Update gradio_app.py

gradio_app.py

@@ -1,8 +1,8 @@
 import gradio as gr
-import requests
 import pandas as pd
 import plotly.express as px
 import plotly.graph_objects as go
+import json
 
 # Color palette for accessibility
 colorblind_palette = [
@@ -14,38 +14,36 @@ colorblind_palette = [
 
 # Cache for data (simple in-memory cache)
 _cached_data = None
-_cache_timestamp = None
 
 def get_detention_data():
     """
-    Get the data which powers TRAC's "ICE Detainees" page and return it as a dataframe.
+    Load the pre-downloaded detention data from CSV file and return it as a dataframe.
     """
-    global _cached_data, _cache_timestamp
+    global _cached_data
     
-    import time
-    current_time = time.time()
-    
-    # Check if we have cached data that's less than 15 minutes old
-    if _cached_data is not None and _cache_timestamp is not None:
-        if current_time - _cache_timestamp < 900:  # 15 minutes in seconds
-            return _cached_data
+    # Return cached data if available
+    if _cached_data is not None:
+        return _cached_data
     
     try:
-        response = requests.get(
-            "https://tracreports.org/immigration/detentionstats/pop_agen_table.json"
-        )
-        response.raise_for_status()
+        # Read the file as text first since it contains JSON
+        with open('ice_detention_data.csv', 'r') as file:
+            json_data = file.read().strip()
+        
+        # Parse the JSON data
+        data = json.loads(json_data)
         
-        df = pd.DataFrame(response.json())
-        df.date = pd.to_datetime(df.date).dt.date
+        # Convert to DataFrame
+        df = pd.DataFrame(data)
+        df['date'] = pd.to_datetime(df['date']).dt.date
         
         # Cache the data
         _cached_data = df
-        _cache_timestamp = current_time
         
         return df
     except Exception as e:
-        # Return empty dataframe if request fails
+        print(f"Error loading data: {e}")
+        # Return empty dataframe if file loading fails
         return pd.DataFrame()
 
 def get_col_prefix(authority):
@@ -245,7 +243,14 @@ def update_chart(dataset, display, authority):
 
 def get_data_info():
     """Get information about the data."""
-    return """"""
+    return """**Data Source:** TRAC Immigration Reports
+
+This dataset contains ICE detention statistics including:
+- Total detainees by arresting authority (ICE vs CBP)
+- Criminal status breakdown (Convicted, Pending charges, Other immigration violators)
+- Historical data from May 2019 to July 2025
+
+The data is sourced from TRAC's ICE Detainees page and represents the most recent snapshot of detention statistics."""
 
 def download_data():
     """Prepare data for download."""
@@ -254,10 +259,18 @@ def download_data():
         return None
     return df.to_csv(index=False)
 
+def refresh_data():
+    """Clear cache and reload data."""
+    global _cached_data
+    _cached_data = None
+    df = get_detention_data()
+    return df
+
 # Create the Gradio interface
 def create_app():
     with gr.Blocks(title="US Immigration Enforcement Data", theme=gr.themes.Soft()) as app:
         gr.Markdown("# US Immigration Enforcement Data")
+        gr.Markdown("*Interactive visualization of ICE detention statistics*")
         
         with gr.Tabs():
             with gr.TabItem("Graphs"):
@@ -307,33 +320,26 @@ def create_app():
                     outputs=[chart, footnote]
                 )
             
-            with gr.TabItem("Data"):
-                gr.Markdown(get_data_info())
+            # with gr.TabItem("Data"):
+            #     gr.Markdown(get_data_info())
                 
-                with gr.Row():
-                    refresh_btn = gr.Button("Refresh Data")
-                    download_btn = gr.DownloadButton(
-                        "Download as CSV",
-                        lambda: download_data(),
-                        filename="ice_detention_data.csv"
-                    )
-                
-                data_display = gr.Dataframe(
-                    label="ICE Detention Data",
-                    wrap=True
-                )
+            #     with gr.Row():
+            #         refresh_btn = gr.Button("Refresh Data")
+            #         download_btn = gr.DownloadButton(
+            #             "Download as CSV",
+            #             lambda: download_data() #,
+            #             #filename="ice_detention_data.csv"
+            #         )
                 
-                def refresh_data():
-                    global _cached_data, _cache_timestamp
-                    _cached_data = None
-                    _cache_timestamp = None
-                    df = get_detention_data()
-                    return df
+            #     data_display = gr.Dataframe(
+            #         label="ICE Detention Data",
+            #         wrap=True
+            #     )
                 
-                refresh_btn.click(refresh_data, outputs=[data_display])
+            #     refresh_btn.click(refresh_data, outputs=[data_display])
                 
-                # Load data on app start
-                app.load(lambda: get_detention_data(), outputs=[data_display])
+            #     # Load data on app start
+            #     app.load(lambda: get_detention_data(), outputs=[data_display])
     
     return app