Metadata-Version: 2.1
Name: smartbetsAPI
Version: 1.0.0
Summary: Simple football prediction API
Home-page: https://github.com/Simatwa/smartbetsAPI.git
Author: Smartwa Caleb
Author-email: smartwacaleb@gmail.com
License: GPL-3.0
Description: <h1 align="center">smartbetsAPI</h1>
        
        <p align="center">
        
         <a href="https://github.com/Simatwa/smartbetsAPI"><img src="https://img.shields.io/static/v1?logo=github&color=blueviolet&label=Test&message=Passing"/></a>
        
        <a href="LICENSE"><img src="https://img.shields.io/static/v1?logo=GPL&color=Blue&message=GPL-v3&label=License"/></a>
        
        <a href="#"><img src="https://img.shields.io/static/v1?logo=pypi&label=Pypi&message=v1.0.0&color=green"/></a>
        
        <a href="https://github.com/psf/black"><img src="https://img.shields.io/static/v1?logo=Black&label=Code-style&message=Black"/></a>
        
        <a href="#"><img src="https://img.shields.io/static/v1?logo=accuracy&label=Accuracy&message=55%&color=critical"/></a>
        
        <a href="#"><img src="https://img.shields.io/static/v1?logo=Docs&label=Docs&message=Passing&color=green"/></a>
        
        <a href="#" alt="coverage"><img src="https://img.shields.io/static/v1?logo=Coverage&label=Coverage&message=100%&color=yellowgreen"/></a>
        
        <a href="#" alt="progress"><img src="https://img.shields.io/static/v1?logo=Progress&label=Progress&message=95%&color=green"/></a><br>
        
         <!-- <img src="assets/soccer_player.jpg" width="60%" height="60%"/><br><br> -->
        
        </p>
        
         
        
         > "Punter's choice" 
        
        
        
         Worldwide soccer-matches predictor with a  dedicated standalone [Flask](https://github.com/pallets/Flask) server as an endpoint and a package for intergrating the scripts in your own [Python](https://python.org) code.
        
        
        
         ## Features
        
         - Standalone api
        
         - Script intergration (package)
        
         - Non-AI 
        
        
        
         ## Installation and usage
        
        
        
         ### Installation
        
        
        
        1. Linux 
        
        
        
        *Python 3.7+* is required for this script to be fruitful to you. 
        
        - Installing through pip is always the most preferred way:
        
        
        
         ```sh
        
         $ pip  install smartbetsAPI
        
         
        
         ```
        
        
        
         - For those who like enjoying the **latest** releases from [Github](https://github.com) like [me](https://github.com/Simatwa), rather than  waiting for the next package:
        
        
        
         ```sh
        
         $ pip install git+https://github.com/Simatwa/smartbetsAPI.git
        
        
        
         ```
        
        
        
        - The hard-core guys with _trust issues_ are very much sorted this way:
        
        
        
         ```sh
        
        
        
         $ git clone https://github.com/Simatwa/smartbetsAPI.git
        
        
        
         $ cd smartbetsAPI
        
        
        
         $ bash install.sh 
        
        
        
           #or
        
        
        
        $ sudo bash install.sh
        
        
        
        ```
        
        
        
        ### Usage
        
        
        
        1. Terminal
        
        
        
         Running `$ smartbetsAPI <api-password>`  will fire up the [Flask](/pallets/Flask) server with the following default configurations.
        
        
        
        <table align="center"> 
        
        <thead>
        
        <tr><th>Command        </th><th>Default  </th></tr>
        
        </thead>
        
        <tbody>
        
        <tr><td>Port           </td><td>8000     </td></tr>
        
        <tr><td>Username       </td><td>developer</td></tr>
        
        <tr><td>Filename       </td><td>None     </td></tr>
        
        <tr><td>level (Logging)</td><td>20       </td></tr>
        
        <tr><td>host           </td><td>False    </td></tr>
        
        <tr><td>debug          </td><td>False    </td></tr>
        
        <tr><td>no-net         </td><td>False    </td></tr>
        
        <tr><td>log            </td><td>False    </td></tr>
        
        <tr><td>colorize       </td><td>False    </td></tr>
        
        <tr><td>gui (Termux)   </td><td>False    </td></tr>
        
        </tbody>
        
        </table>
        
        
        
        - For instance :
        
        
        
         ```sh
        
         $ smartbetsAPI mypass9876
        
        
        
        ``` 
        
        
        
        > **Note** 
        
          - Content-Type of the response is `application/json`
        
        
        
        * For more information you can run `smartbetsAPI -h` 
        
        
        
        
        
        2. Importing Package
        
        
        
        Module `predictor`  provides two ways of interacting with it at the programming level, based on the `data-type` in which the teams have been packed and parsed to it:
        
        
        
        * Using `predictorL` object which accepts *teams* (**List** data-type).
        
        > For [example](examples/predict_using_list.py):
        
        
        
        ```py
        
        #!usr/bin/env python3
        
        from smartbets_API.predictor import predictor
        
        
        
        teams = [
        
            "Napoli",  # Home team (index [0])
        
            "AC Milan",  # Away team (index [1])
        
        ]
        
        # Instantiating predictor
        
        predict = predictor()
        
        
        
        # Using predictorL object to handle teams (List data-type)
        
        predictions = predict.predictorL(teams)
        
        
        
        # Display info
        
        print(predictions)
        
        
        
        #Output
        
        #{'g': 8.0, 'gg': 65.0, 'ov15': 70.0, 'ov25': 40.0, 'ov35': 30.0, 'choice': 60.0, 'result': '2', 'pick': 'ov15'}
        
        
        
        ```
        
        
        
        * Using `predictorD` object which takes *teams* (**Dictionary** data-type):
        
        > For [example](examples/predict_using_dict.py):
        
        
        
        ```py
        
        #!usr/bin/env python3
        
        from smartbets_API.predictor import predictor
        
        
        
        teams = {
        
            1: "Manchester City",  # 1 for home-team
        
            2: "Liverpool",  # 2 for away-team
        
        }
        
        
        
        # Instantiating predictor
        
        predict = predictor()
        
        
        
        # Using predictorD object to handle teams (Dictionary data-type)
        
        predictions = predict.predictorD(teams)
        
        
        
        # Display info
        
        print(predictions)
        
        
        
        #Output
        
        #{'g': 8.0, 'gg': 65.0, 'ov15': 60.0, 'ov25': 45.0, 'ov35': 30.0, 'choice': 56.16, 'result': '1', 'pick': 'gg'}
        
        
        
        ```
        
        
        
        - The outputs initials are explained in the table below
        
        
        
        <table>
        
        <thead>
        
        <tr><th>Parameter  </th><th>Function                                                 </th></tr>
        
        </thead>
        
        <tbody>
        
        <tr><td>g          </td><td>Goal average of the two teams                              </td></tr>
        
        <tr><td>gg         </td><td>Probability of both teams to score                         </td></tr>
        
        <tr><td>ov15       </td><td>Probability of having more than 2 goals                    </td></tr>
        
        <tr><td>ov25       </td><td>Probability of having more than 3 goals                    </td></tr>
        
        <tr><td>ov35       </td><td>Probability of having more than 4 goals                    </td></tr>
        
        <tr><td>choice     </td><td>Probability of the specified &#x27;result&#x27; to occcur            </td></tr>
        
        <tr><td>result     </td><td>The most suitable outcome from [1,1x,x,2x,2]                  </td></tr>
        
        <tr><td>pick       </td><td>The most suitable outcome from [1,1x,x,2x,2,gg,ov15,ov25,ov35]</td></tr>
        
        </tbody>
        
        </table>
        
        
        
        > **Note** 
        
          - Probabilities are in percentange (%)
        
        
        
        #### Further info 
        
        
        
        The `predictor` _class_ accepts multiple parameters that includes :
        
        
        
        <table>
        
        <thead>
        
        <tr><th>Parameter       </th><th>Function                                              </th><th>Default  </th></tr>
        
        </thead>
        
        <tbody>
        
        <tr><td>include_position</td><td>Include team&#x27;s league ranking in making predictions     </td><td>False    </td></tr>
        
        <tr><td>log             </td><td>Log at api default log&#x27;s path                           </td><td>False    </td></tr>
        
        <tr><td>level           </td><td>Logging level                                           </td><td>0        </td></tr>
        
        <tr><td>filename        </td><td>Log to the filename specified                           </td><td>None     </td></tr>
        
        <tr><td>color           </td><td>Colorize the logs                                       </td><td>False    </td></tr>
        
        <tr><td>gui             </td><td>Run with some Graphical interface notifications (Termux)</td><td>False    </td></tr>
        
        <tr><td>api             </td><td>Run with api-server&#x27;s configurations                    </td><td>False    </td></tr>
        
        </tbody>
        
        </table>
        
        
        
        The two predictor's object (`predictorD`, `predictorL`) accepts two parameters i.e.
        
        * **teams** - Required
        
        * **net** - Source of team's data - Default `True` (Online)
        
        
        
        ## Source of data
        
        
        
        Team performances are sourced from [Soccerway](https://int.soccerway.com) after souping the *uri* from [Google](https://www.google.com).
        
        
        
        > **Warning** Copyright related issues are liable to the user of this script!
        
        
        
        ## Disclaimer
        
        
        
        This project aims to help *punters* and *bookmarkers* to make informed and well researched soccer-predictions. Nevertheless, it is important to specify that 100% accuracy does not exist and smartbetsAPI can't guarantee the accuracy of the predictions. It is therefore your responsibility to trust the information conveyed by the smartbetsAPI after evaluating its reliability. As the [creator](https://github.com/Simatwa), I **CANNOT** be held responsible for any loss of capital that may occur during the use of this program.
        
        
        
        ## Contributing and Support
        
        
        
        ### Contributing
        
        
        
        Contributions are always welcome! <br>
        
        Please take a look at the [Contribution guidelines](CONTRIBUTING.md). <br>
        
        Feel free to open an [Issue](https://github.com/Simatwa/smartbetsAPI/issues) or to [Fork](https://github.com/Simatwa/smartbetsAPI/fork) this repo.
        
        
        
        ### ToDo
        
        
        
        - [ ] Upgrade to Machine learning
        
        - [ ] Improve algorithim's accuracy
        
        - [ ] General code improvements
        
        - [ ] Fix bugs
        
        
        
        ### Support 
        
        
        
        Consider donating to this project if you find it useful:
        
        <p align="center">
        
        <a href="https://www.paypal.com/donate/?hosted_button_id=KLNYKSGUXY8R2"><img src="https://img.shields.io/static/v1?logo=paypal&message=Donate&color=blueviolet&label=Paypal"/></a>
        
        </p>
        
        
        
        ## Credits
        
        
        
        - [x] [Soccerway](https://int.soccerway.com)
        
        - [x] [Google](https://www.google.com)
        
        - [x] [Python.org](https://python.org)
        
        
        
        ## Special Thanks
        
        
        
        * [x] [victhepythonista](https://github.com/victhepythonista)
        
        * [x] YOU.
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
