Metadata-Version: 2.4
Name: volleyball_prediction
Version: 0.1.4
Summary: Python package to predict women's volleyball match results.
Author-email: İlayda & Selinay & İrem & Merve <selinydeniz@gmail.com>
License: MIT License
        
        Copyright (c) 2025 Selinay Deniz
        
        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.
        
Project-URL: Homepage, https://github.com/selinydeniz/volleyball_prediction
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas
Requires-Dist: scikit-learn
Requires-Dist: fastapi
Requires-Dist: uvicorn[standard]
Requires-Dist: joblib
Dynamic: license-file

# volleyball_prediction
This Python package contains a machine learning model to predict the outcome of women's volleyball matches. The model can also be provided as a REST API with FastAPI.

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## Features

- Prediction of international matches (example: Türkiye vs. Serbia)
- Ready-trained model (recorded with joblib)
- Get live predictions via API
- Data cleaning and preprocessing with Pandas

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## Installation

You can install it from PyPI with the following command:

```bash
pip install volleyball_prediction


from volleyball_prediction.main import guess

print(guess("Türkiye", "Sırbistan"))
# Output: "Türkiye" veya "Sırbistan"

uvicorn volleyball_prediction.predict_api:app --reload

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