Update app.py

app.py

@@ -1,20 +1,205 @@
-I want to build a Streamlit web app called "💸 Expensive Tracker".
-
-The app should allow users to input and track their expenses. It should look modern, clean, and attractive.
-
-Requirements:
-1. The app should have a sidebar menu with options like "Add Expense", "View Expenses", and "Summary".
-2. Users can input:
-   - Date of expense
-   - Category (Food, Travel, Shopping, Bills, Other)
-   - Amount
-   - Notes (optional)
-3. Expenses should be stored in a pandas DataFrame.
-4. Display all expenses in a table with sorting and filtering options.
-5. Add a summary dashboard that shows:
-   - Total Expenses
-   - Expenses by Category (pie chart)
-   - Expenses Over Time (line/bar chart)
-6. Make the design visually appealing using colors, emojis, and modern layout.
-7. Save the code in `app.py`.
-8. Create a `requirements.txt` file listing the dependencies for Hugging Face Spaces deployment.
+import streamlit as st
+import pandas as pd
+import plotly.express as px
+from io import StringIO
+from datetime import date
+
+# -------------------------------
+# 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);
+    }
+    </style>
+    """,
+    unsafe_allow_html=True,
+)
+
+st.title("💸 Expensive Tracker")
+st.caption("Track expenses, analyze spending by category and over time — attractive, simple, and portable.")
+
+# -------------------------------
+# 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"]
+    )
+
+# -------------------------------
+# 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")
+    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:
+            amount = st.number_input("Amount (₨ or your currency)", min_value=0.0, format="%.2f")
+        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": float(amount), "Notes": notes}
+        st.session_state.expenses = pd.concat([st.session_state.expenses, pd.DataFrame([new_row])], ignore_index=True)
+        st.success("Expense added ✅")
+        st.balloons()
+
+    if not st.session_state.expenses.empty:
+        st.markdown("**Quick preview of latest expenses**")
+        st.dataframe(st.session_state.expenses.tail(6).reset_index(drop=True))
+
+# -------------------------------
+# View Expenses
+# -------------------------------
+elif page == "View Expenses":
+    st.header("All Expenses")
+    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()
+        # Allow filtering
+        st.markdown("Filter")
+        cols = st.columns([1, 1, 1])
+        with cols[0]:
+            min_date = st.date_input("From", value=df["Date"].min())
+        with cols[1]:
+            max_date = st.date_input("To", value=df["Date"].max())
+        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)]
+
+        st.dataframe(filtered.sort_values(by="Date", ascending=False).reset_index(drop=True))
+
+        # 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")
+    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"])
+        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", f"{total:,.2f}")
+        c2.metric("Average Expense", f"{avg:,.2f}")
+        c3.metric("Largest Expense", f"{max_exp:,.2f}")
+        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)
+        fig_pie = px.pie(cat_summary, names="Category", values="Amount", title="Spending by Category", hole=0.4)
+        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()
+        # Fill missing days for smooth line
+        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)")
+        st.plotly_chart(fig_line, use_container_width=True)
+
+        st.markdown("### 🔎 Top 5 Expenses")
+        st.dataframe(df.nlargest(5, "Amount")[["Date", "Category", "Amount", "Notes"]].reset_index(drop=True))
+
+# -------------------------------
+# Import / Export
+# -------------------------------
+elif page == "Import / Export":
+    st.header("Import or Export your data")
+    st.markdown("You can download your current expenses as a CSV or upload a CSV to load expenses.")
+
+    # Download
+    if st.session_state.expenses.empty:
+        st.info("No expenses to export.")
+    else:
+        csv = st.session_state.expenses.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)")
+    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:
+                # Append uploaded
+                uploaded_df = uploaded_df[["Date", "Category", "Amount", "Notes"]] if "Notes" in uploaded_df.columns else uploaded_df.assign(Notes="")
+                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,
+)