Update app.py

app.py

@@ -0,0 +1,72 @@
+import streamlit as st
+import pandas as pd
+import requests
+
+# Helper functions to fetch data dynamically
+def fetch_smartphones():
+    # Replace with a real API or dataset URL for smartphones
+    return pd.DataFrame([
+        {"Model": "iPhone 15", "Processor": "A17 Bionic", "RAM": "6 GB", "Battery": "3200 mAh"},
+        {"Model": "Samsung Galaxy S23", "Processor": "Snapdragon 8 Gen 2", "RAM": "8 GB", "Battery": "3900 mAh"}
+    ])
+
+def fetch_processors():
+    # Replace with a real API or dataset URL for processors
+    return pd.DataFrame([
+        {"Name": "Intel i9-13900K", "Cores": 24, "Threads": 32, "Base Clock": "3.0 GHz"},
+        {"Name": "AMD Ryzen 9 7950X", "Cores": 16, "Threads": 32, "Base Clock": "4.5 GHz"}
+    ])
+
+def fetch_gpus():
+    # Replace with a real API or dataset URL for GPUs
+    return pd.DataFrame([
+        {"Name": "NVIDIA RTX 4090", "VRAM": "24 GB", "Base Clock": "2.23 GHz"},
+        {"Name": "AMD RX 7900 XTX", "VRAM": "24 GB", "Base Clock": "2.3 GHz"}
+    ])
+
+def fetch_laptops():
+    # Replace with a real API or dataset URL for laptops
+    return pd.DataFrame([
+        {"Model": "MacBook Pro 16", "Processor": "M2 Max", "RAM": "32 GB", "Battery Life": "14 hours"},
+        {"Model": "Dell XPS 15", "Processor": "Intel i7-12700H", "RAM": "16 GB", "Battery Life": "10 hours"}
+    ])
+
+# Main App
+def main():
+    st.title("Global Technology Comparisons")
+    st.sidebar.title("Choose a category")
+
+    # Define categories and their respective data-fetching functions
+    categories = {
+        "Smartphones": fetch_smartphones,
+        "Processors": fetch_processors,
+        "GPUs": fetch_gpus,
+        "Laptops": fetch_laptops
+    }
+
+    # User selects the category
+    category = st.sidebar.selectbox("Select a category:", list(categories.keys()))
+
+    # Fetch and display data dynamically
+    st.header(f"{category} Comparisons")
+    data = categories[category]()
+    st.table(data)
+
+    # Comparison tool
+    st.subheader(f"Compare {category}")
+    col1, col2 = st.columns(2)
+
+    # Dropdown for selecting items to compare
+    option1 = col1.selectbox("Select first item:", data.iloc[:, 0])
+    option2 = col2.selectbox("Select second item:", data.iloc[:, 0])
+
+    # Show comparison results
+    if option1 and option2:
+        st.write(f"### Comparison between {option1} and {option2}:")
+        item1 = data[data.iloc[:, 0] == option1].iloc[0]
+        item2 = data[data.iloc[:, 0] == option2].iloc[0]
+        comparison_df = pd.DataFrame({"Feature": data.columns, option1: item1.values, option2: item2.values})
+        st.table(comparison_df)
+
+if __name__ == "__main__":
+    main()