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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": 1718138642, "version": "2.10.7" }, "coin-or-cgl": { "activate.d": false, "binary_prefix": true, "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. Cgl uses the abstract class OsiSolverInterface (see Osi) to use or communicate with a solver. It does not directly call a solver.", "dev_url": "https://github.com/coin-or/Cgl", "doc_source_url": null, "doc_url": null, "home": "https://projects.coin-or.org/Cgl", "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": { "0.60.6": { "weak": [ "coin-or-cgl >=0.60,<0.61.0a0" ] } }, "source_git_url": null, "source_url": "https://github.com/coin-or/Cgl/archive/releases/0.60.6.tar.gz", "subdirs": [ "linux-ppc64le" ], "summary": "COIN-OR Cut Generation Library (Cgl)", "tags": null, "text_prefix": true, "timestamp": 1718138556, "version": "0.60.6" }, "coin-or-clp": { "activate.d": false, "binary_prefix": true, "deactivate.d": false, "description": "Clp (Coin-or linear programming) is an open-source linear programming solver. 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": 1718138456, "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. Many applications may be able to use the Osi to insulate themselves from a specific LP solver. That is, programs written to the OSI standard may be linked to any solver with an OSI interface and should produce correct results. The OSI has been significantly extended compared to its first incarnation. Currently, the OSI supports linear programming solvers and has rudimentary support for integer programming. 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": 1718138390, "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. These utilities include: - classes for storing and manipulating sparse matrices and vectors, - performing matrix factorization, - parsing input files in standard formats, e.g. MPS, - building representations of mathematical programs, - performing simple presolve operations, - warm starting algorithms for mathematical programs, and - comparing floating point numbers with a tolerance, among others.", "dev_url": "https://github.com/coin-or/CoinUtils", "doc_source_url": null, "doc_url": null, "home": "https://projects.coin-or.org/CoinUtils", "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": { "2.11.6": { "weak": [ "coin-or-utils >=2.11,<2.12.0a0" ] } }, "source_git_url": null, "source_url": "https://github.com/coin-or/CoinUtils/archive/releases/2.11.6.tar.gz", "subdirs": [ "linux-ppc64le" ], "summary": "COIN-OR Utilities (CoinUtils)", "tags": null, "text_prefix": true, "timestamp": 1718138328, "version": "2.11.6" }, "coincbc": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Cbc (Coin-or branch and cut) is an open-source mixed integer linear programming solver written in C++. 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": {}, "source_git_url": null, "source_url": "https://github.com/coin-or/Cbc/archive/releases/2.10.7.tar.gz", "subdirs": [ "noarch" ], "summary": "COIN-OR branch and cut (Cbc)", "tags": null, "text_prefix": false, "timestamp": 1718138645, "version": "2.10.7" }, "crcmod": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Python module for generating objects that compute the Cyclic Redundancy Check (CRC)", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://crcmod.sourceforge.net", "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/c/crcmod/crcmod-1.7.tar.gz", "subdirs": [ "linux-ppc64le" ], "summary": "CRC Generator", "tags": null, "text_prefix": false, "timestamp": 1718141210, "version": "1.7" }, "datasets": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Datasets is a lightweight library providing one-line dataloaders for many public datasets and one liners to download and pre-process any of the number of datasets major public datasets provided on the HuggingFace Datasets Hub. Datasets are ready to use in a dataloader for training/evaluating a ML model (Numpy/Pandas/PyTorch/TensorFlow/JAX). Datasets also provide an API for simple, fast, and reproducible data pre-processing for the above public datasets as well as your own local datasets in CSV/JSON/text.", "dev_url": "https://github.com/huggingface/datasets", "doc_source_url": null, "doc_url": "https://huggingface.co/docs/datasets/", "home": "https://github.com/huggingface/datasets", "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/d/datasets/datasets-2.16.1.tar.gz", "subdirs": [ "noarch" ], "summary": "HuggingFace/Datasets is an open library of NLP datasets.", "tags": null, "text_prefix": false, "timestamp": 1718137804, "version": "2.16.1" }, "dateutils": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://pypi.org/project/dateutils", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "0BSD", "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/d/dateutils/dateutils-0.6.12.tar.gz", "subdirs": [ "noarch" ], "summary": "Various utilities for working with date and datetime objects", "tags": null, "text_prefix": false, "timestamp": 1718076488, "version": "0.6.12" }, "deepdiff": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Deep Difference of dictionaries, iterables, strings and other objects. 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Python Fire is a helpful tool for developing and debugging Python code. Python Fire helps with exploring existing code or turning other people's code into a CLI. Python Fire makes transitioning between Bash and Python easier. Python Fire makes using a Python REPL easier by setting up the REPL with the modules and variables you'll need already imported and created.", "dev_url": "https://github.com/google/python-fire", "doc_source_url": null, "doc_url": "https://github.com/google/python-fire/blob/master/doc/guide.md", "home": "https://github.com/google/python-fire", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Apache-2", "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/fire/fire-0.4.0.tar.gz", "subdirs": [ "noarch" ], "summary": "Python Fire is a library for creating command line interfaces (CLIs) from absolutely any Python object.", "tags": null, "text_prefix": false, "timestamp": 1718073475, "version": "0.4.0" }, "flatbuffers": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://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": { "23.1.21": { "weak": [ "flatbuffers >=23.1.21,<24.0a0" ] } }, "source_git_url": null, "source_url": "https://github.com/google/flatbuffers/archive/v23.1.21.tar.gz", "subdirs": [ "linux-ppc64le" ], "summary": "Memory Efficient Serialization Library", "tags": null, "text_prefix": true, "timestamp": 1718052010, "version": "23.1.21" }, "fsspec": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "To produce a template or specification for a file-system interface, that specific implementations should follow, so that applications making use of them can rely on a common behaviour and not have to worry about the specific internal implementation decisions with any given backend. Many such implementations are included in this package, or in sister projects such as s3fs and gcsfs. In addition, if this is well-designed, then additional functionality, such as a key-value store or FUSE mounting of the file-system implementation may be available for all implementations \"for free\".", "dev_url": "https://github.com/intake/filesystem_spec", "doc_source_url": "https://github.com/intake/filesystem_spec/tree/master/docs", "doc_url": "https://filesystem-spec.readthedocs.io", "home": "https://github.com/intake/filesystem_spec", "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": "https://pypi.io/packages/source/f/fsspec/fsspec-2023.10.0.tar.gz", "subdirs": [ "noarch" ], "summary": "A specification for pythonic filesystems", "tags": null, "text_prefix": false, "timestamp": 1718067289, "version": "2023.10.0" }, "gmock": { "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/google/googletest", "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": "https://github.com/google/googletest/archive/refs/tags/v1.13.0.tar.gz", "subdirs": [ "linux-ppc64le" ], "summary": "Google's C++ test framework", "tags": null, "text_prefix": true, "timestamp": 1718131419, "version": "1.13.0" }, "googledrivedownloader": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://pypi.org/project/googledrivedownloader/", "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/g/googledrivedownloader/googledrivedownloader-0.4.tar.gz", "subdirs": [ "noarch" ], "summary": "Minimal class to download shared files from Google Drive.", "tags": null, "text_prefix": false, "timestamp": 1718125408, "version": "0.4" }, "grpc-cpp": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "gRPC is a modern, open source, high-performance remote procedure call (RPC) framework that can run anywhere. gRPC enables client and server applications to communicate transparently, and simplifies the building of connected systems. This package contains the gRPC C++ libraries and header files, as well as the code generation plugins.", "dev_url": null, "doc_source_url": null, "doc_url": "https://grpc.io/docs/", "home": "https://grpc.io/", "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": { "1.54.3": { "weak": [ "grpc-cpp >=1.54.3,<1.55.0a0" ] } }, "source_git_url": "https://github.com/grpc/grpc", "source_url": null, "subdirs": [ "linux-ppc64le" ], "summary": "gRPC - A high-performance, open-source universal RPC framework", "tags": null, "text_prefix": true, "timestamp": 1718067877, "version": "1.54.3" }, "grpcio": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": "https://pypi.org/project/grpcio/", "doc_source_url": null, "doc_url": null, "home": "https://grpc.io", "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/grpc/grpc", "source_url": null, "subdirs": [ "linux-ppc64le" ], "summary": "HTTP/2-based RPC framework", "tags": null, "text_prefix": false, "timestamp": 1718056505, "version": "1.54.3" }, "gtest": { "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/google/googletest", "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": "https://github.com/google/googletest/archive/refs/tags/v1.13.0.tar.gz", "subdirs": [ "linux-ppc64le" ], "summary": "Google's C++ test framework", "tags": null, "text_prefix": true, "timestamp": 1718131398, "version": "1.13.0" }, "hatch-fancy-pypi-readme": { "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/hynek/hatch-fancy-pypi-readme", "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/h/hatch-fancy-pypi-readme/hatch_fancy_pypi_readme-23.1.0.tar.gz", "subdirs": [ "noarch" ], "summary": "Fancy PyPI READMEs with Hatch", "tags": null, "text_prefix": false, "timestamp": 1718050286, "version": "23.1.0" }, "hjson-py": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://github.com/hjson/hjson-py", "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/h/hjson/hjson-3.1.0.tar.gz", "subdirs": [ "noarch" ], "summary": "Hjson, a user interface for JSON.", "tags": null, "text_prefix": true, "timestamp": 1718129107, "version": "3.1.0" }, "holidays": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "A fast, efficient Python library for generating country, province and state specific sets of holidays on the fly. 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PyPI: [https://pypi.org/project/huggingface-hub/](https://pypi.org/project/huggingface-hub/)", "dev_url": "https://github.com/huggingface/huggingface_hub", "doc_source_url": null, "doc_url": "https://huggingface.co/docs/huggingface_hub", "home": "https://github.com/huggingface/huggingface_hub", "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/h/huggingface_hub/huggingface_hub-0.20.0.tar.gz", "subdirs": [ "noarch" ], "summary": "Client library to download and publish models on the huggingface.co hub", "tags": null, "text_prefix": false, "timestamp": 1718137056, "version": "0.20.0" }, "inquirer": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": 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"run_exports": {}, "source_git_url": null, "source_url": null, "subdirs": [ "noarch" ], "summary": "(CDT) OpenJDK Development Toolkit", "tags": null, "text_prefix": false, "timestamp": 1718051236, "version": "11.0.6.10" }, "java-11-openjdk-headless-cos7-ppc64le": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "The OpenJDK runtime environment without audio and video", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://openjdk.java.net/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "ASL 1.1 and ASL 2.0 and BSD and BSD with advertising and GPL+ and GPLv2 and GPLv2 with exceptions and IJG and LGPLv2+ and MIT and MPLv1.1 and MPLv2.0 and Public Domain and W3C and zlib", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": null, "subdirs": [ "noarch" ], "summary": "(CDT) The OpenJDK runtime environment 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null, "source_url": "https://github.com/joblib/joblib/archive/1.3.2.tar.gz", "subdirs": [ "noarch" ], "summary": "Lightweight pipelining: using Python functions as pipeline jobs.", "tags": null, "text_prefix": false, "timestamp": 1718075663, "version": "1.3.2" }, "jsonpatch": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": "https://github.com/stefankoegl/python-json-patch", "doc_source_url": null, "doc_url": "https://python-json-patch.readthedocs.io/en/latest/", "home": "https://github.com/stefankoegl/python-json-patch", "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": "https://pypi.io/packages/source/j/jsonpatch/jsonpatch-1.33.tar.gz", "subdirs": [ "noarch" ], "summary": "Apply JSON-Patches (RFC 6902)", "tags": null, "text_prefix": true, "timestamp": 1718134344, "version": "1.33" }, "keras": { "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/keras-team/keras", "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": "Deep Learning for Python", "tags": null, "text_prefix": false, "timestamp": 1718060353, "version": "2.14.0" }, "langchain": { "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/langchain-ai/langchain", "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": "Building applications with LLMs through composability", "tags": null, "text_prefix": false, "timestamp": 1718134589, "version": "0.1.6" }, "langchain-community": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": "https://github.com/langchain-ai/langchain/tree/master/libs/community", "doc_source_url": null, "doc_url": "https://api.python.langchain.com/en/stable/community_api_reference.html", "home": "https://github.com/langchain-ai/langchain", "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/l/langchain-community/langchain_community-0.0.19.tar.gz", "subdirs": [ "noarch" ], "summary": "Community contributed LangChain integrations.", "tags": null, "text_prefix": false, "timestamp": 1718134497, "version": "0.0.19" }, "langchain-core": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "LangChain Core contains the core abstractions powering LangChain, including LangChain Expression Language.", "dev_url": "https://github.com/langchain-ai/langchain/tree/master/libs/core", "doc_source_url": null, "doc_url": "https://api.python.langchain.com/en/stable/core_api_reference.html", "home": "https://github.com/langchain-ai/langchain", "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/l/langchain-core/langchain_core-0.1.22.tar.gz", "subdirs": [ "noarch" ], "summary": "Core APIs for LangChain, the LLM framework for 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This is the client library to connect to the LangSmith API.", "dev_url": "https://github.com/langchain-ai/langchainplus-sdk", "doc_source_url": null, "doc_url": "https://docs.smith.langchain.com/docs/", "home": "https://smith.langchain.com/", "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/l/langsmith/langsmith-0.0.87.tar.gz", "subdirs": [ "noarch" ], "summary": "Client library to connect to the LangSmith language model tracing and evaluation API.", "tags": null, "text_prefix": false, "timestamp": 1718134393, "version": "0.0.87" }, "leveldb": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "LevelDB supports arbitrary byte arrays as both keys and values, singular get, put and delete operations, batched put and delete, bi-directional 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"https://github.com/xiph/flac/archive/1.3.3.tar.gz", "subdirs": [ "linux-ppc64le" ], "summary": "Flac audio format", "tags": null, "text_prefix": true, "timestamp": 1718141034, "version": "1.3.3" }, "liblightgbm": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/microsoft/LightGBM", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT License", "post_link": false, "pre_link": false, "pre_unlink": false, "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 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"activate.d": false, "binary_prefix": true, "deactivate.d": false, "description": "A fast drop-in alternative to conda, using libsolv for dependency resolution", "dev_url": "https://github.com/mamba-org/mamba", "doc_source_url": null, "doc_url": null, "home": "https://github.com/mamba-org/mamba", "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": { "1.5.6": { "weak": [ "libmambapy >=1.5.6,<1.6.0a0", "libsolv 0.7.24" ] } }, "source_git_url": "https://github.com/mamba-org/mamba", "source_url": null, "subdirs": [ "linux-ppc64le" ], "summary": "A fast drop-in alternative to conda, using libsolv for dependency resolution", "tags": null, "text_prefix": false, "timestamp": 1718143487, "version": "1.5.6" }, "libopenblas": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "OpenBLAS is based on GotoBLAS2 1.13 BSD 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"source_git_url": null, "source_url": null, "subdirs": [ "linux-ppc64le" ], "summary": "Computer vision and machine learning software library.", "tags": null, "text_prefix": true, "timestamp": 1718142598, "version": "4.8.1" }, "libortools": { "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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"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": 1718136899, "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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"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/l/lightning-utilities/lightning-utilities-0.10.0.tar.gz", "subdirs": [ "noarch" ], "summary": "Lightning Utilities.", "tags": null, "text_prefix": false, "timestamp": 1718073507, "version": "0.10.0" }, "llvm-openmp": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": "https://github.com/llvm/llvm-project/", "doc_source_url": null, "doc_url": null, "home": "http://openmp.llvm.org/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Apache-2.0 WITH LLVM-exception", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": { "14.0.6": { "strong": [ "llvm-openmp >=14.0.6" ] } }, "source_git_url": null, "source_url": "https://github.com/llvm/llvm-project/releases/download/llvmorg-14.0.6/llvm-project-14.0.6.src.tar.xz", "subdirs": [ "linux-ppc64le" ], "summary": "The OpenMP API supports multi-platform shared-memory parallel programming in C/C++ and Fortran.", "tags": null, "text_prefix": false, "timestamp": 1718065020, "version": "14.0.6" }, "mamba": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "A fast drop-in alternative to conda, using libsolv for dependency resolution", "dev_url": "https://github.com/mamba-org/mamba", "doc_source_url": null, "doc_url": null, "home": "https://github.com/mamba-org/mamba", "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/mamba-org/mamba", "source_url": null, "subdirs": [ "linux-ppc64le" ], "summary": "A fast drop-in alternative to 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"doc_source_url": null, "doc_url": null, "home": null, "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "BSD", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/xianyi/OpenBLAS/archive/v0.3.26.tar.gz", "subdirs": [ "linux-ppc64le" ], "summary": null, "tags": null, "text_prefix": false, "timestamp": 1718066238, "version": "3.0" }, "numactl": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Control NUMA policy for processes or shared memory", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/numactl/numactl", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": "https://github.com/numactl/numactl.git", "source_url": null, "subdirs": [ "linux-ppc64le" ], "summary": "Control NUMA policy for processes or shared memory", "tags": null, "text_prefix": false, "timestamp": 1718070218, "version": "2.0.16" }, "objsize": { "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/liran-funaro/objsize", "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": "https://pypi.io/packages/source/o/objsize/objsize-0.6.1.tar.gz", "subdirs": [ "noarch" ], "summary": "Traversal over Python's objects subtree and calculate the total size of the subtree in bytes (deep size).", "tags": null, "text_prefix": false, "timestamp": 1718130463, "version": "0.6.1" }, "onnx": { "activate.d": false, "binary_prefix": 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ONNX provides an open source format for AI models. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types. Initially we focus on the capabilities needed for inferencing (evaluation).", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/onnx/onnx/", "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": "https://github.com/onnx/onnx.git", "source_url": null, "subdirs": [ "linux-ppc64le" ], "summary": "Open Neural Network Exchange library", "tags": null, "text_prefix": true, "timestamp": 1718131069, "version": "1.15.0" }, "onnxconverter-common": { "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/microsoft/onnxconverter-common", "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": "https://github.com/microsoft/onnxconverter-common", "source_url": null, "subdirs": [ "noarch" ], "summary": "Common utilities for ONNX converters", "tags": null, "text_prefix": false, "timestamp": 1718131142, "version": "1.14.0" }, "onnxmltools": { "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/onnx/onnxmltools", "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/onnx/onnxmltools.git", "source_url": null, "subdirs": [ "noarch" ], "summary": "ONNXMLTools enables conversion of models to ONNX", "tags": null, "text_prefix": false, "timestamp": 1718132305, "version": "1.12.0" }, "onnxruntime": { "activate.d": false, "binary_prefix": true, "deactivate.d": false, "description": "ONNX Runtime is a cross-platform inference and training machine-learning accelerator.", "dev_url": "https://github.com/microsoft/onnxruntime/", "doc_source_url": null, "doc_url": "https://github.com/microsoft/onnxruntime/tree/master/docs", "home": "http://onnxruntime.ai/", "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": "cross-platform, high performance ML inferencing and training accelerator", "tags": null, "text_prefix": true, "timestamp": 1718132248, "version": "1.16.3" }, "openblas": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "OpenBLAS is based on GotoBLAS2 1.13 BSD version.", "dev_url": "https://github.com/xianyi/OpenBLAS", "doc_source_url": "https://github.com/xianyi/OpenBLAS/blob/develop/README.md", "doc_url": "http://www.openblas.net/", "home": "http://www.openblas.net/", "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": "https://github.com/xianyi/OpenBLAS/archive/v0.3.26.tar.gz", "subdirs": [ "linux-ppc64le" ], "summary": "An optimized BLAS library", "tags": null, "text_prefix": false, "timestamp": 1718066241, "version": "0.3.26" }, "openblas-devel": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": null, "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": null, "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": { "0.3.26": { "weak": [ "libopenblas >=0.3.26,<1.0a0", "blas * openblas" ] } }, "source_git_url": null, "source_url": "https://github.com/xianyi/OpenBLAS/archive/v0.3.26.tar.gz", "subdirs": [ "linux-ppc64le" ], "summary": "OpenBLAS headers and libraries for developing software that used OpenBLAS.", "tags": null, "text_prefix": true, "timestamp": 1718066239, "version": "0.3.26" }, "opencensus": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "OpenCensus makes getting critical telemetry out of your services easy and seamless. 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For details, check out our documentation and tutorials: - HTML (stable): https://orbit-ml.readthedocs.io/en/stable/ - HTML (latest): https://orbit-ml.readthedocs.io/en/latest/ Currently, it supports concrete implementations for the following models: - Exponential Smoothing (ETS) - Local Global Trend (LGT) - Damped Local Trend (DLT) - Kernel Time-based Regression (KTR) It also supports the following sampling/optimization methods for model estimation/inferences: - Markov-Chain Monte Carlo (MCMC) as a full sampling method - Maximum a Posteriori (MAP) as a point estimate method - Variational Inference (VI) as a hybrid-sampling method on approximate distribution PyPI: [https://pypi.org/project/orbit-ml/](https://pypi.org/project/orbit-ml/)", "dev_url": "https://github.com/uber/orbit", "doc_source_url": null, "doc_url": "https://orbit-ml.readthedocs.io/en/stable/", "home": "https://orbit-ml.readthedocs.io/en/stable/", "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/uber/orbit.git", "source_url": null, "subdirs": [ "linux-ppc64le" ], "summary": "Orbit is a package for bayesian time series modeling and inference.", "tags": null, "text_prefix": false, "timestamp": 1718143984, "version": "1.1.4.2" }, "orc": { "activate.d": false, "binary_prefix": true, "deactivate.d": false, "description": "C++ libraries for Apache ORC", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://github.com/apache/orc", "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": { "1.9.0": { "weak": [ "orc >=1.9.0,<1.9.1.0a0" ] } }, "source_git_url": "https://github.com/apache/orc", "source_url": null, "subdirs": [ "linux-ppc64le" ], "summary": "C++ libraries for Apache ORC", "tags": null, "text_prefix": false, "timestamp": 1718067557, "version": "1.9.0" }, "ordered-set": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://github.com/LuminosoInsight/ordered-set", "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/o/ordered-set/ordered-set-4.1.0.tar.gz", "subdirs": [ "noarch" ], "summary": "A MutableSet that remembers its order, so that every entry has an index.", "tags": null, "text_prefix": false, "timestamp": 1718076775, "version": "4.1.0" }, "orjson": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": "https://github.com/ijl/orjson", "doc_source_url": null, "doc_url": "https://github.com/ijl/orjson", "home": "https://github.com/ijl/orjson", "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": null, "subdirs": [ "linux-ppc64le" ], "summary": "orjson is a fast, correct JSON library for Python.", "tags": null, "text_prefix": false, "timestamp": 1718141177, "version": "3.8.0" }, "ortools-cpp": { "activate.d": false, "binary_prefix": false, "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. 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": 1718138949, "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. 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": {}, "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": 1718143835, "version": "9.6" }, "packaging": { "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/pypa/packaging", "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/packaging/packaging-23.2.tar.gz", "subdirs": [ "noarch" ], "summary": "Core utilities for Python packages", "tags": null, "text_prefix": false, "timestamp": 1718050233, "version": "23.2" }, "prophet": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Implements a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. 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null, "doc_url": null, "home": "http://opencv.org/", "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": { "4.8.1": { "weak": [ "py-opencv >=4.8.1,<5.0a0" ] } }, "source_git_url": null, "source_url": null, "subdirs": [ "linux-ppc64le" ], "summary": "Computer vision and machine learning software library.", "tags": null, "text_prefix": false, "timestamp": 1718142655, "version": "4.8.1" }, "pyarrow": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://github.com/apache/arrow", "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/apache/arrow/", "source_url": null, "subdirs": [ "linux-ppc64le" ], "summary": "Python libraries for Apache Arrow", "tags": null, "text_prefix": false, "timestamp": 1718137667, "version": "15.0.1" }, "pybind11": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": "https://pybind11.readthedocs.io/", "home": "https://github.com/pybind/pybind11/", "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": "https://github.com/pybind/pybind11/archive/v2.9.2.tar.gz", "subdirs": [ "linux-ppc64le" ], "summary": "Seamless operability between C++11 and Python", "tags": null, "text_prefix": true, "timestamp": 1718131933, "version": "2.9.2" }, "pybind11-abi": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": 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