GET /api/v1/ports/?format=api&ordering=updated_at&page=907
HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "count": 49863,
    "next": "https://ports.macports.org/api/v1/ports/?format=api&ordering=updated_at&page=908",
    "previous": "https://ports.macports.org/api/v1/ports/?format=api&ordering=updated_at&page=906",
    "results": [
        {
            "name": "octave-statistics",
            "portdir": "octave/octave-statistics",
            "version": "1.7.7",
            "license": "GPL-3+ and public-domain",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/gnu-octave/statistics",
            "description": "Additional statistics functions for Octave.",
            "long_description": "Additional statistics functions for Octave.",
            "active": true,
            "categories": [
                "science",
                "math",
                "octave"
            ],
            "maintainers": [
                {
                    "name": "mps",
                    "github": "Schamschula",
                    "ports_count": 1112
                }
            ],
            "variants": [
                "universal"
            ],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "clang-20"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "octave"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "lib",
                    "ports": [
                        "octave-vrml",
                        "octave-ncarray",
                        "octave-statistics-resampling",
                        "octave-optim",
                        "octave-financial"
                    ]
                }
            ]
        },
        {
            "name": "py38-torchaudio",
            "portdir": "python/py-torchaudio",
            "version": "0.12.0",
            "license": "BSD",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/pytorch/audio",
            "description": "Data manipulation and transformation for audio signal processing, powered by PyTorch",
            "long_description": "The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the same philosophy of providing strong GPU acceleration, having a focus on trainable features through the autograd system, and having consistent style (tensor names and dimension names). Therefore, it is primarily a machine learning library and not a general signal processing library. The benefits of PyTorch can be seen in torchaudio through having all the computations be through PyTorch operations which makes it easy to use and feel like a natural extension.",
            "active": false,
            "categories": [
                "audio",
                "python"
            ],
            "maintainers": [],
            "variants": [
                "universal"
            ],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "cmake",
                        "ninja",
                        "py38-setuptools",
                        "clang-15"
                    ]
                },
                {
                    "type": "fetch",
                    "ports": [
                        "git"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py38-dill",
                        "sox",
                        "py38-pytorch",
                        "zmq",
                        "libomp",
                        "python38",
                        "ffmpeg"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py38-pytest"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "run",
                    "ports": [
                        "py38-transformers"
                    ]
                }
            ]
        },
        {
            "name": "py37-torchaudio",
            "portdir": "python/py-torchaudio",
            "version": "0.12.0",
            "license": "BSD",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/pytorch/audio",
            "description": "Data manipulation and transformation for audio signal processing, powered by PyTorch",
            "long_description": "The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the same philosophy of providing strong GPU acceleration, having a focus on trainable features through the autograd system, and having consistent style (tensor names and dimension names). Therefore, it is primarily a machine learning library and not a general signal processing library. The benefits of PyTorch can be seen in torchaudio through having all the computations be through PyTorch operations which makes it easy to use and feel like a natural extension.",
            "active": false,
            "categories": [
                "audio",
                "python"
            ],
            "maintainers": [],
            "variants": [
                "universal"
            ],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "cmake",
                        "ninja",
                        "py37-setuptools",
                        "clang-14"
                    ]
                },
                {
                    "type": "fetch",
                    "ports": [
                        "git"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py37-dill",
                        "sox",
                        "py37-pytorch",
                        "zmq",
                        "libomp",
                        "python37",
                        "ffmpeg"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py37-pytest"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "py39-torchaudio",
            "portdir": "python/py-torchaudio",
            "version": "0.12.0",
            "license": "BSD",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/pytorch/audio",
            "description": "Data manipulation and transformation for audio signal processing, powered by PyTorch",
            "long_description": "The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the same philosophy of providing strong GPU acceleration, having a focus on trainable features through the autograd system, and having consistent style (tensor names and dimension names). Therefore, it is primarily a machine learning library and not a general signal processing library. The benefits of PyTorch can be seen in torchaudio through having all the computations be through PyTorch operations which makes it easy to use and feel like a natural extension.",
            "active": false,
            "categories": [
                "audio",
                "python"
            ],
            "maintainers": [],
            "variants": [
                "universal"
            ],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "cmake",
                        "clang-18",
                        "py39-installer",
                        "py39-build",
                        "py39-wheel",
                        "py39-setuptools",
                        "ninja"
                    ]
                },
                {
                    "type": "fetch",
                    "ports": [
                        "git"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "sox",
                        "py39-dill",
                        "ffmpeg",
                        "python39",
                        "libomp",
                        "zmq",
                        "py39-pytorch"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py39-pytest"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "run",
                    "ports": [
                        "py39-transformers"
                    ]
                }
            ]
        },
        {
            "name": "py38-pytorch-lightning",
            "portdir": "python/py-pytorch-lightning",
            "version": "1.6.5",
            "license": "Apache-2",
            "platforms": "{darwin any}",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/PyTorchLightning/pytorch-lightning",
            "description": "The lightweight PyTorch wrapper for high-performance AI research.",
            "long_description": "Lightning disentangles PyTorch code to decouple the science from the engineering.",
            "active": false,
            "categories": [
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "py38-setuptools",
                        "clang-15"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "python38"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py38-numpy",
                        "py38-pytorch",
                        "py38-tensorboard",
                        "py38-tqdm",
                        "py38-yaml",
                        "py38-future",
                        "py38-fsspec"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "run",
                    "ports": [
                        "py38-kraken",
                        "py38-transformers"
                    ]
                }
            ]
        },
        {
            "name": "py39-pytorch-lightning",
            "portdir": "python/py-pytorch-lightning",
            "version": "1.6.5",
            "license": "Apache-2",
            "platforms": "{darwin any}",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/PyTorchLightning/pytorch-lightning",
            "description": "The lightweight PyTorch wrapper for high-performance AI research.",
            "long_description": "Lightning disentangles PyTorch code to decouple the science from the engineering.",
            "active": false,
            "categories": [
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "py39-setuptools",
                        "clang-17",
                        "py39-installer",
                        "py39-build",
                        "py39-wheel"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "python39"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py39-tqdm",
                        "py39-yaml",
                        "py39-tensorboard",
                        "py39-pytorch",
                        "py39-numpy",
                        "py39-future",
                        "py39-fsspec"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "run",
                    "ports": [
                        "py39-kraken",
                        "py39-transformers"
                    ]
                }
            ]
        },
        {
            "name": "py37-pytorch-lightning",
            "portdir": "python/py-pytorch-lightning",
            "version": "1.6.5",
            "license": "Apache-2",
            "platforms": "{darwin any}",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/PyTorchLightning/pytorch-lightning",
            "description": "The lightweight PyTorch wrapper for high-performance AI research.",
            "long_description": "Lightning disentangles PyTorch code to decouple the science from the engineering.",
            "active": false,
            "categories": [
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "py37-setuptools",
                        "clang-14"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "python37"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py37-numpy",
                        "py37-pytorch",
                        "py37-tensorboard",
                        "py37-tqdm",
                        "py37-yaml",
                        "py37-future",
                        "py37-fsspec"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "py39-sentence-transformers",
            "portdir": "python/py-sentence-transformers",
            "version": "2.0.0",
            "license": "Apache-2",
            "platforms": "{darwin any}",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/UKPLab/sentence-transformers",
            "description": "Sentence Embeddings using BERT / RoBERTa / XLM-R",
            "long_description": "This framework provides an easy method to compute dense vector representations for sentences, paragraphs, and images. The models are based on transformer networks like BERT / RoBERTa / XLM-RoBERTa etc. and achieve state-of-the-art performance in various task. Text is embedding in vector space such that similar text is close and can efficiently be found using cosine similarity. We provide an increasing number of state-of-the-art pretrained models for more than 100 languages, fine-tuned for various use-cases. Further, this framework allows an easy fine-tuning of custom embeddings models, to achieve maximal performance on your specific task.",
            "active": false,
            "categories": [
                "textproc",
                "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-sentencepiece",
                        "py39-transformers",
                        "py39-tqdm",
                        "py39-nltk",
                        "py39-numpy",
                        "py39-pytorch",
                        "py39-scikit-learn",
                        "py39-scipy"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py39-pytest"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "py38-sentence-transformers",
            "portdir": "python/py-sentence-transformers",
            "version": "2.0.0",
            "license": "Apache-2",
            "platforms": "{darwin any}",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/UKPLab/sentence-transformers",
            "description": "Sentence Embeddings using BERT / RoBERTa / XLM-R",
            "long_description": "This framework provides an easy method to compute dense vector representations for sentences, paragraphs, and images. The models are based on transformer networks like BERT / RoBERTa / XLM-RoBERTa etc. and achieve state-of-the-art performance in various task. Text is embedding in vector space such that similar text is close and can efficiently be found using cosine similarity. We provide an increasing number of state-of-the-art pretrained models for more than 100 languages, fine-tuned for various use-cases. Further, this framework allows an easy fine-tuning of custom embeddings models, to achieve maximal performance on your specific task.",
            "active": false,
            "categories": [
                "textproc",
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "py38-setuptools",
                        "clang-14"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "python38"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py38-pytorch",
                        "py38-scikit-learn",
                        "py38-scipy",
                        "py38-tqdm",
                        "py38-transformers",
                        "py38-sentencepiece",
                        "py38-nltk",
                        "py38-numpy"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py38-pytest"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "py37-fairseq",
            "portdir": "python/py-fairseq",
            "version": "0.12.2",
            "license": "MIT",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/pytorch/fairseq",
            "description": "Facebook AI Research Sequence-to-Sequence Toolkit written in Python.",
            "long_description": "Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks.",
            "active": false,
            "categories": [
                "python"
            ],
            "maintainers": [],
            "variants": [
                "universal"
            ],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "clang-14"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py37-setuptools",
                        "python37"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py37-hydra-core",
                        "py37-numpy",
                        "py37-pytorch",
                        "py37-regex",
                        "py37-sacrebleu",
                        "py37-tqdm",
                        "py37-omegaconf",
                        "py37-cffi",
                        "py37-cython"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py37-pytest"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "py39-fairseq",
            "portdir": "python/py-fairseq",
            "version": "0.12.2",
            "license": "MIT",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/pytorch/fairseq",
            "description": "Facebook AI Research Sequence-to-Sequence Toolkit written in Python.",
            "long_description": "Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks.",
            "active": false,
            "categories": [
                "python"
            ],
            "maintainers": [],
            "variants": [
                "universal"
            ],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "py39-wheel",
                        "py39-installer",
                        "clang-17",
                        "py39-setuptools",
                        "py39-build"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "python39",
                        "py39-setuptools"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py39-sacrebleu",
                        "py39-tqdm",
                        "py39-regex",
                        "py39-cffi",
                        "py39-cython",
                        "py39-hydra-core",
                        "py39-numpy",
                        "py39-omegaconf",
                        "py39-pytorch"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py39-pytest"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "run",
                    "ports": [
                        "py39-transformers"
                    ]
                }
            ]
        },
        {
            "name": "py38-fairseq",
            "portdir": "python/py-fairseq",
            "version": "0.12.2",
            "license": "MIT",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/pytorch/fairseq",
            "description": "Facebook AI Research Sequence-to-Sequence Toolkit written in Python.",
            "long_description": "Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks.",
            "active": false,
            "categories": [
                "python"
            ],
            "maintainers": [],
            "variants": [
                "universal"
            ],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "clang-15"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py38-setuptools",
                        "python38"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py38-hydra-core",
                        "py38-numpy",
                        "py38-pytorch",
                        "py38-regex",
                        "py38-sacrebleu",
                        "py38-tqdm",
                        "py38-omegaconf",
                        "py38-cffi",
                        "py38-cython"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py38-pytest"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "run",
                    "ports": [
                        "py38-transformers"
                    ]
                }
            ]
        },
        {
            "name": "py38-torchvision",
            "portdir": "python/py-torchvision",
            "version": "0.15.2",
            "license": "BSD",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/pytorch/vision",
            "description": "PyTorch datasets, transforms and models specific to computer vision",
            "long_description": "The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision.",
            "active": false,
            "categories": [
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "py38-setuptools",
                        "py38-wheel",
                        "clang-16"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py38-pytorch",
                        "zmq",
                        "python38",
                        "py38-Pillow"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py38-pytest"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "run",
                    "ports": [
                        "py38-allennlp",
                        "py38-kraken",
                        "py38-transformers"
                    ]
                }
            ]
        },
        {
            "name": "py39-torchvision",
            "portdir": "python/py-torchvision",
            "version": "0.15.2",
            "license": "BSD",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/pytorch/vision",
            "description": "PyTorch datasets, transforms and models specific to computer vision",
            "long_description": "The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision.",
            "active": false,
            "categories": [
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "py39-wheel",
                        "py39-build",
                        "py39-installer",
                        "clang-17",
                        "py39-setuptools"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "zmq",
                        "python39",
                        "py39-Pillow",
                        "py39-pytorch"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py39-pytest"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "run",
                    "ports": [
                        "py39-allennlp",
                        "py39-kraken",
                        "py39-transformers"
                    ]
                }
            ]
        },
        {
            "name": "py37-torchvision",
            "portdir": "python/py-torchvision",
            "version": "0.13.0",
            "license": "BSD",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/pytorch/vision",
            "description": "PyTorch datasets, transforms and models specific to computer vision",
            "long_description": "The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision.",
            "active": false,
            "categories": [
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "py37-setuptools",
                        "py37-wheel",
                        "clang-14"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py37-pytorch",
                        "zmq",
                        "python37",
                        "py37-Pillow"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py37-pytest"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "py37-torchtext",
            "portdir": "python/py-torchtext",
            "version": "0.8.1",
            "license": "BSD",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/pytorch/text",
            "description": "PyTorch data loaders and abstractions for text and NLP",
            "long_description": "PyTorch data loaders and abstractions for text and NLP",
            "active": false,
            "categories": [
                "python"
            ],
            "maintainers": [
                {
                    "name": "jonesc",
                    "github": "cjones051073",
                    "ports_count": 220
                }
            ],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "cmake",
                        "py37-setuptools",
                        "clang-9.0",
                        "ninja"
                    ]
                },
                {
                    "type": "fetch",
                    "ports": [
                        "git"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py37-spaCy-models",
                        "py37-spaCy",
                        "py37-pytorch",
                        "py37-nltk",
                        "python37"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "py38-torchtext",
            "portdir": "python/py-torchtext",
            "version": "0.13.1",
            "license": "BSD",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/pytorch/text",
            "description": "PyTorch data loaders and abstractions for text and NLP",
            "long_description": "PyTorch data loaders and abstractions for text and NLP",
            "active": false,
            "categories": [
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "cmake",
                        "ninja",
                        "py38-setuptools",
                        "clang-15"
                    ]
                },
                {
                    "type": "fetch",
                    "ports": [
                        "git"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "zmq",
                        "py38-spaCy-models",
                        "python38",
                        "py38-nltk",
                        "py38-pytorch",
                        "py38-spaCy"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "run",
                    "ports": [
                        "py38-transformers"
                    ]
                }
            ]
        },
        {
            "name": "py39-torchtext",
            "portdir": "python/py-torchtext",
            "version": "0.13.1",
            "license": "BSD",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/pytorch/text",
            "description": "PyTorch data loaders and abstractions for text and NLP",
            "long_description": "PyTorch data loaders and abstractions for text and NLP",
            "active": false,
            "categories": [
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "ninja",
                        "clang-17",
                        "py39-installer",
                        "py39-build",
                        "py39-wheel",
                        "py39-setuptools",
                        "cmake"
                    ]
                },
                {
                    "type": "fetch",
                    "ports": [
                        "git"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py39-spaCy-models",
                        "py39-spaCy",
                        "py39-pytorch",
                        "py39-nltk",
                        "python39",
                        "zmq"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "run",
                    "ports": [
                        "py39-transformers"
                    ]
                }
            ]
        },
        {
            "name": "py38-transformers",
            "portdir": "python/py-transformers",
            "version": "4.21.2",
            "license": "Apache-2",
            "platforms": "{darwin any}",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://huggingface.co/transformers/",
            "description": "State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch",
            "long_description": "🤗 Transformers provides thousands of pretrained models to perform tasks on texts such as classification, information extraction, question answering, summarization, translation, text generation, etc in 100+ languages. Its aim is to make cutting-edge NLP easier to use for everyone.",
            "active": false,
            "categories": [
                "textproc",
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "py38-setuptools",
                        "py38-wheel",
                        "py38-build",
                        "clang-14",
                        "py38-installer"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "python38"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py38-cookiecutter",
                        "py38-datasets",
                        "py38-elasticsearch",
                        "py38-fairseq",
                        "py38-fastapi",
                        "py38-fastprogress",
                        "py38-filelock",
                        "py38-fire",
                        "py38-flake8",
                        "py38-fugashi",
                        "py38-h5py",
                        "py38-importlib-metadata",
                        "py38-isort",
                        "py38-keras2onnx",
                        "py38-matplotlib",
                        "py38-nltk",
                        "py38-numpy",
                        "py38-onnxconverter-common",
                        "py38-packaging",
                        "py38-pandas",
                        "py38-parameterized",
                        "py38-protobuf3",
                        "py38-psutil",
                        "py38-pydantic",
                        "py38-pytorch",
                        "py38-pytorch-lightning",
                        "py38-recommonmark",
                        "py38-regex",
                        "py38-requests",
                        "py38-sacrebleu",
                        "py38-sacremoses",
                        "py38-scikit-learn",
                        "py38-seqeval",
                        "py38-soundfile",
                        "py38-sphinx",
                        "py38-starlette",
                        "py38-tensorboardX",
                        "py38-tensorflow-datasets",
                        "py38-timeout-decorator",
                        "py38-tokenizers",
                        "py38-torchaudio",
                        "py38-torchvision",
                        "py38-tqdm",
                        "py38-unidic",
                        "py38-unidic-lite",
                        "py38-uvicorn",
                        "py38-huggingface_hub",
                        "py38-tensorflow-macos",
                        "py38-torchtext",
                        "py38-faiss",
                        "py38-Pillow",
                        "py38-absl",
                        "py38-black",
                        "py38-conllu"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py38-pytest",
                        "py38-pytest-sugar",
                        "py38-pytest-xdist",
                        "py38-huggingface_hub"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "run",
                    "ports": [
                        "py38-allennlp",
                        "py38-sentence-transformers"
                    ]
                }
            ]
        },
        {
            "name": "py39-transformers",
            "portdir": "python/py-transformers",
            "version": "4.21.2",
            "license": "Apache-2",
            "platforms": "{darwin any}",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://huggingface.co/transformers/",
            "description": "State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch",
            "long_description": "Transformers provides thousands of pretrained models to perform tasks on texts such as classification, information extraction, question answering, summarization, translation, text generation, etc in 100+ languages. Its aim is to make cutting-edge NLP easier to use for everyone.",
            "active": false,
            "categories": [
                "textproc",
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "py39-setuptools",
                        "py39-wheel",
                        "py39-build",
                        "py39-installer",
                        "clang-18"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "python39"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py39-datasets",
                        "py39-elasticsearch",
                        "py39-fairseq",
                        "py39-fastapi",
                        "py39-fastprogress",
                        "py39-filelock",
                        "py39-fire",
                        "py39-fugashi",
                        "py39-h5py",
                        "py39-importlib-metadata",
                        "py39-keras2onnx",
                        "py39-matplotlib",
                        "py39-nltk",
                        "py39-numpy",
                        "py39-onnxconverter-common",
                        "py39-packaging",
                        "py39-pandas",
                        "py39-parameterized",
                        "py39-protobuf3",
                        "py39-psutil",
                        "py39-pydantic",
                        "py39-pytorch",
                        "py39-pytorch-lightning",
                        "py39-recommonmark",
                        "py39-regex",
                        "py39-requests",
                        "py39-sacrebleu",
                        "py39-sacremoses",
                        "py39-scikit-learn",
                        "py39-seqeval",
                        "py39-soundfile",
                        "py39-sphinx",
                        "py39-starlette",
                        "py39-tensorboardX",
                        "py39-tensorflow-datasets",
                        "py39-timeout-decorator",
                        "py39-tokenizers",
                        "py39-torchaudio",
                        "py39-torchtext",
                        "py39-torchvision",
                        "py39-unidic",
                        "py39-unidic-lite",
                        "py39-uvicorn",
                        "py39-huggingface_hub",
                        "py39-tensorflow-macos",
                        "py39-tqdm",
                        "py39-faiss",
                        "py39-Pillow",
                        "py39-absl",
                        "py39-conllu",
                        "py39-cookiecutter"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py39-pytest",
                        "py39-pytest-sugar",
                        "py39-pytest-xdist",
                        "py39-huggingface_hub"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "run",
                    "ports": [
                        "py39-allennlp",
                        "py39-sentence-transformers"
                    ]
                }
            ]
        },
        {
            "name": "py-fairseq",
            "portdir": "python/py-fairseq",
            "version": "0.12.2",
            "license": "MIT",
            "platforms": "any",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/pytorch/fairseq",
            "description": "Facebook AI Research Sequence-to-Sequence Toolkit written in Python.",
            "long_description": "Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks.",
            "active": true,
            "categories": [
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "clang-18"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py310-fairseq"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "py310-fairseq",
            "portdir": "python/py-fairseq",
            "version": "0.12.2",
            "license": "MIT",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/pytorch/fairseq",
            "description": "Facebook AI Research Sequence-to-Sequence Toolkit written in Python.",
            "long_description": "Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks.",
            "active": true,
            "categories": [
                "python"
            ],
            "maintainers": [],
            "variants": [
                "universal"
            ],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "py310-wheel",
                        "py310-installer",
                        "clang-18",
                        "py310-setuptools",
                        "py310-build"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "python310",
                        "py310-setuptools"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py310-hydra-core",
                        "py310-sacrebleu",
                        "py310-omegaconf",
                        "py310-cython",
                        "py310-regex",
                        "py310-numpy",
                        "py310-cffi",
                        "py310-tqdm",
                        "py310-pytorch"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py310-pytest"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "lib",
                    "ports": [
                        "py-fairseq"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py310-transformers"
                    ]
                }
            ]
        },
        {
            "name": "py-pytorch-lightning",
            "portdir": "python/py-pytorch-lightning",
            "version": "1.6.5",
            "license": "Apache-2",
            "platforms": "any",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/PyTorchLightning/pytorch-lightning",
            "description": "The lightweight PyTorch wrapper for high-performance AI research.",
            "long_description": "Lightning disentangles PyTorch code to decouple the science from the engineering.",
            "active": true,
            "categories": [
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "clang-18"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py310-pytorch-lightning"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "py310-pytorch-lightning",
            "portdir": "python/py-pytorch-lightning",
            "version": "1.6.5",
            "license": "Apache-2",
            "platforms": "{darwin any}",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/PyTorchLightning/pytorch-lightning",
            "description": "The lightweight PyTorch wrapper for high-performance AI research.",
            "long_description": "Lightning disentangles PyTorch code to decouple the science from the engineering.",
            "active": true,
            "categories": [
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "py310-setuptools",
                        "clang-18",
                        "py310-installer",
                        "py310-build",
                        "py310-wheel"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "python310"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py310-tensorboard",
                        "py310-pytorch",
                        "py310-fsspec",
                        "py310-tqdm",
                        "py310-yaml",
                        "py310-future",
                        "py310-numpy"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "lib",
                    "ports": [
                        "py-pytorch-lightning"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py310-transformers",
                        "py310-kraken"
                    ]
                }
            ]
        },
        {
            "name": "py-sentence-transformers",
            "portdir": "python/py-sentence-transformers",
            "version": "2.0.0",
            "license": "Apache-2",
            "platforms": "any",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/UKPLab/sentence-transformers",
            "description": "Sentence Embeddings using BERT / RoBERTa / XLM-R",
            "long_description": "This framework provides an easy method to compute dense vector representations for sentences, paragraphs, and images. The models are based on transformer networks like BERT / RoBERTa / XLM-RoBERTa etc. and achieve state-of-the-art performance in various task. Text is embedding in vector space such that similar text is close and can efficiently be found using cosine similarity. We provide an increasing number of state-of-the-art pretrained models for more than 100 languages, fine-tuned for various use-cases. Further, this framework allows an easy fine-tuning of custom embeddings models, to achieve maximal performance on your specific task.",
            "active": true,
            "categories": [
                "textproc",
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "clang-18"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py310-sentence-transformers"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "py310-sentence-transformers",
            "portdir": "python/py-sentence-transformers",
            "version": "2.0.0",
            "license": "Apache-2",
            "platforms": "{darwin any}",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/UKPLab/sentence-transformers",
            "description": "Sentence Embeddings using BERT / RoBERTa / XLM-R",
            "long_description": "This framework provides an easy method to compute dense vector representations for sentences, paragraphs, and images. The models are based on transformer networks like BERT / RoBERTa / XLM-RoBERTa etc. and achieve state-of-the-art performance in various task. Text is embedding in vector space such that similar text is close and can efficiently be found using cosine similarity. We provide an increasing number of state-of-the-art pretrained models for more than 100 languages, fine-tuned for various use-cases. Further, this framework allows an easy fine-tuning of custom embeddings models, to achieve maximal performance on your specific task.",
            "active": true,
            "categories": [
                "textproc",
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "py310-setuptools",
                        "py310-wheel",
                        "py310-build",
                        "py310-installer",
                        "clang-18"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "python310"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py310-pytorch",
                        "py310-sentencepiece",
                        "py310-transformers",
                        "py310-numpy",
                        "py310-scipy",
                        "py310-tqdm",
                        "py310-scikit-learn",
                        "py310-nltk"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py310-pytest"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "lib",
                    "ports": [
                        "py-sentence-transformers"
                    ]
                }
            ]
        },
        {
            "name": "py-torchtext",
            "portdir": "python/py-torchtext",
            "version": "0.13.1",
            "license": "BSD",
            "platforms": "any",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/pytorch/text",
            "description": "PyTorch data loaders and abstractions for text and NLP",
            "long_description": "PyTorch data loaders and abstractions for text and NLP",
            "active": true,
            "categories": [
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "clang-18"
                    ]
                },
                {
                    "type": "fetch",
                    "ports": [
                        "git"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py310-torchtext"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "py-torchaudio",
            "portdir": "python/py-torchaudio",
            "version": "0.12.0",
            "license": "BSD",
            "platforms": "any",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/pytorch/audio",
            "description": "Data manipulation and transformation for audio signal processing, powered by PyTorch",
            "long_description": "The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the same philosophy of providing strong GPU acceleration, having a focus on trainable features through the autograd system, and having consistent style (tensor names and dimension names). Therefore, it is primarily a machine learning library and not a general signal processing library. The benefits of PyTorch can be seen in torchaudio through having all the computations be through PyTorch operations which makes it easy to use and feel like a natural extension.",
            "active": true,
            "categories": [
                "audio",
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "clang-18"
                    ]
                },
                {
                    "type": "fetch",
                    "ports": [
                        "git"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py310-torchaudio"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "py310-torchtext",
            "portdir": "python/py-torchtext",
            "version": "0.13.1",
            "license": "BSD",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/pytorch/text",
            "description": "PyTorch data loaders and abstractions for text and NLP",
            "long_description": "PyTorch data loaders and abstractions for text and NLP",
            "active": true,
            "categories": [
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "ninja",
                        "clang-20",
                        "py310-installer",
                        "py310-build",
                        "py310-wheel",
                        "py310-setuptools",
                        "cmake"
                    ]
                },
                {
                    "type": "fetch",
                    "ports": [
                        "git"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py310-spaCy-models",
                        "py310-spaCy",
                        "py310-pytorch",
                        "py310-nltk",
                        "python310",
                        "zmq"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "lib",
                    "ports": [
                        "py-torchtext"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py310-transformers"
                    ]
                }
            ]
        },
        {
            "name": "py310-torchaudio",
            "portdir": "python/py-torchaudio",
            "version": "0.12.0",
            "license": "BSD",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/pytorch/audio",
            "description": "Data manipulation and transformation for audio signal processing, powered by PyTorch",
            "long_description": "The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the same philosophy of providing strong GPU acceleration, having a focus on trainable features through the autograd system, and having consistent style (tensor names and dimension names). Therefore, it is primarily a machine learning library and not a general signal processing library. The benefits of PyTorch can be seen in torchaudio through having all the computations be through PyTorch operations which makes it easy to use and feel like a natural extension.",
            "active": true,
            "categories": [
                "audio",
                "python"
            ],
            "maintainers": [],
            "variants": [
                "universal"
            ],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "cmake",
                        "clang-18",
                        "py310-installer",
                        "py310-build",
                        "py310-wheel",
                        "py310-setuptools",
                        "ninja"
                    ]
                },
                {
                    "type": "fetch",
                    "ports": [
                        "git"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "sox",
                        "py310-dill",
                        "python310",
                        "ffmpeg",
                        "libomp",
                        "zmq",
                        "py310-pytorch"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py310-pytest"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "lib",
                    "ports": [
                        "py-torchaudio"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py310-transformers"
                    ]
                }
            ]
        },
        {
            "name": "py-torchvision",
            "portdir": "python/py-torchvision",
            "version": "0.15.2",
            "license": "BSD",
            "platforms": "any",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/pytorch/vision",
            "description": "PyTorch datasets, transforms and models specific to computer vision",
            "long_description": "The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision.",
            "active": true,
            "categories": [
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "clang-18"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py310-torchvision"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "py-transformers",
            "portdir": "python/py-transformers",
            "version": "4.21.2",
            "license": "Apache-2",
            "platforms": "any",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://huggingface.co/transformers/",
            "description": "State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch",
            "long_description": "Transformers provides thousands of pretrained models to perform tasks on texts such as classification, information extraction, question answering, summarization, translation, text generation, etc in 100+ languages. Its aim is to make cutting-edge NLP easier to use for everyone.",
            "active": true,
            "categories": [
                "textproc",
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "clang-18"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py310-transformers"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "py310-torchvision",
            "portdir": "python/py-torchvision",
            "version": "0.15.2",
            "license": "BSD",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/pytorch/vision",
            "description": "PyTorch datasets, transforms and models specific to computer vision",
            "long_description": "The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision.",
            "active": true,
            "categories": [
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "py310-wheel",
                        "py310-build",
                        "py310-installer",
                        "clang-20",
                        "py310-setuptools"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "zmq",
                        "python310",
                        "py310-Pillow",
                        "py310-pytorch"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py310-pytest"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "lib",
                    "ports": [
                        "py-torchvision"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py310-allennlp",
                        "py310-transformers",
                        "py310-kraken"
                    ]
                }
            ]
        },
        {
            "name": "py310-transformers",
            "portdir": "python/py-transformers",
            "version": "4.21.2",
            "license": "Apache-2",
            "platforms": "{darwin any}",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://huggingface.co/transformers/",
            "description": "State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch",
            "long_description": "Transformers provides thousands of pretrained models to perform tasks on texts such as classification, information extraction, question answering, summarization, translation, text generation, etc in 100+ languages. Its aim is to make cutting-edge NLP easier to use for everyone.",
            "active": true,
            "categories": [
                "textproc",
                "python"
            ],
            "maintainers": [],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "py310-setuptools",
                        "py310-wheel",
                        "py310-build",
                        "py310-installer",
                        "clang-18"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "python310"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py310-fastprogress",
                        "py310-filelock",
                        "py310-importlib-metadata",
                        "py310-pandas",
                        "py310-cookiecutter",
                        "py310-matplotlib",
                        "py310-tqdm",
                        "py310-sphinx",
                        "py310-scikit-learn",
                        "py310-absl",
                        "py310-protobuf3",
                        "py310-parameterized",
                        "py310-h5py",
                        "py310-pydantic",
                        "py310-psutil",
                        "py310-soundfile",
                        "py310-nltk",
                        "py310-recommonmark",
                        "py310-fastapi",
                        "py310-starlette",
                        "py310-tensorflow-macos",
                        "py310-uvicorn",
                        "py310-pytorch",
                        "py310-tensorflow-datasets",
                        "py310-fire",
                        "py310-seqeval",
                        "py310-timeout-decorator",
                        "py310-unidic-lite",
                        "py310-faiss",
                        "py310-conllu",
                        "py310-onnxconverter-common",
                        "py310-fugashi",
                        "py310-sacremoses",
                        "py310-tokenizers",
                        "py310-elasticsearch",
                        "py310-huggingface_hub",
                        "py310-pytorch-lightning",
                        "py310-unidic",
                        "py310-tensorboardX",
                        "py310-sacrebleu",
                        "py310-keras2onnx",
                        "py310-datasets",
                        "py310-torchaudio",
                        "py310-torchtext",
                        "py310-torchvision",
                        "py310-fairseq",
                        "py310-requests",
                        "py310-regex",
                        "py310-packaging",
                        "py310-numpy",
                        "py310-Pillow"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py310-pytest",
                        "py310-pytest-xdist",
                        "py310-pytest-sugar",
                        "py310-huggingface_hub"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "lib",
                    "ports": [
                        "py-transformers"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py310-allennlp",
                        "py310-sentence-transformers"
                    ]
                }
            ]
        },
        {
            "name": "py38-pyperclip",
            "portdir": "python/py-pyperclip",
            "version": "1.9.0",
            "license": "BSD",
            "platforms": "{darwin any}",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/asweigart/pyperclip",
            "description": "A cross-platform clipboard module for Python",
            "long_description": "A cross-platform clipboard module for Python. It currently handles only plain text.",
            "active": false,
            "categories": [
                "python"
            ],
            "maintainers": [
                {
                    "name": "petr",
                    "github": "petrrr",
                    "ports_count": 596
                }
            ],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "py38-build",
                        "py38-setuptools",
                        "py38-wheel",
                        "py38-installer",
                        "clang-17"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "python38"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py38-pytest"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "lib",
                    "ports": [
                        "py38-mitmproxy"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py38-cmd2"
                    ]
                }
            ]
        },
        {
            "name": "py27-pyperclip",
            "portdir": "python/py-pyperclip",
            "version": "1.8.2",
            "license": "BSD",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/asweigart/pyperclip",
            "description": "A cross-platform clipboard module for Python",
            "long_description": "A cross-platform clipboard module for Python. It currently handles only plain text.",
            "active": false,
            "categories": [
                "python"
            ],
            "maintainers": [
                {
                    "name": "petr",
                    "github": "petrrr",
                    "ports_count": 596
                }
            ],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "clang-9.0",
                        "py27-setuptools"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "python27"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "py35-pyperclip",
            "portdir": "python/py-pyperclip",
            "version": "1.8.2",
            "license": "BSD",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/asweigart/pyperclip",
            "description": "A cross-platform clipboard module for Python",
            "long_description": "A cross-platform clipboard module for Python. It currently handles only plain text.",
            "active": false,
            "categories": [
                "python"
            ],
            "maintainers": [
                {
                    "name": "petr",
                    "github": "petrrr",
                    "ports_count": 596
                }
            ],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "clang-9.0",
                        "py35-setuptools"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "python35"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "py36-pyperclip",
            "portdir": "python/py-pyperclip",
            "version": "1.8.2",
            "license": "BSD",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/asweigart/pyperclip",
            "description": "A cross-platform clipboard module for Python",
            "long_description": "A cross-platform clipboard module for Python. It currently handles only plain text.",
            "active": false,
            "categories": [
                "python"
            ],
            "maintainers": [
                {
                    "name": "petr",
                    "github": "petrrr",
                    "ports_count": 596
                }
            ],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "clang-9.0",
                        "py36-setuptools"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "python36"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "run",
                    "ports": [
                        "py36-cmd2"
                    ]
                }
            ]
        },
        {
            "name": "py37-pyperclip",
            "portdir": "python/py-pyperclip",
            "version": "1.8.2",
            "license": "BSD",
            "platforms": "{darwin any}",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/asweigart/pyperclip",
            "description": "A cross-platform clipboard module for Python",
            "long_description": "A cross-platform clipboard module for Python. It currently handles only plain text.",
            "active": false,
            "categories": [
                "python"
            ],
            "maintainers": [
                {
                    "name": "petr",
                    "github": "petrrr",
                    "ports_count": 596
                }
            ],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "py37-build",
                        "py37-setuptools",
                        "py37-wheel",
                        "py37-installer",
                        "clang-16"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "python37"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py37-pytest"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "lib",
                    "ports": [
                        "py37-mitmproxy"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py37-cmd2"
                    ]
                }
            ]
        },
        {
            "name": "py39-pyperclip",
            "portdir": "python/py-pyperclip",
            "version": "1.9.0",
            "license": "BSD",
            "platforms": "{darwin any}",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://github.com/asweigart/pyperclip",
            "description": "A cross-platform clipboard module for Python",
            "long_description": "A cross-platform clipboard module for Python. It currently handles only plain text.",
            "active": false,
            "categories": [
                "python"
            ],
            "maintainers": [
                {
                    "name": "petr",
                    "github": "petrrr",
                    "ports_count": 596
                }
            ],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "py39-build",
                        "py39-setuptools",
                        "py39-wheel",
                        "py39-installer",
                        "clang-18"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "python39"
                    ]
                },
                {
                    "type": "test",
                    "ports": [
                        "py39-pytest"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "lib",
                    "ports": [
                        "py39-mitmproxy"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "py39-cmd2"
                    ]
                }
            ]
        },
        {
            "name": "py38-awscrt",
            "portdir": "python/py-awscrt",
            "version": "0.19.19",
            "license": "Apache-2",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://aws.amazon.com/cli/",
            "description": "A common runtime for AWS Python projects",
            "long_description": "A common runtime for AWS Python projects",
            "active": false,
            "categories": [
                "devel",
                "python"
            ],
            "maintainers": [
                {
                    "name": "davidgilman1",
                    "github": "dgilman",
                    "ports_count": 141
                }
            ],
            "variants": [
                "universal"
            ],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "clang-16",
                        "py38-build",
                        "py38-installer",
                        "cmake",
                        "py38-setuptools",
                        "py38-wheel"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py38-setuptools",
                        "python38"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "lib",
                    "ports": [
                        "py38-awscli2"
                    ]
                }
            ]
        },
        {
            "name": "py37-awscrt",
            "portdir": "python/py-awscrt",
            "version": "0.14.0",
            "license": "Apache-2",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://aws.amazon.com/cli/",
            "description": "A common runtime for AWS Python projects",
            "long_description": "A common runtime for AWS Python projects",
            "active": false,
            "categories": [
                "devel",
                "python"
            ],
            "maintainers": [
                {
                    "name": "davidgilman1",
                    "github": "dgilman",
                    "ports_count": 141
                }
            ],
            "variants": [
                "universal"
            ],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "cmake",
                        "clang-14"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "python37",
                        "py37-setuptools"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "lib",
                    "ports": [
                        "py37-awscli2"
                    ]
                }
            ]
        },
        {
            "name": "py39-awscrt",
            "portdir": "python/py-awscrt",
            "version": "0.27.6",
            "license": "Apache-2",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://aws.amazon.com/cli/",
            "description": "A common runtime for AWS Python projects",
            "long_description": "A common runtime for AWS Python projects",
            "active": false,
            "categories": [
                "devel",
                "python"
            ],
            "maintainers": [
                {
                    "name": "davidgilman1",
                    "github": "dgilman",
                    "ports_count": 141
                }
            ],
            "variants": [
                "universal"
            ],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "clang-18",
                        "py39-build",
                        "py39-installer",
                        "cmake",
                        "py39-setuptools",
                        "py39-wheel"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py39-setuptools",
                        "python39"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "lib",
                    "ports": [
                        "py39-awscli2"
                    ]
                }
            ]
        },
        {
            "name": "py38-awscli2",
            "portdir": "python/py-awscli2",
            "version": "2.15.53",
            "license": "Apache-2",
            "platforms": "{darwin any}",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://aws.amazon.com/cli/",
            "description": "Universal Command Line Environment for Amazon Web Services.",
            "long_description": "Universal Command Line Environment for Amazon Web Services.",
            "active": false,
            "categories": [
                "devel",
                "python"
            ],
            "maintainers": [
                {
                    "name": "davidgilman1",
                    "github": "dgilman",
                    "ports_count": 141
                }
            ],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "clang-16",
                        "py38-flit_core",
                        "py38-setuptools",
                        "py38-build",
                        "py38-installer"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py38-docutils",
                        "py38-jmespath",
                        "py38-prompt_toolkit",
                        "py38-ruamel-yaml",
                        "python38",
                        "py38-urllib3",
                        "py38-awscrt",
                        "py38-ruamel-yaml-clib",
                        "py38-colorama",
                        "py38-cryptography",
                        "py38-dateutil",
                        "py38-distro"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "awscli_select"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "py37-awscli2",
            "portdir": "python/py-awscli2",
            "version": "2.4.25",
            "license": "Apache-2",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://aws.amazon.com/cli/",
            "description": "Universal Command Line Environment for Amazon Web Services.",
            "long_description": "Universal Command Line Environment for Amazon Web Services.",
            "active": false,
            "categories": [
                "devel",
                "python"
            ],
            "maintainers": [
                {
                    "name": "davidgilman1",
                    "github": "dgilman",
                    "ports_count": 141
                }
            ],
            "variants": [
                "universal"
            ],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "clang-13",
                        "py37-setuptools"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py37-cryptography",
                        "py37-dateutil",
                        "py37-distro",
                        "py37-docutils",
                        "py37-jmespath",
                        "py37-prompt_toolkit",
                        "python37",
                        "py37-ruamel-yaml-clib",
                        "py37-urllib3",
                        "py37-wcwidth",
                        "py37-awscrt",
                        "py37-ruamel-yaml",
                        "py37-colorama"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "awscli_select"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "py39-awscli2",
            "portdir": "python/py-awscli2",
            "version": "2.31.22",
            "license": "Apache-2",
            "platforms": "{darwin >= 20}",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://aws.amazon.com/cli/",
            "description": "Universal Command Line Environment for Amazon Web Services.",
            "long_description": "Universal Command Line Environment for Amazon Web Services.",
            "active": false,
            "categories": [
                "devel",
                "python"
            ],
            "maintainers": [
                {
                    "name": "davidgilman1",
                    "github": "dgilman",
                    "ports_count": 141
                }
            ],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "clang-18",
                        "py39-flit_core",
                        "py39-setuptools",
                        "py39-build",
                        "py39-installer"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py39-jmespath",
                        "py39-prompt_toolkit",
                        "py39-ruamel-yaml",
                        "python39",
                        "py39-urllib3",
                        "py39-awscrt",
                        "py39-ruamel-yaml-clib",
                        "py39-colorama",
                        "py39-dateutil",
                        "py39-distro",
                        "py39-docutils"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "awscli_select"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "astyle",
            "portdir": "devel/astyle",
            "version": "3.6.13",
            "license": "MIT",
            "platforms": "darwin",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://astyle.sourceforge.net",
            "description": "source code beautifier for the C, C++, C# and Java programming languages",
            "long_description": "Artistic Style is a source code indenter, source code formatter, and source code beautifier for the C, C++, C# and Java programming languages.",
            "active": true,
            "categories": [
                "devel"
            ],
            "maintainers": [],
            "variants": [
                "debug",
                "java",
                "universal"
            ],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "cmake",
                        "clang-20"
                    ]
                }
            ],
            "depends_on": [
                {
                    "type": "run",
                    "ports": [
                        "py36-gpilab-framework",
                        "py39-gpilab-framework",
                        "py38-gpilab-framework",
                        "py37-gpilab-framework"
                    ]
                }
            ]
        },
        {
            "name": "py-awscli2",
            "portdir": "python/py-awscli2",
            "version": "2.31.33",
            "license": "Apache-2",
            "platforms": "any",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://aws.amazon.com/cli/",
            "description": "Universal Command Line Environment for Amazon Web Services.",
            "long_description": "Universal Command Line Environment for Amazon Web Services.",
            "active": true,
            "categories": [
                "devel",
                "python"
            ],
            "maintainers": [
                {
                    "name": "davidgilman1",
                    "github": "dgilman",
                    "ports_count": 141
                }
            ],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "clang-18"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py313-awscli2"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "py-awscrt",
            "portdir": "python/py-awscrt",
            "version": "0.28.4",
            "license": "Apache-2",
            "platforms": "any",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://aws.amazon.com/cli/",
            "description": "A common runtime for AWS Python projects",
            "long_description": "A common runtime for AWS Python projects",
            "active": true,
            "categories": [
                "devel",
                "python"
            ],
            "maintainers": [
                {
                    "name": "davidgilman1",
                    "github": "dgilman",
                    "ports_count": 141
                }
            ],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "pkgconfig",
                        "clang-18"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "openssl3",
                        "py313-awscrt"
                    ]
                }
            ],
            "depends_on": []
        },
        {
            "name": "py310-awscli2",
            "portdir": "python/py-awscli2",
            "version": "2.31.33",
            "license": "Apache-2",
            "platforms": "{darwin >= 20}",
            "epoch": 0,
            "replaced_by": null,
            "homepage": "https://aws.amazon.com/cli/",
            "description": "Universal Command Line Environment for Amazon Web Services.",
            "long_description": "Universal Command Line Environment for Amazon Web Services.",
            "active": true,
            "categories": [
                "devel",
                "python"
            ],
            "maintainers": [
                {
                    "name": "davidgilman1",
                    "github": "dgilman",
                    "ports_count": 141
                }
            ],
            "variants": [],
            "dependencies": [
                {
                    "type": "build",
                    "ports": [
                        "clang-18",
                        "py310-setuptools",
                        "py310-flit_core",
                        "py310-build",
                        "py310-installer"
                    ]
                },
                {
                    "type": "lib",
                    "ports": [
                        "py310-jmespath",
                        "py310-prompt_toolkit",
                        "py310-distro",
                        "python310",
                        "py310-ruamel-yaml-clib",
                        "py310-awscrt",
                        "py310-ruamel-yaml",
                        "py310-urllib3",
                        "py310-colorama",
                        "py310-dateutil",
                        "py310-docutils"
                    ]
                },
                {
                    "type": "run",
                    "ports": [
                        "awscli_select"
                    ]
                }
            ],
            "depends_on": []
        }
    ]
}