expense_tracker.py

import streamlit as st
import pandas as pd
import matplotlib.pyplot as plt
import os
from datetime import date

st.set_page_config(page_title="Expense Tracker", page_icon="💰", layout="wide")
st.title("💰 Expense Tracker with Visuals")

DATA_FILE = "expenses.csv"

# Load or create data
if os.path.exists(DATA_FILE):
    df = pd.read_csv(DATA_FILE)
else:
    df = pd.DataFrame(columns=["Date", "Category", "Description", "Amount"])

# ── Sidebar: Add Expense ──────────────────────────────────────────────────────
st.sidebar.header("➕ Add New Expense")
with st.sidebar:
    exp_date = st.date_input("Date", value=date.today())
    category = st.selectbox("Category", ["Food", "Transport", "Shopping",
                                          "Entertainment", "Health", "Bills", "Other"])
    description = st.text_input("Description")
    amount = st.number_input("Amount (₹)", min_value=0.0, step=10.0)
    budget = st.number_input("Monthly Budget (₹)", min_value=0.0, step=100.0, value=10000.0)

    if st.button("Add Expense", use_container_width=True):
        if amount > 0 and description:
            new_row = pd.DataFrame([[str(exp_date), category, description, amount]],
                                   columns=["Date", "Category", "Description", "Amount"])
            df = pd.concat([df, new_row], ignore_index=True)
            df.to_csv(DATA_FILE, index=False)
            st.success("Expense added!")
            st.rerun()
        else:
            st.error("Please fill all fields.")

    # CSV Upload
    st.markdown("---")
    st.subheader("📂 Upload CSV")
    uploaded = st.file_uploader("Upload expenses CSV", type=["csv"])
    if uploaded:
        uploaded_df = pd.read_csv(uploaded)
        df = pd.concat([df, uploaded_df], ignore_index=True)
        df.to_csv(DATA_FILE, index=False)
        st.success("CSV uploaded!")
        st.rerun()

# ── Main Dashboard ────────────────────────────────────────────────────────────
if df.empty:
    st.info("No expenses yet. Add one from the sidebar!")
else:
    df["Amount"] = pd.to_numeric(df["Amount"], errors="coerce")
    df["Date"] = pd.to_datetime(df["Date"])

    total = df["Amount"].sum()
    col1, col2, col3 = st.columns(3)
    col1.metric("Total Spent", f"₹{total:,.2f}")
    col2.metric("Monthly Budget", f"₹{budget:,.2f}")
    remaining = budget - total
    col3.metric("Remaining", f"₹{remaining:,.2f}", delta=f"{'Over budget!' if remaining < 0 else 'OK'}")

    if remaining < 0:
        st.error("⚠️ You have exceeded your budget!")
    elif remaining < budget * 0.2:
        st.warning("⚠️ Only 20% of budget remaining!")

    st.markdown("---")
    col_a, col_b = st.columns(2)

    # Pie Chart
    with col_a:
        st.subheader("📊 Spending by Category")
        cat_data = df.groupby("Category")["Amount"].sum()
        fig1, ax1 = plt.subplots()
        ax1.pie(cat_data, labels=cat_data.index, autopct="%1.1f%%", startangle=90)
        ax1.axis("equal")
        st.pyplot(fig1)

    # Bar Chart by Date
    with col_b:
        st.subheader("📅 Daily Spending")
        daily = df.groupby(df["Date"].dt.date)["Amount"].sum()
        fig2, ax2 = plt.subplots()
        ax2.bar(daily.index.astype(str), daily.values, color="steelblue")
        ax2.set_xlabel("Date")
        ax2.set_ylabel("Amount (₹)")
        plt.xticks(rotation=45, ha="right")
        st.pyplot(fig2)

    # Expense Table
    st.markdown("---")
    st.subheader("📋 All Expenses")
    st.dataframe(df.sort_values("Date", ascending=False), use_container_width=True)

    # Export
    st.download_button("⬇️ Export to CSV", df.to_csv(index=False),
                       file_name="expense_report.csv", mime="text/csv")

    # Excel Export
    excel_path = "expense_report.xlsx"
    df.to_excel(excel_path, index=False)
    with open(excel_path, "rb") as f:
        st.download_button("⬇️ Export to Excel", f, file_name="expense_report.xlsx",
                           mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet")