| Name | topsisx JSON |
| Version |
0.1.2
JSON |
| download |
| home_page | https://github.com/<your-username>/topsisx |
| Summary | A Python library for Multi-Criteria Decision Making (TOPSIS, AHP, VIKOR, etc.) |
| upload_time | 2025-07-14 07:55:20 |
| maintainer | None |
| docs_url | None |
| author | Your Name |
| requires_python | >=3.6 |
| license | None |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# TOPSISX 📊
[](https://pypi.org/project/topsisx/)
[](https://pepy.tech/project/topsisx)
[](https://github.com/yourusername/topsisx/blob/main/LICENSE)
---
TOPSISX is a Python library for multi-criteria decision-making (MCDM) using methods like **TOPSIS**, **AHP**, **Entropy Weighting**, and **VIKOR**. It also supports PDF report generation and visualizations.
---
## 🚀 Features
- 📈 **TOPSIS**: Rank alternatives based on weighted criteria.
- 📊 **AHP**: Calculate weights using Analytic Hierarchy Process.
- 📋 **Entropy Weighting**: Objective weight calculation.
- 📑 **PDF Reports**: Generate professional reports of results.
- 🖼️ **Visualizations**: Plot graphs for better insights.
---
## 📦 Installation
Install the package from PyPI:
```bash
pip install topsisx
⚡ Quick Start
Here’s how you can use topsisx in your project:
python
Copy
Edit
from topsisx.topsis import topsis
# Sample data
data = [
[250, 16, 12, 5],
[200, 16, 8, 3],
[300, 32, 16, 4],
[275, 32, 8, 4],
[225, 16, 16, 2]
]
weights = [0.25, 0.25, 0.25, 0.25]
impacts = ['+', '+', '-', '+']
ranked = topsis(data, weights, impacts)
print(ranked)
📖 Documentation
Go to topsisx.readthedocs.io (Coming Soon 🚧)
👨💻 Contributing
We welcome contributions! Please open an issue or pull request on GitHub.
https://github.com/SuvitKumar003/ranklib
📝 License
This project is licensed under the MIT License.
Raw data
{
"_id": null,
"home_page": "https://github.com/<your-username>/topsisx",
"name": "topsisx",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.6",
"maintainer_email": null,
"keywords": null,
"author": "Your Name",
"author_email": "your_email@example.com",
"download_url": "https://files.pythonhosted.org/packages/b3/c6/28d2d38f211017ae9684ee25bbcfae3511dae646ea70d18a2597d770c6e0/topsisx-0.1.2.tar.gz",
"platform": null,
"description": "# TOPSISX \ud83d\udcca\r\n\r\n[](https://pypi.org/project/topsisx/)\r\n[](https://pepy.tech/project/topsisx)\r\n[](https://github.com/yourusername/topsisx/blob/main/LICENSE)\r\n\r\n---\r\n\r\nTOPSISX is a Python library for multi-criteria decision-making (MCDM) using methods like **TOPSIS**, **AHP**, **Entropy Weighting**, and **VIKOR**. It also supports PDF report generation and visualizations.\r\n\r\n---\r\n\r\n## \ud83d\ude80 Features\r\n- \ud83d\udcc8 **TOPSIS**: Rank alternatives based on weighted criteria.\r\n- \ud83d\udcca **AHP**: Calculate weights using Analytic Hierarchy Process.\r\n- \ud83d\udccb **Entropy Weighting**: Objective weight calculation.\r\n- \ud83d\udcd1 **PDF Reports**: Generate professional reports of results.\r\n- \ud83d\uddbc\ufe0f **Visualizations**: Plot graphs for better insights.\r\n\r\n---\r\n\r\n## \ud83d\udce6 Installation\r\n\r\nInstall the package from PyPI:\r\n\r\n```bash\r\npip install topsisx\r\n\r\n\u26a1 Quick Start\r\nHere\u2019s how you can use topsisx in your project:\r\n\r\npython\r\nCopy\r\nEdit\r\nfrom topsisx.topsis import topsis\r\n\r\n# Sample data\r\ndata = [\r\n [250, 16, 12, 5],\r\n [200, 16, 8, 3],\r\n [300, 32, 16, 4],\r\n [275, 32, 8, 4],\r\n [225, 16, 16, 2]\r\n]\r\n\r\nweights = [0.25, 0.25, 0.25, 0.25]\r\nimpacts = ['+', '+', '-', '+']\r\n\r\nranked = topsis(data, weights, impacts)\r\nprint(ranked)\r\n\ud83d\udcd6 Documentation\r\nGo to topsisx.readthedocs.io (Coming Soon \ud83d\udea7)\r\n\r\n\ud83d\udc68\u200d\ud83d\udcbb Contributing\r\nWe welcome contributions! Please open an issue or pull request on GitHub.\r\nhttps://github.com/SuvitKumar003/ranklib\r\n\r\n\ud83d\udcdd License\r\nThis project is licensed under the MIT License.\r\n\r\n\r\n\r\n",
"bugtrack_url": null,
"license": null,
"summary": "A Python library for Multi-Criteria Decision Making (TOPSIS, AHP, VIKOR, etc.)",
"version": "0.1.2",
"project_urls": {
"Homepage": "https://github.com/<your-username>/topsisx"
},
"split_keywords": [],
"urls": [
{
"comment_text": null,
"digests": {
"blake2b_256": "8bd91a91d8255502ea55bf2f113cd50c7709e305415a245561b762ade4cc0eb9",
"md5": "bf34feec709fc241b6c935891d2712cd",
"sha256": "b9b347fde525a2b2f461682da6831266e97882c51ec7a0db619f4ad9738111ad"
},
"downloads": -1,
"filename": "topsisx-0.1.2-py3-none-any.whl",
"has_sig": false,
"md5_digest": "bf34feec709fc241b6c935891d2712cd",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.6",
"size": 7326,
"upload_time": "2025-07-14T07:55:17",
"upload_time_iso_8601": "2025-07-14T07:55:17.983003Z",
"url": "https://files.pythonhosted.org/packages/8b/d9/1a91d8255502ea55bf2f113cd50c7709e305415a245561b762ade4cc0eb9/topsisx-0.1.2-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "b3c628d2d38f211017ae9684ee25bbcfae3511dae646ea70d18a2597d770c6e0",
"md5": "8fe875be90cc635afa9c33aa8eb642c2",
"sha256": "8cc9b30ea1db83debd5655fa70900e1c49f15babf806450e942e657029504c2a"
},
"downloads": -1,
"filename": "topsisx-0.1.2.tar.gz",
"has_sig": false,
"md5_digest": "8fe875be90cc635afa9c33aa8eb642c2",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.6",
"size": 6594,
"upload_time": "2025-07-14T07:55:20",
"upload_time_iso_8601": "2025-07-14T07:55:20.428707Z",
"url": "https://files.pythonhosted.org/packages/b3/c6/28d2d38f211017ae9684ee25bbcfae3511dae646ea70d18a2597d770c6e0/topsisx-0.1.2.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-07-14 07:55:20",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "<your-username>",
"github_project": "topsisx",
"github_not_found": true,
"lcname": "topsisx"
}
