{ "info": { "author": "Rigetti", "author_email": "info@rigetti.com", "bugtrack_url": null, "classifiers": [], "description": "# Forest Benchmarking\n\n[![pipeline status](https://gitlab.com/rigetti/forest-benchmarking/badges/master/pipeline.svg)](https://gitlab.com/rigetti/forest-benchmarking/commits/master)\n[![Build Status](https://semaphoreci.com/api/v1/rigetti/forest-benchmarking/branches/master/shields_badge.svg)](https://semaphoreci.com/rigetti/forest-benchmarking)\n[![Documentation Status](https://readthedocs.org/projects/forest-benchmarking/badge/?version=latest)](https://forest-benchmarking.readthedocs.io/en/latest/?badge=latest)\n\nA library for quantum characterization, verification, validation (QCVV), and benchmarking using [pyQuil](https://github.com/rigetti/pyquil).\n\n## Installation\n\n`forest-benchmarking` can be installed from source or via the Python package manager PyPI.\n\n**Note**: NumPy and SciPy must be pre-installed for installation to be successful, due to cvxpy.\n\n### Source\n\n```bash\ngit clone https://github.com/rigetti/forest-benchmarking.git\ncd forest-benchmarking/\npip install numpy scipy\npip install -e .\n```\n\n### PyPI\n\n```bash\npip install numpy scipy\npip install forest-benchmarking\n```\n\n## Library Philosophy\n\nThe core philosophy of `forest-benchmarking` is to separate:\n\n* Experiment design and or generation\n* Data collection\n* Data analysis\n* Data visualisation\n\nWe ask that code contributed to this repository respect this separation.\nWe also ask that an example of how to use your contributed code is placed\nin the `/examples/` directory along with the standard documentation found in `/docs/`.\n\n## Testing\n\nThe unit tests can be run locally using `pytest`, but beware that the test dependencies\nmust be installed beforehand using `pip install -r requirements.txt`.\n\n## Disclaimer\n\nThis package is currently in alpha (v0.x), and therefore you should not expect that APIs\nwill necessarily be stable between releases. 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