{"id":13776752,"url":"https://github.com/pasqal-io/pyqtorch","last_synced_at":"2025-04-05T18:05:50.760Z","repository":{"id":61979164,"uuid":"451881855","full_name":"pasqal-io/pyqtorch","owner":"pasqal-io","description":"PyTorch-based state vector simulator","archived":false,"fork":false,"pushed_at":"2025-04-03T15:50:03.000Z","size":5309,"stargazers_count":44,"open_issues_count":12,"forks_count":16,"subscribers_count":8,"default_branch":"main","last_synced_at":"2025-04-03T21:38:49.192Z","etag":null,"topics":["quantum-machine-learning","torch"],"latest_commit_sha":null,"homepage":"https://pasqal-io.github.io/pyqtorch/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/pasqal-io.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"docs/CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"docs/CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-01-25T13:09:42.000Z","updated_at":"2025-04-01T08:42:49.000Z","dependencies_parsed_at":"2024-02-22T14:25:47.671Z","dependency_job_id":"113dfff5-d7fb-40b1-ba2c-8af3883f2dfe","html_url":"https://github.com/pasqal-io/pyqtorch","commit_stats":null,"previous_names":["pasqal-io/pyq"],"tags_count":66,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pasqal-io%2Fpyqtorch","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pasqal-io%2Fpyqtorch/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pasqal-io%2Fpyqtorch/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pasqal-io%2Fpyqtorch/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pasqal-io","download_url":"https://codeload.github.com/pasqal-io/pyqtorch/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247085993,"owners_count":20881158,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["quantum-machine-learning","torch"],"created_at":"2024-08-03T18:00:32.596Z","updated_at":"2025-04-05T18:05:50.732Z","avatar_url":"https://github.com/pasqal-io.png","language":"Python","funding_links":[],"categories":["Quantum simulators"],"sub_categories":[],"readme":"# pyqtorch\n\n**pyqtorch** is a [PyTorch](https://pytorch.org/)-based state vector simulator designed for quantum machine learning.\nIt acts as the main backend for [`Qadence`](https://github.com/pasqal-io/qadence), a digital-analog quantum programming interface.\n`pyqtorch` allows for writing fully differentiable quantum programs using both digital and analog operations; enabled via a intuitive, torch-based syntax.\n\n[![Linting / Tests/ Documentation](https://github.com/pasqal-io/pyqtorch/actions/workflows/test.yml/badge.svg)](https://github.com/pasqal-io/pyqtorch/actions/workflows/test.yml)\n[![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)\n[![Pypi](https://badge.fury.io/py/pyqtorch.svg)](https://pypi.org/project/pyqtorch/)\n![Coverage](https://img.shields.io/codecov/c/github/pasqal-io/pyqtorch?style=flat-square)\n\n\n## Installation guide\n\n`pyqtorch` can be installed from PyPI with `pip` as follows:\n\n```bash\npip install pyqtorch\n```\n\n## Install from source\n\nWe recommend to use the [`hatch`](https://hatch.pypa.io/latest/) environment manager to install `pyqtorch` from source:\n\n```bash\npython -m pip install hatch\n\n# get into a shell with all the dependencies\npython -m hatch shell\n\n# run a command within the virtual environment with all the dependencies\npython -m hatch run python my_script.py\n```\n\nPlease note that `hatch` will not combine nicely with other environment managers such Conda. If you want to use Conda, install `pyqtorch` from source using `pip`:\n\n```bash\n# within the Conda environment\npython -m pip install -e .\n```\n\n## Contributing\n\nPlease refer to [CONTRIBUTING](CONTRIBUTING.md) to learn how to contribute to `pyqtorch`.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpasqal-io%2Fpyqtorch","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpasqal-io%2Fpyqtorch","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpasqal-io%2Fpyqtorch/lists"}