Reference library

ML engineering pipelines

Feature prep, batch inference, model-serving hooks, and production ML workflow glue.

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ML engineering pipelines easy

How to Simulate an Airflow ML Pipeline in Python

Mock an Airflow ML pipeline in plain Python by defining steps, simulating their execution with delays, and returning a success summary.

airflow ml pipeline
Python 
from datetime import datetime, timedelta
import time


class MLPipeline:
    def __init__(self, pipeline_name):
        self.pipeline_name = pipeline_name
        self.steps = []

    def add_step(self, step_name, duration_seconds):
        self.steps.append({"name": step_name, "duration": duration_seconds})

    def …
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