Spaces:
Sleeping
Sleeping
| import pandas as pd | |
| import streamlit as st | |
| import matplotlib.pyplot as plt | |
| import io | |
| from pre import preprocess_uploaded_file | |
| from collections import defaultdict | |
| def generate_weekly_report(uploaded_files): | |
| # Create a dictionary to store the number of failures for each environment and day | |
| environment_daily_failures = {} | |
| 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']) | |
| # Get the environment variable from the data frame | |
| environment = data['Environment'].iloc[0] | |
| # Create a unique key for each environment and day | |
| key = (environment, start_date) | |
| # Add the number of failures to the corresponding environment and day in the dictionary | |
| if key in environment_daily_failures: | |
| environment_daily_failures[key] += num_failures | |
| else: | |
| environment_daily_failures[key] = num_failures | |
| # Create a list of unique environments | |
| unique_environments = list(set([key[0] for key in environment_daily_failures.keys()])) | |
| # Create a larger line chart with separate lines for each environment | |
| plt.figure(figsize=(12, 8)) | |
| for environment in unique_environments: | |
| # Filter the data for the current environment | |
| environment_data = [(key[1], value) for key, value in environment_daily_failures.items() if key[0] == environment] | |
| # Sort the data by date | |
| environment_data.sort(key=lambda x: x[0]) | |
| # Extract dates and failures for the current environment | |
| dates = [date.strftime("%d-%b") for date, _ in environment_data] | |
| failures = [count for _, count in environment_data] | |
| # Plot the data as a line | |
| plt.plot(dates, failures, marker='o', linestyle='-', label=f'Environment: {environment}') | |
| plt.xlabel('Date', fontsize=14) | |
| plt.ylabel('Number of Failures', fontsize=14) | |
| plt.title('Trends in Failure Rates Over Days', fontsize=16) | |
| plt.xticks(rotation=45, fontsize=12) | |
| plt.yticks(fontsize=12) | |
| plt.grid(True) | |
| plt.legend(fontsize=12) # Add a legend to differentiate environments | |
| # Add labels with the number of failures at each data point with larger font | |
| for environment in unique_environments: | |
| environment_data = [(key[1], value) for key, value in environment_daily_failures.items() if key[0] == environment] | |
| for i in range(len(environment_data)): | |
| plt.text(environment_data[i][0].strftime("%d-%b"), environment_data[i][1], str(environment_data[i][1]), ha='center', va='bottom', fontsize=12) | |
| plt.tight_layout() | |
| # Display the larger line chart | |
| st.pyplot(plt) | |