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JetStream: Cloud Data Manager - A comprehensive tool for managing local-to-cloud uploads with queue management, statistics, and folder analysis

Project description

NOAA JetStream — Cloud Data Management Transfer System

jetstream

A comprehensive web-based application for managing Google Cloud Storage uploads with features including job queuing, real-time analytics, cloud bucket analysis, and batch processing capabilities.

Features

  • Upload Management
  • Analytics & Monitoring
  • Cloud Bucket Analysis
  • File Filtering
  • Web Dashboard

Screenshots

Dashboard Upload Jobs Analytics
Home Uploads Analytics

Prerequisites

  • Python 3.9+
  • Google Cloud SDK (includes gsutil) — for cloud upload features
  • Permissions to target GCS buckets

Google Cloud Setup

Required only for cloud upload features:

# Install Google Cloud SDK
# Download from: https://cloud.google.com/sdk/docs/install

# Authenticate
gcloud auth login --no-launch-browser
gcloud auth application-default login --no-launch-browser

# Verify access (optional)
gsutil ls
gcloud auth list

Installation

Option 1: Install from PyPI (Recommended)

pip install noaa-jetstream

Using Anaconda/conda? If you see dependency resolver warnings, use uv (recommended) or --no-cache-dir:

# Option A: use uv (faster, cleaner resolver — recommended for conda users)
pip install uv
uv pip install noaa-jetstream
# May need to create virtual environment first, so do it in a local directory then activate uv venv then .venv\Activate\scripts.bat

# Option B: skip pip cache
pip install --no-cache-dir --no-user noaa-jetstream

Upgrade

uv pip install --no-cache --upgrade noaa-jetstream

Option 2: Install from Source (Development)

# Clone the repository
git clone https://github.com/MichaelAkridge-NOAA/jetstream.git
cd jetstream

# Install in development mode
pip install -e .

# Or using uv (recommended)
pip install uv
uv pip install -e ".[dev]"
# May need to pip install uvicorn, pip install fastapi, pip install google-cloud-storage separately

Starting the Application

If Installed via pip

# Start the server (opens browser automatically)
jetstream

# view options
jetstream --help
# With custom options
jetstream --port 9000
jetstream --host 127.0.0.1 --port 8080
jetstream --no-browser
jetstream --log-level debug

If Running from Source

# Using the CLI
python main.py

# Or with the diagnostic startup script
python start.py

# Or directly with uvicorn
python -m uvicorn jetstream.main:app --reload

The application will start on http://localhost:8000 and automatically open in your default browser.

Desktop Shortcuts

Desktop and Start Menu shortcuts are included with the default install. The shortcut will automatically use the JetStream icon (icon.ico) when created.

# Create desktop + Start Menu shortcut (uses JetStream icon automatically)
jetstream-create-shortcuts

# Remove shortcuts
jetstream-remove-shortcuts

Shortcuts launch JetStream directly using the current Python environment and open a terminal window. On Windows a .lnk shortcut is created on the desktop and in the Start Menu. On macOS/Linux a .app/.desktop shortcut is created in Applications.

Troubleshooting Startup Issues

If the server appears to start but you can't connect:

  1. Run diagnostics:

    python diagnose.py
    
  2. Run with debug logging:

    jetstream --log-level debug
    # or from source:
    python -m uvicorn jetstream.main:app --reload --log-level debug
    

Troubleshooting

Cannot connect to GCS:

  • Verify authentication: gcloud auth list
  • Check bucket permissions
  • Ensure Application Default Credentials are set

Jobs stuck in queue:

  • Check queue status in dashboard
  • Verify no jobs are blocking the queue
  • Restart the application if needed

Database errors:

  • Delete jetstream.db to reset (loses history)
  • Check file permissions in application directory

API not responding:

  • Check if port 8000 is already in use
  • View logs in terminal for error messages
  • Ensure all dependencies are installed

Disclaimer

This repository is a scientific product and is not official communication of the National Oceanic and Atmospheric Administration, or the United States Department of Commerce. All NOAA GitHub project content is provided on an 'as is' basis and the user assumes responsibility for its use. Any claims against the Department of Commerce or Department of Commerce bureaus stemming from the use of this GitHub project will be governed by all applicable Federal law. Any reference to specific commercial products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply their endorsement, recommendation or favoring by the Department of Commerce. The Department of Commerce seal and logo, or the seal and logo of a DOC bureau, shall not be used in any manner to imply endorsement of any commercial product or activity by DOC or the United States Government.

License

See the LICENSE.md for details

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