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Cross Shard Query Scatter Gather Mock in Python
Simulate a distributed database cross-shard query using a scatter-gather pattern with a mock Python implementation.
from dataclasses import dataclass
from typing import List, Dict
@dataclass
class NodeResponse:
node_id: int
data: Dict[str, float]
def mock_query_shard(shard_id: int, shard_data: Dict[str, float], query: str) -> NodeResponse:
"""Simulate querying a single shard, returning matches whose value > 50."""
…
How to Build a Shard Map Mock Dict in Python
Implement a dictionary-like class that distributes keys across multiple shards using Python's hash() for realistic data partitioning.
class ShardMap:
def __init__(self, shard_count):
self.shards = {i: {} for i in range(shard_count)}
self.shard_count = shard_count
def _shard_for(self, key):
return hash(key) % self.shard_count
def __getitem__(self, key):
return self.shards[self._shard_for(key)][key]
d…
How to Implement Consistent Hashing in Python
Build a consistent hash ring in Python that distributes keys across nodes and minimizes remapping when nodes are added or removed.
import hashlib
from bisect import bisect_right
class ConsistentHashRing:
def __init__(self, nodes, replicas=3):
self.replicas = replicas
self.ring = {}
self.sorted_keys = []
for node in nodes:
self.add_node(node)
def _hash(self, key):
return int(hashlib.md…
How to Mock a Cross-Shard Saga in Python
Simulate a distributed saga with compensating transactions across multiple database shards using a lightweight Python class that tracks executed steps and rolls them back in reverse on failure.
import json
class SagaState:
def __init__(self, saga_id):
self.saga_id = saga_id
self.executed_steps = []
self.compensations = []
def execute_step(self, shard, step_name, operation):
self.executed_steps.append((shard, step_name))
print(f"[Saga {self.saga_id}] Executin…
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
…
Simulate a GIN Index for JSONB in Python
Build a mock Generalized Inverted Index (GIN) that flattens JSON documents into key-value tokens for fast lookup queries, mimicking PostgreSQL JSONB indexing.
import json
import random
from collections import defaultdict
# Mock GIN (Generalized Inverted Index) for JSONB key-value pairs
class GINIndex:
def __init__(self):
self.posting_lists = defaultdict(list) # token -> list of doc_ids
def index(self, doc_id, json_obj):
"""Index a JSON documen…
Snowflake ID Generator with Cluster Index Mock in Python
A thread-safe Snowflake ID generator mock that creates unique 64-bit IDs across simulated cluster nodes and maintains a sorted in-memory index for range queries.
import time
import threading
class SnowflakeIDGenerator:
def __init__(self, machine_id, datacenter_id):
self.machine_id = machine_id
self.datacenter_id = datacenter_id
self.sequence = 0
self.last_timestamp = -1
self.machine_bits = 5
self.datacenter_bits = 5
…
Two Phase Commit Cross Shard Mock in Python
Simulates a two-phase commit across shards with failure handling to demonstrate distributed transaction coordination in Python.
"""Mock cross-shard two-phase commit with caution handling."""
class Shard:
def __init__(self, name):
self.name = name
self.prepared = False
self.committed = False
self.aborted = False
def prepare(self):
# Simulate potential failure (1 in 3 chance on third shard)
…
How to Test X-Content-Type-Options nosniff in Python with Mocks
Mock httpx responses and verify that a server's X-Content-Type-Options header includes nosniff to prevent MIME sniffing.
import httpx
from unittest.mock import Mock, patch
def fetch_headers(url: str) -> dict:
response = httpx.get(url)
return dict(response.headers)
def mock_nosniff_check(response) -> bool:
content_type = response.headers.get("content-type", "")
x_content_type_options = response.headers.get("x-content-ty…
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}",
…
How to Drain a Connection Pool Before Exit in Python
Gracefully close all pooled sockets using a thread-safe ConnectionPool that drains connections before program exit.
import socket
import threading
import time
import random
class ConnectionPool:
def __init__(self, size=5):
self.pool = []
self.lock = threading.Lock()
self.closed = False
for _ in range(size):
self.pool.append(self.create_connection())
def create_connection(sel…
How to Mock Image Signing Cost in Python
Create a deterministic mock signing cost calculator that predicts resource usage for image signatures before real signing infrastructure is staged.
import math
import struct
def sign_image_cost(image_signature: bytes) -> int:
"""Deterministic mock signing cost based on image signature bytes."""
if not image_signature:
raise ValueError("Empty image signature")
digest = 0
for byte in image_signature:
digest = (digest * 31 + byte) &…
How to Smoke Test a Deployment in Python with unittest.mock
Run a post-deploy smoke test by mocking the deployment status check to verify your health-check logic returns PASS/FAIL.
import unittest
from unittest.mock import Mock, patch
class DeploymentService:
def check_status(self):
return "unknown"
def smoke_test_deploy():
service = DeploymentService()
with patch.object(service, "check_status", return_value="healthy") as mock_check:
status = service.check_status()
…
Mock Kubernetes HPA CPU Scaling in Python
Python function that simulates CPU utilization and calculates desired replicas using the Kubernetes HPA formula.
import random
import time
def simulate_cpu_utilization(target_utilization=50, samples=10):
"""Simulate CPU utilization readings for HPA mock."""
utilizations = []
for _ in range(samples):
# Simulate fluctuating CPU with random noise around target
current = target_utilization + random.unif…
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