scalable-pypeline 2.2.1

PypeLine - Python pipelines for the Real World

______ __   ________  _____  _     _____  _   _  _____ 
| ___ \\ \ / /| ___ \|  ___|| |   |_   _|| \ | ||  ___|
| |_/ / \ V / | |_/ /| |__  | |     | |  |  \| || |__  
|  __/   \ /  |  __/ |  __| | |     | |  | . ` ||  __| 
| |      | |  | |    | |___ | |_____| |_ | |\  || |___ 
\_|      \_/  \_|    \____/ \_____/\___/ \_| \_/\____/                                 

Overview

PypeLine is a versatile open-source library designed to streamline the management of data workflows and APIs. With PypeLine, you can efficiently schedule cron jobs, execute complex Directed Acyclical Graph (DAG) pipelines, and set up a Flask API complete with OpenAPI documentation.

Key Features

• Cron Job Scheduling: Easily schedule recurring tasks with flexible cron job functionality, ensuring that your processes run reliably at specified intervals.
• DAG Pipelines: Define and execute DAGs to manage complex data workflows with dependencies. PypeLine handles the execution order and parallelism, ensuring that each task runs in the correct sequence.
• Flask API with OpenAPI: Quickly configure a RESTful API using Flask, with built-in support for OpenAPI documentation, allowing for clear, standardized documentation of your endpoints.

Requirements

• RabbitMQ
• Redis
• Docker (optional for dev)

Getting Started

Install PypeLines:

pip install scalable-pypeline[flask,web,workers]>=1.2.3

Configure your Flask project (app.py)

from flask import Flask
from pypeline.flask import FlaskPypeline
from pypeline_demo.api import bp
from pypeline_demo.config import Config
from pypeline_demo.extensions import dramatiq



def create_app():
    app = Flask(__name__)

    dramatiq.init_app(app)

    # Initialize your app with a configuration
    app.config.from_object(Config)

    pypeline = FlaskPypeline()
    pypeline.init_app(app, init_api=True)

    # Register API blueprints you wish 
    app.extensions["pypeline_core_api"].register_blueprint(bp)
    # Register application blueprints to application
    app.register_blueprint(bp)

    return app


if __name__ == "__main__":
    app = create_app()
    app.run(port=5001)

Configure Dramatiq extension (extensions.py)

from pypeline.dramatiq import Dramatiq


dramatiq = Dramatiq()

Setup your yaml configuration for pypelines (pypeline.yaml)

serviceConfig:
    - name: pipeline-worker
      registeredTasks:
          - handler: pypeline_demo.pipeline.a
          - handler: pypeline_demo.pipeline.b
          - handler: pypeline_demo.pipeline.c
          - handler: pypeline_demo.scheduled_tasks.cron_task

pipelines:
    demo_pipeline:
        name: Demo Pipeline
        description: Pipeline to show examples of DAG Adjacency
        schemaVersion: 1
        config:
            dagAdjacency:
                a:
                    - b
                    - c
            metadata:
                maxRetry: 1
                retryBackoff: 180
                retryBackoffMax: 300
                retryJitter: true
                maxTtl: 10800
                queue: new-queue
            taskDefinitions:
                a:
                    handler: pypeline_demo.pipeline.a
                b:
                    handler:  pypeline_demo.pipeline.b
                c:
                    handler:  pypeline_demo.pipeline.c
scheduledTasks:
    cron-task:
        name: Example cron task
        enabled: true
        config:
            task: pypeline_demo.scheduled_tasks.cron_task
            queue: new-queue
            schedule:
                minute: '*'
                hour: '*'
                dayOfWeek: '*'
                dayOfMonth: '*'
                monthOfYear: '*'
        schemaVersion: 1

Setup your modules to be executed by yaml (pipeline.py && scheduled_tasks.py)

import time


def a(event):
    print("A")


def b(event):
    print("B")
    time.sleep(10)


def c(event):
    print("C")

def cron_task():
    print("HI")

Configure your environment variables (demo.env)

SERMOS_BASE_URL=local
PYPELINE_CLIENT_PKG_NAME=pypeline_demo
REDIS_URL=redis://:password@localhost:6379/0
RABBITMQ_URL=amqp://admin:password@localhost:5672

Start Rabbit & Redis as your message broker and backend results storage. We use docker compose for this.

DEMO PROJECT COMING SOON!

Testing

If you are developing pypeline and want to test this package, install the test dependencies:

$ pip install -e .[test]

Now, run the tests:

$ tox