Update app.py

app.py

@@ -1,5 +1,4 @@
 import streamlit as st
-import pandas as pd
 import numpy as np
 from translate import Translator
 
@@ -33,56 +32,74 @@ battery_types = {"Lithium-Ion": 0.95, "Lead-Acid": 0.8}
 battery_choice = st.selectbox(translate_text("Select Battery Type", lang_code), options=battery_types.keys())
 battery_efficiency = battery_types[battery_choice]
 
-# Table for appliance selection
-st.subheader(translate_text("Appliances Input", lang_code))
-appliance_data = pd.DataFrame(columns=["Appliance", "Wattage (W)", "Hours per Day", "Quantity"])
-default_appliances = ["LED Bulb", "Fan", "Refrigerator", "Microwave Oven", "Water Pump", "Iron", "Inverter AC", "Others"]
-
-# Appliance input table
-for appliance in default_appliances:
-    wattage = st.number_input(translate_text(f"{appliance} - Wattage:", lang_code), min_value=0, step=1, key=f"{appliance}_wattage")
-    hours = st.number_input(translate_text(f"{appliance} - Hours per Day:", lang_code), min_value=0, step=1, key=f"{appliance}_hours")
-    quantity = st.number_input(translate_text(f"{appliance} - Quantity:", lang_code), min_value=0, step=1, key=f"{appliance}_quantity")
+# Appliance selection
+st.subheader(translate_text("Select Appliances", lang_code))
+appliances = [
+    "LED Bulb", "Fan", "Refrigerator", "Microwave Oven", 
+    "Water Pump", "Iron", "Inverter AC", "Dishwasher", 
+    "Geyser", "Heater", "Computer", "Water Dispenser", "Others"
+]
+
+selected_appliances = st.multiselect(translate_text("Choose Appliances:", lang_code), options=appliances)
+
+# Appliance input
+appliance_data = []
+for appliance in selected_appliances:
+    wattage = st.number_input(
+        translate_text(f"{appliance} - Wattage (W):", lang_code), min_value=0, step=1, key=f"{appliance}_wattage"
+    )
+    hours = st.number_input(
+        translate_text(f"{appliance} - Daily Usage (hours):", lang_code), min_value=0, step=1, key=f"{appliance}_hours"
+    )
+    quantity = st.number_input(
+        translate_text(f"{appliance} - Quantity:", lang_code), min_value=0, step=1, key=f"{appliance}_quantity"
+    )
     if wattage > 0 and hours > 0 and quantity > 0:
-        appliance_data = pd.concat([appliance_data, pd.DataFrame([[appliance, wattage, hours, quantity]], columns=appliance_data.columns)], ignore_index=True)
-
-if not appliance_data.empty:
-    st.write(translate_text("Selected Appliances", lang_code))
-    st.dataframe(appliance_data)
+        appliance_data.append({"Appliance": appliance, "Wattage": wattage, "Hours": hours, "Quantity": quantity})
 
-# System recommendations
+# Calculate recommendations
 if st.button(translate_text("Calculate Recommendations", lang_code)):
-    total_energy_consumption = sum(appliance_data["Wattage (W)"] * appliance_data["Hours per Day"] * appliance_data["Quantity"]) / 1000  # in kWh
-    total_load = sum(appliance_data["Wattage (W)"] * appliance_data["Quantity"])  # in Watts
-
-    st.write(translate_text(f"Total Load: {total_load} Watts", lang_code))
-    st.write(translate_text(f"Total Energy Consumption: {total_energy_consumption:.2f} kWh/day", lang_code))
-
-    # Calculate solar panel and battery requirements
-    solar_panel_capacity = 550  # Fixed capacity of a solar panel
-    sunlight_hours = 5  # Average peak sunlight hours
-    panels_required = np.ceil(total_energy_consumption / (solar_panel_capacity / 1000 * sunlight_hours))
-
-    battery_capacity_kWh = total_energy_consumption / battery_efficiency  # Battery capacity in kWh
-    battery_capacity_ah = battery_capacity_kWh * 1000 / 48  # Assuming a 48V system
-    batteries_required = np.ceil(battery_capacity_ah / 200)  # Assuming 200 Ah per battery
-
-    st.subheader(translate_text("System Recommendations", lang_code))
-    st.write(translate_text(f"Solar Panels Required: {int(panels_required)} (550W each)", lang_code))
-    st.write(translate_text(f"Batteries Required: {int(batteries_required)} (200 Ah, 48V system)", lang_code))
-
-    # Suggestions
-    st.subheader(translate_text("System Design Suggestions", lang_code))
-    suggestions = [
-        "Ensure panels are installed at the optimal tilt angle.",
-        "Consider a hybrid system for grid integration.",
-        "Use MPPT charge controllers for efficiency.",
-        "Plan for future system expansion.",
-        "Choose high-quality and reliable components.",
-        "Consult a certified solar installer for best practices."
-    ]
-    for suggestion in suggestions:
-        st.write(translate_text(suggestion, lang_code))
+    if not appliance_data:
+        st.error(translate_text("Please select and fill details for at least one appliance.", lang_code))
+    else:
+        total_load = sum(item["Wattage"] * item["Quantity"] for item in appliance_data)  # in Watts
+        total_energy_consumption = sum(
+            item["Wattage"] * item["Hours"] * item["Quantity"] for item in appliance_data
+        ) / 1000  # in kWh/day
+
+        # Solar panel calculation
+        solar_panel_capacity = 550  # Fixed capacity of a solar panel in Watts
+        sunlight_hours = 5  # Average peak sunlight hours
+        panels_required = np.ceil(total_energy_consumption / (solar_panel_capacity / 1000 * sunlight_hours))
+
+        # Inverter calculation (20% buffer added)
+        inverter_capacity = np.ceil(total_load * 1.2 / 1000)  # in kW
+
+        # Battery requirement
+        battery_capacity_kWh = total_energy_consumption / battery_efficiency  # in kWh
+        battery_capacity_ah = battery_capacity_kWh * 1000 / 48  # Assuming a 48V system
+        batteries_required = np.ceil(battery_capacity_ah / 200)  # Assuming 200 Ah per battery
+
+        # Output
+        st.subheader(translate_text("System Recommendations", lang_code))
+        st.write(translate_text(f"Total Load: {total_load} Watts", lang_code))
+        st.write(translate_text(f"Inverter Required: {inverter_capacity} kW", lang_code))
+        st.write(translate_text(f"Solar Panels Required: {int(panels_required)} (550W each)", lang_code))
+        st.write(translate_text(f"Batteries Required: {int(batteries_required)} (200 Ah, 48V system)", lang_code))
+
+        # Suggestions
+        st.subheader(translate_text("System Design Suggestions", lang_code))
+        suggestions = [
+            "Ensure panels are installed at the optimal tilt angle.",
+            "Consider a hybrid system for grid integration.",
+            "Use MPPT charge controllers for efficiency.",
+            "Plan for future system expansion.",
+            "Choose high-quality and reliable components.",
+            "Consult a certified solar installer for best practices."
+        ]
+        for suggestion in suggestions:
+            st.write(translate_text(suggestion, lang_code))
+