SportsGoWhere

Steps to install and run project:

1. Clone github repository

2. Open repository in Visual Studio Code

3. Open up the terminal on Visual Studio Code

4. Check requirements: Flask==2.2.2 Flask_Bcrypt==1.0.1 Flask_Login==0.6.2 flask_sqlalchemy==3.0.3 Flask_WTF==1.1.1 itsdangerous==2.1.2 mysql_connector_repackaged==0.3.1 pandas==1.3.5 python_bcrypt==0.3.2 pytz==2021.3 requests==2.25.1 SQLAlchemy==2.0.4 WTForms==3.0.1

5. Download and install MySQL Workbench (preferably host="localhost", database = 'sportsgowhere',user="root", password="password")

6. Open up Visual Studio Code and edit the following files with the correct values for host, user, password, database:

(1) app.config['SQLALCHEMY_DATABASE_URI'] = "mysql://root:password@localhost/sportsgowhere" (line 13 in init.py)

(2) mydb = mysql.connector.connect(host="localhost", user="root", password="password", database="sportsgowhere") (line 70 in routes.py)

(3) mydb = connection.connect(host="localhost", database = 'sportsgowhere',user="root", passwd="password",use_pure=True) (line 12 in nearestCarparks.py)

(4) mydb = connection.connect(host="localhost", database = 'sportsgowhere',user="root", passwd="password",use_pure=True) (line 11 in nearestEateries.py)

7. Set up local database and connection in MySQL Workbench
8. On Visual Studio Code, open up the terminal and change directory to Flask_Learn (cd Flask_Learn)
9. Type the following commands: with app.app_context(): db.create_all()
10. Open up MySQL Workbench and check that there are 4 new tables: accounts, recentsearches, favorites, sportsfacilities
11. On your local database, import the 3 csv files with their respective names (sportsfacilities.csv as sportsfacilities, hdbcarparks.csv as hdbcarparks, healthiereateries.csv as healthiereateries)
12. Open up Visual Studio code and run run.py
13. Open the IP address in your browser
14. Enjoy our website

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File and Logic Organisation

• SportsGoWhere/Flask_Learn/run.py: runs the application
• Datasets directory: csv files for carparks, eateries, and sports facilities
• Flask_Learn/NearestFinder: Python logic files to find nearest carparks, eateries, and implement geolocation.
• Flask_Learn/flaskblog/routes.py: Contol functions to respond to user inputs and render required html file.
• Flask_Learn/flaskblog/apimanagers.py: Python code to provide interface for carpark, PSI, datetime, and weather APIs.
• Flask_Learn/flaskblog/models.py: Creates the tables for the entities and establishes relation between datasets.
• SportsGoWhere/Flask_Learn/flaskblog/templates: directory contains all html files which each correspond to a view.