Added all improvements

.gitignore

@@ -0,0 +1,2 @@
+.venv
+__pycache__

README.md

@@ -1 +1,59 @@
-# UrbanMatch-PythonTask
+<<<<<<< HEAD
+# Marriage Matchmaking App
+
+## Brief Description
+The Marriage Matchmaking App is a simple backend application designed to help users find potential matches based on their profile information. The app allows users to create, read, update, and delete profiles with details such as name, age, gender, email, city, and interests.
+
+## What is Provided?
+This project provides a basic skeleton for a FastAPI-based backend application. 
+#### Github repo: **https://github.com/abhishek-UM/UrbanMatch-PythonTask/tree/master**
+
+The provided code includes:
+
+### Basic Project Structure:
+
+- **main.py** : The main application file with basic CRUD operations for user profiles.
+- **models.py**: SQLAlchemy models defining the User schema.
+- **database.py**: Database configuration and setup.
+- **schemas.py**: Pydantic schemas for data validation and serialization.
+
+### Functionality:
+
+- Create User Endpoint: Create a new user profile.
+- Read Users Endpoint: Retrieve a list of user profiles.
+- Read User by ID Endpoint: Retrieve a user profile by ID.
+- SQLite Database: The application uses SQLite as the database to store user profiles.
+
+## What is Required?
+### Tasks:
+1. Add User Update Endpoint:
+   - Implement an endpoint to update user details by ID in the main.py file.
+2. Add User Deletion Endpoint:
+   - Implement an endpoint to delete a user profile by ID.
+3. Find Matches for a User:
+   - Implement an endpoint to find potential matches for a user based on their profile information.
+4. Add Email Validation:
+   - Add validation to ensure the email field in user profiles contains valid email addresses.
+
+## Instructions:
+Implement the required endpoints and email validation:
+
+1. Add the necessary code for the update, delete, match and validation endpoints 
+2. Test Your Implementation:
+    1. Verify that users can be updated and deleted correctly.
+    2. Check that matches are correctly retrieved for a given user.
+    3. Ensure email validation is working as expected.
+
+## Submit Your Work:
+Provide the updated code files (main.py, models.py, database.py, and schemas.py).
+Include a brief report explaining your approach and any assumptions made.
+
+
+### Prerequisites
+- Python 3.7+
+- FastAPI
+- SQLAlchemy
+- SQLite
+=======
+# UrbanMatch-PythonTask
+>>>>>>> f167553ae8b55f1b45acad5e31b8664f61fad37c

database.py

@@ -0,0 +1,12 @@
+from sqlalchemy import create_engine
+from sqlalchemy.ext.declarative import declarative_base
+from sqlalchemy.orm import sessionmaker
+
+SQLALCHEMY_DATABASE_URL = "sqlite:///./sql_app.db"
+
+engine = create_engine(
+    SQLALCHEMY_DATABASE_URL, connect_args={"check_same_thread": False}
+)
+SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
+
+Base = declarative_base()

main.py

@@ -0,0 +1,176 @@
+from fastapi import FastAPI, HTTPException, Depends
+from sqlalchemy.orm import Session
+from database import SessionLocal, engine, Base
+import models, schemas
+from typing import List
+from pydantic import EmailStr
+
+app = FastAPI()
+
+Base.metadata.create_all(bind=engine)
+
+
+class MatchingAlgorithm:
+    WEIGHTS = {"age": 0.3, "location": 0.3, "interests": 0.4}
+
+    MAX_AGE_DIFF = 10
+
+    @staticmethod
+    def calculate_age_score(user_age: int, match_age: int) -> float:
+        """Calculate age compatibility (0 to 1)"""
+        age_diff = abs(user_age - match_age)
+        if age_diff > MatchingAlgorithm.MAX_AGE_DIFF:
+            return 0
+        return 1 - (age_diff / MatchingAlgorithm.MAX_AGE_DIFF)
+
+    @staticmethod
+    def calculate_location_score(user_city: str, match_city: str) -> float:
+        """Calculate location compatibility (0 or 1)"""
+        return 1.0 if user_city.lower() == match_city.lower() else 0.0
+
+    @staticmethod
+    def calculate_interests_score(
+        user_interests: List[str], match_interests: List[str]
+    ) -> float:
+        """Calculate interests compatibility (0 to 1)"""
+        user_interests_set = set(interest.lower() for interest in user_interests)
+        match_interests_set = set(interest.lower() for interest in match_interests)
+
+        if not user_interests_set or not match_interests_set:
+            return 0.0
+
+        common_interests = len(user_interests_set.intersection(match_interests_set))
+        total_interests = len(user_interests_set)
+
+        return common_interests / total_interests
+
+
+def get_db():
+    db = SessionLocal()
+    try:
+        yield db
+    finally:
+        db.close()
+
+
+@app.post("/users/", response_model=schemas.User)
+def create_user(user: schemas.UserCreate, db: Session = Depends(get_db)):
+    existing_user = (
+        db.query(models.User).filter(models.User.email == user.email).first()
+    )
+    if existing_user:
+        raise HTTPException(status_code=400, detail="Email already registered")
+
+    user_data = user.dict()
+    db_user = models.User(**user_data)
+    db.add(db_user)
+    db.commit()
+    db.refresh(db_user)
+    return db_user
+
+
+@app.get("/users/", response_model=List[schemas.User])
+def read_users(skip: int = 0, limit: int = 10, db: Session = Depends(get_db)):
+    users = db.query(models.User).offset(skip).limit(limit).all()
+    return users
+
+
+@app.get("/users/{user_id}", response_model=schemas.User)
+def read_user(user_id: int, db: Session = Depends(get_db)):
+    user = db.query(models.User).filter(models.User.id == user_id).first()
+    if user is None:
+        raise HTTPException(status_code=404, detail="User not found")
+    return user
+
+
+@app.put("/users/{user_id}", response_model=schemas.User)
+def update_user(
+    user_id: int, user_update: schemas.UserUpdate, db: Session = Depends(get_db)
+):
+    db_user = db.query(models.User).filter(models.User.id == user_id).first()
+    if db_user is None:
+        raise HTTPException(status_code=404, detail="User not found")
+
+    if user_update.email and user_update.email != db_user.email:
+        existing_user = (
+            db.query(models.User).filter(models.User.email == user_update.email).first()
+        )
+        if existing_user:
+            raise HTTPException(status_code=400, detail="Email already registered")
+
+    update_data = user_update.dict(exclude_unset=True)
+    for key, value in update_data.items():
+        setattr(db_user, key, value)
+
+    db.commit()
+    db.refresh(db_user)
+    return db_user
+
+
+@app.delete("/users/{user_id}")
+def delete_user(user_id: int, db: Session = Depends(get_db)):
+    db_user = db.query(models.User).filter(models.User.id == user_id).first()
+    if db_user is None:
+        raise HTTPException(status_code=404, detail="User not found")
+
+    db.delete(db_user)
+    db.commit()
+    return {"message": "User deleted successfully"}
+
+
+@app.get("/users/{user_id}/matches", response_model=List[schemas.UserMatch])
+def find_matches(
+    user_id: int,
+    db: Session = Depends(get_db),
+    min_age: int = None,
+    max_age: int = None,
+):
+    """Find matches for a user"""
+    user = db.query(models.User).filter(models.User.id == user_id).first()
+    if not user:
+        raise HTTPException(status_code=404, detail="User not found")
+
+    matches_query = db.query(models.User).filter(
+        models.User.id != user_id,
+        models.User.gender != user.gender,
+    )
+
+    if min_age:
+        matches_query = matches_query.filter(models.User.age >= min_age)
+    if max_age:
+        matches_query = matches_query.filter(models.User.age <= max_age)
+
+    potential_matches = matches_query.all()
+    scored_matches = []
+
+    for match in potential_matches:
+        age_score = MatchingAlgorithm.calculate_age_score(user.age, match.age)
+        location_score = MatchingAlgorithm.calculate_location_score(
+            user.city, match.city
+        )
+        interests_score = MatchingAlgorithm.calculate_interests_score(
+            user.interests, match.interests
+        )
+
+        total_score = (
+            age_score * MatchingAlgorithm.WEIGHTS["age"]
+            + location_score * MatchingAlgorithm.WEIGHTS["location"]
+            + interests_score * MatchingAlgorithm.WEIGHTS["interests"]
+        )
+
+        if total_score > 0.5:
+            scored_matches.append(
+                {
+                    "user": match,
+                    "compatibility_score": round(total_score, 2),
+                    "match_details": {
+                        "age_compatibility": round(age_score, 2),
+                        "location_compatibility": round(location_score, 2),
+                        "interests_compatibility": round(interests_score, 2),
+                    },
+                }
+            )
+
+    scored_matches.sort(key=lambda x: x["compatibility_score"], reverse=True)
+
+    return scored_matches

models.py

@@ -0,0 +1,14 @@
+from sqlalchemy import Column, Integer, String, JSON
+from database import Base
+
+
+class User(Base):
+    __tablename__ = "users"
+
+    id = Column(Integer, primary_key=True, index=True)
+    name = Column(String, index=True)
+    age = Column(Integer)
+    gender = Column(String)
+    email = Column(String, unique=True, index=True)
+    city = Column(String, index=True)
+    interests = Column(JSON)

schemas.py

@@ -0,0 +1,42 @@
+from pydantic import BaseModel, EmailStr
+from typing import List, Optional, Dict
+
+
+class UserBase(BaseModel):
+    name: str
+    age: int
+    gender: str
+    email: EmailStr
+    city: str
+    interests: List[str]
+
+
+class UserCreate(UserBase):
+    pass
+
+
+class UserUpdate(BaseModel):
+    name: Optional[str] = None
+    age: Optional[int] = None
+    email: Optional[EmailStr] = None
+    city: Optional[str] = None
+    interests: Optional[List[str]] = None
+
+
+class MatchDetails(BaseModel):
+    age_compatibility: float
+    location_compatibility: float
+    interests_compatibility: float
+
+
+class UserMatch(BaseModel):
+    user: "User"
+    compatibility_score: float
+    match_details: MatchDetails
+
+
+class User(UserBase):
+    id: int
+
+    class Config:
+        orm_mode = True