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How to mock SLI availability success ratio in Python
Simulate request outcomes with deterministic randomness and compute the SLI availability success ratio to check if a target is met.
import random
from collections import defaultdict
def mock_availability(num_requests=1000, target_ratio=0.995):
"""
Simulate request outcomes and compute the SLI availability success ratio.
Args:
num_requests: Total number of requests to simulate
target_ratio: Target availability rati…How to Mock a Server-Side Load Balancer in Python
A simple Python class that mimics a server-side load balancer with round-robin, random, and least-connections selection strategies.
import itertools
import random
class LoadBalancer:
def __init__(self, servers=None):
self.servers = servers if servers else ["server1", "server2", "server3"]
self.counter = itertools.count(1)
def round_robin(self):
return next(self.counter) % len(self.servers)
def random_selectio…How to Shuffle Items by Group in Python
Randomly shuffle items within each group while keeping groups contiguous, using a seed for reproducible results.
import random
def shuffle_sort_groups(items, group_key, seed=None):
"""Randomize order within groups, keeping groups contiguous."""
rng = random.Random(seed)
groups = {}
for item in items:
key = group_key(item)
groups.setdefault(key, []).append(item)
result = []
for k…Build a Mock Random Forest Classifier in Python
Create a simple random-forest-like classifier with random majority voting between trees, including fit, predict, and predict_proba methods.
import random
class MockRandomForest:
def __init__(self, n_trees=10, random_state=42):
self.n_trees = n_trees
self.random_state = random_state
self.classes_ = None
self._class_counts = None
random.seed(random_state)
def fit(self, X, y):
self.classes_ = sorted(…How to Do Random Search for Hyperparameter Tuning in Python
A mock random search that samples hyperparameter combinations from a grid and ranks them by a dummy score, with a reproducible seed.
import random
# Mock random search over a small hyperparameter grid
param_grid = {
"learning_rate": [0.001, 0.01, 0.1],
"batch_size": [16, 32, 64],
"num_layers": [1, 2, 3]
}
def random_search(grid, n_iter=5, seed=42):
"""Perform random search over a hyperparameter grid."""
random.seed(seed)
k…How to Generate Experiment Tracking Run IDs in Python
Generate unique experiment run IDs with timestamps and random suffixes for tracking ML pipeline executions.
import random
import string
import time
def generate_run_id(prefix="exp"):
timestamp = time.strftime("%Y%m%d_%H%M%S")
suffix = "".join(random.choices(string.ascii_lowercase + string.digits, k=6))
return f"{prefix}_{timestamp}_{suffix}"
if __name__ == "__main__":
# Simulate tracking three experiment r…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…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.
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 =…How to implement a canary traffic split in Python
Route incoming traffic between stable and canary model or service versions using a weight-based random split with deterministic testing.
import random
def canary_route(service_name: str, canary_weight: float = 0.2) -> str:
"""Route traffic between stable and canary versions based on weight."""
rng = random.Random(42) # deterministic for reproducible demo
if rng.random() < canary_weight:
return f"{service_name}-canary"
return …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 Do Random Assignment in Python for A/B Tests
Assign each item to a binary group (0 or 1) with uniform probability using a small reusable function, optionally weighted, for A/B testing mocks.
import random
def random_assignment_uniform_mock(items, weights=None):
"""Assign each item to a group (0 or 1) with uniform probability."""
if weights is None:
# Default: each item independently gets 0 or 1 with 50% probability
return [random.randint(0, 1) for _ in items]
# Optional weight…How to Mock Stratified Assignment by Segment in Python
Simulate stratified assignment for A/B experiments by sampling a fixed proportion of units from each segment, with deterministic seeds for reproducibility.
import random
def stratified_assignment(segments, seed=None):
"""
Mock stratified assignment: given a dict of segment -> population size,
return a dict of segment -> sampled unit ids (deterministic with seed).
"""
if seed is not None:
random.seed(seed)
rng = random.Random(seed)
res…How to create a global control holdout group in Python
This code implements a deterministic global control holdout group, randomly selecting a fraction of users to be excluded from feature rollouts for experiment validation.
import random
class GlobalControl:
def __init__(self, population_size, holdout_fraction=0.2, seed=42):
random.seed(seed)
self.population_size = population_size
self.holdout_fraction = holdout_fraction
self.holdout_size = int(population_size * holdout_fraction)
self.holdout_…Simulate a Ramp Rollout Percentage in Python
Simulates a percentage-based ramp rollout with deterministic seeding, returning success/failure/in-progress counts for a mock user population.
import random
from enum import Enum
class RolloutStatus(Enum):
SUCCESS = "success"
FAILED = "failed"
IN_PROGRESS = "in_progress"
def simulate_ramp_rollout(total_users: int, percentage: int, seed: int = 42) -> dict:
"""
Simulates a mock ramp rollout for a given percentage of users.
Returns sta…Monitor Database Index Bloat in Python
Simulates index bloat checks for database tables using random ratio thresholds and reports alerts per index.
import random
import time
class IndexBloatMonitor:
def __init__(self, thresholds=(0.5, 0.8, 0.9)):
self.thresholds = thresholds
self.indices = {
"users_pk": 48.2,
"orders_created_idx": 124.7,
"products_name_idx": 15.3,
"payments_user_idx": 203.9,
…How to Hash Passwords Securely in Python
Hash passwords with PBKDF2, random salts, and constant pepper, plus generate secure API keys using Python's stdlib.
import hashlib
import secrets
import time
import hmac
def hash_password(password: str, salt: str = None, pepper: str = "static-pepper") -> dict:
"""Hash a password with a random salt and constant pepper."""
if salt is None:
salt = secrets.token_hex(16)
salted = f"{pepper}{salt}{password}"
dig…How to Hash Passwords with bcrypt in Python
Hash a plaintext password with bcrypt using a randomly generated salt, then verify a plaintext attempt against the stored hash.
import bcrypt
def hash_password(password: str) -> str:
"""Hash a password using bcrypt with a generated salt."""
salt = bcrypt.gensalt()
return bcrypt.hashpw(password.encode("utf-8"), salt).decode("utf-8")
def check_password(password: str, hashed: str) -> bool:
"""Verify a plaintext password against …How to Salt Passwords per User in Python
Hash each user's password with a unique random salt using hashlib, and verify logins with timing-safe comparison.
import hashlib
import secrets
def hash_password(password: str, salt: str | None = None) -> tuple[str, str]:
"""Hash a password with a random salt (or provided salt).
Returns:
(salt_hex, password_hash_hex)
"""
if salt is None:
salt = secrets.token_hex(16)
salted = (salt + password)…How to Implement a Manual Approval Gate Mock in Python
Simulates a manual approval workflow with threshold-based rules, random decisions for medium amounts, and logs each result with timing.
import random
import time
def approve_request(amount: float) -> bool:
if amount <= 1000:
return True
if amount <= 5000:
return random.random() < 0.7
return False
def main():
requests = [500, 1200, 7500, 3000, 50]
for amount in requests:
start = time.perf_counter()
…How to Mock a CI Pipeline with Build, Test, and Deploy Stages in Python
Simulate a three-stage CI pipeline (build, test, deploy) in Python with random pass/fail logic, early exit on failure, and measured stage durations.
import time
import random
from dataclasses import dataclass
@dataclass
class StageResult:
name: str
status: str
duration: float
def run_stage(name: str, success_chance: float = 0.9) -> StageResult:
"""Simulate a pipeline stage with random success/failure."""
start = time.time()
time.sleep(r…Browse by section
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