refactored codebase

app.py

@@ -1,40 +1,10 @@
-from io import BytesIO
-from dotenv import load_dotenv
-import os
-from gamification.objects import SimpleIndividualUserLevel
-from utils import *
-from fastapi import FastAPI, File, HTTPException, Header, UploadFile,status
-from tokenManagement import *
-from jwtcoding import *
-from fastapi.responses import JSONResponse
-import docx
-import fitz
-from gamification.routes import gamification
-from scraper import scrapeCourse
-import asyncio
-from google import genai 
-from typing import Optional,List
-from pydantic import BaseModel
-import re
-from bson.json_util import dumps
-import threading
-import concurrent.futures
-from gamification.pointLogic import get_all_simple_points_func,get_dream_job
-from pydantic import BaseModel
-from datetime import datetime
-from bson import ObjectId
-import os 
-from concurrent.futures import ThreadPoolExecutor
-executor = ThreadPoolExecutor(max_workers=5)
-
+from controller.imports import *
 
-load_dotenv()
+import logging
+from datetime import datetime
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
 
-CX = os.getenv("SEARCH_ENGINE_ID")
-API_KEY = os.getenv("GOOGLE_API_KEY")
-PINECONE_API_KEY=os.getenv("PINECONE_API_KEY")
-GEMINI_API_KEY=os.getenv("GEMINI_API_KEY")
-MONGO_URI=os.getenv("MONGO_URI")
 app = FastAPI()
 app.mount('/gamification',gamification)
 
@@ -73,7 +43,19 @@ class UserCourse(BaseModel):
     timeframeToAchieveDreamRole:str
     recommendedCourses: Optional[List[RecommendedCourse]]=None
     
-
+class LeaderBoardRanking(BaseModel):
+    userId:str
+    firstName:str
+    lastName:str
+    totalpoints:float
+    lastUpdated:datetime
+    careerPath:str
+    class Config:
+        json_encoder ={
+        ObjectId:str
+        }
+    
+    
 
 class CourseRecommendation(BaseModel):
     courseName: str
@@ -93,8 +75,6 @@ def extract_course_info(text: str) -> CourseRecommendation:
     return CourseRecommendation(courseName=coursename, completionTime=completiontime)
 
 
-import re
-from urllib.parse import urlparse
 
 def extract_provider(url):
     # Parse the URL
@@ -159,10 +139,6 @@ def get_course_func(query):
             
 
 
-
-
-
-
 @app.post("/ai/upload",tags=["AI"])
 async def upload_file(file: UploadFile = File(...),authorization: str = Header(...)):
      # Extract the token from the Authorization header (Bearer token)
@@ -242,37 +218,6 @@ def ask_ai_about_resume(req:AiAnalysis,authorization: str = Header(...)):
 @app.post("/ai/recommend",tags=["AI"])
 def ask_ai_to_recommnd_courses(request:UserCourse,authorization:str=Header(...)):
     """
-User Profile Information for Career Development
-
-This section defines the parameters used to gather information from the user to understand their current employment situation, learning preferences, challenges, and goals related to achieving their dream role.
-
-Parameters:
-
-    employment_status (str): 
-        A description of the user's current employment situation (e.g., "unemployed", "part-time", "full-time").
-    
-    interim_role (str): 
-        Indicates whether the user is willing to prepare for an interim role to gain experience and income while pursuing their dream role (e.g., "yes" or "no").
-    
-    desired_role (str): 
-        The role the user ultimately wishes to obtain (e.g., "Full-Stack Developer", "Data Scientist").
-    
-    motivation (str): 
-        The user's reasons or motivations for pursuing the desired role.
-    
-    learning_preference (str): 
-        Describes how the user prefers to learn new skills (e.g., "online courses", "self-study", "bootcamp").
-    
-    hours_spent_learning (str or int): 
-        The number of hours per day the user can dedicate to learning.
-    
-    challenges (str): 
-        Outlines any obstacles or challenges the user faces in reaching their dream role.
-    
-    timeframe_to_achieve_dream_role (str): 
-        The ideal timeframe the user has in mind for achieving their dream role (e.g., "6-12 months").
-    
-
     """
     
 
@@ -423,19 +368,7 @@ def protected_route(authorization: str = Header(...)):
 
 
 
-class LeaderBoardRanking(BaseModel):
-    userId:str
-    firstName:str
-    lastName:str
-    totalpoints:float
-    lastUpdated:datetime
-    careerPath:str
-    class Config:
-        json_encoder ={
-        ObjectId:str
-        }
-    
-    
+
 def create_leaderboard_ranking( document: LeaderBoardRanking) -> bool:
 
     collection = db['LeaderBoard']
@@ -479,16 +412,12 @@ def get_user_id_from_docKey(dockId):
 
         
     
+ 
+ 
    
-   
-# MongoDB connection setup
 client = MongoClient(MONGO_URI)
 db = client.crayonics
-collection = db['Points']
-import logging
-from datetime import datetime
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger(__name__)
+collection = db['Points']   
 
 def handle_change2(new_point):
     logger.info(f"Extra info: {new_point}")
@@ -533,11 +462,8 @@ def handle_change2(new_point):
 
 
 def handle_change3(userId:str):
-    logger.info(f"Extra info: {userId}")
-    print("No leaderboard so creating one now")
 
-    print("========================================================")
-    print("Leveled User", userId)
+
 
     if not userId:
         raise ValueError("User ID not found in inserted document")
@@ -545,17 +471,15 @@ def handle_change3(userId:str):
                 # Fetch user details
     try:
         leveleduser = get_all_users(user_id=userId)
-        print("========================================================")
-        print("Leveled User", leveleduser)
+     
     except Exception as e:
-        logger.error(f"Error fetching user details for userId {userId}: {e}")
+
         leveleduser = {}  # Default empty dict to prevent KeyError
 
         # Fetch user points
     try:
         points = get_all_simple_points_func(userId=userId)
-        print("========================================================")
-        print("Points", points)
+     
     except Exception as e:
         logger.error(f"Error fetching points for userId {userId}: {e}")
         points = SimpleIndividualUserLevel(totalpoints=0)
@@ -728,9 +652,8 @@ def handle_change(change=None):
                 
     logger.info(f"Change detected:")
 
-# Function to run the change stream in a separate thread (non-blocking)
 def watch_change_stream():
-    with concurrent.futures.ThreadPoolExecutor(max_workers=10) as executor:  # Limit to 10 threads, adjust as needed
+    with concurrent.futures.ThreadPoolExecutor(max_workers=10) as executor:  # Limited to 10 threads, because there are only 10 server worker 
         with collection.watch() as stream:
             for change in stream:
                 # Submit the handle_change task to the thread pool

controller/imports.py

@@ -0,0 +1,40 @@
+from io import BytesIO
+from dotenv import load_dotenv
+import os
+from gamification.objects import SimpleIndividualUserLevel
+from utils import *
+from fastapi import FastAPI, File, HTTPException, Header, UploadFile,status
+from tokenManagement import *
+from jwtcoding import *
+from fastapi.responses import JSONResponse
+import docx
+import fitz
+from gamification.routes import gamification
+from scraper import scrapeCourse
+import asyncio
+from google import genai 
+from typing import Optional,List
+from pydantic import BaseModel
+import re
+from bson.json_util import dumps
+import threading
+import concurrent.futures
+from gamification.pointLogic import get_all_simple_points_func,get_dream_job
+from pydantic import BaseModel
+from datetime import datetime
+from bson import ObjectId
+import os 
+import re
+from urllib.parse import urlparse
+
+from concurrent.futures import ThreadPoolExecutor
+executor = ThreadPoolExecutor(max_workers=5)
+
+
+load_dotenv()
+
+CX = os.getenv("SEARCH_ENGINE_ID")
+API_KEY = os.getenv("GOOGLE_API_KEY")
+PINECONE_API_KEY=os.getenv("PINECONE_API_KEY")
+GEMINI_API_KEY=os.getenv("GEMINI_API_KEY")
+MONGO_URI=os.getenv("MONGO_URI")

scraper.py → controller/scraper.py

@@ -1,5 +1,3 @@
-
-
 def scrapeCourse(url):
     import requests
     from bs4 import BeautifulSoup

gamification/routes.py

@@ -1,8 +1,8 @@
 from fastapi import FastAPI,HTTPException, Header
 from gamification.objects import *
 from gamification.logic import *
-from jwtcoding import decode_jwt
-from tokenManagement import verify_access_token
+from controller.jwtcoding import decode_jwt
+from controller.tokenManagement import verify_access_token
 
 class EditableUserLevel(BaseModel):
     levelId : str

testing.py

@@ -1,28 +0,0 @@
-
-from typing import List
-
-from bson import ObjectId
-from pymongo import MongoClient
-
-from app import MONGO_URI
-
-
-def get_all_users(user_id:str =None) -> List:
-    client = MongoClient(MONGO_URI)
-    db = client.crayonics
-    collection = db['users']
-    # Insert the document
-    if user_id==None:
-        results= collection.find()
-        if results:
-            result = [result for result in  results]
-            return result
-        
-        client.close()
-    else:
-        result = collection.find_one(filter={"_id":ObjectId(user_id.strip())})
-        return result
-
-
-
-print(get_all_users(user_id="67c9b68678fbf39f4ed94e01"))