qdrive

Dataset management and measurement library for the qHarbor data platform.

qdrive is the Python interface for creating, managing, and syncing scientific datasets with qHarbor.

Features

• 📦 Create & manage datasets — Store measurements with rich metadata (tags, attributes, descriptions)
• 📁 Multi-file support with versioning — Attach xarray, NumPy, JSON, HDF5 or any file, with automatic version tracking
• 🔍 Powerful search — Filter datasets by attributes, date range, tags, or text
• ☁️ Cloud sync — Automatic synchronization via the sync agent
• 📊 Measurement tools — Built-in do0D, do1D, do2D sweep functions using native qHarbor format, compatible with QCoDeS parameters

Installation

pip install qdrive

To install the background services (syncs your data to qHarbor automatically):

etiket-services install

Other useful commands (though the service is managed automatically in the background):

etiket-services status      # Check service status
etiket-services start       # Start services
etiket-services stop        # Stop services
etiket-services restart     # Restart services
etiket-services update      # Update packages
etiket-services update --no-connectors  # Update core packages only
etiket-services uninstall   # Remove services

For programmatic control of the sync agent (managing sync sources, viewing sync status, debugging), see the etiket-sdk package. You can also manage the services through the DataQruiser desktop application.

Quick Start

Authentication

import qdrive.authenticate as qauth

# See available institutions and login methods
qauth.print_login_methods()

# Log in with SSO (opens browser)
qauth.log_in_with_sso("MyInstitution")

# Check if logged in
qauth.is_logged_in()  # Returns True/False

# Log out
qauth.logout()

Scopes

from qdrive.scopes import get_scopes, set_default_scope

# List available scopes
get_scopes()

# Set default scope (by name or UUID)
set_default_scope("MyScope")

Create a dataset

from qdrive import dataset

ds = dataset.create(
    'Qubit T2* measurement',
    tags=['calibration'],
    attributes={'sample': 'Q7-R3', 'fridge': 'BlueFors-1'}
)

Add files to a dataset

import numpy as np
import xarray as xr

# Add various file types
ds['config.json'] = {'param1': 42, 'param2': 'value'}
ds['raw_data.npz'] = np.random.rand(100, 100)
ds['measurement.hdf5'] = xr.Dataset({'signal': (['time'], np.sin(np.linspace(0, 10, 100)))})
ds['script.py'] = __file__  # Attach the current script

Retrieve and access data

from qdrive import dataset

ds = dataset('59c40af3-cef3-49aa-8747-64707a9b080a')  # Load by UUID

# Access files in multiple formats
xr_data = ds['measurement.hdf5'].xarray
json_data = ds['config.json'].json

Search datasets

from qdrive.dataset.search import search_datasets

results = search_datasets(
    search_query='T2*',
    attributes={'sample': 'Q7-R3'},
    ranking=1
)

for ds in results:
    print(ds.name, ds.uuid)

Documentation

• 📖 Full Documentation
• 🖥️ DataQruiser App — Browse and visualize your data
• 💬 Support

License

Proprietary — © 2026 QHarbor B.V. All Rights Reserved.