Create weekly.py

weekly.py

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+import pandas as pd
+import streamlit as st
+import matplotlib.pyplot as plt
+import io
+from pre import preprocess_uploaded_file, add_app_description
+
+from collections import defaultdict
+
+def generate_weekly_report(uploaded_files):
+    # Create a defaultdict to store the number of failures for each day
+    daily_failures = defaultdict(int)
+
+    for uploaded_file in uploaded_files:
+        # Preprocess the uploaded CSV file (you can use your existing preprocessing code)
+        data = preprocess_uploaded_file(uploaded_file)
+
+        # Extract the start date from the 'Start datetime' column for this file
+        start_date = data['Start datetime'].dt.date.iloc[0]
+
+        # Calculate the number of failures for this file
+        num_failures = len(data[data['Status'] == 'FAILED'])
+
+        # Add the number of failures to the corresponding day in the defaultdict
+        daily_failures[start_date] += num_failures
+
+    # Sort the dictionary by date
+    sorted_daily_failures = dict(sorted(daily_failures.items()))
+
+    # Extract dates and failures from the sorted dictionary
+    dates = list(sorted_daily_failures.keys())
+    failures = list(sorted_daily_failures.values())
+
+
+     # Format the dates as "DD-Mon" strings (e.g., "07-Feb")
+    formatted_dates = [date.strftime("%d-%b") for date in dates]
+
+     # Get the environment variable from the first file (assuming it's the same for all files)
+    environment = data['Environment'].iloc[0]
+
+
+        # Create a larger line chart to show the trend in failure rates over days
+    plt.figure(figsize=(12, 8))
+    plt.plot(formatted_dates, failures, marker='o', linestyle='-')
+    plt.xlabel('Date', fontsize=14)  # Increase font size for X-axis label
+    plt.ylabel('Number of Failures', fontsize=14)  # Increase font size for Y-axis label
+    plt.title(f'Trends in Failure Rates Over Days for Environment: {environment}', fontsize=16) # Increase title font size
+    plt.xticks(rotation=45, fontsize=12)  # Increase font size and rotation for X-axis ticks
+    plt.yticks(fontsize=12)  # Increase font size for Y-axis ticks
+    plt.grid(False)
+    
+    # Add labels with the number of failures at each data point with larger font
+    for i in range(len(dates)):
+        plt.text(formatted_dates[i], failures[i], str(failures[i]), ha='center', va='bottom', fontsize=12)
+
+    plt.tight_layout()
+    # Display the bar chart
+    st.pyplot(plt)