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How to Use the Adapter Pattern to Mock a Legacy System in Python
This code demonstrates the Adapter pattern, allowing a modern interface to interact with a legacy system by wrapping its outdated method.
class LegacySystem:
def legacy_method(self, data):
return f"Legacy processed: {data}"
class ModernInterface:
def process(self, data):
raise NotImplementedError
class Adapter(ModernInterface):
def __init__(self, legacy):
self.legacy = legacy
def process(self, data):
re…
How to implement read-your-writes sticky routing in Python
A mock StickyRouter class that routes all requests for the same key to the same node, ensuring read-after-write consistency.
import random
class StickyRouter:
def __init__(self, nodes):
self.nodes = nodes
self.routes = {}
def route(self, key):
if key not in self.routes:
self.routes[key] = random.choice(self.nodes)
return self.routes[key]
def read(self, key):
node = self.rout…
How to implement round-robin load balancing in Python
Implement a client-side round-robin load balancer that distributes requests sequentially across a list of mock servers using itertools.cycle.
import itertools
import random
class MockServer:
def __init__(self, name):
self.name = name
def handle_request(self, request_id):
return f"Server {self.name} handled request #{request_id}"
class RoundRobinLoadBalancer:
def __init__(self, servers):
self.servers = servers
…
How to mock a SPIFFE workload identity in Python
Generate a mock SPIFFE ID and token for a workload using a trust domain, namespace, and service account.
import hashlib
import json
from dataclasses import dataclass, asdict
@dataclass
class SPIFFEIdentity:
trust_domain: str
namespace: str
service_account: str
@property
def id(self) -> str:
return f"spiffe://{self.trust_domain}/ns/{self.namespace}/sa/{self.service_account}"
def mock_workl…
How to mock an external service in Python with an anti-corruption facade
This code implements an anti-corruption facade that mocks an external API, allowing client code to interact with a simulated service while keeping the same interface.
class AntiCorruptionFacade:
"""Mocks a real API while keeping the same interface."""
def __init__(self, data_store):
self._data_store = data_store
self._calls = []
def get_user(self, user_id):
self._calls.append(f"get_user({user_id})")
return self._data_store.get(u…
Idempotent Consumer Event Processing in Python
Track processed event IDs to skip duplicates and count event types for a reliable, idempotent consumer.
import json
from collections import defaultdict
class EventProcessor:
def __init__(self):
self.processed_ids = set()
self.counts = defaultdict(int)
def process_event(self, event):
event_id = event["id"]
if event_id in self.processed_ids:
return {"status": "skipped"…
Mock a Sidecar Logger with Python Metrics
Simulate a sidecar logger that tracks request counts, error rates, and endpoint hits, producing a metrics snapshot.
import random
import time
from collections import defaultdict
class SidecarLogger:
def __init__(self):
self.metrics = defaultdict(int)
self.total_requests = 0
self.error_count = 0
def log_request(self, endpoint, status_code):
"""Simulate logging a request and updating metrics…
Scatter Gather Aggregate Pattern in Python
Simulates a scatter/gather/aggregate pattern by distributing work across items, gathering results, and aggregating them.
import random
def process_items(items, scatter_fn, gather_fn, aggregate_fn):
"""Simple scatter/gather/aggregate pattern simulation."""
scattered = [scatter_fn(item) for item in items]
gathered = [gather_fn(item) for item in scattered]
return aggregate_fn(gathered)
if __name__ == "__main__":
data …
Strangler Fig Migration Pattern in Python
Gradually reroute calls from a legacy service to a modern replacement using a runtime switch and feature detection.
from dataclasses import dataclass
@dataclass
class PaymentService:
def process(self, amount: float) -> str:
return f"Legacy processed ${amount:.2f}"
class StranglerFig:
def __init__(self):
self._new_service = None
def attach_new(self, service):
self._new_service = service
de…
How to Use Broadcast Variables as Read-Only in PySpark (Mock Example)
Share a lookup dict across Spark executors with a broadcast variable and verify its read-only behavior in a local mock.
from pyspark import SparkContext, SparkConf
def main():
conf = SparkConf().setAppName("BroadcastMock").setMaster("local[2]")
sc = SparkContext(conf=conf)
lookup = {"a": 1, "b": 2, "c": 3}
broadcast_lookup = sc.broadcast(lookup)
data = ["a", "b", "c", "a", "unknown"]
rdd = sc.parallel…
How to Run Batch Predictions with a Mock Model in Python
Build a lightweight mock model class and run predictions across a batch of samples, returning results as a plain Python list.
import numpy as np
class MockModel:
def __init__(self, weights):
self.weights = np.array(weights)
def predict(self, X):
return X @ self.weights
def predict_batch(model, batch):
"""Run predictions for a batch of samples and return results as a list."""
return model.predict(np.array(ba…
How to do feature selection with VarianceThreshold in Python
This code demonstrates how to use scikit-learn's VarianceThreshold to remove low-variance features from a NumPy array, keeping only those that vary enough to be useful for modeling.
import numpy as np
from sklearn.feature_selection import VarianceThreshold
def main():
# Mock dataset: 4 samples, 5 features
X = np.array([
[0.1, 0.2, 1.0, 1.0, 0.5],
[0.2, 0.2, 0.0, 1.0, 0.4],
[0.1, 0.2, 1.0, 1.0, 0.6],
[0.3, 0.2, 1.0, 0.0, 0.5]
])
# Select features w…
How to Create a Mock That Returns Inverse Counter Values in Python
Builds a Mock whose side_effect returns the inverse (1/count) of each Counter value, defaulting to 0.0 for unseen keys.
from collections import Counter
from unittest.mock import Mock
def inverse_mock(counter: Counter) -> Mock:
"""
Return a Mock that mimics the inverse of a Counter:
each key returns a value representing the inverse of its count.
The Mock's side_effect maps keys to their inverse counts.
"""
mock …
How to Create a Sticky Consistent Mock with unittest.mock in Python
Shows how to use unittest.mock.patch.object to mock a method consistently across multiple calls, returning a sticky value every time.
from unittest.mock import patch
class Database:
def fetch(self, key):
return f"real value for {key}"
def get_value(db, key):
return db.fetch(key)
if __name__ == "__main__":
db = Database()
with patch.object(db, "fetch", return_value="sticky value") as mock_fetch:
result1 = get_value(…
How to Mock an Exposure Event Log Record in Python
Generate a realistic exposure event record with UUID, UTC timestamp, and risk level for testing or experimentation.
import uuid
from datetime import datetime, timezone
def mock_exposure_event(person_id: str, location: str, duration_minutes: int) -> dict:
return {
"event_id": str(uuid.uuid4()),
"person_id": person_id,
"location": location,
"duration_minutes": duration_minutes,
"timestamp…
How to Replicate Data Across All Shards in Python
Mocks a global table that replicates a key-value pair to every shard, ensuring reads return the same value from any shard.
from dataclasses import dataclass
from typing import Dict, List
@dataclass
class Shard:
id: str
data: Dict[str, int]
class GlobalTable:
def __init__(self, shards: List[Shard]):
self._shards = {s.id: s for s in shards}
def set_value(self, key: str, value: int) -> None:
"""Replicate …
How to mock directory-based sharding in Python
Simulates distributing files into logical shards using a deterministic hash of each filename, mocking how a database might shard rows across nodes.
import os
import hashlib
from collections import defaultdict
from pathlib import Path
def get_shard_for_key(key: str, num_shards: int) -> int:
"""Return a deterministic shard index (0..num_shards-1) for a key."""
digest = hashlib.md5(key.encode('utf-8')).hexdigest()
return int(digest, 16) % num_shards
…
Rebalance Shard Ranges Across Nodes in Python
A mock rebalancing function that shuffles shard ranges and distributes them evenly across nodes using round-robin assignment.
import random
from dataclasses import dataclass
@dataclass
class Shard:
id: int
start: int
end: int
def rebalance_shards(shards: list[Shard], node_count: int) -> dict[int, list[Shard]]:
"""Mock rebalancing of shard ranges across nodes."""
all_ranges = [(s.start, s.end) for s in shards]
random…
Simulate PostgreSQL Vacuum to Reclaim Space in Python
A Python class that safely rewrites a data file to remove deleted rows and reclaim physical space, mimicking PostgreSQL's VACUUM operation.
import shutil
import os
class VacuumCleaner:
"""Simulates PostgreSQL-style vacuum reclaiming dead space in a file."""
def __init__(self, filepath, fill_ratio=0.7, dead_marker="[DELETED]"):
self.filepath = filepath
self.fill_ratio = fill_ratio
self.dead_marker = dead_marker
…
How to Verify Passwords in Constant Time in Python
Use hmac.compare_digest to verify passwords in constant time, preventing timing attacks that could reveal password length or character positions.
import hmac
import time
# Mock of a constant-time password comparison (prevents timing attacks)
def verify_password(stored_password: str, supplied_password: str) -> bool:
# hmac.compare_digest runs in constant time (for a given length)
return hmac.compare_digest(stored_password.encode(), supplied_password.enc…
Generate a docker-compose.yml with mock services in Python
Build a docker-compose.yml string from a Python dict of service names and images, then write it to a file.
import yaml
from pathlib import Path
def generate_mock_compose(services: dict) -> str:
compose = {
"version": "3.9",
"services": {}
}
for name, image in services.items():
compose["services"][name] = {
"image": image,
"container_name": f"mock-{name}",
…
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