# QLev
<p>
<a href="https://pypi.org/project/QLev/">
<img src="https://img.shields.io/pypi/v/QLev"
alt="PyPI package version">
</a>
<a href="https://www.python.org">
<img src="https://img.shields.io/pypi/pyversions/QLev"
alt="Python versions">
</a>
<a href="https://pypi.org/project/QLev/">
<img src="https://img.shields.io/pypi/dm/QLev.svg?label=PyPI%20downloads"
alt="PyPI Downloads">
</a>
</p>
## Introduction
The QLev package is mainly used for:
* Levenshtein distance
* levenshtein distance normalized
* levenshtein distance considering the keyboard keys range
## Requirements
* Python 3 or later
## Installation
```bash
pip install QLev
```
## Guide
To use simple the levenshtein distance you can:
```python
from QLev import levenshteinDistance
diff = levenshteinDistance('Guacamole','Guecamole')
print(diff)
```
If you want to use the normalized metric, you can:
```python
from QLev import levN
diff = levN('Guacamole','Guecamole')
print(diff)
```
If you want to know the euclidian distance between two chars, you can:
```python
from QLev import qwertyDistance
diff = qwertyDistance('g','a')
print(diff)
```
To have a metric that uses the qwerty matrix between strings, you can:
```python
from QLev import qwertyN
diff = qwertyN('Guacamole','Guecamole')
print(diff)
```
To have a metric that uses levenshtein distance and the qwerty matrix between strings, you can:
```python
from QLev import QLev
diff = QLev('Guacamole','Guecamole')
print(diff)
```
## License
MIT License
Copyright (c) 2022 Alysson Amaral
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Raw data
{
"_id": null,
"home_page": "https://github.com/alyssonamaral/QLev",
"name": "QLev",
"maintainer": null,
"docs_url": null,
"requires_python": null,
"maintainer_email": null,
"keywords": "python, levenshtein, qwerty, vector",
"author": "Alysson Amaral",
"author_email": "alysson.amaral@outlook.com",
"download_url": "https://files.pythonhosted.org/packages/5b/6e/accbd20333b739cecd73b5f178ae5b8a7b3bf3ef97b80d682ff18a890cb7/qlev-1.9.1.tar.gz",
"platform": null,
"description": "# QLev\n\n<p>\n\n <a href=\"https://pypi.org/project/QLev/\">\n <img src=\"https://img.shields.io/pypi/v/QLev\"\n alt=\"PyPI package version\">\n </a>\n <a href=\"https://www.python.org\">\n <img src=\"https://img.shields.io/pypi/pyversions/QLev\"\n alt=\"Python versions\">\n </a>\n <a href=\"https://pypi.org/project/QLev/\">\n <img src=\"https://img.shields.io/pypi/dm/QLev.svg?label=PyPI%20downloads\"\n alt=\"PyPI Downloads\">\n </a>\n</p>\n\n## Introduction\nThe QLev package is mainly used for:\n\n* Levenshtein distance\n* levenshtein distance normalized\n* levenshtein distance considering the keyboard keys range \n\n## Requirements\n* Python 3 or later\n\n## Installation\n```bash\npip install QLev\n```\n\n## Guide\n\nTo use simple the levenshtein distance you can:\n\n```python\nfrom QLev import levenshteinDistance\n\ndiff = levenshteinDistance('Guacamole','Guecamole')\n\nprint(diff)\n```\nIf you want to use the normalized metric, you can:\n\n```python\nfrom QLev import levN\n\ndiff = levN('Guacamole','Guecamole')\n\nprint(diff)\n```\nIf you want to know the euclidian distance between two chars, you can:\n\n```python\nfrom QLev import qwertyDistance\n\ndiff = qwertyDistance('g','a')\n\nprint(diff)\n```\n\nTo have a metric that uses the qwerty matrix between strings, you can:\n\n```python\nfrom QLev import qwertyN\n\ndiff = qwertyN('Guacamole','Guecamole')\n\nprint(diff)\n```\n\nTo have a metric that uses levenshtein distance and the qwerty matrix between strings, you can:\n\n```python\nfrom QLev import QLev\n\ndiff = QLev('Guacamole','Guecamole')\n\nprint(diff)\n```\n\n\n## License\n\nMIT License\n\nCopyright (c) 2022 Alysson Amaral\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n",
"bugtrack_url": null,
"license": null,
"summary": "String distance metrics based on Levenshtein and Qwerty Matrix Distance",
"version": "1.9.1",
"project_urls": {
"Homepage": "https://github.com/alyssonamaral/QLev"
},
"split_keywords": [
"python",
" levenshtein",
" qwerty",
" vector"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "19eb55bdc75e1f93e38ca9d49009bfe6a30f5c94c8d213dd8ec5d359d35bb489",
"md5": "19f3efd202641d56464084fc035b878f",
"sha256": "e1a690c01a9da66f67cbb78c3e82c733178a978a1f120321fc5b511a31538e28"
},
"downloads": -1,
"filename": "QLev-1.9.1-py3-none-any.whl",
"has_sig": false,
"md5_digest": "19f3efd202641d56464084fc035b878f",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": null,
"size": 5144,
"upload_time": "2024-08-30T00:18:02",
"upload_time_iso_8601": "2024-08-30T00:18:02.350028Z",
"url": "https://files.pythonhosted.org/packages/19/eb/55bdc75e1f93e38ca9d49009bfe6a30f5c94c8d213dd8ec5d359d35bb489/QLev-1.9.1-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "5b6eaccbd20333b739cecd73b5f178ae5b8a7b3bf3ef97b80d682ff18a890cb7",
"md5": "26447a002434be3b0cb26b68ddda2243",
"sha256": "118230d60c2fad618cbb6aabd799d6f7a5bf0dec8e8aab8eb17b2b584f1bf77e"
},
"downloads": -1,
"filename": "qlev-1.9.1.tar.gz",
"has_sig": false,
"md5_digest": "26447a002434be3b0cb26b68ddda2243",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 4427,
"upload_time": "2024-08-30T00:18:03",
"upload_time_iso_8601": "2024-08-30T00:18:03.828624Z",
"url": "https://files.pythonhosted.org/packages/5b/6e/accbd20333b739cecd73b5f178ae5b8a7b3bf3ef97b80d682ff18a890cb7/qlev-1.9.1.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-08-30 00:18:03",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "alyssonamaral",
"github_project": "QLev",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"lcname": "qlev"
}
JSON
