datagrok-celery-task 0.1.4

Celery Task wrapper to integrate Python functions into the Datagrok platform.

Datagrok Python Celery Task Library

This package provides a Celery task wrapper for integrating Python functions into the Datagrok platform. It enables logging, progress tracking, and seamless communication between Celery workers and Datagrok’s infrastructure.

Refer to the Datagrok Help for more information about the platform.

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Installation

Install the package using pip:

pip install datagrok-celery-task

Usage

To define tasks compatible with Datagrok, use the DatagrokTask base class and configure your Celery app with the provided Settings class.

from celery import Celery
from datagrok_celery_task import DatagrokTask, Settings
import logging

# Always create a Settings object. Provide properties manually only if not launched by Datagrok.
settings = Settings(log_level=logging.DEBUG)

# Create a Celery app
app = Celery(settings.celery_name, broker=settings.broker_url)

# Define a simple Datagrok task
@app.task(base=DatagrokTask)
def echo(c, **kwargs):
    print("Received USER_API_KEY:", kwargs.get("USER_API_KEY", "empty"))
    print("Received data:", c)

# Define a task that reports progress
@app.task(bind=True, base=DatagrokTask)
def progress_task(self: DatagrokTask, a):
    self.update_state(meta={"percent": 10, "description": "Starting"})
    print(a)
    return "Task completed"

Notes

• When Datagrok manages the Celery worker, environment variables will auto-populate Settings.
• Prins will appear in Datagrok log messages of the FuncCall. Please note, that it will work only when Celery prefork worker pool is used.
• Bind task bind=True and use self.update_state to manually update platform's progress bar.
• Tasks can return results or raise Exception.

License

See License.md.