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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
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.
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…
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.
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…
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.
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…
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.
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…
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.
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…
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…
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.
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 _ …
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.
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…
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.
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":…
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- Open a sample, read How it works, and copy the code block
- 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.