Update app.py

app.py

@@ -1,57 +1,54 @@
-import streamlit as st
 import requests
+import sqlite3
+import pandas as pd
+import matplotlib.pyplot as plt
 
-# Function to fetch data from API
-def fetch_api_data(api_url, headers=None):
-    try:
-        # Bypass SSL verification for testing (set verify=False). Use with caution!
-        response = requests.get(api_url, headers=headers, verify=False)
-        if response.status_code == 200:
-            return response.json()
-        else:
-            st.error(f"Failed to fetch data: {response.status_code} - {response.text}")
-            return None
-    except requests.exceptions.SSLError as ssl_error:
-        st.error("SSL Error: Certificate verification failed.")
-        st.error(str(ssl_error))
-        return None
-    except requests.exceptions.ConnectionError as conn_error:
-        st.error("Connection Error: Unable to reach the server.")
-        st.error(str(conn_error))
-        return None
-    except Exception as e:
-        st.error(f"An unexpected error occurred: {str(e)}")
-        return None
+# Fetch data from the non-SSL API (example API URL)
+def fetch_data_from_api():
+    api_url = "http://example.com/api"  # Replace with your actual non-SSL API URL
+    response = requests.get(api_url)
+    data = response.json()  # Assumes the response is in JSON format
+    return data
 
-# Streamlit app
-def main():
-    st.title("API Data Viewer")
-    st.markdown("""
-    This app allows you to fetch and display data from an API. 
-    If the server uses an invalid SSL certificate, SSL verification can be bypassed for testing purposes.
-    """)
+# Store data in SQLite
+def store_data_in_sqlite(data):
+    conn = sqlite3.connect('data.db')
+    cursor = conn.cursor()
 
-    # Input API URL and optional API key
-    api_url = st.text_input("Enter API URL", placeholder="https://api.example.com/data")
-    api_key = st.text_input("Enter API Key (if required)", type="password", placeholder="Optional")
+    # Create table if it does not exist
+    cursor.execute('''CREATE TABLE IF NOT EXISTS api_data (
+                        id INTEGER PRIMARY KEY AUTOINCREMENT,
+                        name TEXT,
+                        value INTEGER)''')
 
-    # Fetch Data button
-    if st.button("Fetch Data"):
-        if api_url:
-            # Set headers if API key is provided
-            headers = {"Authorization": f"Bearer {api_key}"} if api_key else None
-            data = fetch_api_data(api_url, headers)
-            
-            if data:
-                st.success("Data fetched successfully!")
-                st.json(data)  # Display raw JSON data
+    # Insert data into the database
+    for item in data:
+        cursor.execute("INSERT INTO api_data (name, value) VALUES (?, ?)", (item['name'], item['value']))
+    
+    conn.commit()
+    conn.close()
 
-                # Optionally show structured data in a table if the response is a list of objects
-                if isinstance(data, list) and all(isinstance(item, dict) for item in data):
-                    st.write("Structured Data View:")
-                    st.dataframe(data)
-        else:
-            st.error("Please provide a valid API URL.")
+# Function to retrieve data for the chart
+def get_data_for_chart():
+    conn = sqlite3.connect('data.db')
+    df = pd.read_sql_query("SELECT name, value FROM api_data", conn)
+    conn.close()
+    return df
+
+# Function to plot a chart
+def plot_chart(df):
+    plt.figure(figsize=(8,6))
+    plt.bar(df['name'], df['value'])
+    plt.xlabel('Name')
+    plt.ylabel('Value')
+    plt.title('API Data Visualization')
+    plt.xticks(rotation=45)
+    plt.tight_layout()
+    plt.show()
 
 if __name__ == "__main__":
-    main()
+    # Fetch, store data and visualize
+    data = fetch_data_from_api()
+    store_data_in_sqlite(data)
+    df = get_data_for_chart()
+    plot_chart(df)