Database queries for Dashboard

db.py

+from pymongo import MongoClient
+import json
+from bson import ObjectId
+import pandas as pd
+from datetime import datetime, timedelta, timezone
+
+# Importing the dataset in the database
+
+def import_expenses(user_id):
+    # Connect to the local MongoDB server
+    client = MongoClient('mongodb://localhost:27017/')
+    db = client['financial_management']
+    expenses_collection = db['expenses']
+
+    # The ObjectId of the user "tushar"
+    user_object_id = ObjectId(user_id)
+
+    file_path = 'data/Expenses.txt'
+    with open(file_path, 'r') as file:
+        for line in file:
+            expense_data = json.loads(line.strip())
+            # Add the UserID reference before inserting
+            expense_data['UserID'] = user_object_id
+            expenses_collection.insert_one(expense_data)
+
+    print("Data import complete.")
+
+
+#Importing catergories data into categories collection
+def import_categories():
+    # Connect to the local MongoDB server
+    client = MongoClient('mongodb://localhost:27017/')
+    db = client['financial_management']
+    categories_collection = db['categories']
+
+    # List of categories to be inserted
+    categories_list = [
+        {"CategoryID": 1, "CategoryName": "All"},
+        {"CategoryID": 2, "CategoryName": "Housing"},
+        {"CategoryID": 3, "CategoryName": "Utilities"},
+        {"CategoryID": 4, "CategoryName": "Groceries"},
+        {"CategoryID": 5, "CategoryName": "Transportation"},
+        {"CategoryID": 6, "CategoryName": "Entertainment"},
+        {"CategoryID": 7, "CategoryName": "Education"},
+        {"CategoryID": 8, "CategoryName": "Miscellaneous"}
+        
+    ]
+
+   # Insert all categories into the database
+    categories_collection.insert_many(categories_list)
+
+    print("Categories import complete.")
+
+
+# Function to retrieve the database connection
+def get_db():
+    client = MongoClient('mongodb://localhost:27017/')
+    return client['financial_management']
+
+# Function to fetch expenses and category data from MongoDB and return as DataFrames
+def fetch_data():
+    db = get_db()
+    expenses_data = list(db.expenses.find({}, {'_id': 0, 'Amount': 1, 'DateOfExpense': 1, 'CategoryID': 1, 'MerchantName': 1}))
+    categories_data = list(db.categories.find({}, {'_id': 0}))
+    
+    expenses_df = pd.DataFrame(expenses_data)
+    categories_df = pd.DataFrame(categories_data)
+    
+    # Convert date strings to datetime objects
+    expenses_df['DateOfExpense'] = pd.to_datetime(expenses_df['DateOfExpense'])
+    return expenses_df, categories_df
+
+# Function to fetch budget data for a given category and date range
+def get_budget_data(category_id, start_date, end_date):
+    db = get_db()
+    budgets = list(db.budgets.find({
+        "UserID": ObjectId("662947d472ecb2349f29cbe1"), 
+        "CategoryID": category_id,
+        "StartDate": {"$gte": start_date},
+        "EndDate": {"$lte": end_date}
+    }))
+    return budgets
+
+# Function to calculate the start and end of the current month
+def get_time_bounds():
+    now = datetime.now(timezone.utc).replace(hour=0, minute=0, second=0, microsecond=0)
+    start = now.replace(day=1)  # Start of this month
+    end = (start.replace(month=start.month % 12 + 1, day=1) - timedelta(microseconds=1))  # End of this month
+    return start, end
+
+# Function to fetch budget status, total spent, and total budget for a user and category
+def get_budget_status(user_id, category_id):
+    db = get_db()
+    category_id = int(category_id)
+
+    if category_id == 1:  # Assuming '1' is the ID for 'All'
+        category_filter = {}
+    else:
+        category_filter = {"CategoryID": category_id}
+
+    start_of_month, end_of_month = get_time_bounds()
+
+    monthly_budgets = list(db.budgets.find({
+        "UserID": ObjectId(user_id),
+        **category_filter,
+        "StartDate": {"$gte": start_of_month, "$lte": end_of_month},
+    }))
+
+    expenses = list(db.expenses.find({
+        "UserID": ObjectId(user_id),
+        **category_filter
+    }))
+
+    # Convert expenses to DataFrame and filter by date
+    expenses_df = pd.DataFrame(expenses)
+    if not expenses_df.empty:
+        expenses_df['DateOfExpense'] = pd.to_datetime(expenses_df['DateOfExpense']).dt.tz_localize(timezone.utc)
+
+    filtered_expenses_df = expenses_df[(expenses_df['DateOfExpense'] >= start_of_month) & (expenses_df['DateOfExpense'] <= end_of_month)]
+    total_spent = filtered_expenses_df['Amount'].sum() if not expenses_df.empty else 0
+
+    # Calculate total budget for the month
+    total_budget = sum(b['BudgetLimit'] for b in monthly_budgets)
+
+    # Calculate budget left
+    monthly_budget_left = total_budget - total_spent
+    budget_status = f"£{monthly_budget_left:.2f}" if monthly_budget_left >= 0 else "Budget exceeded"
+    
+    # Returning total spent and budget limit for pie chart visualization
+    return budget_status, total_spent, total_budget
+
+
+
+
+# Function to update the monthly budget in the database
+def update_budget_in_db(user_id, category_id, amount, db):
+    start_of_month, end_of_month = get_time_bounds()
+
+    budgets_collection = db.budgets
+    budgets_collection.update_one(
+        {
+            "UserID": ObjectId(user_id),
+            "CategoryID": category_id
+        },
+        {
+            "$set": {
+                "BudgetLimit": amount,
+                "StartDate": start_of_month,
+                "EndDate": end_of_month
+            }
+        },
+        upsert=True
+    )
+
+# Function to fetch all budgets from the database
+def fetch_all_budgets():
+    db = get_db()
+    return list(db.budgets.find({}, {'_id': 0, 'CategoryID': 1, 'BudgetLimit': 1, 'StartDate': 1, 'EndDate': 1, 'Period': 1}))
+
+
+# Function to fetch all categories from the database
+def fetch_categories():
+    db = get_db()
+    categories = list(db.categories.find({}, {'_id': 0, 'CategoryID': 1, 'CategoryName': 1}))
+    return categories
+
+
+
+
+
+
+
+
+# Calling the function created above to set up the database
+
+# Importing expenses from Expenses.txt
+# import_expenses('662947d472ecb2349f29cbe1') #Uncomment this to import expenses from data/expenses.txt
+
+# Importing  categories
+# import_categories() #Uncomment this to import expenses from data/categories.txt
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