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How to Stage ML Model Workflows with Python Classes
Defines a Stage class to model ML pipeline stages with variants and mocks, printing grammar for Model, Staging, and Production stages.
class Stage:
def __init__(self, name):
self.name = name
self.mocks = []
self.variants = []
def add_mock(self, mock_name):
self.mocks.append(mock_name)
def add_variant(self, variant_name, productions=()):
self.variants.append((variant_name, list(productions)))
…How to Trigger Model Retraining on Drift in Python
Automatically detects accuracy drift in a mock ML model and triggers retraining when performance falls below a threshold.
import random
import time
class MockModel:
def __init__(self, name):
self.name = name
self.accuracy = 0.85
self.version = 1
def train(self, data_size):
# Simulate training time and accuracy improvement
time.sleep(0.1)
drift = random.uniform(-0.02, 0.02)
…How to implement a canary traffic split in Python
Route incoming traffic between stable and canary model or service versions using a weight-based random split with deterministic testing.
import random
def canary_route(service_name: str, canary_weight: float = 0.2) -> str:
"""Route traffic between stable and canary versions based on weight."""
rng = random.Random(42) # deterministic for reproducible demo
if rng.random() < canary_weight:
return f"{service_name}-canary"
return …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.
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…K-Fold Cross Validation in Python: A Simple Implementation
Implements k-fold cross validation from scratch, splitting data into folds and computing MSE scores for a baseline mean-predictor model.
import random
from statistics import mean
def cross_validation_scores(data, labels, k=5, seed=42):
random.seed(seed)
indices = list(range(len(data)))
random.shuffle(indices)
fold_size = len(indices) // k
folds = []
for i in range(k):
if i == k - 1:
folds.append(indices[i *…Load CSV Training Data Without Pandas in Python
This code loads a CSV file into a list of dictionaries using only the standard library, ideal for small ML training data without heavy dependencies.
import csv
from pathlib import Path
def load_csv(path):
"""Load CSV file into list of dicts without pandas."""
rows = []
with open(path, newline='', encoding='utf-8') as f:
reader = csv.DictReader(f)
for row in reader:
rows.append(dict(row))
return rows
if __name__ == "__m…Mock a Flyte ML workflow in Python
Build a lightweight mock of a Flyte ML pipeline with dataclasses and a simple execution loop that passes outputs between tasks.
from dataclasses import dataclass, field
from typing import List, Dict, Optional
import time
@dataclass
class FlyteTask:
name: str
inputs: Dict = field(default_factory=dict)
outputs: Dict = field(default_factory=dict)
def run(self) -> Dict:
time.sleep(0.1) # simulate work
return sel…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.
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…One Hot Encode Categories in Python
Convert a list of categorical strings into one-hot encoded numeric vectors using pure Python and NumPy.
import numpy as np
categories = ["red", "green", "blue", "red", "blue", "green", "red"]
unique = sorted(set(categories))
lookup = {cat: i for i, cat in enumerate(unique)}
one_hot = []
for cat in categories:
row = [0] * len(unique)
row[lookup[cat]] = 1
one_hot.append(row)
print("Categories:", categories…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).
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…How to create a global control holdout group in Python
This code implements a deterministic global control holdout group, randomly selecting a fraction of users to be excluded from feature rollouts for experiment validation.
import random
class GlobalControl:
def __init__(self, population_size, holdout_fraction=0.2, seed=42):
random.seed(seed)
self.population_size = population_size
self.holdout_fraction = holdout_fraction
self.holdout_size = int(population_size * holdout_fraction)
self.holdout_…How to Hash Passwords with bcrypt in Python
Hash a plaintext password with bcrypt using a randomly generated salt, then verify a plaintext attempt against the stored hash.
import bcrypt
def hash_password(password: str) -> str:
"""Hash a password using bcrypt with a generated salt."""
salt = bcrypt.gensalt()
return bcrypt.hashpw(password.encode("utf-8"), salt).decode("utf-8")
def check_password(password: str, hashed: str) -> bool:
"""Verify a plaintext password against …Generate a docker-compose.yml with mock services in Python
Build a docker-compose.yml string from a Python dict of service names and images, then write it to a file.
import yaml
from pathlib import Path
def generate_mock_compose(services: dict) -> str:
compose = {
"version": "3.9",
"services": {}
}
for name, image in services.items():
compose["services"][name] = {
"image": image,
"container_name": f"mock-{name}",
…How to Generate a Kubernetes Deployment Manifest in Python
Generate a Kubernetes Deployment manifest as YAML from a Python dictionary using PyYAML.
import yaml
deployment = {
"apiVersion": "apps/v1",
"kind": "Deployment",
"metadata": {
"name": "mock-app",
"labels": {"app": "mock-app"}
},
"spec": {
"replicas": 3,
"selector": {
"matchLabels": {"app": "mock-app"}
},
"template": {
…How to Merge Helm Chart Values Per Environment in Python
Merge default Helm chart values with environment-specific overrides using a recursive dictionary merge function, then write each environment's YAML file.
from pathlib import Path
import json
import tempfile
DEFAULT_VALUES = {
"image": "nginx:latest",
"replicas": 1,
"resources": {"cpu": "100m", "memory": "128Mi"},
}
ENV_OVERRIDES = {
"dev": {"replicas": 1, "resources": {"cpu": "50m"}},
"staging": {"replicas": 2, "resources": {"cpu": "250m", "memor…How to mock Kustomize overlay patches in Python
Simulate Kustomize overlay behavior by deep-merging a base Kubernetes manifest with a patch dictionary in pure Python.
import json
SOURCE = {
"apiVersion": "apps/v1",
"kind": "Deployment",
"metadata": {"name": "app", "namespace": "prod"},
"spec": {
"replicas": 3,
"template": {
"spec": {
"containers": [{"name": "app", "image": "nginx:1.19"}]
}
}
}
}
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