Cloud + Python
Cloud SDK patterns — storage, serverless handlers, secrets, and deployment helpers.
Generate an Idempotency-Key header mock with UUID in Python
This code provides a mock idempotency service that generates a UUID-based Idempotency-Key header token and validates it, useful for simulating production API behavior in tests.
import uuid
class MockIdempotencyService:
def __init__(self):
self._tokens = {}
def get_token(self, header_name="Idempotency-Key"):
token = str(uuid.uuid4())
self._tokens[header_name] = token
return token
def validate(self, header_name="Idempotency-Key"):
return s…
How to Calculate Cloud Cost Estimates with a Python Dictionary
Mocks a cloud pricing calculator using a dictionary of service rates and computes total estimated cost for given service hours.
def estimate_cost(service, hours, rate_table=None):
if rate_table is None:
rate_table = {
"basic": 50,
"standard": 75,
"premium": 100
}
if service not in rate_table:
raise ValueError(f"Unknown service: {service}")
return rate_table[service] * hour…
How to Mock Azure Service Bus Queue in Python
A lightweight in-memory mock of the Azure Service Bus queue API for local testing without cloud dependencies.
import json
import time
from collections import deque
class ServiceBusQueueMock:
def __init__(self, queue_name):
self.queue_name = queue_name
self._messages = deque()
self._dead_letter_queue = deque()
self._message_counter = 0
def send_message(self, body, message_id=None, prop…
How to Parse Cloud JSON Data in Python
A helper function that safely parses JSON payloads from cloud services into a clean dict with defaults and error handling.
import json
from typing import Dict, Any
def parse_cloud_data(payload: str) -> Dict[str, Any]:
"""Parse a JSON payload from a cloud service into a clean dict."""
try:
data = json.loads(payload)
return {
"status": data.get("status", "unknown"),
"region": data.get("region…
How to plan reserved capacity from a CSV in Python
Read a CSV of workloads with csv.DictReader and compute a mock reserved capacity plan with headroom per service.
import csv
import io
def plan_reserved_capacity(workloads_csv: str) -> list[dict]:
"""Read a CSV of workloads and return a plan for reserved capacity per service."""
reader = csv.DictReader(io.StringIO(workloads_csv))
plan = []
for row in reader:
service = row["service"]
avg_load = fl…
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