Reference library

ML engineering pipelines

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

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How to Build a Mock Offline Feature Store in Python

Build an in-memory mock of an offline feature store with a dict-based FeatureStore class for storing and retrieving ML features by entity ID.

feature-store ml-pipeline mock

Python

from datetime import datetime
from collections import defaultdict


class FeatureStore:
    """Simple in-memory mock of an offline feature store."""

    def __init__(self):
        self._features = defaultdict(dict)

    def ingest(self, entity_id, feature_name, value, timestamp=None):
        ts = timestamp or datet…

14 0 Open

ML engineering pipelines medium

How to Mock MLflow Model Registration in Python

Build a lightweight in-memory mock of MLflow's MlflowClient to test model registration, versioning, and stage transitions without a tracking server.

mlflow mocking model-registry

Python

from mlflow.tracking import MlflowClient
from mlflow.entities import ModelVersion, Model


class MockMlflowClient:
    """Minimal mock of MlflowClient's model registration methods."""
    
    def __init__(self):
        self.registered_models = {}
        self.model_versions = {}
    
    def register_model(self, mod…

14 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 easy

Model registry version mock in Python

A simple in-memory model registry that stores model versions with metadata and supports version listing and latest retrieval.

ml-engineering model-registry versioning

Python

class ModelRegistry:
    def __init__(self):
        self.models = {}

    def register(self, name, version, model_type, metrics=None):
        if name not in self.models:
            self.models[name] = []
        entry = {
            "version": version,
            "model_type": model_type,
            "metrics": m…

13 0 Open

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