Reference library

Python Code Samples

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

2 matches
Observability & SRE easy

Generate Synthetic CPU Utilization Metrics in Python

Creates realistic time-series CPU utilization samples with timestamps, noise, and output as structured JSON for observability demos and testing.

observability metrics time-series
Python
from datetime import datetime, timedelta
import random
import json


def generate_metric_samples(base_value, noise, count=60, interval_minutes=1):
    """Generate realistic CPU utilization samples for a given time window."""
    timestamps = []
    values = []

    now = datetime.utcnow()
    start_time = now - timede…
14 0 Open
Observability & SRE easy

Generate Synthetic SRE Metrics and Calculate Availability in Python

Create realistic service metrics with random latency, error rate, and request counts, then compute availability and summarize the stream for SLO checks.

sre synthetic-data metrics
Python
from datetime import datetime, timedelta
import random

def generate_service_metrics(service_name: str, minutes: int = 30) -> list[dict]:
    """Generate synthetic SRE metrics for a service across recent minutes."""
    metrics = []
    now = datetime.now()
    
    for i in range(minutes):
        timestamp = now - t…
14 0 Open

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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.