Zenaton examples for Python

Zenaton helps developers to easily run, monitor and orchestrate background jobs on your workers without managing a queuing system. In addition to this, a monitoring dashboard shows you in real-time tasks executions and helps you to handle errors.

This repository contains examples of workflows built with Zenaton. These examples illustrates how Zenaton orchestrates tasks that are executed on different workers.

Installation

Download this repo

git clone https://github.com/zenaton/examples-python.git && cd examples-python

then add an .env file

cp .env.example .env

and populate it with your application id and api token found here.

Or use the .env.example file in this repo.

These a the minimal requirements to run the Zenaton client:

ZENATON_APP_ID=*****************
ZENATON_API_TOKEN=***************************
ZENATON_APP_ENV=dev

Running Locally

Install dependencies

pip3 install -r requirements.txt

Then, you need to install a Zenaton worker

curl https://install.zenaton.com | sh

and start it, and make it listen to your configuration:

zenaton start; zenaton listen --env=.env --boot=boot.py

Your all set!

Running on Docker

Simply run

docker-compose build; docker-compose up

You're all set!

Your workflows will be processed by your worker, so you won't see anything except the stdout and stderr, respectively zenaton.out and zenaton.err. Look at these files :)

Example 1: Single task execution

This example showcases

A single execution of a task.

python3 launch_task.py

Example 2 : Sequential tasks execution

This example showcases

a sequential execution of three tasks. The second and third tasks are executed only when the previous one is processed.
In a sequential task execution, you can get the output of a task. The result of a task can be used by the next one.

python3 launch_sequential.py

Example 3: Parallel tasks execution

This example showcases

a parallel execution of 2 tasks
a third task that is executed only after both first two tasks were processed

python3 launch_parallel.py

Example 4: Asynchronous tasks execution

this example showcases

Asynchronous executions of Task A and Task B (fire and forget)
Then sequential executions of Task C and Task D

python3 launch_asynchronous.py

When a task is dispatched asynchronously, the workflow continues its execution without waiting for the task completion. Consequently, a task asynchronous dispatching always returns a null value.