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Python Code Samples

Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.

315 matches
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 easy

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…
15 0 Open
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…
16 0 Open
ML engineering pipelines easy

How to Build a Simple ML Pipeline with ZenML in Python

Build a mock machine learning pipeline with ZenML steps for data loading, training, and evaluation, and run it to print the final accuracy.

zenml ml pipeline
Python
from zenml import pipeline, step


@step
def load_data() -> dict:
    """Simulate loading data from a source."""
    return {"accuracy": 0.0, "loss": 1.0}


@step
def train_model(data: dict) -> dict:
    """Simulate training a model."""
    data["accuracy"] = 0.95
    data["loss"] = 0.1
    return data


@step
def eva…
13 0 Open
ML engineering pipelines medium

How to Build an sklearn Pipeline with ColumnTransformer in Python

A mock example showing how to chain preprocessing and a regression model into a single sklearn Pipeline, scaling numeric features and one-hot encoding categorical features with ColumnTransformer.

sklearn pipeline columntransformer
Python
import numpy as np
from sklearn.compose import ColumnTransformer
from sklearn.preprocessing import StandardScaler, OneHotEncoder
from sklearn.pipeline import Pipeline
from sklearn.linear_model import LinearRegression

# Mock dataset
X = np.array([[1, 'red'], [2, 'blue'], [3, 'red'], [4, 'green'], [5, 'blue']], dtype=o…
14 0 Open
ML engineering pipelines easy

How to Create a Mock Metaflow Flow in Python

Build a minimal Metaflow flow with two sequential steps that pass data between them using instance attributes.

metaflow ml-pipelines workflow
Python
from metaflow import FlowSpec, step, current


class MockFlow(FlowSpec):
    """A minimal Metaflow flow to demonstrate basic steps and branching."""

    @step
    def start(self):
        self.category = "mock"
        print(f"Start step for {self.category} flow")
        self.next(self.process)

    @step
    def pr…
16 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 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…
15 0 Open
ML engineering pipelines easy

How to Mock train_test_split in Python for Unit Testing

Build a lightweight mock of sklearn's train_test_split to unit test ML pipeline code without needing the full library or deterministic random state.

train_test_split mock unit-testing
Python
import numpy as np
from sklearn.model_selection import train_test_split
from unittest.mock import patch

def mock_train_test_split(X, y, test_size=0.25, random_state=None, **kwargs):
    """A simple mock implementation of train_test_split."""
    n_samples = len(X)
    n_test = int(n_samples * test_size)
    n_train =…
13 0 Open
ML engineering pipelines easy

How to Run Batch Predictions with a Mock Model in Python

Build a lightweight mock model class and run predictions across a batch of samples, returning results as a plain Python list.

numpy batch ml
Python
import numpy as np

class MockModel:
    def __init__(self, weights):
        self.weights = np.array(weights)

    def predict(self, X):
        return X @ self.weights

def predict_batch(model, batch):
    """Run predictions for a batch of samples and return results as a list."""
    return model.predict(np.array(ba…
15 0 Open
ML engineering pipelines medium

How to Train a Gradient Boosting Regressor in Python

Build and evaluate a scikit-learn GradientBoostingRegressor on a synthetic dataset, printing test MSE and feature importances.

sklearn gradient-boosting regression
Python
import numpy as np
from sklearn.ensemble import GradientBoostingRegressor
from sklearn.metrics import mean_squared_error

def train_gradient_boosting_mock():
    # Toy regression dataset
    np.random.seed(42)
    X = np.random.rand(100, 3) * 10
    y = 2 * X[:, 0] - 1.5 * X[:, 1] + 0.5 * X[:, 2] + np.random.normal(0,…
14 0 Open
ML engineering pipelines medium

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.

flyte ml-pipeline dataclass
Python
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…
17 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
A/B testing & experimentation easy

How to Build a Guardrail Metrics Monitor in Python

This code implements a mock monitor that records metric values, checks them against thresholds, and summarizes pass/alert statistics.

metrics monitoring ab-testing
Python
import random
import time
from collections import defaultdict


class GuardrailMetricsMonitor:
    def __init__(self):
        self.metrics = defaultdict(list)
        self.thresholds = {
            "prompt_toxicity": 0.8,
            "response_length": 500,
            "latency_ms": 1000,
        }

    def record(s…
16 0 Open
A/B testing & experimentation easy

How to Build a Simple Binary Protocol Parser Mock in Python

Defines a mock binary protocol with field definitions, encoding, and decoding to simulate network packet parsing for A/B testing and experiment setup.

binary protocol mock
Python
class SimpleProtocol:
    def __init__(self, name, version):
        self.name = name
        self.version = version
        self.fields = []

    def add_field(self, field_name, field_size):
        self.fields.append((field_name, field_size))

    def parse(self, data):
        if len(data) != sum(size for _, size i…
12 0 Open
A/B testing & experimentation easy

How to Create a Mock That Returns Inverse Counter Values in Python

Builds a Mock whose side_effect returns the inverse (1/count) of each Counter value, defaulting to 0.0 for unseen keys.

mock counter testing
Python
from collections import Counter
from unittest.mock import Mock

def inverse_mock(counter: Counter) -> Mock:
    """
    Return a Mock that mimics the inverse of a Counter:
    each key returns a value representing the inverse of its count.
    The Mock's side_effect maps keys to their inverse counts.
    """
    mock …
14 0 Open
A/B testing & experimentation medium

How to Simulate Geo Experiments in Python

Build a mock geo experiment simulator with ramp-up/down periods, measuring weekly lift between treatment and control markets.

geo-experiment ab-testing simulation
Python
import random
import math
from dataclasses import dataclass

@dataclass
class GeoMarket:
    name: str
    base_demand: float
    geo_coefficient: float

def simulate_geo_experiment(markets, weeks=12, control_weeks=6):
    """
    Simulates a geo experiment with ramp-up and ramp-down periods.
    Returns weekly lift p…
19 0 Open
Database scaling & optimization medium

Build a Full Text Search Index in Python

Create a simple inverted index for full-text search with the standard library, supporting multi-word AND queries across documents.

search inverted-index text-processing
Python
import re
from collections import defaultdict


class SimpleTextIndex:
    def __init__(self):
        self.index = defaultdict(list)
        self.documents = {}

    def add_document(self, doc_id, text):
        self.documents[doc_id] = text
        words = set(re.findall(r'\w+', text.lower()))
        for word in wo…
14 0 Open
Database scaling & optimization easy

Build a Partial Index Mock in Python for Database Filtering

Simulate a partial database index by filtering keys with a predicate, then return a limited mock lookup dictionary.

partial-index database mock
Python
data = [
    "alpha", "beta", "gamma", "delta", "epsilon",
    "zeta", "eta", "theta", "iota", "kappa"
]

filtered_keys = [item for item in data if len(item) >= 5]

def mock_partial_index(keys, filter_func, limit=3):
    result = {}
    for key in keys:
        if not filter_func(key):
            continue
        res…
15 0 Open
Database scaling & optimization medium

Database Helper in Python with SQLite Scaling Optimization

Build a beginner-friendly SQLite database helper class with WAL, indexed queries, and efficient batch inserts for scaling.

sqlite database scalability
Python
import sqlite3
from contextlib import contextmanager


class DatabaseHelper:
    """Beginner-friendly helper for SQLite database operations with scaling tips."""

    def __init__(self, db_path):
        self.db_path = db_path

    @contextmanager
    def connection(self):
        """Context manager for automatic comm…
15 0 Open
Database scaling & optimization medium

How to Build a Connection Pool Reuse Mock in Python

Build a mock connection pool with context manager to track connection reuse, acquires, and releases in Python.

connection-pool context-manager database
Python
import time
from contextlib import contextmanager


class Connection:
    def __init__(self, name):
        self.name = name
        self.in_use = False
        self.busy_since = None

    def fetch(self):
        return f"data from {self.name}"


class ConnectionPool:
    def __init__(self, size=3):
        self.conn…
14 0 Open
Database scaling & optimization medium

How to Build a Shard Map Mock Dict in Python

Implement a dictionary-like class that distributes keys across multiple shards using Python's hash() for realistic data partitioning.

dict sharding hash
Python
class ShardMap:
    def __init__(self, shard_count):
        self.shards = {i: {} for i in range(shard_count)}
        self.shard_count = shard_count

    def _shard_for(self, key):
        return hash(key) % self.shard_count

    def __getitem__(self, key):
        return self.shards[self._shard_for(key)][key]

    d…
16 0 Open
Database scaling & optimization easy

How to Create a Data Helper Class in Python for JSON Files

Build a beginner-friendly Python helper class to read, write, filter, and summarize JSON data files with clean, reusable methods.

json data-helper file-io
Python
import json
from pathlib import Path


class DataHelper:
    """Simple beginner-friendly helper for reading and writing JSON data files."""

    @staticmethod
    def read_json(filename):
        file_path = Path(filename)
        if file_path.exists():
            with file_path.open("r", encoding="utf-8") as f:
    …
14 0 Open

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PythonSkillset code samples are short, focused examples organised by topic and difficulty. Every snippet is server-rendered HTML — readable by search engines and easy to copy. Open any sample, read the notes, copy the code, then press Try in editor to run it in the browser with Pyodide.

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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.