add error

monitor.py

@@ -288,22 +288,58 @@ When autopilot is ON, I will automatically apply to new listings."""
             grouped['failures'] = grouped['total'] - grouped['successes']
             grouped['error_rate'] = grouped['failures'] / grouped['total']
 
-            # Prepare plot
+            # Ensure index is sorted by date for plotting
+            grouped = grouped.sort_index()
+
+            # Prepare plot: convert dates to matplotlib numeric x-values so bars and line align
+            import matplotlib.dates as mdates
             fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 8), sharex=True)
-            grouped[['successes','failures']].plot(kind='bar', stacked=True, ax=ax1, color=['#2E8B57','#C44A4A'])
+
+            dates = pd.to_datetime(grouped.index).to_pydatetime()
+            x = mdates.date2num(dates)
+            width = 0.6  # width in days for bars
+
+            successes = grouped['successes'].values
+            failures = grouped['failures'].values
+
+            ax1.bar(x, successes, width=width, color='#2E8B57', align='center')
+            ax1.bar(x, failures, bottom=successes, width=width, color='#C44A4A', align='center')
             ax1.set_ylabel('Count')
             ax1.set_title('Autopilot: Successes vs Failures (by day)')
+            ax1.set_xticks(x)
+            ax1.set_xlim(min(x) - 1, max(x) + 1)
+            ax1.xaxis.set_major_locator(mdates.AutoDateLocator())
+            ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
 
-            ax2.plot(grouped.index, grouped['error_rate'], marker='o', color='#3333AA')
+            # Plot error rate line on same x (date) axis
-            ax2.set_ylim(0,1)
+            ax2.plot(x, grouped['error_rate'].values, marker='o', color='#3333AA', linewidth=2)
+            ax2.set_ylim(-0.02, 1.02)
             ax2.set_ylabel('Error rate')
             ax2.set_xlabel('Date')
             ax2.set_title('Daily Error Rate (failures / total)')
+            ax2.grid(True, alpha=0.3)
+            ax2.set_xticks(x)
+            ax2.set_xlim(min(x) - 1, max(x) + 1)
+            ax2.xaxis.set_major_locator(mdates.AutoDateLocator())
+            ax2.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
+            fig.autofmt_xdate()
 
             plt.tight_layout()
             plot_path = DATA_DIR / 'error_rate.png'
-            fig.savefig(plot_path)
+            tmp_path = DATA_DIR / 'error_rate.tmp.png'
+            # Save to a temp file first and atomically replace to ensure overwrite
+            fig.savefig(tmp_path, format='png')
             plt.close(fig)
+            try:
+                tmp_path.replace(plot_path)
+            except Exception:
+                # Fallback: try removing existing and renaming
+                try:
+                    if plot_path.exists():
+                        plot_path.unlink()
+                    tmp_path.rename(plot_path)
+                except Exception:
+                    logger.exception(f"Failed to write plot to {plot_path}")
 
             # Summary
             total_attempts = int(grouped['total'].sum())

tests/test_errorrate_runner.py

@@ -0,0 +1,123 @@
+#!/usr/bin/env python3
+"""Simple test runner for the monitor's error-rate plot generator.
+
+Run from the repository root (where `monitor.py` and `data/` live):
+
+    python3 tests/test_errorrate_runner.py
+
+This will call `TelegramBot._generate_error_rate_plot()` and print the result.
+"""
+import os
+import sys
+import logging
+
+logging.basicConfig(level=logging.INFO)
+
+import pandas as pd
+import matplotlib
+matplotlib.use('Agg')
+import matplotlib.pyplot as plt
+import json
+
+DATA_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', 'data'))
+APPLICATIONS_FILE = os.path.join(DATA_DIR, 'applications.json')
+
+def generate_error_rate_plot(applications_file: str):
+    if not os.path.exists(applications_file):
+        print('No applications.json found at', applications_file)
+        return None, ''
+    try:
+        with open(applications_file, 'r', encoding='utf-8') as f:
+            apps = json.load(f)
+        if not apps:
+            return None, ''
+
+        rows = []
+        for _id, rec in apps.items():
+            ts = rec.get('timestamp')
+            try:
+                dt = pd.to_datetime(ts)
+            except Exception:
+                dt = pd.NaT
+            rows.append({'id': _id, 'company': rec.get('company'), 'success': bool(rec.get('success')), 'ts': dt})
+        df = pd.DataFrame(rows)
+        df = df.dropna(subset=['ts'])
+        if df.empty:
+            return None, ''
+
+        df['date'] = df['ts'].dt.floor('D')
+        grouped = df.groupby('date').agg(total=('id','count'), successes=('success', lambda x: x.sum()))
+        grouped['failures'] = grouped['total'] - grouped['successes']
+        grouped['error_rate'] = grouped['failures'] / grouped['total']
+        grouped = grouped.sort_index()
+
+        # Plot
+        fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 8), sharex=True)
+        grouped[['successes','failures']].plot(kind='bar', stacked=True, ax=ax1, color=['#2E8B57','#C44A4A'])
+        ax1.set_ylabel('Count')
+        ax1.set_title('Autopilot: Successes vs Failures (by day)')
+
+        import matplotlib.dates as mdates
+        dates = pd.to_datetime(grouped.index).to_pydatetime()
+        x = mdates.date2num(dates)
+        width = 0.6
+
+        ax1.bar(x, grouped['successes'].values, width=width, color='#2E8B57', align='center')
+        ax1.bar(x, grouped['failures'].values, bottom=grouped['successes'].values, width=width, color='#C44A4A', align='center')
+        ax1.set_xticks(x)
+        ax1.set_xlim(min(x) - 1, max(x) + 1)
+        ax1.xaxis.set_major_locator(mdates.AutoDateLocator())
+        ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
+
+        ax2.plot(x, grouped['error_rate'].values, marker='o', color='#3333AA', linewidth=2)
+        ax2.set_ylim(-0.02, 1.02)
+        ax2.set_ylabel('Error rate')
+        ax2.set_xlabel('Date')
+        ax2.set_title('Daily Error Rate (failures / total)')
+        ax2.grid(True, alpha=0.3)
+        ax2.set_xticks(x)
+        ax2.set_xlim(min(x) - 1, max(x) + 1)
+        ax2.xaxis.set_major_locator(mdates.AutoDateLocator())
+        ax2.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
+        fig.autofmt_xdate()
+
+        plot_path = os.path.join(DATA_DIR, 'error_rate.png')
+        tmp_path = os.path.join(DATA_DIR, 'error_rate.tmp.png')
+        fig.savefig(tmp_path, format='png')
+        plt.close(fig)
+        try:
+            # Atomic replace where possible
+            os.replace(tmp_path, plot_path)
+        except Exception:
+            try:
+                if os.path.exists(plot_path):
+                    os.remove(plot_path)
+                os.rename(tmp_path, plot_path)
+            except Exception as e:
+                print('Failed to write plot file:', e)
+                return None, ''
+
+        total_attempts = int(grouped['total'].sum())
+        total_success = int(grouped['successes'].sum())
+        total_fail = int(grouped['failures'].sum())
+        overall_error = (total_fail / total_attempts) if total_attempts>0 else 0.0
+        summary = f"<b>Total attempts:</b> {total_attempts}\n<b>Successes:</b> {total_success}\n<b>Failures:</b> {total_fail}\n<b>Overall error rate:</b> {overall_error:.1%}"
+        return plot_path, summary
+    except Exception as e:
+        print('Error generating plot:', e)
+        return None, ''
+
+def main():
+    # Use the local implementation to avoid importing the full monitor (Playwright heavy)
+    plot_path, summary = generate_error_rate_plot(APPLICATIONS_FILE)
+    if plot_path:
+        print("PLOT_PATH:", plot_path)
+        print("EXISTS:", os.path.exists(plot_path))
+        print("SUMMARY:\n", summary)
+        sys.exit(0)
+    else:
+        print("No plot generated (insufficient data or error)")
+        sys.exit(3)
+
+if __name__ == '__main__':
+    main()