refresh data button

app.py

@@ -1,5 +1,6 @@
 import subprocess
 import logging
+from datetime import datetime
 import gradio as gr
 import pandas as pd
 from apscheduler.schedulers.background import BackgroundScheduler
@@ -30,15 +31,6 @@ from tabs.about import about_olas_predict
 
 
 def refresh_data():
-    # Run the pull_data.py script and wait for it to finish
-    try:
-        result = subprocess.run(["python", "./scripts/pull_data.py"], check=True)
-        logging.info("Script executed successfully: %s", result)
-    except subprocess.CalledProcessError as e:
-        logging.error("Failed to run script: %s", e)
-        return  # Stop execution if the script fails
-
-    # Reload dataframes
     try:
         global tools_df, trades_df, error_df, error_overall_df, winning_rate_df, winning_rate_overall_df, trades_count_df, trades_winning_rate_df
         logging.info("Refreshing data...")
@@ -55,12 +47,27 @@ def refresh_data():
     except Exception as e:
         logging.error("Failed to refresh data: %s", e)
 
+
+def pull_refresh_data():
+    # Run the pull_data.py script and wait for it to finish
+    try:
+        result = subprocess.run(["python", "./scripts/pull_data.py"], check=True)
+        logging.info("Script executed successfully: %s", result)
+    except subprocess.CalledProcessError as e:
+        logging.error("Failed to run script: %s", e)
+        return  # Stop execution if the script fails
+
+    refresh_data()
+
+        
 tools_df = pd.read_csv("./data/tools.csv", low_memory=False)
 trades_df = pd.read_csv("./data/all_trades_profitability.csv")
 trades_df = prepare_trades(trades_df)
 
+
 demo = gr.Blocks()
 
+
 INC_TOOLS = [
     'prediction-online', 
     'prediction-offline', 
@@ -76,7 +83,6 @@ INC_TOOLS = [
 ]
 
 
-# TOOLS DATA
 error_df = get_error_data(
     tools_df=tools_df,
     inc_tools=INC_TOOLS
@@ -153,6 +159,21 @@ with demo:
             with gr.Row():
                 trade_details_plot
 
+            with gr.Row():
+                with gr.Column():
+                    refresh_button = gr.Button("Refresh Data")
+                with gr.Column():
+                    latest_data_label = gr.Label(
+                        value=f"Last Datepoint: {trades_df['creation_timestamp'].max()}"
+                    )
+
+            def refresh_callback():
+                refresh_data()
+                latest_data_label.value = f"Last Datepoint: {trades_df['creation_timestamp'].max()}"
+                return latest_data_label.value
+
+            refresh_button.click(refresh_callback, outputs=latest_data_label)
+
         with gr.TabItem("🚀 Tool Winning Dashboard"):
             with gr.Row():
                 gr.Markdown("# Plot showing overall winning rate")
@@ -302,10 +323,8 @@ with demo:
 
 # Create the scheduler
 scheduler = BackgroundScheduler(timezone=utc)
-scheduler.add_job(refresh_data, CronTrigger(hour=0, minute=0))  # Runs daily at 12 AM UTC
+scheduler.add_job(pull_refresh_data, CronTrigger(hour=0, minute=0))  # Runs daily at 12 AM UTC
 scheduler.start()
-# scheduler = BackgroundScheduler(timezone=utc)
-# scheduler.add_job(refresh_data, CronTrigger(hour='*'))  # Runs every hour
-# scheduler.start()
+
 
 demo.queue(default_concurrency_limit=40).launch()

data/all_trades_profitability.csv

@@ -1,3 +1,3 @@
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+size 30934774

data/fpmmTrades.csv

@@ -1,3 +1,3 @@
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+size 68441241

data/fpmms.csv

@@ -1,3 +1,3 @@
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+size 423147

data/requests.csv

@@ -1,3 +1,3 @@
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+size 144528918

data/summary_profitability.csv

@@ -1,3 +1,3 @@
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+size 54358

data/t_map.pkl

@@ -1,3 +1,3 @@
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