app.py

import streamlit as st
import pandas as pd
import plotly.express as px
from io import StringIO
from datetime import date

# -------------------------------
# Helpers
# -------------------------------
def format_rs(amount):
    """Format numeric amount into Rupee string with thousands separators."""
    try:
        # show no decimals for rupee amounts
        return f"Rs {int(round(float(amount))):,}"
    except Exception:
        return str(amount)

def ensure_numeric_amount(col):
    """Convert amount column to numeric (int) safely."""
    return pd.to_numeric(col, errors="coerce").fillna(0).astype(int)

# -------------------------------
# Page config & CSS
# -------------------------------
st.set_page_config(page_title="💸 Expensive Tracker", page_icon="💳", layout="centered")

st.markdown(
    """
    <style>
    /* Page background gradient */
    .reportview-container {
        background: linear-gradient(135deg,#0f172a,#3b4252);
        color: #e6eef8;
    }
    .stButton>button {
        background: linear-gradient(90deg,#ff7a18,#af002d);
        color: white;
        border-radius: 10px;
        padding: 0.55em 1em;
        font-weight: 600;
    }
    .stButton>button:hover {
        transform: scale(1.02);
        filter: brightness(1.05);
    }
    .card {
        background: rgba(255,255,255,0.06);
        padding: 12px;
        border-radius: 12px;
        border: 1px solid rgba(255,255,255,0.06);
        box-shadow: 0 6px 18px rgba(0,0,0,0.3);
    }
    .dataframe td, .dataframe th {
        color: #e6eef8 !important;
    }
    </style>
    """,
    unsafe_allow_html=True,
)

st.title("💸 Expensive Tracker")
st.caption("Track expenses in Rupees (Rs). Enter whole numbers like 100, 500, 10000.")

# -------------------------------
# Initialize in-memory storage
# -------------------------------
if "expenses" not in st.session_state:
    # columns: Date, Category, Amount, Notes
    st.session_state.expenses = pd.DataFrame(
        columns=["Date", "Category", "Amount", "Notes"]
    )

# Ensure Amount column numeric if loaded previously
if not st.session_state.expenses.empty:
    st.session_state.expenses["Amount"] = ensure_numeric_amount(st.session_state.expenses["Amount"])

# -------------------------------
# Sidebar navigation
# -------------------------------
st.sidebar.header("⚙️ Menu")
page = st.sidebar.radio("Choose view", ["Add Expense", "View Expenses", "Summary", "Import / Export"])

# Common categories
CATEGORIES = ["Food", "Travel", "Shopping", "Bills", "Entertainment", "Health", "Other"]

# -------------------------------
# Add Expense
# -------------------------------
if page == "Add Expense":
    st.header("Add a new expense (Amount in Rs)")
    with st.form("add_expense_form", clear_on_submit=True):
        c1, c2, c3 = st.columns([1, 1, 1])
        with c1:
            exp_date = st.date_input("Date", value=date.today())
        with c2:
            category = st.selectbox("Category", options=CATEGORIES)
        with c3:
            # Integer rupee input
            amount = st.number_input("Amount (Rs)", min_value=0, step=1, format="%d", value=0)
        notes = st.text_area("Notes (optional)", max_chars=200, placeholder="Where/what for?")
        submitted = st.form_submit_button("➕ Add Expense")

    if submitted:
        new_row = {
            "Date": pd.to_datetime(exp_date).date(),
            "Category": category,
            "Amount": int(amount),
            "Notes": notes
        }
        st.session_state.expenses = pd.concat([st.session_state.expenses, pd.DataFrame([new_row])], ignore_index=True)
        st.success(f"Expense added ✅ {format_rs(amount)}")
        st.balloons()

    if not st.session_state.expenses.empty:
        st.markdown("**Quick preview of latest expenses**")
        preview = st.session_state.expenses.tail(6).reset_index(drop=True).copy()
        # Format Amount column for display
        preview["Amount (Rs)"] = preview["Amount"].apply(format_rs)
        st.dataframe(preview[["Date", "Category", "Amount (Rs)", "Notes"]])

# -------------------------------
# View Expenses
# -------------------------------
elif page == "View Expenses":
    st.header("All Expenses (Amounts in Rs)")
    if st.session_state.expenses.empty:
        st.info("No expenses yet — add some from the 'Add Expense' tab.")
    else:
        df = st.session_state.expenses.copy()
        df["Amount"] = ensure_numeric_amount(df["Amount"])
        # Allow filtering
        st.markdown("Filter")
        cols = st.columns([1, 1, 1])
        with cols[0]:
            min_date = st.date_input("From", value=pd.to_datetime(df["Date"]).min().date())
        with cols[1]:
            max_date = st.date_input("To", value=pd.to_datetime(df["Date"]).max().date())
        with cols[2]:
            sel_cat = st.multiselect("Category", options=["All"] + CATEGORIES, default=["All"])
        filtered = df[
            (pd.to_datetime(df["Date"]) >= pd.to_datetime(min_date)) &
            (pd.to_datetime(df["Date"]) <= pd.to_datetime(max_date))
        ]
        if sel_cat and "All" not in sel_cat:
            filtered = filtered[filtered["Category"].isin(sel_cat)]

        display_df = filtered.sort_values(by="Date", ascending=False).reset_index(drop=True).copy()
        display_df["Amount (Rs)"] = display_df["Amount"].apply(format_rs)
        st.dataframe(display_df[["Date", "Category", "Amount (Rs)", "Notes"]])

        # Option to delete last entry or clear all
        st.markdown("---")
        cdel, cclear = st.columns(2)
        with cdel:
            if st.button("🗑️ Delete last entry"):
                st.session_state.expenses = st.session_state.expenses[:-1].reset_index(drop=True)
                st.success("Last entry removed.")
        with cclear:
            if st.button("⚠️ Clear all expenses"):
                st.session_state.expenses = pd.DataFrame(columns=["Date", "Category", "Amount", "Notes"])
                st.success("All expenses cleared.")

# -------------------------------
# Summary Dashboard
# -------------------------------
elif page == "Summary":
    st.header("Summary Dashboard (Rs)")
    if st.session_state.expenses.empty:
        st.info("No data yet — add expenses to see the summary.")
    else:
        df = st.session_state.expenses.copy()
        df["Date"] = pd.to_datetime(df["Date"])
        df["Amount"] = ensure_numeric_amount(df["Amount"])

        total = df["Amount"].sum()
        avg = df["Amount"].mean()
        max_exp = df["Amount"].max()
        st.markdown("<div class='card'>", unsafe_allow_html=True)
        c1, c2, c3 = st.columns(3)
        c1.metric("Total Spent", format_rs(total))
        c2.metric("Average Expense", format_rs(avg))
        c3.metric("Largest Expense", format_rs(max_exp))
        st.markdown("</div>", unsafe_allow_html=True)

        st.markdown("### 📊 Expenses by Category")
        cat_summary = df.groupby("Category", as_index=False)["Amount"].sum().sort_values("Amount", ascending=False)
        # For plotly, keep numeric values; labels can show Rs via hover
        fig_pie = px.pie(cat_summary, names="Category", values="Amount", title="Spending by Category", hole=0.4)
        fig_pie.update_traces(textinfo="percent+label", hovertemplate="%{label}: Rs %{value:,}<extra></extra>")
        st.plotly_chart(fig_pie, use_container_width=True)

        st.markdown("### 🕒 Expenses Over Time")
        timeseries = df.groupby(pd.Grouper(key="Date", freq="D"))["Amount"].sum().reset_index()
        timeseries = timeseries.set_index("Date").resample("D").sum().fillna(0).reset_index()
        fig_line = px.bar(timeseries, x="Date", y="Amount", title="Daily Spending (bar)")
        fig_line.update_traces(hovertemplate="Date: %{x}<br>Amount: Rs %{y:,}<extra></extra>")
        st.plotly_chart(fig_line, use_container_width=True)

        st.markdown("### 🔎 Top 5 Expenses")
        top5 = df.nlargest(5, "Amount")[["Date", "Category", "Amount", "Notes"]].reset_index(drop=True).copy()
        top5["Amount (Rs)"] = top5["Amount"].apply(format_rs)
        st.dataframe(top5[["Date", "Category", "Amount (Rs)", "Notes"]])

# -------------------------------
# Import / Export
# -------------------------------
elif page == "Import / Export":
    st.header("Import or Export your data (CSV)")
    st.markdown("You can download your current expenses as a CSV or upload a CSV to load expenses. Amounts are stored as integers (Rs).")

    # Download
    if st.session_state.expenses.empty:
        st.info("No expenses to export.")
    else:
        # Ensure numeric amounts before export
        export_df = st.session_state.expenses.copy()
        export_df["Amount"] = ensure_numeric_amount(export_df["Amount"])
        csv = export_df.to_csv(index=False)
        st.download_button("⬇️ Download CSV", data=csv, file_name="expenses.csv", mime="text/csv")

    st.markdown("---")
    st.markdown("Upload a CSV file (columns: Date, Category, Amount, Notes). Amounts should be numeric (Rs).")
    uploaded = st.file_uploader("Upload CSV", type=["csv"])
    if uploaded is not None:
        try:
            uploaded_df = pd.read_csv(uploaded, parse_dates=["Date"])
            # Basic validation
            required = {"Date", "Category", "Amount"}
            if not required.issubset(set(uploaded_df.columns)):
                st.error("CSV must include at least Date, Category, and Amount columns.")
            else:
                # Normalize columns and types
                if "Notes" not in uploaded_df.columns:
                    uploaded_df["Notes"] = ""
                uploaded_df = uploaded_df[["Date", "Category", "Amount", "Notes"]]
                uploaded_df["Amount"] = ensure_numeric_amount(uploaded_df["Amount"])
                uploaded_df["Date"] = pd.to_datetime(uploaded_df["Date"]).dt.date
                st.session_state.expenses = pd.concat([st.session_state.expenses, uploaded_df], ignore_index=True)
                st.success("Uploaded expenses added to your tracker.")
        except Exception as e:
            st.error(f"Failed to parse CSV: {e}")

# -------------------------------
# Footer / Tips
# -------------------------------
st.markdown("---")
st.markdown(
    "<div style='text-align:center;opacity:0.8'>Made with ❤️ — Deploy to Hugging Face Spaces (SDK: Streamlit). "
    "Tip: Use the Import/Export tab to keep your data between sessions.</div>",
    unsafe_allow_html=True,
)