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Python Code Samples

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

81 matches
Big data & Spark easy

Compaction Small Files Mock in Python

Simulates a small-files compaction job by creating small mock files and merging them into a single output file using Python's standard library.

compaction file-io mock
Python
from pathlib import Path
import tempfile
import os


def create_small_files(directory: Path, file_count: int = 5, lines_per_file: int = 3):
    """Create several small mock files with sample content."""
    directory.mkdir(exist_ok=True)
    for i in range(file_count):
        file_path = directory / f"part-{i:04d}.tx…
18 0 Open
Big data & Spark easy

How to Broadcast a Small Lookup Table in Python

Simulates broadcasting a small lookup table by iterating key-value pairs and emitting packed rows to subscribers with deterministic output.

broadcast lookup-table dictionary
Python
import random

# Generate a deterministic mock broadcast of a small lookup table
# with 5 keys and random integer values (seeded for reproducibility)

data = {
    "sensor_a": 22,
    "sensor_b": 87,
    "sensor_c": 43,
    "sensor_d": 65,
    "sensor_e": 31,
}

# Simulate a broadcast to subscribers by iterating and p…
14 0 Open
ML engineering pipelines easy

How to Compute a Confusion Matrix in Python

Compute a multi-class confusion matrix from true and predicted labels using pure Python dictionaries and nested lists, then format it for readable output.

confusion-matrix classification ml-metrics
Python
from collections import defaultdict

def compute_confusion_matrix(y_true, y_pred, labels):
    """Compute confusion matrix using Python dicts and nested lists."""
    label_index = {label: i for i, label in enumerate(labels)}
    matrix = [[0] * len(labels) for _ in range(len(labels))]
    
    for true, pred in zip(y…
14 0 Open
ML engineering pipelines medium

How to Mock Kedro Pipeline Nodes in Python

Create a modular Kedro pipeline with node functions, namespacing, and input/output mapping to mock pipeline execution locally.

kedro pipeline modular
Python
from kedro.pipeline import Pipeline, node
from kedro.pipeline.modular_pipeline import pipeline as modular_pipeline


def preprocess(data: list) -> list:
    """Clean data by removing None values."""
    return [item for item in data if item is not None]


def transform(data: list) -> list:
    """Add 1 to each numeric…
15 0 Open
ML engineering pipelines easy

How to Mock Shadow Mode Inference in Python

Simulates running multiple candidate models in shadow mode by adding randomized delays and returning their outputs alongside a primary model's output.

ml-pipeline shadow-mode simulation
Python
import random
import time


def shadow_mode_inference(candidates, mock_delay=0.1):
    """
    Simulates running multiple candidate models in 'shadow mode'
    by adding tiny randomized delays and returning their outputs
    alongside the primary model's output.
    """
    primary_output = "primary: answer"
    shado…
13 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…
16 0 Open
A/B testing & experimentation easy

Generate a Mock Multi-Armed Bandit Report in Python

Simulate a multi-armed bandit experiment with random pulls and rewards, then output a JSON report with per-arm statistics.

bandit simulation random
Python
import random
import json

def generate_mock_bandit_report(num_arms=5, num_rounds=100, seed=42):
    random.seed(seed)
    arms = ["A", "B", "C", "D", "E"][:num_arms]
    true_means = {arm: random.uniform(0.3, 0.7) for arm in arms}
    pulls = {arm: 0 for arm in arms}
    rewards = {arm: 0 for arm in arms}

    for _ …
16 0 Open
Production deployment patterns easy

How to Mock a GitHub Actions Workflow in Python

Build a dataclass-based model of a GitHub Actions workflow and simulate its execution to validate steps and outputs before deployment.

github-actions dataclasses mock
Python
import json
from dataclasses import dataclass, asdict
from typing import List, Dict, Any


@dataclass
class Step:
    name: str
    run: str


@dataclass
class Job:
    name: str
    steps: List[Step]
    runs_on: str = "ubuntu-latest"


@dataclass
class Workflow:
    name: str
    jobs: List[Job]

    def to_github_a…
13 0 Open
Production deployment patterns easy

How to simulate GitLab CI stages in Python

Build a lightweight Python mock of GitLab CI pipeline stages to test job sequencing and output locally.

gitlab ci simulation
Python
def mock_gitlab_ci_stages():
    stages = ["build", "test", "deploy"]
    stage_status = {}

    for stage in stages:
        jobs = []

        if stage == "build":
            jobs = ["compile", "package"]
        elif stage == "test":
            jobs = ["unit", "integration", "e2e"]
        elif stage == "deploy":…
14 0 Open

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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.