Update app.py

app.py

@@ -11,21 +11,10 @@ import io
 import time
 import asyncio
 from simple_salesforce import Salesforce
-import smtplib
-from email.mime.text import MIMEText
 
 # Configure logging
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
 
-# Email configuration
-EMAIL_CONFIG = {
-    'sender_email': 'your-email@gmail.com',  # Replace with your Gmail address
-    'app_password': 'your-app-password',    # Replace with your Gmail App Password
-    'recipient_email': 'recipient@example.com',  # Replace with recipient email
-    'smtp_server': 'smtp.gmail.com',
-    'smtp_port': 587
-}
-
 # Salesforce configuration
 try:
     sf = Salesforce(
@@ -86,8 +75,7 @@ picklist_mapping = {
         'maintenance': 'Smart Log',
         'cell': 'Cell Analysis',
         'uv': 'UV Verification',
-        'weight log': 'Smart Log',
-        'wegit log': 'Smart Log'  # Added mapping for 'Wegit Log'
+        'weight log': 'Smart Log'
     }
 }
 
@@ -176,7 +164,7 @@ def save_to_salesforce(df, reminders_df):
             amc_date_str = None
             if pd.notna(row['amc_date']):
                 try:
-                    amc_date = pd.to_datetime(row['amc_date'], format='%m/%d/%Y').strftime('%Y-%m-%d')
+                    amc_date = pd.to_datetime(row['amc_date']).strftime('%Y-%m-%d')
                     amc_date_str = amc_date
                     amc_date_dt = datetime.strptime(amc_date, '%Y-%m-%d')
                     if status_mapped == "Active" and current_date.date() <= amc_date_dt.date() <= next_30_days.date():
@@ -212,22 +200,6 @@ def save_to_salesforce(df, reminders_df):
     except Exception as e:
         logging.error(f"Failed to save to Salesforce: {str(e)}")
 
-# Send email alert
-def send_email_alert(subject, body):
-    try:
-        msg = MIMEText(body)
-        msg['Subject'] = subject
-        msg['From'] = EMAIL_CONFIG['sender_email']
-        msg['To'] = EMAIL_CONFIG['recipient_email']
-
-        with smtplib.SMTP(EMAIL_CONFIG['smtp_server'], EMAIL_CONFIG['smtp_port']) as server:
-            server.starttls()
-            server.login(EMAIL_CONFIG['sender_email'], EMAIL_CONFIG['app_password'])
-            server.send_message(msg)
-        logging.info(f"Email alert sent successfully to {EMAIL_CONFIG['recipient_email']}")
-    except Exception as e:
-        logging.error(f"Failed to send email alert: {str(e)}")
-
 # Summarize logs
 def summarize_logs(df):
     try:
@@ -251,9 +223,7 @@ def detect_anomalies(df):
         anomalies = df[df["anomaly"] == -1][["device_id", "usage_hours", "downtime", "timestamp"]]
         if anomalies.empty:
             return "No anomalies detected.", anomalies
-        anomaly_summary = "\n".join([f"- Device ID: {row['device_id']}, Usage: {row['usage_hours']}, Downtime: {row['downtime']}, Timestamp: {row['timestamp']}" for _, row in anomalies.head(5).iterrows()])
-        send_email_alert("Anomaly Detection Alert", f"Anomalies detected:\n{anomaly_summary}")
-        return anomaly_summary, anomalies
+        return "\n".join([f"- Device ID: {row['device_id']}, Usage: {row['usage_hours']}, Downtime: {row['downtime']}, Timestamp: {row['timestamp']}" for _, row in anomalies.head(5).iterrows()]), anomalies
     except Exception as e:
         logging.error(f"Anomaly detection failed: {str(e)}")
         return f"Anomaly detection failed: {str(e)}", pd.DataFrame()
@@ -263,19 +233,13 @@ def check_amc_reminders(df, current_date):
     try:
         if "device_id" not in df.columns or "amc_date" not in df.columns:
             return "AMC reminders require 'device_id' and 'amc_date' columns.", pd.DataFrame()
-        # Parse amc_date with explicit format and handle timezone
-        df["amc_date"] = pd.to_datetime(df["amc_date"], format='%m/%d/%Y', errors='coerce').dt.tz_localize('UTC').dt.tz_convert('Asia/Kolkata')
-        current_date = pd.to_datetime(current_date).tz_localize('Asia/Kolkata')
-        logging.info(f"Current date for AMC: {current_date}")
-        logging.info(f"AMC dates parsed: {df['amc_date'].dropna().tolist()}")
+        df["amc_date"] = pd.to_datetime(df["amc_date"], errors='coerce')
+        current_date = pd.to_datetime(current_date)
         df["days_to_amc"] = (df["amc_date"] - current_date).dt.days
-        logging.info(f"Days to AMC: {df['days_to_amc'].dropna().tolist()}")
-        reminders = df[(df["days_to_amc"] >= 0) & (df["days_to_amc"] <= 30) & (df["status"] == "Active")][["device_id", "log_type", "status", "timestamp", "usage_hours", "downtime", "amc_date"]]
+        reminders = df[(df["days_to_amc"] >= 0) & (df["days_to_amc"] <= 30)][["device_id", "log_type", "status", "timestamp", "usage_hours", "downtime", "amc_date"]]
         if reminders.empty:
             return "No AMC reminders due within the next 30 days.", reminders
-        reminder_summary = "\n".join([f"- Device ID: {row['device_id']}, AMC Date: {row['amc_date'].date()}" for _, row in reminders.head(5).iterrows()])
-        send_email_alert("AMC Reminder Alert", f"AMC reminders due within 30 days:\n{reminder_summary}")
-        return reminder_summary, reminders
+        return "\n".join([f"- Device ID: {row['device_id']}, AMC Date: {row['amc_date']}" for _, row in reminders.head(5).iterrows()]), reminders
     except Exception as e:
         logging.error(f"AMC reminder generation failed: {str(e)}")
         return f"AMC reminder generation failed: {str(e)}", pd.DataFrame()
@@ -554,11 +518,10 @@ async def process_logs(file_obj, lab_site_filter, equipment_type_filter, date_ra
             if missing_columns:
                 return f"Missing columns: {missing_columns}", "<p>Missing required columns.</p>", None, '<p>No device cards available.</p>', None, None, None, None, "", "", "", None, cached_df_state, last_modified_state
 
-            # Handle mixed timestamp formats with ISO8601 and coerce errors
-            df["timestamp"] = pd.to_datetime(df["timestamp"], format='ISO8601', errors='coerce')
-            # Convert UTC-aware timestamps to IST directly
-            df["timestamp"] = df["timestamp"].dt.tz_convert('Asia/Kolkata')
-            df["amc_date"] = pd.to_datetime(df["amc_date"], format='%m/%d/%Y', errors='coerce').dt.tz_localize('UTC').dt.tz_convert('Asia/Kolkata')
+            df["timestamp"] = pd.to_datetime(df["timestamp"], errors='coerce')
+            df["amc_date"] = pd.to_datetime(df["amc_date"], errors='coerce')
+            if df["timestamp"].dt.tz is None:
+                df["timestamp"] = df["timestamp"].dt.tz_localize('UTC').dt.tz_convert('Asia/Kolkata')
             if df.empty:
                 return "No data available.", "<p>No data available.</p>", None, '<p>No device cards available.</p>', None, None, None, None, "", "", "", None, df, current_modified_time
         else:
@@ -602,7 +565,7 @@ async def process_logs(file_obj, lab_site_filter, equipment_type_filter, date_ra
         # Run critical tasks concurrently
         with ThreadPoolExecutor(max_workers=2) as executor:
             future_anomalies = executor.submit(detect_anomalies, filtered_df)
-            future_amc = executor.submit(check_amc_reminders, df)  # Use full df for AMC
+            future_amc = executor.submit(check_amc_reminders, filtered_df, datetime.now())
 
             summary = f"Step 1: Summary Report\n{summarize_logs(filtered_df)}"
             anomalies, anomalies_df = future_anomalies.result()