Update app.py

app.py

@@ -1,5 +1,6 @@
 import streamlit as st
 import pandas as pd
+import requests
 import plotly.graph_objects as go
 import time
 
@@ -13,6 +14,45 @@ st.markdown(
     </p>
     """, unsafe_allow_html=True)
 
+# Google Drive Dataset Link
+DATASET_URL = "https://drive.google.com/uc?id=1QY9yv2mhz4n8bOTi4ahbjBpapltqXV6D"
+
+# Step 1: Function to fetch and load dataset
+@st.cache_data
+def fetch_and_load_dataset(url):
+    """Fetch the dataset from Google Drive."""
+    progress_text = "Fetching dataset from Google Drive..."
+    progress_bar = st.progress(0)
+    
+    # Download process
+    try:
+        response = requests.get(url, stream=True)
+        total_size = int(response.headers.get('content-length', 0))
+        downloaded_size = 0
+        chunks = []
+        
+        for data in response.iter_content(chunk_size=8192):
+            downloaded_size += len(data)
+            progress_bar.progress(min(1.0, downloaded_size / total_size), text=progress_text)
+            chunks.append(data)
+        
+        file_content = b''.join(chunks)
+        df = pd.read_excel(file_content, engine="openpyxl")  # Assuming an Excel file
+        st.success("Dataset loaded successfully!")
+        return df
+    
+    except Exception as e:
+        st.error(f"Error fetching dataset: {e}")
+        return None
+
+# Load dataset dynamically from Google Drive
+dataset = fetch_and_load_dataset(DATASET_URL)
+
+# Display the dataset preview
+if dataset is not None:
+    st.subheader("Dataset Preview")
+    st.dataframe(dataset.head())
+
 # Sidebar for User Inputs
 st.sidebar.header("Input Product Details")
 
@@ -41,27 +81,21 @@ use_dryer = st.sidebar.checkbox("Use Tumble Dryer?")
 transport_mode = st.sidebar.selectbox("Transport Mode", ["Plane", "Ship", "Train", "Truck"])
 transport_distance = st.sidebar.number_input("Transport Distance (km)", min_value=0, step=50)
 
-# Fiber Impact Data
-fiber_impact_data = {
-    "Cotton": {"Water": 10000, "Energy": 60, "Carbon": 3.18},
-    "Polyester": {"Water": 62, "Energy": 125, "Carbon": 4.8},
-    "Nylon": {"Water": 70, "Energy": 120.47, "Carbon": 5.4},
-    "Acrylic": {"Water": 50, "Energy": 175, "Carbon": 6.2},
-    "Viscose": {"Water": 200, "Energy": 100, "Carbon": 4.2},
-}
-
-# Transportation emission factors (kgCO2e per km per ton)
-transport_emissions_factors = {
-    "Plane": 1.102,
-    "Ship": 0.011,
-    "Train": 0.05,
-    "Truck": 0.25,
-}
-
-# Washing and drying emission factors
-washing_energy = {"Cold": 0.02, "30°C": 0.1, "40°C": 0.2, "60°C": 0.5}  # Energy per cycle (MJ)
-dryer_energy = 0.5  # Additional energy per drying cycle (MJ)
-dryer_carbon = 0.3  # Additional carbon emissions per drying cycle (kgCO2e)
+# Step 2: Extract data dynamically from the loaded dataset
+@st.cache_data
+def extract_fiber_impact(dataset):
+    """Extract relevant data for fiber impacts from the dataset."""
+    fiber_data = {}
+    for _, row in dataset.iterrows():
+        fiber_name = row["Fiber"]
+        water = row["Water Footprint"]
+        energy = row["Energy Footprint"]
+        carbon = row["Carbon Footprint"]
+        fiber_data[fiber_name] = {"Water": water, "Energy": energy, "Carbon": carbon}
+    return fiber_data
+
+# Load fiber impact data dynamically
+fiber_impact_data = extract_fiber_impact(dataset)
 
 # Function to calculate footprints
 def calculate_footprints(weight, composition, lifecycle_inputs):
@@ -72,11 +106,12 @@ def calculate_footprints(weight, composition, lifecycle_inputs):
 
     # Fiber contributions
     for fiber, percentage in composition.items():
-        data = fiber_impact_data[fiber]
-        fraction = percentage / 100
-        water_footprint += data["Water"] * weight * fraction
-        energy_footprint += data["Energy"] * weight * fraction
-        carbon_footprint += data["Carbon"] * weight * fraction
+        if fiber in fiber_impact_data:
+            data = fiber_impact_data[fiber]
+            fraction = percentage / 100
+            water_footprint += data["Water"] * weight * fraction
+            energy_footprint += data["Energy"] * weight * fraction
+            carbon_footprint += data["Carbon"] * weight * fraction
 
     # Transportation impacts
     transport_factor = transport_emissions_factors[lifecycle_inputs["transport_mode"]]
@@ -112,11 +147,11 @@ composition = {
 
 # Run Calculations and Display Progress Bar
 if total_percentage == 100:
-    progress_text = "Calculating Footprints..."
+    st.write("Processing calculations...")
     progress_bar = st.progress(0)
     for i in range(1, 101):
         time.sleep(0.01)
-        progress_bar.progress(i, text=progress_text)
+        progress_bar.progress(i)
 
     # Call the calculation function
     water_fp, energy_fp, carbon_fp = calculate_footprints(product_weight, composition, user_inputs)