Update pages/dashboard.py

pages/dashboard.py

@@ -7,34 +7,24 @@ import streamlit as st
 import pandas as pd
 import plotly.express as px
 import plotly.graph_objects as go
-from datetime import datetime, timedelta
+from datetime import datetime
 from typing import Dict, List, Optional, Any
 
 from utils.storage import load_data, save_data, get_cached_data, set_cached_data
-from utils.error_handling import handle_data_exceptions, ErrorHandler, ValidationError, DataError
+from utils.error_handling import handle_data_exceptions, ValidationError, DataError
 from utils.logging import get_logger, log_info, log_error, log_warning
 
-
 # Initialize logger
 logger = get_logger(__name__)
 
-
 @handle_data_exceptions
 def load_dashboard_data() -> Dict[str, Any]:
-    """
-    Load dashboard data with caching
-    
-    Returns:
-        Dict: Dashboard data including metrics, charts data, etc.
-    """
-    # Try to get from cache first
     cached_data = get_cached_data("dashboard_data")
     if cached_data:
         log_info("Using cached dashboard data")
         return cached_data
-    
+
     try:
-        # Load data from storage
         data = {
             "metrics": load_data("dashboard_metrics.json", default={}),
             "user_activity": load_data("user_activity.json", default=[]),
@@ -42,13 +32,9 @@ def load_dashboard_data() -> Dict[str, Any]:
             "recent_events": load_data("recent_events.json", default=[]),
             "performance_data": load_data("performance_data.json", default=[])
         }
-        
-        # Cache the data
         set_cached_data("dashboard_data", data)
         log_info("Dashboard data loaded and cached successfully")
-        
         return data
-        
     except Exception as e:
         log_error("Failed to load dashboard data", error=e)
         return {
@@ -59,99 +45,51 @@ def load_dashboard_data() -> Dict[str, Any]:
             "performance_data": []
         }
 
-
 @handle_data_exceptions
 def create_metrics_cards(metrics: Dict[str, Any]) -> None:
-    """
-    Create and display metrics cards
-    
-    Args:
-        metrics: Dictionary containing metric values
-    """
     if not metrics:
         st.warning("No metrics data available")
         return
-    
-    # Create columns for metrics
+
     cols = st.columns(4)
-    
-    # Total Users
     with cols[0]:
-        total_users = metrics.get("total_users", 0)
-        st.metric(
-            label="Total Users",
-            value=f"{total_users:,}",
-            delta=metrics.get("users_change", 0)
-        )
-    
-    # Active Sessions
+        st.metric("Total Users", f"{metrics.get('total_users', 0):,}", delta=metrics.get("users_change", 0))
     with cols[1]:
-        active_sessions = metrics.get("active_sessions", 0)
-        st.metric(
-            label="Active Sessions",
-            value=f"{active_sessions:,}",
-            delta=metrics.get("sessions_change", 0)
-        )
-    
-    # System Health
+        st.metric("Active Sessions", f"{metrics.get('active_sessions', 0):,}", delta=metrics.get("sessions_change", 0))
     with cols[2]:
-        system_health = metrics.get("system_health", 0)
-        st.metric(
-            label="System Health",
-            value=f"{system_health:.1f}%",
-            delta=f"{metrics.get('health_change', 0):.1f}%"
-        )
-    
-    # Response Time
+        st.metric("System Health", f"{metrics.get('system_health', 0):.1f}%", delta=f"{metrics.get('health_change', 0):.1f}%")
     with cols[3]:
-        response_time = metrics.get("avg_response_time", 0)
-        st.metric(
-            label="Avg Response Time",
-            value=f"{response_time:.0f}ms",
-            delta=f"{metrics.get('response_change', 0):.0f}ms",
-            delta_color="inverse"
-        )
-
+        st.metric("Avg Response Time", f"{metrics.get('avg_response_time', 0):.0f}ms", delta=f"{metrics.get('response_change', 0):.0f}ms", delta_color="inverse")
 
 @handle_data_exceptions
 def create_activity_chart(activity_data: List[Dict]) -> None:
-    """
-    Create user activity chart
-    
-    Args:
-        activity_data: List of activity data points
-    """
     if not activity_data:
         st.warning("No activity data available")
         return
-    
-    try:
-        df = pd.DataFrame(activity_data)
-        
-        if df.empty:
-            st.warning("Activity data is empty")
-            return
-        
-        # Ensure required columns exist
-        if 'timestamp' not in df.columns:
-            df['timestamp'] = pd.date_range(start='2024-01-01', periods=len(df), freq='H')
-        
-        if 'users' not in df.columns:
-            df['users'] = [0] * len(df)
-        
-        # Convert timestamp to datetime if it's not already
-        df['timestamp'] = pd.to_datetime(df['timestamp'])
-        
-        # Create the chart
-        fig = px.line(
-            df,
-            x='timestamp',
-            y='users',
-            title='User Activity Over Time',
-            labels={'users': 'Active Users', 'timestamp': 'Time'}
-        )
-        
-        fig.update_layout(
-            xaxis_title="Time",
-            yaxis_title="Active Users",
-        )
+
+    df = pd.DataFrame(activity_data)
+    if df.empty:
+        st.warning("Activity data is empty")
+        return
+
+    if 'timestamp' not in df.columns:
+        df['timestamp'] = pd.date_range(start='2024-01-01', periods=len(df), freq='H')
+    if 'users' not in df.columns:
+        df['users'] = [0] * len(df)
+
+    df['timestamp'] = pd.to_datetime(df['timestamp'])
+
+    fig = px.line(
+        df,
+        x='timestamp',
+        y='users',
+        title='User Activity Over Time',
+        labels={'users': 'Active Users', 'timestamp': 'Time'}
+    )
+
+    fig.update_layout(
+        xaxis_title="Time",
+        yaxis_title="Active Users",
+    )
+
+    st.plotly_chart(fig, use_container_width=True)