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Python Code Samples

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97 matches
Caching & Redis easy

How to Use lru_cache in Python for Cache-on-Miss Population

Demonstrates lru_cache to automatically populate cache on a miss and serve subsequent calls from cache, with cache info stats.

lru_cache caching functools
Python
from functools import lru_cache

@lru_cache(maxsize=None)
def fetch_user(user_id):
    """Simulates a slow database fetch."""
    print(f"Cache miss: fetching user {user_id} from database")
    return {"id": user_id, "name": f"User {user_id}"}

if __name__ == "__main__":
    user = fetch_user(1)
    print(f"First call…
15 0 Open
Reliability & rate limiting easy

How to Implement Message Visibility Timeout Renewal in Python

Simulate queue message visibility control with timeout renewal using a simple Python class that tracks received time and visibility state.

visibility-timeout queue sqs
Python
import time
import uuid

class Message:
    def __init__(self, body, visibility_timeout=30):
        self.body = body
        self.visibility_timeout = visibility_timeout
        self.receipt_handle = str(uuid.uuid4())
        self.received_at = time.time()
        self.deleted = False

    def is_visible(self):
     …
14 0 Open
Reliability & rate limiting easy

How to Mock a Try Confirm Cancel Pattern in Python

Define a simple class with confirm and cancel methods, execute a try confirm with error handling, and print the final state.

try-except mock class
Python
class TCC:
    def __init__(self):
        self.confirmed = False
        self.cancelled = False

    def confirm(self):
        self.confirmed = True
        return "confirmed"

    def cancel(self):
        self.cancelled = True
        return "cancelled"

    def try_confirm(self):
        try:
            result =…
13 0 Open
Observability & SRE easy

How to Calculate Apdex Score from Latency Data in Python

Generate simulated latency samples and compute the Apdex score to gauge user satisfaction with an application's performance.

apdex latency observability
Python
import random
import statistics

def generate_latencies(count=100, base=100, stddev=30):
    return [max(0, random.gauss(base, stddev)) for _ in range(count)]

def apdex(latencies, threshold=200):
    satisfied = sum(1 for lat in latencies if lat < threshold)
    tolerating = sum(1 for lat in latencies if lat >= thres…
15 0 Open
Observability & SRE easy

How to Calculate Percentile Latency in Python

Generate mock latency samples with occasional spikes and compute 50th, 90th, 95th, and 99th percentile values in milliseconds.

percentile latency slo
Python
import random
import statistics

def generate_latency_samples(n=1000):
    """Generate realistic mock latency data (ms) with occasional spikes."""
    samples = []
    for _ in range(n):
        # Normal case: ~50ms with jitter
        base = random.gauss(50, 5)
        # 2% spike chance: slow downstream or GC pause
 …
14 0 Open
Observability & SRE easy

How to Check Service Readiness Dependencies in Python

This code simulates a readiness check for external dependencies (database, cache, queue) with mock availability data and reports readiness status.

readiness dependencies health-check
Python
import sys
from datetime import datetime


def check_dependencies(config):
    results = []
    for dep, required in config.items():
        available = mock_availability(dep)
        status = "READY" if available >= required else "NOT READY"
        results.append((dep, available, required, status))
    return result…
11 0 Open
Observability & SRE easy

How to Create a Deep Health Check Database in Python

Setup a SQLite-backed health check database, insert mock data with response times and statuses, and generate a report ordered by most recent check.

sqlite health-check database
Python
import sqlite3
from datetime import datetime, timedelta
from pathlib import Path

DB_PATH = Path("deep_health_check.db")


def setup_database():
    conn = sqlite3.connect(DB_PATH)
    cursor = conn.cursor()
    cursor.execute("""
        CREATE TABLE IF NOT EXISTS health_checks (
            id INTEGER PRIMARY KEY AU…
14 0 Open
Observability & SRE easy

How to Generate and Propagate W3C Trace Context Headers in Python

Generate and propagate W3C traceparent and tracestate headers for distributed tracing in Python, with mock service headers.

observability tracing w3c
Python
import uuid


def generate_w3c_traceparent(trace_id=None, parent_id=None, flags="01"):
    if trace_id is None:
        trace_id = uuid.uuid4().hex[:32]
    if parent_id is None:
        parent_id = uuid.uuid4().hex[:16]
    return f"00-{trace_id}-{parent_id}-{flags}"


def create_mock_headers(service_name, trace_id=N…
14 0 Open
Observability & SRE easy

How to Ship Logs to an Aggregator Endpoint in Python

Ship batched log entries to a mock HTTP aggregator endpoint with proper error handling and response status.

logging requests json
Python
import json
import requests
from datetime import datetime, timezone

LOG_ENTRIES = [
    {"timestamp": "2024-01-15T10:00:00Z", "level": "INFO", "message": "Server started"},
    {"timestamp": "2024-01-15T10:00:05Z", "level": "WARN", "message": "High memory usage"},
    {"timestamp": "2024-01-15T10:00:10Z", "level": "E…
13 0 Open
Microservices patterns easy

How to Mock Eventual Consistency UI Notes in Python

Simulates a UI note that shows local state until a pending server update is confirmed, mocking eventual consistency behavior in distributed systems.

eventual-consistency microservices ui
Python
class EventualConsistencyNote:
    def __init__(self, entity_id, note):
        self.entity_id = entity_id
        self.note = note
        self.confirmed = False
        self.pending_updates = []

    def add_pending_update(self, update):
        self.pending_updates.append(update)

    def confirm_update(self):
    …
17 0 Open
ML engineering pipelines easy

How to Impute Missing Values with Mean in Python

Replace None values in a list with the mean of the existing values using Python's statistics module.

imputation missing-data statistics
Python
import statistics
from statistics import mean


def impute_mean(values):
    """Replace None with the mean of the non-None values."""
    # Filter out None to compute the mean of existing values
    valid = [v for v in values if v is not None]
    if not valid:
        return values  # nothing to impute if all are Non…
14 0 Open
ML engineering pipelines easy

How to Mock train_test_split in Python for Unit Testing

Build a lightweight mock of sklearn's train_test_split to unit test ML pipeline code without needing the full library or deterministic random state.

train_test_split mock unit-testing
Python
import numpy as np
from sklearn.model_selection import train_test_split
from unittest.mock import patch

def mock_train_test_split(X, y, test_size=0.25, random_state=None, **kwargs):
    """A simple mock implementation of train_test_split."""
    n_samples = len(X)
    n_test = int(n_samples * test_size)
    n_train =…
12 0 Open
ML engineering pipelines easy

How to Save and Load PyTorch Model State Dict in Python

This code demonstrates how to save a PyTorch model's state dict to a file and load it back into a new model instance, verifying weights match.

pytorch state-dict model
Python
import torch
import torch.nn as nn

class SimpleNet(nn.Module):
    def __init__(self):
        super().__init__()
        self.fc1 = nn.Linear(4, 8)
        self.fc2 = nn.Linear(8, 2)

    def forward(self, x):
        x = torch.relu(self.fc1(x))
        return self.fc2(x)

if __name__ == "__main__":
    model = Simp…
13 0 Open
A/B testing & experimentation easy

Bonferroni Correction in Python

Applies the Bonferroni correction to a list of p-values to control the family-wise error rate when performing multiple comparisons.

statistics p-values multiple-comparisons
Python
import numpy as np

def bonferroni_correction(p_values, alpha=0.05):
    """Apply Bonferroni correction to a list of p-values."""
    n = len(p_values)
    corrected_alpha = alpha / n
    significant = [p < corrected_alpha for p in p_values]
    return corrected_alpha, significant

if __name__ == "__main__":
    # Moc…
17 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
A/B testing & experimentation easy

How to Build a Guardrail Metrics Monitor in Python

This code implements a mock monitor that records metric values, checks them against thresholds, and summarizes pass/alert statistics.

metrics monitoring ab-testing
Python
import random
import time
from collections import defaultdict


class GuardrailMetricsMonitor:
    def __init__(self):
        self.metrics = defaultdict(list)
        self.thresholds = {
            "prompt_toxicity": 0.8,
            "response_length": 500,
            "latency_ms": 1000,
        }

    def record(s…
15 0 Open
A/B testing & experimentation easy

How to Calculate Minimum Sample Size for a T-Test in Python

Compute the minimum sample size per group for a two-sample t-test using effect size, significance level, and statistical power.

sample-size statistics ab-testing
Python
import math
from scipy.stats import norm


def min_sample_size(effect_size, alpha=0.05, power=0.8):
    """
    Calculate minimum sample size for a two-sample t-test (equal groups).

    Args:
        effect_size: Cohen's d (standardized mean difference)
        alpha: significance level (Type I error)
        power: …
15 0 Open
A/B testing & experimentation easy

How to Calculate Secondary Metrics in Python

Computes distribution, variability, and spread of a numeric dataset using Python's statistics and collections modules.

statistics data-analysis metrics
Python
import random
import statistics
from collections import Counter

def explore_secondary_metrics(data):
    """Calculate secondary metrics: distribution, variability, and spread."""
    if not data:
        return "No data provided"
    
    total = sum(data)
    mean = statistics.mean(data)
    median = statistics.medi…
16 0 Open
A/B testing & experimentation easy

How to Mock a Confidence Interval for a Proportion in Python

Simulate a Bernoulli sample and compute a 95% confidence interval for a proportion using the normal approximation in Python.

confidence-interval simulation statistics
Python
import random
import math

def mock_ci(n=100, p_true=0.5, z=1.96, seed=42):
    """Simulate a sample proportion and compute its 95% confidence interval."""
    random.seed(seed)
    successes = sum(1 for _ in range(n) if random.random() < p_true)
    p_hat = successes / n
    se = math.sqrt(p_hat * (1 - p_hat) / n)
  …
15 0 Open
Database scaling & optimization easy

How to Mock Replica Lag Monitoring in Python

Simulates database replica lag with a mock monitor class that generates realistic lag metrics and health statuses.

replica-lag monitoring simulation
Python
import time
import random
from datetime import datetime, timedelta

class MockReplicaLagMonitor:
    def __init__(self, replicas=3, base_lag=0.5, jitter=0.2):
        self.replicas = [f"replica-{i}" for i in range(replicas)]
        self.base_lag = base_lag
        self.jitter = jitter
        self.last_write = dateti…
13 0 Open
Production deployment patterns easy

How to Build a Synthetic Monitor Mock in Python

Simulates a synthetic monitoring system in Python that collects latency samples, averages them, and reports service status as UP or DEGRADED.

monitoring dataclass simulation
Python
import random
import time
from dataclasses import dataclass, field
from statistics import mean


@dataclass
class SyntheticMonitor:
    service: str
    endpoint: str
    latency_ms: list[float] = field(default_factory=list)

    def check(self) -> float:
        latency = random.uniform(50.0, 250.0)
        self.late…
13 0 Open
Production deployment patterns easy

How to Create a Liveness Probe HTTP Mock in Python

Build a lightweight HTTP server in Python that mimics a Kubernetes-style liveness endpoint, returning JSON health status for local testing.

http healthcheck mock-server
Python
import http.server
import threading
import time


class LivenessHandler(http.server.BaseHTTPRequestHandler):
    def do_GET(self):
        if self.path == "/healthz":
            self.send_response(200)
            self.send_header("Content-Type", "application/json")
            self.end_headers()
            self.wfi…
15 0 Open
Production deployment patterns easy

How to Mock Docker Image Non-Root User in Python

This Python class simulates Docker image layers and inspects whether the final user is a non-root user, returning UID, GID, and security status.

docker security mock
Python
from pathlib import Path


class DockerImageMock:
    def __init__(self, name, tag):
        self.name = name
        self.tag = tag
        self.layers = []
        self.user = "root"

    def add_file(self, path, content):
        self.layers.append({"file": path, "content": content})

    def set_user(self, usernam…
11 0 Open
Production deployment patterns easy

How to Simulate a Packer AMI Build in Python

A simple Python class that mimics a Packer AMI build lifecycle — creates a build object, transitions its state to completed, and prints a JSON snapshot.

packer ami mock
Python
import json


class PackerBuildMock:
    def __init__(self, name, ami_id, region="us-east-1", state="pending"):
        self.name = name
        self.ami_id = ami_id
        self.region = region
        self.state = state

    def build(self):
        if self.state == "pending":
            self.state = "completed"
  …
13 0 Open

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