Code Editor for app.py

import streamlit as st
import pandas as pd
import plotly.express as px
from datetime import datetime
from sqlalchemy import create_engine, Column, Integer, Float, String, Date
from sqlalchemy.orm import DeclarativeBase, Session

# Database setup
class Base(DeclarativeBase):
    pass

class Transaction(Base):
    __tablename__ = 'transactions'
    
    id = Column(Integer, primary_key=True)
    date = Column(Date, nullable=False)
    category = Column(String, nullable=False)
    amount = Column(Float, nullable=False)
    description = Column(String)

# Create database and tables
engine = create_engine('sqlite:///finance.sqlite')
Base.metadata.create_all(bind=engine)

# Page config
st.set_page_config(page_title="Personal Finance Manager", layout="wide")
st.title("Personal Finance Manager 💰")

# Sidebar for adding transactions
with st.sidebar:
    st.header("Add New Transaction")
    
    # Transaction form
    with st.form("transaction_form"):
        date = st.date_input("Date", datetime.now())
        category = st.selectbox(
            "Category",
            ["Food", "Transportation", "Housing", "Entertainment", "Shopping", "Healthcare", "Other"]
        )
        amount = st.number_input("Amount", min_value=0.0, step=0.01)
        description = st.text_input("Description")
        
        submit = st.form_submit_button("Add Transaction")
        
        if submit:
            with Session(engine) as session:
                transaction = Transaction(
                    date=date,
                    category=category,
                    amount=amount,
                    description=description
                )
                session.add(transaction)
                session.commit()
            st.success("Transaction added successfully!")

# Main content
tab1, tab2 = st.tabs(["Transactions", "Analytics"])

with tab1:
    # Display transactions
    with Session(engine) as session:
        transactions = session.query(Transaction).all()
        if transactions:
            df = pd.DataFrame([
                {
                    "Date": t.date,
                    "Category": t.category,
                    "Amount": t.amount,
                    "Description": t.description
                }
                for t in transactions
            ])
            st.dataframe(
                df.sort_values("Date", ascending=False),
                use_container_width=True,
                hide_index=True
            )
        else:
            st.info("No transactions recorded yet. Add your first transaction using the sidebar!")

with tab2:
    if transactions:
        col1, col2 = st.columns(2)
        
        with col1:
            # Spending by category pie chart
            fig1 = px.pie(
                df,
                values="Amount",
                names="Category",
                title="Spending by Category"
            )
            st.plotly_chart(fig1, use_container_width=True)
        
        with col2:
            # Spending over time line chart
            fig2 = px.line(
                df.groupby("Date")["Amount"].sum().reset_index(),
                x="Date",
                y="Amount",
                title="Daily Spending"
            )
            st.plotly_chart(fig2, use_container_width=True)
        
        # Summary statistics
        st.subheader("Summary Statistics")
        total_spent = df["Amount"].sum()
        avg_transaction = df["Amount"].mean()
        num_transactions = len(df)
        
        col1, col2, col3 = st.columns(3)
        col1.metric("Total Spent", f"${total_spent:.2f}")
        col2.metric("Average Transaction", f"${avg_transaction:.2f}")
        col3.metric("Number of Transactions", num_transactions)
        
        # Category breakdown
        st.subheader("Category Breakdown")
        category_stats = df.groupby("Category")["Amount"].agg(["sum", "mean", "count"]).round(2)
        category_stats.columns = ["Total Amount", "Average Amount", "Number of Transactions"]
        st.dataframe(category_stats, use_container_width=True)