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How to Implement a Weighted DNS Resolver with Failover in Python
Simulates a weighted DNS load balancer that distributes traffic across IPs by weight and automatically fails over when a server is marked unhealthy.
import random
import time
class WeightedDNSResolver:
def __init__(self, records):
self.records = records # list of (ip, weight)
self.total_weight = sum(weight for _, weight in records)
self.failed_ips = set()
def resolve(self):
available = [(ip, weight) for ip, weight in self…How to Mock a Kafka Rebalance Listener in Python
Simulate Kafka consumer rebalance callbacks (on_partitions_revoked and on_partitions_assigned) with a mock consumer to test listener logic.
import time
from collections import defaultdict
class MockKafkaConsumer:
def __init__(self):
self.assignments = defaultdict(list)
self.rebalances = 0
def assign(self, partitions):
self.rebalances += 1
self.assignments.clear()
for partition in partitions:
s…Check Covariate Balance in Python
Compute standardized mean differences and KS tests to check covariate balance between treatment and control groups in Python.
import numpy as np
from scipy import stats
def balance_check(treatment, covariate):
"""Check covariate balance between treatment and control groups."""
treat_vals = covariate[treatment == 1]
control_vals = covariate[treatment == 0]
# Standardized mean difference
pooled_std = np.sqrt((np.var(t…Epsilon Greedy Bandit Mock in Python
A simple epsilon-greedy multi-armed bandit simulation that balances exploration and exploitation to estimate true means of several Bernoulli-like reward distributions.
import random
class Bandit:
def __init__(self, true_mean):
self.true_mean = true_mean
self.estimated_mean = 0.0
self.n_pulls = 0
def pull(self):
return random.gauss(self.true_mean, 1.0)
def update(self, reward):
self.n_pulls += 1
self.estimated_mean += (r…How to Generate an Orthogonal Array for A/B Testing in Python
Generate a mock orthogonal array for multi-layer experiments with NumPy, ensuring balanced level combinations across experiment groups.
import numpy as np
def orthogonal_mock_layers(n_experiments: int, n_layers: int, n_levels: int) -> np.ndarray:
"""Generate an orthogonal array for multi-layer experiment design using base-level logic."""
ortho = np.indices((n_levels,) * n_layers).reshape(n_layers, -1).T
ortho = ortho % n_levels # Classic…Consistent Hashing with Virtual Buckets in Python
This code maps many virtual buckets onto a few physical buckets using a consistent hashing ring, ensuring balanced distribution with minimal remapping when physical buckets change.
import random
class VirtualBuckets:
"""Maps many virtual buckets onto few physical buckets using consistent hashing."""
def __init__(self, physical_buckets, virtual_factor=100):
self.physical = list(physical_buckets)
self.virtual_factor = virtual_factor
self.ring = []
self…Browse by section
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