Create app.py

app.py

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+import os
+from pathlib import Path
+from datetime import date
+import io
+
+import pandas as pd
+import streamlit as st
+import altair as alt
+
+# ---------- Constants ----------
+DATA_DIR = Path("data")
+DATA_FILE = DATA_DIR / "expenses.csv"
+CATEGORIES = ["Food", "Transport", "Bills", "Shopping", "Entertainment", "Other"]
+
+# ---------- Helpers ----------
+def ensure_data_file():
+    """Create data directory and CSV file with headers if missing."""
+    DATA_DIR.mkdir(exist_ok=True)
+    if not DATA_FILE.exists():
+        df = pd.DataFrame(columns=["Date", "Category", "Description", "Amount"])
+        df.to_csv(DATA_FILE, index=False)
+
+def load_expenses() -> pd.DataFrame:
+    ensure_data_file()
+    try:
+        df = pd.read_csv(DATA_FILE, parse_dates=["Date"]) if DATA_FILE.exists() else pd.DataFrame(columns=["Date", "Category", "Description", "Amount"]) 
+        if "Date" in df.columns:
+            df["Date"] = pd.to_datetime(df["Date"]).dt.date
+        return df
+    except Exception as e:
+        st.error(f"Could not load expenses: {e}")
+        return pd.DataFrame(columns=["Date", "Category", "Description", "Amount"]) 
+
+def save_expenses(df: pd.DataFrame):
+    ensure_data_file()
+    df.to_csv(DATA_FILE, index=False)
+
+def add_expense(row: dict):
+    df = load_expenses()
+    df = pd.concat([df, pd.DataFrame([row])], ignore_index=True)
+    save_expenses(df)
+
+def clear_expenses():
+    ensure_data_file()
+    df = pd.DataFrame(columns=["Date", "Category", "Description", "Amount"])
+    save_expenses(df)
+
+def get_summary(df: pd.DataFrame):
+    if df.empty:
+        return {"total": 0.0, "count": 0}
+    total = df["Amount"].sum()
+    count = len(df)
+    return {"total": total, "count": count}
+
+def csv_download_button(df: pd.DataFrame, filename: str = "expenses.csv"):
+    buffer = io.StringIO()
+    df.to_csv(buffer, index=False)
+    buffer.seek(0)
+    st.download_button("Download CSV", buffer, file_name=filename, mime="text/csv")
+
+# ---------- App UI ----------
+st.set_page_config(page_title="Expense Tracker", page_icon="💸", layout="centered")
+st.title("💸 Simple Expense Tracker")
+st.write("Add and track your expenses. Data persists to `data/expenses.csv` on the Space.")
+
+# Load data
+df = load_expenses()
+
+# Form to add expense
+with st.form("expense_form", clear_on_submit=True):
+    col1, col2 = st.columns(2)
+    with col1:
+        expense_date = st.date_input("Date", value=date.today())
+        category = st.selectbox("Category", options=CATEGORIES)
+    with col2:
+        amount = st.number_input("Amount", min_value=0.0, format="%.2f")
+        description = st.text_input("Description")
+
+    submitted = st.form_submit_button("Add expense")
+
+    if submitted:
+        if amount <= 0:
+            st.warning("Amount must be greater than 0.")
+        else:
+            row = {
+                "Date": expense_date.isoformat(),
+                "Category": category,
+                "Description": description,
+                "Amount": float(amount),
+            }
+            add_expense(row)
+            st.success("Expense added!")
+            df = load_expenses()
+
+# Sidebar actions
+st.sidebar.header("Actions")
+if st.sidebar.button("Refresh"):
+    df = load_expenses()
+
+if st.sidebar.button("Clear all expenses"):
+    if st.sidebar.checkbox("Confirm clear all (check to confirm)"):
+        clear_expenses()
+        st.sidebar.success("All expenses cleared")
+        df = load_expenses()
+
+# Display table and summary
+st.subheader("Expenses")
+if df.empty:
+    st.info("No expenses yet — add one using the form above.")
+else:
+    df["Amount"] = pd.to_numeric(df["Amount"], errors="coerce").fillna(0.0)
+    if "Date" in df.columns:
+        try:
+            df["Date"] = pd.to_datetime(df["Date"]).dt.date
+        except Exception:
+            pass
+
+    st.dataframe(df.sort_values(by="Date", ascending=False))
+
+    summary = get_summary(df)
+    st.markdown(f"**Total:** {summary['total']:.2f}   —   **Count:** {summary['count']}")
+
+    # Chart: total by category
+    st.subheader("Spending by category")
+    cat_df = df.groupby("Category", as_index=False)["Amount"].sum()
+    if not cat_df.empty:
+        chart = alt.Chart(cat_df).mark_bar().encode(
+            x=alt.X("Category:N", sort="-y"),
+            y=alt.Y("Amount:Q"),
+            tooltip=[alt.Tooltip("Category"), alt.Tooltip("Amount:Q", format=".2f")],
+        )
+        st.altair_chart(chart, use_container_width=True)
+
+    # Monthly cumulative line
+    st.subheader("Monthly spending (cumulative)")
+    df_line = df.copy()
+    df_line["Date"] = pd.to_datetime(df_line["Date"])
+    df_line["YearMonth"] = df_line["Date"].dt.to_period("M").dt.to_timestamp()
+    monthly = df_line.groupby("YearMonth")["Amount"].sum().reset_index()
+    if not monthly.empty:
+        line = alt.Chart(monthly).mark_line(point=True).encode(
+            x="YearMonth:T",
+            y="Amount:Q",
+            tooltip=[alt.Tooltip("YearMonth:T", title="Month"), alt.Tooltip("Amount:Q", format=".2f")],
+        )
+        st.altair_chart(line, use_container_width=True)
+
+# Download CSV
+st.subheader("Export")
+if not df.empty:
+    csv_download_button(df)
+
+st.caption("Data is stored locally in the app's `data/expenses.csv`. On Hugging Face Spaces this file persists across runs unless you explicitly remove it.")