Reference library

ML engineering pipelines

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

2 matches
ML engineering pipelines easy

How to Build a Mock TFX Pipeline in Python

Simulate a TFX-style ML pipeline with simple Python functions to understand component orchestration, data flow, and artifact passing.

tfx ml-pipeline orchestration
Python
# Mock TFX pipeline to illustrate component orchestration

def CsvExampleGen(data_path):
    """Mock component: Simulates reading CSV data."""
    print(f"ExampleGen: Reading from {data_path}")
    return {"records": 100, "name": "examples"}

def StatisticsGen(example_artifact):
    """Mock component: Simulates genera…
15 0 Open
ML engineering pipelines medium

How to mock an artifact store with local paths in Python for ML pipelines

Create a temporary local artifact store with dummy files and metadata to test ML pipeline code without real storage.

ml-pipelines mock tempfile
Python
import tempfile
from pathlib import Path
import json


def create_artifact_store_mock(base_path: Path = None):
    """Create a local artifact store mock directory structure."""
    if base_path is None:
        base_path = Path(tempfile.mkdtemp())

    store_layout = {
        "artifacts": [
            {"name": "mode…
13 0 Open

Browse by section

Each section groups closely related Python snippets.

ML engineering pipelines — Python code examples

What you will find here

This page collects ml engineering pipelines snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.

Samples vs tutorials and challenges

Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.