Update app.py

app.py

@@ -1,67 +1,124 @@
-"""
-
-    # Add a new blank custom appliance
-    with st.expander("Quick add custom appliance"):
-        new_name = st.text_input("Appliance name", key='new_name')
-        new_cat = st.selectbox("Category", options=list(DEFAULT_APPLIANCES.keys()), key='new_cat')
-        new_power = st.number_input("Power (W)", min_value=1, value=100, key='new_power')
-        new_qty = st.number_input("Quantity", min_value=0, value=1, key='new_qty')
-        new_hours = st.number_input("Hours/day", min_value=0.0, value=1.0, key='new_hours')
-        if st.button("Add appliance"):
-            st.session_state.appliances.append({
-                'category': new_cat,
-                'name': new_name or 'Custom',
-                'qty': new_qty,
-                'power_w': new_power,
-                'hours_per_day': new_hours
+import streamlit as st
+import pandas as pd
+import plotly.express as px
+from fpdf import FPDF
+
+st.set_page_config(page_title="Solar System Sizing Calculator", layout="wide")
+
+# Default appliance power ratings (W)
+DEFAULTS = {
+    "LED Light": 10,
+    "Fan": 75,
+    "AC (1.5 ton)": 1500,
+    "Refrigerator": 200,
+    "TV": 100,
+    "Laptop/Computer": 120,
+    "Washing Machine": 500,
+    "Water Pump": 750
+}
+
+st.title("☀️ Solar System Sizing Calculator")
+st.markdown("Enter your household appliances to estimate the ideal solar system size.")
+
+# Sidebar for appliance input
+appliances = []
+total_energy_wh = 0
+
+with st.sidebar:
+    st.header("Appliance Details")
+    for device, power in DEFAULTS.items():
+        qty = st.number_input(f"Number of {device}s", min_value=0, value=0, step=1)
+        hours = st.number_input(f"Usage hours/day for {device}", min_value=0, value=0, step=1)
+        power_w = st.number_input(f"Power (W) for {device}", min_value=1, value=power, step=1)
+        if qty > 0 and hours > 0:
+            energy = qty * power_w * hours
+            total_energy_wh += energy
+            appliances.append({
+                "Device": device,
+                "Quantity": qty,
+                "Power (W)": power_w,
+                "Hours/day": hours,
+                "Daily Energy (Wh)": energy
             })
-            st.experimental_rerun()
-
-    st.markdown("**Edit existing appliances (set qty/hours).**")
-
-    # Show appliance inputs in an editable table-like UI
-    for i, row in enumerate(st.session_state.appliances):
-        cols = st.columns([1.2, 0.6, 0.8, 0.9, 0.6])
-        cols[0].write(f"**{row['name']}**  ")
-        qty = cols[1].number_input(f"qty_{i}", min_value=0, value=int(row['qty']), key=f"qty_{i}")
-        power = cols[2].number_input(f"power_{i}", min_value=1, value=int(row['power_w']), key=f"power_{i}")
-        hours = cols[3].number_input(f"hours_{i}", min_value=0.0, value=float(row['hours_per_day']), step=0.25, key=f"hours_{i}")
-        remove = cols[4].button("Remove", key=f"remove_{i}")
-        if remove:
-            st.session_state.appliances.pop(i)
-            st.experimental_rerun()
-        # write back edits
-        st.session_state.appliances[i]['qty'] = qty
-        st.session_state.appliances[i]['power_w'] = power
-        st.session_state.appliances[i]['hours_per_day'] = hours
-
-    st.markdown("---")
-    advanced = st.expander("Advanced options")
-    with advanced:
-        depth_of_discharge = st.slider("Battery depth of discharge (usable fraction)", min_value=0.2, max_value=0.95, value=0.8)
-        inverter_efficiency = st.slider("Inverter & battery round-trip efficiency", min_value=0.5, max_value=1.0, value=0.9)
-        inverter_margin = st.number_input("Inverter sizing margin (x)", min_value=1.0, value=1.25, step=0.05)
-
-with col2:
-    st.header("Results")
-
-    # Build dataframe from session_state appliances
-    appliances_df = pd.DataFrame(st.session_state.appliances)
-    if appliances_df.empty:
-        st.info("Add appliances to see results.")
-    else:
-        total_wh, detailed_df = calculate_energy(appliances_df)
-        total_kwh = total_wh / 1000.0
-
-        system_kw = recommend_system(total_kwh, avg_sun_hours, system_efficiency)
-        num_panels = recommend_panels(system_kw, panel_wattage)
-        inverter_kw = recommend_inverter(system_kw, inverter_margin)
-        battery_kwh = recommend_battery(total_kwh, days_of_autonomy, depth_of_discharge, inverter_efficiency)
-
-        # cost savings estimate (monthly)
-        monthly_kwh = total_kwh * 30
-        monthly_savings = monthly_kwh * tariff
-
-        st.metric(label="Total daily energy", value=f"{total_kwh:.2f} kWh")
-        st.metric(label="Recommended solar capacity", value=f"{system_kw:.2f} kW")
-        st.metric(label="Estima
+
+    st.subheader("Custom Appliance")
+    custom_name = st.text_input("Custom Appliance Name")
+    custom_qty = st.number_input("Custom Quantity", min_value=0, value=0)
+    custom_power = st.number_input("Custom Power (W)", min_value=1, value=100)
+    custom_hours = st.number_input("Custom Usage Hours/day", min_value=0, value=0)
+    if custom_name and custom_qty > 0 and custom_hours > 0:
+        energy = custom_qty * custom_power * custom_hours
+        total_energy_wh += energy
+        appliances.append({
+            "Device": custom_name,
+            "Quantity": custom_qty,
+            "Power (W)": custom_power,
+            "Hours/day": custom_hours,
+            "Daily Energy (Wh)": energy
+        })
+
+# Convert to DataFrame
+df = pd.DataFrame(appliances)
+
+# Main results
+if not df.empty:
+    total_energy_kwh = total_energy_wh / 1000
+    st.subheader("📊 Energy Consumption Summary")
+    st.dataframe(df)
+
+    fig = px.pie(df, values="Daily Energy (Wh)", names="Device", title="Energy Usage Breakdown")
+    st.plotly_chart(fig, use_container_width=True)
+
+    st.subheader("🔍 System Recommendations")
+    sun_hours = st.number_input("Average sunlight hours/day", min_value=1, value=5)
+    efficiency = st.slider("System efficiency (%)", min_value=50, max_value=100, value=80) / 100
+    system_size_kw = total_energy_kwh / (sun_hours * efficiency)
+
+    panel_watt = st.number_input("Solar panel wattage (W)", min_value=50, value=350)
+    num_panels = (system_size_kw * 1000) / panel_watt
+
+    battery_days = st.number_input("Days of backup (battery)", min_value=0, value=1)
+    battery_capacity_kwh = total_energy_kwh * battery_days
+
+    inverter_size_kw = system_size_kw * 1.25  # buffer
+
+    st.write(f"**Total Daily Energy:** {total_energy_kwh:.2f} kWh")
+    st.write(f"**Recommended Solar System Size:** {system_size_kw:.2f} kW")
+    st.write(f"**Number of Panels ({panel_watt}W):** {num_panels:.0f}")
+    st.write(f"**Battery Capacity:** {battery_capacity_kwh:.2f} kWh")
+    st.write(f"**Recommended Inverter Size:** {inverter_size_kw:.2f} kW")
+
+    # PDF Export
+    if st.button("Download PDF Report"):
+        class PDF(FPDF):
+            def header(self):
+                self.set_font('Arial', 'B', 14)
+                self.cell(200, 10, "Solar System Sizing Report", ln=True, align="C")
+
+            def chapter_title(self, title):
+                self.set_font('Arial', 'B', 12)
+                self.cell(0, 10, title, ln=True)
+
+            def chapter_body(self, body):
+                self.set_font('Arial', '', 10)
+                self.multi_cell(0, 10, body)
+
+        pdf = PDF()
+        pdf.add_page()
+        pdf.chapter_title("Energy Consumption Details")
+        for _, row in df.iterrows():
+            pdf.chapter_body(f"{row['Device']}: {row['Quantity']} × {row['Power (W)']}W × {row['Hours/day']}h = {row['Daily Energy (Wh)']} Wh")
+        pdf.chapter_title("System Recommendations")
+        pdf.chapter_body(
+            f"Total Daily Energy: {total_energy_kwh:.2f} kWh\n"
+            f"Recommended Solar System Size: {system_size_kw:.2f} kW\n"
+            f"Number of Panels ({panel_watt}W): {num_panels:.0f}\n"
+            f"Battery Capacity: {battery_capacity_kwh:.2f} kWh\n"
+            f"Inverter Size: {inverter_size_kw:.2f} kW"
+        )
+
+        pdf.output("solar_report.pdf")
+        with open("solar_report.pdf", "rb") as f:
+            st.download_button("Download Report", f, file_name="solar_report.pdf")
+else:
+    st.warning("Please enter appliance details in the sidebar.")