qdrive 0.2.60

Dataset management and measurement library for scientific data

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

Quick Start

Log in

import qdrive
qdrive.launch_GUI()

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

GPL-3.0 — © 2024-2026 QHarbor B.V. See LICENCE for details.