Disruptive Technologies Python Client

Documentation

• Python API Reference
• Developer Documentation

Installation

The package can be installed through pip:

pip install --upgrade disruptive

or from source:

pip install .

Requirements

• Python 3.9-3.13

Authentication

The package is authenticated by providing Service Account credentials in either of the following ways.

• By setting the following environment variables:

export DT_SERVICE_ACCOUNT_KEY_ID="<SERVICE_ACCOUNT_KEY_ID>"export DT_SERVICE_ACCOUNT_SECRET="<SERVICE_ACCOUNT_SECRET>"export DT_SERVICE_ACCOUNT_EMAIL="<SERVICE_ACCOUNT_EMAIL>"

• By providing the credentials programmatically:

importdisruptiveasdtdt.default_auth=dt.Auth.service_account(
key_id="<SERVICE_ACCOUNT_KEY_ID>",
secret="<SERVICE_ACCOUNT_SECRET>",
email="<SERVICE_ACCOUNT_EMAIL>",
)

See Python API Authentication for more details.

Usage

Once authenticated, most functionality can be accessed through resource methods on the following format.

disruptive.<Resource>.<method>()

A few common uses are showcased in the snippet below. See the Python API Reference for full documentation.

importdisruptiveasdt# Fetch a sensor, specified by its ID.sensor=dt.Device.get_device('<DEVICE_ID>')
# Printing the returned object will list all attributes.print(sensor)
# Set a new label on the sensor.dt.Device.set_label(sensor.device_id, sensor.project_id, key='nb', value='99')
# Get touch- and temperature event history for the sensor.history=dt.EventHistory.list_events(
sensor.device_id,
sensor.project_id,
event_types=[
dt.events.TOUCH,
dt.events.TEMPERATURE,
]
)
# Initiate an event stream for all devices in the sensor's project.foreventindt.Stream.event_stream(sensor.project_id):
# Print new events data as they arrive.print(event.data)

Logging

The simplest method is enabled by setting disruptive.log_level.

dt.log_level=dt.logging.INFO

If more fine-grained control is desired, the standard library logging can also be used.

logging.basicConfig(
filename='example.log',
format='[%(asctime)s.%(msecs)03d] %(levelname)-8s - %(message)s',
datefmt='%Y-%m-%d %H:%M:%S',
)
logging.getLogger('disruptive').setLevel(logging.INFO)

For both methods, the standard levels DEBUG, INFO, WARNING, ERROR, and CRITICAL are supported.

Examples

A few examples has been provided. Before running, the required environment variables listed at the start of each example must be set.

python examples/example_name.py

Exceptions

If a request is unsuccessful or has been provided with invalid parameters, an exception is raised. A list of available exceptions are available in the API Reference.

Development

This repository uses uv to manage dependencies.

Unit-tests

uv run --extra extra pytest tests/

Linting

uv run ruff check .

Type-Checking

uv run mypy disruptive/