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GitHub - LiveViewTech/cron-visualizer: An interactive Python tool for visualizing cron job schedules. Generates a monthly calendar view you can click to get detailed daily or weekly timelines.

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