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Python implementation of LabThings, based on the Flask microframework

Project description

Python LabThings (for Flask)

LabThings ReadTheDocs PyPI Code style: black codecov

A thread-based Python implementation of the LabThings API structure, based on the Flask microframework.


pip install labthings

Quickstart example

This example assumes a PretendSpectrometer class, which already has data and integration_time attributes, as well as an average_data(n) method. LabThings allows you to easily convert this existing instrument control code into a fully documented, standardised web API complete with auto-discovery and automatic background task threading.

#!/usr/bin/env python
import time

from labthings import ActionView, PropertyView, create_app, fields, find_component, op
from labthings.example_components import PretendSpectrometer
from labthings.json import encode_json

Class for our lab component functionality. This could include serial communication,
equipment API calls, network requests, or a "virtual" device as seen here.

Create a view to view and change our integration_time value,
and register is as a Thing property

# Wrap in a semantic annotation to autmatically set schema and args
class DenoiseProperty(PropertyView):
    """Value of integration_time"""

    schema = fields.Int(required=True, minimum=100, maximum=500)
    semtype = "LevelProperty"

    def get(self):
        # When a GET request is made, we'll find our attached component
        my_component = find_component("org.labthings.example.mycomponent")
        return my_component.integration_time

    def put(self, new_property_value):
        # Find our attached component
        my_component = find_component("org.labthings.example.mycomponent")

        # Apply the new value
        my_component.integration_time = new_property_value

        return my_component.integration_time

Create a view to quickly get some noisy data, and register is as a Thing property

class QuickDataProperty(PropertyView):
    """Show the current data value"""

    # Marshal the response as a list of floats
    schema = fields.List(fields.Float())

    def get(self):
        # Find our attached component
        my_component = find_component("org.labthings.example.mycomponent")

Create a view to start an averaged measurement, and register is as a Thing action

class MeasurementAction(ActionView):
    # Expect JSON parameters in the request body.
    # Pass to post function as dictionary argument.
    args = {
        "averages": fields.Integer(
            missing=20, example=20, description="Number of data sets to average over",
    # Marshal the response as a list of numbers
    schema = fields.List(fields.Number)

    # Main function to handle POST requests
    def post(self, args):
        """Start an averaged measurement"""

        # Find our attached component
        my_component = find_component("org.labthings.example.mycomponent")

        # Get arguments and start a background task
        n_averages = args.get("averages")

        # Return the task information
        return my_component.average_data(n_averages)

# Create LabThings Flask app
app, labthing = create_app(
    title="My Lab Device API",
    description="Test LabThing-based API",

# Attach an instance of our component
# Usually a Python object controlling some piece of hardware
my_spectrometer = PretendSpectrometer()
labthing.add_component(my_spectrometer, "org.labthings.example.mycomponent")

# Add routes for the API views we created
labthing.add_view(DenoiseProperty, "/integration_time")
labthing.add_view(QuickDataProperty, "/quick-data")
labthing.add_view(MeasurementAction, "/actions/measure")

# Start the app
if __name__ == "__main__":
    from labthings import Server



Much of the code surrounding default response formatting has been liberally taken from Flask-RESTful. The integrated Marshmallow support was inspired by Flask-Marshmallow and Flask-ApiSpec.

Developer notes

Changelog generation

  • npm install -g conventional-changelog-cli
  • conventional-changelog -r 1 --config ./changelog.config.js -i -s

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