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JobtasticMixins

Package includes:

AVGTimeRedis class

The class that helps automate calculate an avarage time for different kind tasks and saves result into Redis DB

Install

pip install jobtastic-mixins

or install from Github

pip install https://github.com/abbasovalex/JobtasticMixins/archive/master.zip

Usage

  1. You must will add the mixin class as first argument
  2. You should set default_avg_time in the seconds
  3. You must use self.update_progress() without arguments
class YourTask(AVGTimeRedis, JobtasticTask):
    default_avg_time = 60 # 1 minute
    
    ...
    
    def calculate_result(self, ..., **kwargs):
        ...

default_avg_time used when task still never calculated It will be encompass arithmetical mean after task was executed. Forecast accuracy depends from count executed tasks

Example with AVGTimeRedis class

The class that helps automate calculate an avarage time for different kind tasks and saves result into Redis DB

Let's take a look at the example task using with JobtasticMixins and AVGTimeRedis class:

from time import sleep
from jobtastic import JobtasticTask
from jobtasticmixins import AVGTimeRedis


class LotsOfDivisionTask(AVGTimeRedis, JobtasticTask):
    """
    Division is hard. Make Celery do it a bunch.
    """
    significant_kwargs = [
        ('numerators', str),
        ('denominators', str),
    ]
    herd_avoidance_timeout = 60
    cache_duration = 0
    # optional variable was added. by default is 30 seconds   
    default_avg_time = 90

    def calculate_result(self, numerators, denominators, **kwargs):
        results = []
        for count, divisors in enumerate(zip(numerators, denominators)):
            numerator, denominator = divisors
            results.append(numerator / denominator)
            # it will be auto calculated
            self.update_progress()
            sleep(0.1)

        # set finish=True for avoid trouble
        self.update_progress(finish=True)
        return results

Under the hood:

  1. AVGTimeRedis gets settings.BROKER_URL and connects to Redis
  2. It counts the tasks and the workers and uses to calculating

More details you can see into source

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