PSG Connect FastAPI Backend

This project is a backend service built with FastAPI that provides web scraping functionality for PSG Connect. It offers a RESTful API for clients to fetch student data from the PSG Tech website.

Features

• Web scraping API endpoint
• Student profile, attendance, exam results, and CA marks retrieval
• Error handling for various scenarios
• CORS middleware for cross-origin requests

Requirements

• Python 3.7+
• FastAPI
• Uvicorn (ASGI server)
• Pydantic
• Custom scraping module (dataFetchFunctions)

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/psg-connect-backend.git
   cd psg-connect-backend
   

2. Create a virtual environment and activate it:

   python -m venv venv
   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`
   

3. Install the required packages:

   pip install -r requirements.txt
   

Usage

Run the FastAPI server:

uvicorn main:app --reload

The API will be available at http://localhost:8000. You can access the interactive API documentation at http://localhost:8000/docs.

API Endpoints

• GET /: Welcome message
• GET /online: Check if the service is online
• POST /fetch_data: Fetch student data (requires username and password)

Code Structure

from fastapi import FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
import uvicorn
from dataFetchFunctions import CAMarksWebScrapper
from dataExceptions import InvalidUsernameOrPasswordException, ScrappingError, NoSemResultsAvailable, NoCAMarksAvailable, AttendanceUpdateInProcessException, NoTimeTableDataException

app = FastAPI()

# CORS middleware configuration
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

class Credentials(BaseModel):
    username: str
    password: str

# API endpoints implementation
# ...

Deployment

This project is designed to be deployed using a Heroku-style Procfile. Make sure to configure your deployment environment accordingly.

Error Handling

The backend handles various exceptions:

• Invalid username or password
• Scraping errors
• No semester results available
• No CA marks available
• Attendance update in process
• No timetable data available

Contributing

1. Fork the repository
2. Create your feature branch: git checkout -b feature/my-new-feature
3. Commit your changes: git commit -am 'Add some feature'
4. Push to the branch: git push origin feature/my-new-feature
5. Submit a pull request