Disruptive Technologies Python Client
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:
import disruptive as dt
dt.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.
import disruptive as dt
# 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.
for event in dt.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
Set up the development virtualenv environment:
make
Run unit-tests against the currently active python version:
make test
Lint the package code using MyPy and flake8:
make lint
Build the package distribution:
make build
1 maintainer
Metadata
1 maintainer
Release files for disruptive 1.7.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| disruptive-1.7.3.tar.gz | 59.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| disruptive-1.7.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 114.0 kB
Release files / disruptive-1.7.3.tar.gz
| Download URL | disruptive-1.7.3.tar.gz |
|---|---|
| Size | 59.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.12.9
|
Release files / disruptive-1.7.3-py3-none-any.whl
| Download URL | disruptive-1.7.3-py3-none-any.whl |
|---|---|
| Size | 54.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.12.9
|
