Reference library

Python Code Samples

Medium snippets you can copy, study, and run in the browser editor.

3 matches
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…
13 0 Open
ML engineering pipelines medium

How to Mock ROC AUC in Python

Compute ROC AUC from scratch in Python using pairwise comparisons between positive and negative score distributions, ideal for testing ML models without sklearn.

machine-learning model-evaluation auc
Python 
import random
from math import comb


def mock_roc_auc(scores, labels):
    """Compute mock ROC AUC by simulating a classifier's score distribution."""
    random.seed(42)
    n = len(labels)
    pos_scores = [scores[i] for i in range(n) if labels[i] == 1]
    neg_scores = [scores[i] for i in range(n) if labels[i] == …
12 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,…
13 0 Open

Browse by section

Each section groups closely related Python snippets.

Guide: free Python code samples library

Copy-ready Python snippets for learners and developers

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.

How to use this library

  1. Pick a topic section — strings, lists, files, functions, and more
  2. Open a sample, read How it works, and copy the code block
  3. Run it in the IDE, tweak values, then take a related quiz or tutorial lesson

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.

Related coding tools

Free online Python IDE Write and run Python in your browser — no install. Free Python code formatter Format with autopep8 — side-by-side PEP 8 cleanup.