# Qiskit Algorithms
[](https://opensource.org/licenses/Apache-2.0)
## Installation
We encourage installing Qiskit Algorithms via the pip tool (a python package manager).
```bash
pip install qiskit-algorithms
```
**pip** will handle all dependencies automatically and you will always install the latest
(and well-tested) version.
If you want to work on the very latest work-in-progress versions, either to try features ahead of
their official release or if you want to contribute to Algorithms, then you can install from source.
To do this follow the instructions in the
[documentation](https://qiskit-community.github.io/qiskit-algorithms/getting_started.html#installation).
----------------------------------------------------------------------------------------------------
### Optional Installs
Some optimization algorithms require specific libraries to be run:
* **Scikit-quant**, may be installed using the command `pip install scikit-quant`.
* **SnobFit**, may be installed using the command `pip install SQSnobFit`.
* **NLOpt**, may be installed using the command `pip install nlopt`.
[//]: # (### Creating Your First Algorithm in Qiskit)
[//]: # (### Further examples)
----------------------------------------------------------------------------------------------------
## Contribution Guidelines
If you'd like to contribute to Qiskit Algorithms, please take a look at our
[contribution guidelines](https://github.com/qiskit-community/qiskit-algorithms/blob/main/CONTRIBUTING.md).
This project adheres to Qiskit's [code of conduct](https://github.com/qiskit-community/qiskit-algorithms/blob/main/CODE_OF_CONDUCT.md).
By participating, you are expected to uphold this code.
We use [GitHub issues](https://github.com/qiskit-community/qiskit-algorithms/issues) for tracking requests and bugs. Please
[join the Qiskit Slack community](https://qisk.it/join-slack)
and for discussion and simple questions.
For questions that are more suited for a forum, we use the **Qiskit** tag in [Stack Overflow](https://stackoverflow.com/questions/tagged/qiskit).
## Authors and Citation
Qiskit Algorithms was inspired, authored and brought about by the collective work of a team of researchers.
Algorithms continues to grow with the help and work of
[many people](https://github.com/qiskit-community/qiskit-algorithms/graphs/contributors), who contribute
to the project at different levels.
If you use Qiskit, please cite as per the provided
[BibTeX file](https://github.com/Qiskit/qiskit/blob/main/CITATION.bib).
## License
This project uses the [Apache License 2.0](https://github.com/qiskit-community/qiskit-algorithms/blob/main/LICENSE.txt).
Raw data
{
"_id": null,
"home_page": "https://github.com/qiskit-community/qiskit-algorithms",
"name": "qiskit-algorithms",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": "",
"keywords": "qiskit sdk quantum algorithms",
"author": "Qiskit Algorithms Development Team",
"author_email": "qiskit@us.ibm.com",
"download_url": "https://files.pythonhosted.org/packages/76/f9/f5e95c3f9c3b886afa4f56adc58074af34e0e5bd0bde55e747b6cb45f0b2/qiskit-algorithms-0.3.0.tar.gz",
"platform": null,
"description": "# Qiskit Algorithms\n\n[](https://opensource.org/licenses/Apache-2.0)\n\n## Installation\n\nWe encourage installing Qiskit Algorithms via the pip tool (a python package manager).\n\n```bash\npip install qiskit-algorithms\n```\n\n**pip** will handle all dependencies automatically and you will always install the latest\n(and well-tested) version.\n\nIf you want to work on the very latest work-in-progress versions, either to try features ahead of\ntheir official release or if you want to contribute to Algorithms, then you can install from source.\nTo do this follow the instructions in the\n [documentation](https://qiskit-community.github.io/qiskit-algorithms/getting_started.html#installation).\n\n\n----------------------------------------------------------------------------------------------------\n\n### Optional Installs\n\nSome optimization algorithms require specific libraries to be run:\n\n* **Scikit-quant**, may be installed using the command `pip install scikit-quant`.\n\n* **SnobFit**, may be installed using the command `pip install SQSnobFit`.\n\n* **NLOpt**, may be installed using the command `pip install nlopt`.\n\n[//]: # (### Creating Your First Algorithm in Qiskit)\n\n[//]: # (### Further examples)\n\n----------------------------------------------------------------------------------------------------\n\n## Contribution Guidelines\n\nIf you'd like to contribute to Qiskit Algorithms, please take a look at our\n[contribution guidelines](https://github.com/qiskit-community/qiskit-algorithms/blob/main/CONTRIBUTING.md).\nThis project adheres to Qiskit's [code of conduct](https://github.com/qiskit-community/qiskit-algorithms/blob/main/CODE_OF_CONDUCT.md).\nBy participating, you are expected to uphold this code.\n\nWe use [GitHub issues](https://github.com/qiskit-community/qiskit-algorithms/issues) for tracking requests and bugs. Please\n[join the Qiskit Slack community](https://qisk.it/join-slack)\nand for discussion and simple questions.\nFor questions that are more suited for a forum, we use the **Qiskit** tag in [Stack Overflow](https://stackoverflow.com/questions/tagged/qiskit).\n\n## Authors and Citation\n\nQiskit Algorithms was inspired, authored and brought about by the collective work of a team of researchers.\nAlgorithms continues to grow with the help and work of\n[many people](https://github.com/qiskit-community/qiskit-algorithms/graphs/contributors), who contribute\nto the project at different levels.\nIf you use Qiskit, please cite as per the provided\n[BibTeX file](https://github.com/Qiskit/qiskit/blob/main/CITATION.bib).\n\n## License\n\nThis project uses the [Apache License 2.0](https://github.com/qiskit-community/qiskit-algorithms/blob/main/LICENSE.txt).\n",
"bugtrack_url": null,
"license": "Apache-2.0",
"summary": "Qiskit Algorithms: A library of quantum computing algorithms",
"version": "0.3.0",
"project_urls": {
"Bug Tracker": "https://github.com/qiskit-community/qiskit-algorithms/issues",
"Documentation": "https://qiskit-community.github.io/qiskit-algorithms/",
"Homepage": "https://github.com/qiskit-community/qiskit-algorithms",
"Source Code": "https://github.com/qiskit-community/qiskit-algorithms"
},
"split_keywords": [
"qiskit",
"sdk",
"quantum",
"algorithms"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "e02f9a71fc36ff8de0188d4325399e1ad29c8fce2c2b427dae6c900003510943",
"md5": "62ad07c26d5287f0e3640219d54bbdac",
"sha256": "8ae1aa8aafc32864890a31c06d19f100a79df6412350f1f4b8c124cd17b3f731"
},
"downloads": -1,
"filename": "qiskit_algorithms-0.3.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "62ad07c26d5287f0e3640219d54bbdac",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.8",
"size": 308560,
"upload_time": "2024-02-19T12:07:56",
"upload_time_iso_8601": "2024-02-19T12:07:56.030949Z",
"url": "https://files.pythonhosted.org/packages/e0/2f/9a71fc36ff8de0188d4325399e1ad29c8fce2c2b427dae6c900003510943/qiskit_algorithms-0.3.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "76f9f5e95c3f9c3b886afa4f56adc58074af34e0e5bd0bde55e747b6cb45f0b2",
"md5": "4295a087d3f76d78faa675d15b8bdce2",
"sha256": "02eedcbb079c6da371421a50cb296ff1dc6ce4a1c478ec521ff6e62c9bc53e10"
},
"downloads": -1,
"filename": "qiskit-algorithms-0.3.0.tar.gz",
"has_sig": false,
"md5_digest": "4295a087d3f76d78faa675d15b8bdce2",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.8",
"size": 240473,
"upload_time": "2024-02-19T12:07:57",
"upload_time_iso_8601": "2024-02-19T12:07:57.367532Z",
"url": "https://files.pythonhosted.org/packages/76/f9/f5e95c3f9c3b886afa4f56adc58074af34e0e5bd0bde55e747b6cb45f0b2/qiskit-algorithms-0.3.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-02-19 12:07:57",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "qiskit-community",
"github_project": "qiskit-algorithms",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"requirements": [],
"tox": true,
"lcname": "qiskit-algorithms"
}
JSON
