuptools"
]
},
{
"type": "lib",
"ports": [
"python35",
"py35-boto3",
"py35-requests"
]
}
],
"depends_on": []
},
{
"name": "py37-smart_open",
"portdir": "python/py-smart_open",
"version": "6.3.0",
"license": "MIT",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/RaRe-Technologies/smart_open",
"description": "Utils for streaming large files (S3, HDFS, gzip, bz2...)",
"long_description": "Utils for streaming large files (S3, HDFS, gzip, bz2...)",
"active": false,
"categories": [
"textproc",
"python"
],
"maintainers": [
{
"name": "stromnov",
"github": "stromnov",
"ports_count": 2946
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py37-setuptools",
"py37-wheel",
"py37-build",
"clang-14",
"py37-installer"
]
},
{
"type": "lib",
"ports": [
"python37"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py37-gensim"
]
}
]
},
{
"name": "py38-smart_open",
"portdir": "python/py-smart_open",
"version": "7.0.4",
"license": "MIT",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/piskvorky/smart_open",
"description": "Utils for streaming large files (S3, HDFS, gzip, bz2...)",
"long_description": "Utils for streaming large files (S3, HDFS, gzip, bz2...)",
"active": false,
"categories": [
"textproc",
"python"
],
"maintainers": [
{
"name": "stromnov",
"github": "stromnov",
"ports_count": 2946
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py38-wheel",
"py38-installer",
"clang-16",
"py38-setuptools",
"py38-build"
]
},
{
"type": "lib",
"ports": [
"py38-wrapt",
"python38"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py38-gensim"
]
}
]
},
{
"name": "boost176-numpy",
"portdir": "devel/boost176",
"version": "1.76.0",
"license": "Boost-1",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "http://www.boost.org",
"description": "Boost.Numpy library",
"long_description": "Boost.Numpy library",
"active": false,
"categories": [
"devel"
],
"maintainers": [
{
"name": "michaelld",
"github": "michaelld",
"ports_count": 439
},
{
"name": "mascguy",
"github": "mascguy",
"ports_count": 382
}
],
"variants": [
"clang11",
"clang12",
"clang13",
"clang14",
"clang15",
"clang16",
"clang17",
"clang18",
"clang10",
"clang19",
"clang20",
"clang50",
"clang60",
"clang70",
"clang80",
"clang90",
"clangdevel",
"mpich",
"openmpi",
"python27",
"python39",
"python310",
"python311",
"python312",
"debug",
"no_static",
"no_single",
"universal"
],
"dependencies": [
{
"type": "build",
"ports": [
"clang-17"
]
},
{
"type": "lib",
"ports": [
"boost176"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"boost-numpy"
]
}
]
},
{
"name": "boost171-numpy",
"portdir": "devel/boost171",
"version": "1.71.0",
"license": "Boost-1",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "http://www.boost.org",
"description": "Boost.Numpy library",
"long_description": "Boost.Numpy library",
"active": false,
"categories": [
"devel"
],
"maintainers": [
{
"name": "michaelld",
"github": "michaelld",
"ports_count": 439
},
{
"name": "mascguy",
"github": "mascguy",
"ports_count": 382
}
],
"variants": [
"mpich",
"openmpi",
"python27",
"python39",
"python310",
"python311",
"python312",
"clang10",
"clang11",
"clang12",
"clang13",
"clang14",
"clang15",
"clang16",
"clang17",
"clang18",
"clang19",
"clang50",
"clang60",
"clang70",
"clang80",
"clang90",
"clangdevel",
"debug",
"no_static",
"no_single",
"universal"
],
"dependencies": [
{
"type": "build",
"ports": [
"clang-17"
]
},
{
"type": "lib",
"ports": [
"boost171",
"python310",
"py310-numpy"
]
}
],
"depends_on": []
},
{
"name": "boost178-numpy",
"portdir": "devel/boost178",
"version": "1.78.0",
"license": "Boost-1",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "http://www.boost.org",
"description": "Boost.Numpy library",
"long_description": "Boost.Numpy library",
"active": false,
"categories": [
"devel"
],
"maintainers": [
{
"name": "michaelld",
"github": "michaelld",
"ports_count": 439
},
{
"name": "mascguy",
"github": "mascguy",
"ports_count": 382
}
],
"variants": [
"clang20",
"clang50",
"clang60",
"clang70",
"clang10",
"clang11",
"clang12",
"clang13",
"clang14",
"clang15",
"clang16",
"clang17",
"clang18",
"clang19",
"clang80",
"clang90",
"clangdevel",
"mpich",
"openmpi",
"python27",
"python39",
"python310",
"python311",
"python312",
"debug",
"no_static",
"no_single",
"universal"
],
"dependencies": [
{
"type": "build",
"ports": [
"clang-17"
]
},
{
"type": "lib",
"ports": [
"boost178",
"python312",
"py312-numpy"
]
}
],
"depends_on": []
},
{
"name": "py36-preshed",
"portdir": "python/py-preshed",
"version": "3.0.6",
"license": "MIT",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/explosion/preshed",
"description": "Cython hash tables that assume keys are pre-hashed",
"long_description": "Cython hash tables that assume keys are pre-hashed",
"active": false,
"categories": [
"python"
],
"maintainers": [
{
"name": "jonesc",
"github": "cjones051073",
"ports_count": 232
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-9.0",
"py36-setuptools"
]
},
{
"type": "lib",
"ports": [
"py36-cython",
"python36",
"py36-murmurhash",
"py36-cymem"
]
},
{
"type": "test",
"ports": [
"py36-pytest"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py36-spaCy",
"py36-thinc"
]
}
]
},
{
"name": "py35-preshed",
"portdir": "python/py-preshed",
"version": "3.0.6",
"license": "MIT",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/explosion/preshed",
"description": "Cython hash tables that assume keys are pre-hashed",
"long_description": "Cython hash tables that assume keys are pre-hashed",
"active": false,
"categories": [
"python"
],
"maintainers": [
{
"name": "jonesc",
"github": "cjones051073",
"ports_count": 232
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-9.0",
"py35-setuptools"
]
},
{
"type": "lib",
"ports": [
"py35-cython",
"python35",
"py35-murmurhash",
"py35-cymem"
]
},
{
"type": "test",
"ports": [
"py35-pytest"
]
}
],
"depends_on": []
},
{
"name": "py27-preshed",
"portdir": "python/py-preshed",
"version": "3.0.6",
"license": "MIT",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/explosion/preshed",
"description": "Cython hash tables that assume keys are pre-hashed",
"long_description": "Cython hash tables that assume keys are pre-hashed",
"active": false,
"categories": [
"python"
],
"maintainers": [
{
"name": "jonesc",
"github": "cjones051073",
"ports_count": 232
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-9.0",
"py27-setuptools"
]
},
{
"type": "lib",
"ports": [
"py27-cython",
"python27",
"py27-murmurhash",
"py27-cymem"
]
},
{
"type": "test",
"ports": [
"py27-pytest"
]
}
],
"depends_on": []
},
{
"name": "py38-preshed",
"portdir": "python/py-preshed",
"version": "4.0.0",
"license": "MIT",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/explosion/preshed",
"description": "Cython hash tables that assume keys are pre-hashed",
"long_description": "Cython hash tables that assume keys are pre-hashed",
"active": false,
"categories": [
"python"
],
"maintainers": [
{
"name": "jonesc",
"github": "cjones051073",
"ports_count": 232
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py38-wheel",
"py38-build",
"py38-installer",
"clang-16",
"py38-setuptools"
]
},
{
"type": "lib",
"ports": [
"python38",
"py38-cymem",
"py38-cython",
"py38-murmurhash"
]
},
{
"type": "test",
"ports": [
"py38-pytest"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py38-spaCy",
"py38-thinc"
]
}
]
},
{
"name": "py37-preshed",
"portdir": "python/py-preshed",
"version": "4.0.0",
"license": "MIT",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/explosion/preshed",
"description": "Cython hash tables that assume keys are pre-hashed",
"long_description": "Cython hash tables that assume keys are pre-hashed",
"active": false,
"categories": [
"python"
],
"maintainers": [
{
"name": "jonesc",
"github": "cjones051073",
"ports_count": 232
}
],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py37-wheel",
"py37-build",
"py37-installer",
"clang-16",
"py37-setuptools"
]
},
{
"type": "lib",
"ports": [
"python37",
"py37-cymem",
"py37-cython",
"py37-murmurhash"
]
},
{
"type": "test",
"ports": [
"py37-pytest"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py37-spaCy",
"py37-thinc"
]
}
]
},
{
"name": "py39-preshed",
"portdir": "python/py-preshed",
"version": "4.0.0",
"license": "MIT",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/explosion/preshed",
"description": "Cython hash tables that assume keys are pre-hashed",
"long_description": "Cython hash tables that assume keys are pre-hashed",
"active": false,
"categories": [
"python"
],
"maintainers": [
{
"name": "jonesc",
"github": "cjones051073",
"ports_count": 232
}
],
"variants": [
"universal"
],
"dependencies": [
{
"type": "build",
"ports": [
"py39-wheel",
"py39-build",
"py39-installer",
"clang-17",
"py39-setuptools"
]
},
{
"type": "lib",
"ports": [
"python39",
"py39-cymem",
"py39-cython",
"py39-murmurhash"
]
},
{
"type": "test",
"ports": [
"py39-pytest"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py39-thinc",
"py39-spaCy"
]
}
]
},
{
"name": "py39-donfig",
"portdir": "python/py-donfig",
"version": "0.8.1.post1",
"license": "BSD and MIT",
"platforms": "darwin",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/pytroll/donfig",
"description": "Donfig is a python library meant to make configuration easier for other python packages. Donfig can be configured programmatically, by environment variables, or from YAML files in standard locations.",
"long_description": "Donfig is a python library meant to make configuration easier for other python packages. Donfig can be configured programmatically, by environment variables, or from YAML files in standard locations.",
"active": false,
"categories": [
"python"
],
"maintainers": [
{
"name": "mps",
"github": "Schamschula",
"ports_count": 1638
}
],
"variants": [
"universal"
],
"dependencies": [
{
"type": "build",
"ports": [
"clang-17",
"py39-installer",
"py39-versioneer",
"py39-setuptools",
"py39-wheel",
"py39-build"
]
},
{
"type": "lib",
"ports": [
"py39-yaml",
"python39"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py39-zarr"
]
}
]
},
{
"name": "py-mesh-tensorflow",
"portdir": "python/py-mesh-tensorflow",
"version": "0.1.18.20210305",
"license": "Apache-2",
"platforms": "any",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/tensorflow/mesh",
"description": "Mesh TensorFlow - Model Parallelism Made Easier",
"long_description": "Mesh TensorFlow (mtf) is a language for distributed deep learning, capable of specifying a broad class of distributed tensor computations. The purpose of Mesh TensorFlow is to formalize and implement distribution strategies for your computation graph over your hardware/processors. For example: Split the batch over rows of processors and split the units in the hidden layer across columns of processors. Mesh TensorFlow is implemented as a layer over TensorFlow.",
"active": false,
"categories": [
"python"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-17"
]
},
{
"type": "lib",
"ports": [
"py39-mesh-tensorflow"
]
}
],
"depends_on": []
},
{
"name": "py37-mesh-tensorflow",
"portdir": "python/py-mesh-tensorflow",
"version": "0.1.18.20210305",
"license": "Apache-2",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/tensorflow/mesh",
"description": "Mesh TensorFlow - Model Parallelism Made Easier",
"long_description": "Mesh TensorFlow (mtf) is a language for distributed deep learning, capable of specifying a broad class of distributed tensor computations. The purpose of Mesh TensorFlow is to formalize and implement distribution strategies for your computation graph over your hardware/processors. For example: Split the batch over rows of processors and split the units in the hidden layer across columns of processors. Mesh TensorFlow is implemented as a layer over TensorFlow.",
"active": false,
"categories": [
"python"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"py37-installer",
"py37-pytest-runner",
"py37-setuptools",
"py37-wheel",
"py37-build",
"clang-14"
]
},
{
"type": "lib",
"ports": [
"python37"
]
},
{
"type": "run",
"ports": [
"py37-absl",
"py37-future",
"py37-gin-config",
"py37-six"
]
}
],
"depends_on": [
{
"type": "run",
"ports": [
"py37-tensor2tensor"
]
}
]
},
{
"name": "py38-mesh-tensorflow",
"portdir": "python/py-mesh-tensorflow",
"version": "0.1.18.20210305",
"license": "Apache-2",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/tensorflow/mesh",
"description": "Mesh TensorFlow - Model Parallelism Made Easier",
"long_description": "Mesh TensorFlow (mtf) is a language for distributed deep learning, capable of specifying a broad class of distributed tensor computations. The purpose of Mesh TensorFlow is to formalize and implement distribution strategies for your computation graph over your hardware/processors. For example: Split the batch over rows of processors and split the units in the hidden layer across columns of processors. Mesh TensorFlow is implemented as a layer over TensorFlow.",
"active": false,
"categories": [
"python"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-16",
"py38-pytest-runner",
"py38-setuptools",
"py38-wheel",
"py38-build",
"py38-installer"
]
},
{
"type": "lib",
"ports": [
"python38"
]
},
{
"type": "run",
"ports": [
"py38-absl",
"py38-future",
"py38-gin-config",
"py38-six"
]
}
],
"depends_on": [
{
"type": "run",
"ports": [
"py38-tensor2tensor"
]
}
]
},
{
"name": "py39-mesh-tensorflow",
"portdir": "python/py-mesh-tensorflow",
"version": "0.1.18.20210305",
"license": "Apache-2",
"platforms": "{darwin any}",
"epoch": 0,
"replaced_by": null,
"homepage": "https://github.com/tensorflow/mesh",
"description": "Mesh TensorFlow - Model Parallelism Made Easier",
"long_description": "Mesh TensorFlow (mtf) is a language for distributed deep learning, capable of specifying a broad class of distributed tensor computations. The purpose of Mesh TensorFlow is to formalize and implement distribution strategies for your computation graph over your hardware/processors. For example: Split the batch over rows of processors and split the units in the hidden layer across columns of processors. Mesh TensorFlow is implemented as a layer over TensorFlow.",
"active": false,
"categories": [
"python"
],
"maintainers": [],
"variants": [],
"dependencies": [
{
"type": "build",
"ports": [
"clang-17",
"py39-pytest-runner",
"py39-setuptools",
"py39-wheel",
"py39-build",
"py39-installer"
]
},
{
"type": "lib",
"ports": [
"python39"
]
},
{
"type": "run",
"ports": [
"py39-absl",
"py39-future",
"py39-gin-config",
"py39-six"
]
}
],
"depends_on": [
{
"type": "lib",
"ports": [
"py-mesh-tensorflow"
]
},
{
"type": "run",
"ports": [
"py39-tensor2tensor"
]
}
]
}
]
}