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It can be used as a callable library or using a stand-alone executable. It can be called through AIMMS (through the AIMMSlinks project), AMPL (natively), CMPL, GAMS (through the GAMSlinks project), JuMP, Mathematica, MiniZinc, MPL (through the CoinMP project), PuLP, Python (e.g., cbcpy), and OpenSolver for Excel, among others.", "dev_url": "https://github.com/coin-or/Cbc", "doc_source_url": null, "doc_url": null, "home": "https://projects.coin-or.org/Cbc", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "EPL-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": { "2.10.7": { "weak": [ "coin-or-cbc >=2.10,<2.11.0a0" ] } }, "source_git_url": null, "source_url": "https://github.com/coin-or/Cbc/archive/releases/2.10.7.tar.gz", "subdirs": [ "linux-ppc64le" ], "summary": "COIN-OR branch and cut (Cbc)", "tags": null, "text_prefix": true, "timestamp": 1748473166, "version": "2.10.7" }, "coin-or-cgl": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "The COIN-OR Cut Generation Library (Cgl) is a collection of cut generators that can be used with other COIN-OR packages that make use of cuts, such as, among others, the linear solver Clp or the mixed integer linear programming solvers Cbc or BCP. 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It is primarily meant to be used as a callable library, but a basic, stand-alone executable version is also available. It is designed to find solutions of mathematical optimization problems of the form minimize c'x such that lhs \u2264 Ax \u2264 rhs and lb \u2264 x \u2264 ub CLP includes primal and dual Simplex solvers. Both dual and primal algorithms can use matrix storage methods provided by the user (0-1 and network matrices are already supported in addition to the default sparse matrix). The dual algorithm has Dantzig and Steepest edge row pivot choices; new ones may be provided by the user. The same is true for the column pivot choice of the primal algorithm. The primal can also use a non linear cost which should work for piecewise linear convex functions. CLP also includes a barrier method for solving LPs.", "dev_url": "https://github.com/coin-or/Clp", "doc_source_url": null, "doc_url": null, "home": "https://projects.coin-or.org/Clp", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "EPL-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": { "1.17.7": { "weak": [ "coin-or-clp >=1.17,<1.18.0a0" ] } }, "source_git_url": null, "source_url": "https://github.com/coin-or/Clp/archive/releases/1.17.7.tar.gz", "subdirs": [ "linux-ppc64le" ], "summary": "COIN-OR linear programming (Clp)", "tags": null, "text_prefix": true, "timestamp": 1748472959, "version": "1.17.7" }, "coin-or-osi": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Osi (Open Solver Interface) provides an abstract base class to a generic linear programming (LP) solver, along with derived classes for specific solvers. 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Among others the following operations are supported: - creating the LP formulation; - directly modifying the formulation by adding rows/columns; - modifying the formulation by adding cutting planes provided by CGL; - solving the formulation (and resolving after modifications); - extracting solution information; - invoking the underlying solver's branch-and-bound component.", "dev_url": "https://github.com/coin-or/Osi", "doc_source_url": null, "doc_url": null, "home": "https://github.com/coin-or/Osi", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "EPL-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": { "0.108.7": { "weak": [ "coin-or-osi >=0.108,<0.109.0a0" ] } }, "source_git_url": null, "source_url": "https://github.com/coin-or/Osi/archive/releases/0.108.7.tar.gz", "subdirs": [ "linux-ppc64le" ], "summary": "Coin OR Open Solver Interface (OSI)", "tags": null, "text_prefix": true, "timestamp": 1748472881, "version": "0.108.7" }, "coin-or-utils": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "CoinUtils (Coin-OR Utilities) is an open-source collection of classes and functions that are generally useful to more than one COIN-OR project. 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C++ Libraries and protoc, the protobuf compiler.", "tags": null, "text_prefix": false, "timestamp": 1748447559, "version": "3.21.12" }, "libsndfile": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": "https://github.com/erikd/libsndfile", "doc_source_url": null, "doc_url": null, "home": "http://www.mega-nerd.com/libsndfile", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "LGPL-2.1", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": { "1.0.31": { "weak": [ "libsndfile >=1.0.31,<1.1.0a0" ] } }, "source_git_url": null, "source_url": "https://github.com/libsndfile/libsndfile/releases/download/1.0.31/libsndfile-1.0.31.tar.bz2", "subdirs": [ "linux-ppc64le" ], "summary": "libsndfile - a C library for reading and writing files containing sampled sound (such as MS Windows WAV and the Apple/SGI AIFF format) through one standard library interface", "tags": null, "text_prefix": true, "timestamp": 1748473819, "version": "1.0.31" }, "libtensorflow": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "TensorFlow provides multiple APIs.The lowest level API, TensorFlow Core provides you with complete programming control. 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"recipe_origin": null, "run_exports": {}, "source_git_url": "https://github.com/microsoft/LightGBM", "source_url": null, "subdirs": [ "linux-ppc64le" ], "summary": "Light Gradient Boosting Machine that uses tree based learning algorithms", "tags": null, "text_prefix": false, "timestamp": 1748475336, "version": "4.2.0" }, "lightning-app": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Use Lightning Apps to build everything from production-ready, multi-cloud ML systems to simple research demos.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/Lightning-AI/lightning", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Apache-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": "https://github.com/Lightning-AI/lightning", "source_url": null, "subdirs": [ "noarch" ], "summary": "Use Lightning Apps to build 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After modeling your problem in the programming language of your choice, you can use any of a half dozen solvers to solve it: commercial solvers such as Gurobi or CPLEX, or open-source solvers such as SCIP, GLPK, or Google's GLOP and award-winning CP-SAT.", "dev_url": "https://github.com/google/or-tools", "doc_source_url": null, "doc_url": null, "home": "https://developers.google.com/optimization", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Apache-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": { "9.6": { "weak": [ "libortools >=9.6,<9.7.0a0" ] } }, "source_git_url": null, "source_url": "https://github.com/google/or-tools/archive/v9.6.tar.gz", "subdirs": [ "linux-ppc64le" ], "summary": "Google Operations Research Tools (or-tools) python package", "tags": null, "text_prefix": false, "timestamp": 1748473569, "version": "9.6" }, "ortools-python": { "activate.d": false, "binary_prefix": true, "deactivate.d": false, "description": "OR-Tools is an open source software suite for optimization, tuned for tackling the world's toughest problems in vehicle routing, flows, integer and linear programming, and constraint programming. 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It includes: -SSL.Connection objects, wrapping the methods of Python's portable sockets -Callbacks written in Python -Extensive error-handling mechanism, mirroring OpenSSL's error codes and much more.", "dev_url": "https://github.com/pyca/pyopenssl", "doc_source_url": "https://github.com/pyca/pyopenssl/blob/master/doc/index.rst", "doc_url": "https://pyopenssl.readthedocs.org/en/stable/", "home": "https://github.com/pyca/pyopenssl", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Apache-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.io/packages/source/p/pyOpenSSL/pyopenssl-24.2.1.tar.gz", "subdirs": [ "noarch" ], "summary": "Python wrapper module around the OpenSSL library", "tags": null, "text_prefix": false, "timestamp": 1748446492, "version": "24.2.1" }, "pytest-subprocess": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": "https://github.com/aklajnert/pytest-subprocess", "doc_source_url": null, "doc_url": null, "home": "https://pypi.org/project/pytest-subprocess/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.io/packages/source/p/pytest-subprocess/pytest_subprocess-1.5.2.tar.gz", "subdirs": [ "noarch" ], "summary": "A plugin to fake subprocess for pytest", "tags": null, "text_prefix": false, "timestamp": 1748455076, "version": "1.5.2" }, "python-flatbuffers": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "FlatBuffers is an efficient cross platform serialization library for C++, C#, C, Go, Java, JavaScript, Lobster, Lua, TypeScript, PHP, Python, and Rust. It was originally created at Google for game development and other performance-critical applications. This package is the python runtime library. The flatc compiler is in the flatbuffers conda package.", "dev_url": "https://github.com/google/flatbuffers", "doc_source_url": "https://github.com/google/flatbuffers/tree/master/docs", "doc_url": "https://google.github.io/flatbuffers/", "home": "https://google.github.io/flatbuffers/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Apache-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.io/packages/source/f/flatbuffers/flatbuffers-23.1.21.tar.gz", "subdirs": [ "noarch" ], "summary": "Python runtime library for use with the Flatbuffers serialization format.", "tags": null, "text_prefix": false, "timestamp": 1748457124, "version": "23.1.21" }, "python-multipart": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "python-multipart is an Apache2 licensed streaming multipart parser for Python. It's still under some development, but test coverage is currently 100%. Documentation is available [here](http://andrew-d.github.io/python-multipart/).", "dev_url": "https://github.com/andrew-d/python-multipart", "doc_source_url": null, "doc_url": "http://andrew-d.github.io/python-multipart/", "home": "https://github.com/andrew-d/python-multipart", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Apache-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/Kludex/python-multipart/archive/refs/tags/0.0.7.tar.gz", "subdirs": [ "noarch" ], "summary": "A streaming multipart parser for Python.", "tags": null, "text_prefix": false, "timestamp": 1748454720, "version": "0.0.7" }, "pytorch-base": { "activate.d": true, "binary_prefix": false, "deactivate.d": true, "description": "PyTorch is an optimized tensor library for deep learning using GPUs and CPUs", "dev_url": "https://github.com/pytorch/pytorch", "doc_source_url": null, "doc_url": "https://pytorch.org/docs/stable/index.html", "home": "http://pytorch.org/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "BSD 3-Clause", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": "https://github.com/pytorch/pytorch.git", "source_url": null, "subdirs": [ "linux-ppc64le" ], "summary": "PyTorch is an optimized tensor library for deep learning using GPUs and CPUs.", "tags": null, "text_prefix": true, "timestamp": 1748464918, "version": "2.1.2" }, "pytorch-cpu": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Meta-package to install CPU-only PyTorch variant", "dev_url": "https://github.com/pytorch/pytorch", "doc_source_url": null, "doc_url": "https://pytorch.org/docs/stable/index.html", "home": "http://pytorch.org/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "BSD 3-Clause", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": null, "subdirs": [ "linux-ppc64le" ], "summary": "Meta-package to install CPU-only PyTorch variant", "tags": null, "text_prefix": false, "timestamp": 1748471334, "version": "2.1.2" }, "pytorch-lightning": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "PyTorch Lightning is the lightweight PyTorch wrapper for ML researchers. 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Write less boilerplate.", "tags": null, "text_prefix": false, "timestamp": 1748466164, "version": "2.3.3" }, "pytorch-lightning-bolts": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/PyTorchLightning/pytorch-lightning-bolts/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Apache-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": "https://github.com/PyTorchLightning/pytorch-lightning-bolts", "source_url": null, "subdirs": [ "noarch" ], "summary": "Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch.", "tags": null, "text_prefix": false, "timestamp": 1748466242, "version": "0.7.0" }, "re-assert": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/asottile/re-assert", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.io/packages/source/r/re-assert/re_assert-1.1.0.tar.gz", "subdirs": [ "noarch" ], "summary": "show where your regex match assertion failed!", "tags": null, "text_prefix": false, "timestamp": 1748451328, "version": "1.1.0" }, "rust": { "activate.d": true, "binary_prefix": false, "deactivate.d": true, "description": null, "dev_url": "https://doc.rust-lang.org/std/", "doc_source_url": null, "doc_url": "https://www.rust-lang.org/en-US/documentation.html", "home": "https://www.rust-lang.org", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": null, "subdirs": [ "linux-ppc64le" ], "summary": "Rust is a systems programming language that runs blazingly fast, prevents segfaults, and guarantees thread safety. This package provides the compiler (rustc) and the documentation utilities rustdoc.", "tags": null, "text_prefix": true, "timestamp": 1748445591, "version": "1.81.0" }, "rust-std-powerpc64le-unknown-linux-gnu": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": "https://doc.rust-lang.org/std/", "doc_source_url": null, "doc_url": "https://www.rust-lang.org/en-US/documentation.html", "home": "https://www.rust-lang.org", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": null, "subdirs": [ "noarch" ], "summary": "Rust is a systems programming language that runs blazingly fast, prevents segfaults, and guarantees thread safety. This package provides the compiler (rustc) and the documentation utilities rustdoc.", "tags": null, "text_prefix": false, "timestamp": 1748445507, "version": "1.81.0" }, "rust_linux-ppc64le": { "activate.d": true, "binary_prefix": false, "deactivate.d": false, "description": "Rust is a systems programming language that runs blazingly fast, prevents segfaults, and guarantees thread safety.", "dev_url": "https://github.com/rust-lang", "doc_source_url": "https://github.com/rust-lang/rust/tree/master/src/doc", "doc_url": "https://doc.rust-lang.org/", "home": "https://www.rust-lang.org", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "BSD-3-Clause", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": null, "subdirs": [ "linux-ppc64le" ], "summary": "A safe systems programming language (conda activation scripts)", "tags": null, "text_prefix": false, "timestamp": 1748446254, "version": "1.81.0" }, "safeint": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/dcleblanc/SafeInt", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/dcleblanc/SafeInt/archive/refs/tags/3.0.26.tar.gz", "subdirs": [ "linux-ppc64le" ], "summary": "SafeInt is a class library for C++ that manages integer overflows.", "tags": null, "text_prefix": false, "timestamp": 1748467729, "version": "3.0.26" }, "scikit-build-core": { "activate.d": true, "binary_prefix": false, "deactivate.d": true, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://pypi.org/project/scikit-build-core/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Apache-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.io/packages/source/s/scikit-build-core/scikit_build_core-0.10.7.tar.gz", "subdirs": [ "noarch" ], "summary": "Build backend for CMake based projects", "tags": null, "text_prefix": false, "timestamp": 1748455133, "version": "0.10.7" }, "scikit-learn": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Scikit-learn is an open source machine learning library that supports supervised and unsupervised learning. 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