main.py

from fastapi import FastAPI, HTTPException, Query
from supabase import create_client, Client
from typing import List
import uvicorn
from datetime import datetime, timedelta
from collections import Counter
from dotenv import load_dotenv
import os

load_dotenv()
app = FastAPI()

# Initialize Supabase client
url: str = os.getenv("SUPABASE_URL")
key: str = os.getenv("SUPABASE_KEY")
supabase: Client = create_client(url, key)

table = "receipt_radar_structured_data_duplicate"

@app.get("/")
def test():
    return {"message":"Application is working !!"}

@app.get("/test")
def test1():
    return {"Api response !!"}

@app.get("/user-analytics")
async def get_user_analytics(
    hush_id: str = Query(..., description="User's hush ID"),
    limit: int = 5
):
    # Fetch all necessary data in one query
    response = supabase.table(table).select("*").eq("user_id", hush_id).execute()
    
    # Process the data for different analytics
    total_amount = sum(float(item['total_cost']) for item in response.data if item['total_cost'] is not None)
    
    dates = [datetime.strptime(item['Date'], "%d-%m-%Y") for item in response.data if item['Date'] is not None]
    date_counts = Counter(dates)
    
    avg_transaction = total_amount / len(response.data) if response.data else 0
    
    item_counts = Counter(item['brand'] for item in response.data)
    
    category_counts = Counter(item['purchase_category'] for item in response.data)
    
    category_spending = {}
    brand_spending = {}
    for item in response.data:
        category = item['purchase_category']
        brand = item['brand_category']
        cost = float(item['total_cost'])
        category_spending[category] = category_spending.get(category, 0) + cost
        brand_spending[brand] = brand_spending.get(brand, 0) + cost
    
    sorted_categories = sorted(category_spending.items(), key=lambda x: x[1], reverse=True)
    sorted_brands = sorted(brand_spending.items(), key=lambda x: x[1], reverse=True)

    return {
        "total_amount_spent": total_amount,
        # "frequency_of_purchases": dict(date_counts),
        "average_transaction_value": avg_transaction,
        "most_purchased_items": dict(item_counts.most_common(limit)),
        "purchase_categories": dict(category_counts),
        "categories_with_highest_spending": dict(sorted_categories[:limit]),
        "brand_preferences": dict(sorted_brands[:limit])
    }


@app.get("/total-amount-spent")
async def get_total_amount_spent(hush_id: str = Query(..., description="User's hush ID")):
    response = supabase.table(table).select("total_cost").eq("user_id", hush_id).execute()
    print(response)
    total_amount = sum(float(item['total_cost']) for item in response.data if item['Total_cost'] is not None)
    return {"total_amount_spent": total_amount}

@app.get("/frequency-of-purchases")
async def get_frequency_of_purchases(hush_id: str = Query(..., description="User's hush ID")):
    response = supabase.table(table).select("Date").eq("user_id", hush_id).execute()
    print(response)
    dates = [datetime.strptime(item['Date'], "%d-%m-%Y") for item in response.data if item['Date'] is not None]
    print(dates)
    # dates = []
    # for item in response.data:
    #     if item['Date']:
    #         date = datetime.fromisoformat(item['Date'].replace('Z', '+00:00'))
    #         dates.append(date.strftime("%Y-%m-%d"))  # Format as YYYY-MM-DD
    date_counts = Counter(dates)
    return {"frequency_of_purchases": dict(date_counts)}

@app.get("/average-transaction-value")
async def get_average_transaction_value(hush_id: str = Query(..., description="User's hush ID")):
    response = supabase.table(table).select("total_cost").eq("user_id", hush_id).execute()
    total_amount = sum(float(item['total_cost']) for item in response.data)
    avg_transaction = total_amount / len(response.data) if response.data else 0
    return {"average_transaction_value": avg_transaction}

@app.get("/most-purchased-items")
async def get_most_purchased_items(hush_id: str = Query(..., description="User's hush ID"), limit: int = 5):
    response = supabase.table(table).select("brand").eq("user_id", hush_id).execute()
    item_counts = Counter(item['brand'] for item in response.data)
    return {"most_purchased_items": dict(item_counts.most_common(limit))}

@app.get("/purchase-categories")
async def get_purchase_categories(hush_id: str = Query(..., description="User's hush ID")):
    response = supabase.table(table).select("purchase_category").eq("user_id", hush_id).execute()
    category_counts = Counter(item['purchase_category'] for item in response.data)
    return {"purchase_categories": dict(category_counts)}

@app.get("/categories-with-highest-spending")
async def get_categories_with_highest_spending(hush_id: str = Query(..., description="User's hush ID"), limit: int = 5):
    response = supabase.table(table).select("purchase_category,total_cost").eq("user_id", hush_id).execute()
    category_spending = {}
    for item in response.data:
        category = item['purchase_category']
        cost = float(item['total_cost'])
        category_spending[category] = category_spending.get(category, 0) + cost
    sorted_categories = sorted(category_spending.items(), key=lambda x: x[1], reverse=True)
    return {"categories_with_highest_spending": dict(sorted_categories[:limit])}

@app.get("/brand-preferences")
async def get_brand_preferences(hush_id: str = Query(..., description="User's hush ID"), limit: int = 5):
    response = supabase.table(table).select("brand_category,total_cost").eq("user_id", hush_id).execute()
    brand_spending = {}
    for item in response.data:
        brand = item['brand_category']
        cost = float(item['total_cost'])
        brand_spending[brand] = brand_spending.get(brand, 0) + cost
    sorted_brands = sorted(brand_spending.items(), key=lambda x: x[1], reverse=True)
    return {"brand_preferences": dict(sorted_brands[:limit])}