AWS Deadline Cloud Software Viewer - GUI Application

A modern Python Qt desktop application for querying and displaying available software packages from AWS Deadline Cloud.

Features

Modern Qt Interface - Clean, professional design with intuitive controls
Automated Job Submission - Submit jobs and monitor completion automatically
Data Display - View software packages in an organized table with Name, Version, and Build Hash
CSV Export - Export data for reporting and analysis
Persistent Settings - Saves your Farm and Queue IDs for convenience
Progress Tracking - Real-time status updates and progress bar

Prerequisites

• Python 3.8 or higher
• AWS Deadline Cloud CLI - pip install deadline[gui]
• AWS Credentials - Configured via aws configure
• PyQt6 - Installed automatically via requirements

Installation

Quick Install

Run the installation script which will check all requirements and install dependencies:

python install.py

Manual Installation

1. Install Python dependencies:

   pip install -r requirements.txt

2. Install AWS Deadline Cloud CLI:

   pip install deadline[gui]

3. Configure AWS credentials:

   aws configure

Usage

Running the Application

python deadline_software_viewer.py

Or on Windows, you can double-click deadline_software_viewer.py if Python is associated with .py files.

Using the Application

1. Enter Your Configuration:

   • Farm ID: Your AWS Deadline Cloud farm ID (format: farm-xxxxxxxx)
   • Queue ID: Your AWS Deadline Cloud queue ID (format: queue-xxxxxxxxxxxx)

   Tip: These values are saved automatically and will be pre-filled on next launch

2. Find Your Farm and Queue IDs:

   # List available farms
   deadline farm list
   
   # List queues for a specific farm
   deadline queue list --farm-id farm-xxxxxxxx

3. Submit Job & Fetch Data:

   • Click the " Submit Job & Fetch Software List" button
   • The application will:
     • Submit the job to AWS Deadline Cloud
     • Monitor the job until completion
     • Retrieve and parse the results
     • Display the software packages in the table

4. Export Results:

   • Once data is loaded, click " Export to CSV"
   • Choose a location to save the CSV file
   • File includes Name, Version, and Build Hash columns

Application Architecture

Components

deadline_software_viewer.py
├── MainWindow              # Main GUI window
├── JobSubmitter            # Background thread for AWS operations
├── SoftwareParser          # Parse conda output data
└── Qt Widgets              # Tables, buttons, progress bars

How It Works

1. Job Submission: Uses deadline bundle submit to submit the job template
2. Monitoring: Polls job status every 5 seconds using deadline job get
3. Log Retrieval: Fetches job logs using deadline job logs
4. Parsing: Extracts software info using regex pattern matching
5. Display: Populates Qt table with parsed data

Features in Detail

Configuration Management

• Auto-save: Farm and Queue IDs are automatically saved to ~/.deadline_software_viewer.json
• Validation: Input validation ensures proper ID formats
• Persistence: Settings persist across application sessions

Job Management

• Background Processing: Job submission and monitoring run in a separate thread
• Progress Updates: Real-time status messages and progress bar
• Error Handling: Clear error messages with troubleshooting information
• Timeout Protection: 5-minute maximum wait time with appropriate error handling

Data Display

• Sortable Table: Click column headers to sort data
• Row Selection: Select rows to highlight data
• Alternating Colors: Easy-to-read alternating row colors
• Responsive Layout: Table columns auto-adjust to content

Export Functionality

• CSV Format: Standard CSV with headers
• Timestamped Files: Default filename includes date and time
• Custom Location: Choose where to save exported files

Troubleshooting

"Module not found" Error

Problem: ModuleNotFoundError: No module named 'PyQt6'

Solution:

pip install -r requirements.txt

"deadline: command not found"

Problem: AWS Deadline Cloud CLI is not installed

Solution:

pip install deadline[gui]

"Authentication Error"

Problem: AWS credentials are not configured

Solution:

aws configure
# Enter your AWS Access Key ID, Secret Access Key, and region

"Bundle directory not found"

Problem: The list_software/ directory is missing

Solution: Ensure the directory structure is intact:

project/
├── deadline_software_viewer.py
├── requirements.txt
├── install.py
└── list_software/
    └── template.yaml

"Job Timeout"

Problem: Job exceeded 5-minute maximum wait time

Possible Causes:

• No available workers in the queue
• Worker nodes are busy with other jobs
• Network connectivity issues

Solution:

• Check queue status: deadline queue get --farm-id <farm-id> --queue-id <queue-id>
• Verify workers are available and healthy
• Check AWS Deadline Cloud console for queue status

"No software packages found"

Problem: Job completed but no data was parsed

Possible Causes:

• Job failed to execute conda search command
• Output format changed
• Conda not available on worker nodes

Solution:

• Check job logs manually: deadline job logs --farm-id <farm-id> --queue-id <queue-id> --job-id <job-id>
• Verify conda is installed on worker nodes
• Check that the deadline-cloud conda channel is accessible

Keyboard Shortcuts

• Enter: Submit job (when focus is on Farm or Queue ID fields)
• Ctrl+Q: Quit application
• Ctrl+C: Copy selected table cells

Configuration File Location

Settings are stored in your home directory:

• Windows: C:\Users\<username>\.deadline_software_viewer.json
• macOS: /Users/<username>/.deadline_software_viewer.json
• Linux: /home/<username>/.deadline_software_viewer.json

Technical Details

Dependencies

• PyQt6: Modern Qt6 bindings for Python
• AWS Deadline Cloud CLI: For job submission and monitoring
• Python Standard Library: subprocess, json, re, pathlib

Performance

• Lightweight: Minimal resource usage
• Responsive: UI remains responsive during long-running operations
• Efficient: Background threading prevents UI freezing

Security

• No Credentials Stored: AWS credentials are managed by AWS CLI
• Local Storage: Settings file only contains Farm and Queue IDs
• Read-only Operations: Application only reads job logs, no destructive operations

Development

Project Structure

list_software/
├── README.md                       # Original CLI documentation
├── GUI_README.md                   # This file
├── requirements.txt                # Python dependencies
├── install.py                      # Installation script
├── deadline_software_viewer.py     # Main application
└── list_software/                  # Job bundle
    └── template.yaml               # Deadline Cloud job template

Extending the Application

The application is designed to be extensible. Common enhancements:

1. Add Search/Filter: Filter table by software name or version
2. Multiple Channels: Query different conda channels
3. Comparison Mode: Compare software across different environments
4. Scheduled Queries: Automatically query at intervals
5. Notifications: Alert when new software versions are available

Code Style

• Follows PEP 8 Python style guidelines
• Type hints for better code clarity
• Comprehensive docstrings
• Modular design with clear separation of concerns

Known Limitations

• Job timeout is fixed at 5 minutes
• Only supports the deadline-cloud conda channel
• Requires manual Farm and Queue ID input (no auto-discovery)
• CSV export only (no JSON or Excel formats)

Roadmap

Future enhancements planned:

• Dark mode theme option
• Auto-discovery of farms and queues
• Job history and caching
• Advanced filtering and search
• Multiple export formats (JSON, Excel)
• Batch job submission
• Real-time log streaming
• Software comparison tools

Support

For issues related to:

• This Application: Check troubleshooting section above
• AWS Deadline Cloud: AWS Deadline Cloud Documentation
• PyQt6: PyQt6 Documentation

License

This tool is provided as-is for use with AWS Deadline Cloud.

Version History

• v1.0.0 (2024-12) - Initial release
  • Modern Qt6 GUI interface
  • Job submission and monitoring
  • Data parsing and display
  • CSV export functionality
  • Persistent configuration

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