Reference library

Python Code Samples

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

4 matches
Strings & text easy

How to Truncate a String with Ellipsis in Python

A function that shortens text to a maximum length and appends an ellipsis when truncation occurs, handling edge cases.

strings truncation text-processing
Python
def truncate_with_ellipsis(text: str, max_length: int) -> str:
    """Truncate text to max_length, appending ellipsis if truncated."""
    if len(text) <= max_length:
        return text
    if max_length <= 3:
        return text[:max_length]
    return text[: max_length - 3] + "..."

if __name__ == "__main__":
    t…
11 0 Open
ML engineering pipelines medium

How to Detect Data Drift with PSI in Python

Calculate the Population Stability Index (PSI) in Python to compare expected vs actual distributions and detect data drift in machine learning pipelines.

data drift psi monitoring
Python
import numpy as np

def calculate_psi(expected, actual, buckets=10):
    """Calculate Population Stability Index (PSI) between two distributions."""
    # Create bucket edges based on expected distribution percentiles
    edges = np.percentile(expected, np.linspace(0, 100, buckets + 1))
    edges[-1] = np.inf  # Ensur…
13 0 Open
A/B testing & experimentation medium

Epsilon Greedy Bandit Mock in Python

A simple epsilon-greedy multi-armed bandit simulation that balances exploration and exploitation to estimate true means of several Bernoulli-like reward distributions.

bandit epsilon-greedy exploration
Python
import random


class Bandit:
    def __init__(self, true_mean):
        self.true_mean = true_mean
        self.estimated_mean = 0.0
        self.n_pulls = 0

    def pull(self):
        return random.gauss(self.true_mean, 1.0)

    def update(self, reward):
        self.n_pulls += 1
        self.estimated_mean += (r…
12 0 Open
A/B testing & experimentation medium

How to simulate a contextual bandit in Python

Simulate a contextual multi-armed bandit with random features and epsilon-greedy action selection in Python.

bandit-algorithms simulation epsilon-greedy
Python
import random


class ContextualBandit:
    def __init__(self, n_actions=3, n_features=4):
        self.n_actions = n_actions
        self.n_features = n_features
        self.theta = [random.random() for _ in range(n_actions * n_features)]

    def mock_context(self):
        return [random.uniform(-1, 1) for _ in ra…
13 0 Open

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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.