Cron Schedule Visualizer

An interactive Python tool for visualizing cron job schedules with dark mode graphics. This tool generates a clickable monthly calendar view with detailed daily timeline visualizations showing exactly when your cron jobs execute. Click on a day or the weekly view link to generate more detailed views.

Features

• Interactive Monthly Calendar: Click on any day or on week view to see detailed execution patterns
• Pixel-Perfect Daily Timelines: 24hrs x 60min = 1440px wide images where 1 pixel = 1 minute
• Week View: Stack 7 days vertically for week-at-a-glance visualization
• Dark Mode Theme: Modern, consistent dark color scheme throughout
• Multiple Cron Jobs: Support for multiple cron expressions separated by |
• Thumbnail Previews: Mini timeline previews in calendar cells
• Execution Visualization: Bright green execution bars for maximum visibility
• Time Labels: Dual time format (24-hour and AM/PM)
• Human-Readable Descriptions: Convert cron syntax to plain English

Screenshots

The tool generates three types of visualizations:

1. Monthly Calendar View: Interactive calendar with thumbnail previews
2. Daily Timeline View: 1440px wide detailed timeline (1 pixel = 1 minute)
3. Week View: 7 daily timelines stacked vertically

Installation

Prerequisites

• Python 3.7 or higher
• Windows, macOS, or Linux (macOS and Ubuntu/Debian are untested)

Install Dependencies

pip install pandas seaborn matplotlib pillow numpy

Or install all dependencies at once:

pip install -r requirements.txt

Platform-Specific Notes

• Windows: Uses os.startfile() to open images
• macOS: Uses open command to open images
• Linux: Uses xdg-open to open images (requires desktop environment)
• Headless Linux: Images are generated but won't auto-open (manually open PNG files)

Requirements File

If you prefer to use a requirements.txt file, create one with:

pandas>=1.3.0
seaborn>=0.11.0
matplotlib>=3.5.0
pillow>=8.0.0
numpy>=1.21.0

Installation on Different Platforms

Windows

pip install pandas seaborn matplotlib pillow numpy

macOS

pip install pandas seaborn matplotlib pillow numpy

Ubuntu/Linux

# Install Python and pip (if not already installed)
sudo apt-get update
sudo apt-get install python3 python3-pip

# Install dependencies
pip3 install pandas seaborn matplotlib pillow numpy

# Install image viewing utilities (if not already installed)
sudo apt-get install xdg-utils

Usage

Basic Usage

from main import generate_monthly_calendar

# Simple cron job - every 15 minutes during business hours
cron_string = "*/15 9-17 * * *"
generate_monthly_calendar(cron_string, year=2025, month=6)

Advanced Usage

# Multiple cron jobs separated by |
cron_string = "3-10 0-4,18-23 * * * | */15 10-22 * * * | 27 14 1-3,15 * *"
generate_monthly_calendar(cron_string, year=2025, month=6)

Running the Script

cd cronVisualizer
python main.py

Cron Expression Format

The tool supports standard cron expressions with 5 fields:

minute hour dayOfMonth month dayOfWeek

Supported Syntax

• * - Any value
• */n - Every n units
• n-m - Range from n to m
• n,m,p - Specific values
• Multiple jobs: job1 | job2 | job3

Examples

# Every 15 minutes during business hours
"*/15 9-17 * * *"

# 4 times a day at specific hours
"0 9,12,15,18 * * *"

# 2:30 PM on 1st and 15th of every month
"27 14 1,15 * *"

# Midnight every Sunday
"0 0 * * 0"

# Complex multi-job example
"3-10 0-4,18-23 * * * | */15 10-22 * * * | 27 14 1-3,15 * *"

Output Files

The tool generates PNG files in the current directory:

• cron_calendar_X.png - Monthly calendar view
• daily_timeline_YYYY-MM-DD.png - Daily timeline view
• week_view_YYYY-MM_weekX.png - Week view

Dependencies Explained

• pandas: Data manipulation and calendar matrix creation
• seaborn: Statistical plotting enhancements
• matplotlib: Interactive plotting and calendar visualization
• pillow (PIL): Image creation and text rendering
• numpy: Array operations for timeline data
• calendar: Built-in Python calendar utilities
• datetime: Date and time manipulation
• platform: Cross-platform OS detection
• subprocess: Cross-platform command execution

Troubleshooting

Common Issues

1. Image won't open:
   • Windows: Ensure default image viewer is configured
   • macOS: Images open with Preview by default
   • Linux: Requires desktop environment with xdg-open support
   • Headless servers: Images are generated but won't auto-open
2. Font errors: The tool falls back to default font if arial.ttf is not found
3. Missing dependencies: Install all required packages with pip
4. Large output files: Timeline images are intentionally high resolution
5. Month or year boundaries: Spanning the boundary between two months or years is untested and may not work as expected

Platform-Specific Issues

• Linux/Ubuntu: Install desktop environment for image viewing: sudo apt-get install xdg-utils
• macOS: No additional requirements for image viewing
• Windows: No additional requirements for image viewing

Performance Notes

• Large cron expressions may take a moment to process
• Image files are optimized for precision over file size
• Calendar generation is fast, timeline rendering takes more time