Reference library

ML engineering pipelines

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

5 matches

Bayesian Optimization in Python: A Simplified Mock Implementation

A toy Bayesian optimization loop with a Gaussian process prior, expected improvement acquisition, and noisy sampling to find a function's minimum.

bayesian-optimization gaussian-process hyperparameter-tuning

Python

import random
import math

class BayesianOptimizer:
    def __init__(self, noise=0.1):
        self.noise = noise
        self.observations = []
    
    def objective(self, x):
        return (math.sin(3*x) + 0.5*x) / (1 + x**2)
    
    def gaussian_process_prior(self, x1, x2, length_scale=0.5):
        return math.…

12 0 Open

ML engineering pipelines medium

How to Build a Mock ML Pipeline with Prefect in Python

Create a lightweight Prefect flow with mock preprocessing, training, and evaluation tasks to prototype an ML pipeline end-to-end.

prefect machine-learning pipeline

Python

from prefect import task, flow
from datetime import datetime


@task
def preprocess_data(raw_value: float) -> float:
    """Mock preprocessing: normalize the input value."""
    return raw_value / 100.0


@task
def train_model(features: float) -> dict:
    """Mock training: return a fake model artifact."""
    return …

12 0 Open

ML engineering pipelines medium

How to Create a Mock ONNX Model in Python

Build and export a minimal mock ONNX model with a Reshape and Gemm layer using the onnx helper API.

onnx model-export mlops

Python

import onnx
import numpy as np
from onnx import helper, TensorProto

def create_mock_model():
    # Define input and output tensors
    input_tensor = helper.make_tensor_value_info('input', TensorProto.FLOAT, [1, 3, 224, 224])
    output_tensor = helper.make_tensor_value_info('output', TensorProto.FLOAT, [1, 10])

   …

16 0 Open

ML engineering pipelines medium

How to Mock a Kubeflow Pipeline in Python

Build a minimal in-memory mock of a Kubeflow pipeline DAG using dataclasses and OrderedDict to chain component functions.

kubeflow pipelines mlops

Python

from typing import Dict, Any
from dataclasses import dataclass, field
from collections import OrderedDict


@dataclass
class KubeflowPipelineMock:
    """A minimal mock of a Kubeflow pipeline DAG."""
    name: str
    components: OrderedDict[str, callable] = field(default_factory=OrderedDict)

    def add_component(se…

14 0 Open

ML engineering pipelines medium

Training Pipeline Orchestration Mock DAG in Python

Build a mock DAG orchestrator that runs ML pipeline stages in dependency order using topological sorting (Kahn's algorithm).

dag pipeline topological-sort

Python

from collections import deque
from dataclasses import dataclass, field


@dataclass
class DAGNode:
    name: str
    task: callable
    dependencies: list[str] = field(default_factory=list)


class MockDAG:
    def __init__(self, nodes: list[DAGNode]):
        self.nodes = {n.name: n for n in nodes}
        self.execu…

13 0 Open

Browse by section

Each section groups closely related Python snippets.