digistudio-qc-utils 0.3.0

CLI utilities for QFieldCloud: upload to GCP, clean old files, and more

digistudio-qc-utils

CLI utilities for QFieldCloud: upload photos to Google Cloud Storage, clean old files, and more.

Features

• Upload photos to GCP: Copy photos from QFieldCloud to a Google Cloud Storage bucket
• Clean old photos: Remove photos older than a specified number of days from QFieldCloud
• Flexible filtering: Use glob patterns to filter which files to process (default: *.jpg)
• Dry-run mode: Test cleanup operations without actually deleting files
• Progress reporting: See detailed progress and summary of operations

Installation

Requirements

• Python 3.10 or higher
• uv package manager

Install dependencies

uv sync

This will install the package in development mode with all dependencies.

Configuration

Environment Variables

Create a .env file or export these environment variables:

# QFieldCloud authentication (required for both commands)
export QFIELDCLOUD_USERNAME="your_username"
export QFIELDCLOUD_PASSWORD="your_password"

# Optional: QFieldCloud API URL (default: https://app.qfield.cloud/api/v1/)
export QFIELDCLOUD_URL="https://app.qfield.cloud/api/v1/"

# Alternative: use token authentication
export QFIELDCLOUD_TOKEN="your_token"

GCP Service Account

For the upload command, you need a GCP service account JSON file with permissions to write to Cloud Storage.

See .env.example for a complete list of environment variables.

Usage

Upload photos to GCP

Upload photos from QFieldCloud to a Google Cloud Storage bucket:

qc-to-gcp upload \
  --qc-project-id "your-qfield-project-id" \
  --gcp-bucket "your-gcs-bucket" \
  --gcp-bucket-directory "photos/2024" \
  --gcp-auth-file "path/to/service-account.json" \
  --qc-filter "*.jpg"

Options:

• --qc-project-id: QFieldCloud project ID (required)
• --gcp-bucket: GCP bucket name (required)
• --gcp-bucket-directory: Directory path in bucket (required)
• --gcp-auth-file: Path to GCP service account JSON file (required)
• --qc-filter: File pattern to match (default: *.jpg)
• --verbose, -v: Enable verbose logging

Features:

• Intelligently compares file lists to skip existing files (only 2 API calls instead of N+1)
• Handles subdirectories properly (DCIM/, files/, etc.)
• Shows progress for each file
• Provides detailed analysis summary before upload
• Uses temporary storage for downloads

Clean old photos from QFieldCloud

Remove photos older than a specified number of days:

qc-clean \
  --qc-project-id "your-qfield-project-id" \
  --keep-days 15 \
  --qc-filter "*.jpg"

Options:

• --qc-project-id: QFieldCloud project ID (required)
• --keep-days: Keep files newer than this many days (default: 15)
• --qc-filter: File pattern to match (default: *.jpg)
• --dry-run: Show what would be deleted without actually deleting
• --verbose, -v: Enable verbose logging and show detailed file list

Example with dry-run:

qc-clean \
  --qc-project-id "693d753d-2b71-44e1-892f-dd2e77852c4a" \
  --keep-days 30 \
  --qc-filter "*.jpg" \
  --dry-run

Development

Project structure

qc-utils/
├── src/qc_utils/
│   ├── __init__.py
│   ├── cli.py              # CLI entry points
│   ├── commands/
│   │   ├── clean.py        # Clean command implementation
│   │   └── upload.py       # Upload command implementation
│   └── core/
│       ├── filters.py      # File filtering utilities
│       ├── gcp_client.py   # GCP Storage client wrapper
│       └── qfield_client.py # QFieldCloud client wrapper
├── pyproject.toml
└── README.md

Run linting

uv run ruff check .
uv run ruff format .

Run type checking

uv run basedpyright

License

[Add your license here]

Credits

This tool replaces the historical bash/Python scripts with a modern CLI architecture.