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Post a message to a Slack webhook in Python
Send a message to a Slack webhook endpoint using the standard library's urllib.request, handling the POST request and response cleanly.
import json
from urllib import request
def post_to_slack(webhook_url: str, message: str) -> dict:
payload = json.dumps({"text": message}).encode("utf-8")
req = request.Request(
webhook_url,
data=payload,
headers={"Content-Type": "application/json"},
method="POST",
)
wit…Rename Files in Folder with Numeric Prefix in Python
Renames all files in a folder by adding a sequential numeric prefix (e.g., 01_, 02_) to each filename using pathlib.
from pathlib import Path
def rename_with_numeric_prefix(folder_path):
folder = Path(folder_path)
for index, file_path in enumerate(folder.iterdir(), start=1):
if file_path.is_file():
new_name = f"{index:02d}_{file_path.name}"
new_path = file_path.with_name(new_name)
…Filter Records by Required Fields in Python
Filter a list of dictionaries, keeping only records where every required field is present and not None.
def filter_records(records, required_fields):
"""Return only records that have all required fields non-null."""
return [
record for record in records
if all(record.get(field) is not None for field in required_fields)
]
if __name__ == "__main__":
sample_records = [
{"name": "Al…How to Implement a Sliding Window Average in Python
Compute the average of the most recent N values in a stream using a bounded deque, efficiently updating the total as new values arrive.
from collections import deque
class SlidingWindowAverage:
def __init__(self, window_size):
self.window_size = window_size
self.window = deque(maxlen=window_size)
self.total = 0
def add(self, value):
if len(self.window) == self.window_size:
self.total -= self.windo…Parallel Extract Multiple Sources with Threads in Python
Extract data from multiple sources in parallel using ThreadPoolExecutor and verify results match sequential processing.
import threading
from concurrent.futures import ThreadPoolExecutor
def extract_from_source(source):
"""Simulate extracting data from a source."""
return f"Data from {source}"
def main():
sources = ["source_a", "source_b", "source_c", "source_d"]
# Sequential extraction for comparison
sequent…Test a Python Pipeline with Fixture Sample Rows
Test pipeline functions with sample rows provided by a pytest fixture, verifying required keys and value constraints.
import pytest
def get_value(data: dict, key: str):
return data.get(key)
def sample_rows():
return [
{"name": "Alice", "age": 30, "city": "London"},
{"name": "Bob", "age": 25, "city": "Paris"},
{"name": "Charlie", "age": 35, "city": "Berlin"},
]
@pytest.fixture
def sample_data(…Validate dict schema at pipeline boundary in Python
This code validates a dictionary against a TypedDict schema at a pipeline boundary, enforcing required fields and types with custom error messages.
from typing import Any, TypedDict
class Person(TypedDict):
name: str
age: int
email: str
def validate_person(data: dict[str, Any]) -> Person:
errors: list[str] = []
if not isinstance(data.get("name"), str) or not data["name"].strip():
errors.append("name must be a non-empty string")
…How to Enforce Tag Policies on AWS Resources in Python
Build a reusable Python class that checks AWS resources against a required-tag policy and reports compliance with missing tags.
import json
from dataclasses import dataclass, field
from typing import Dict, List
@dataclass
class Resource:
arn: str
tags: Dict[str, str] = field(default_factory=dict)
class TagPolicyEnforcer:
def __init__(self, required_tags: List[str]):
self.required_tags = set(required_tags)
def enfor…How to Evaluate Mock NACL Rules in Python
Simulate numbered AWS Network ACL rule evaluation with HMAC integrity checks on request payloads.
import base64
import json
import hmac
import hashlib
def evaluate_mock_rule(rule_number, request_data, secret):
"""
Simulates evaluating an NACL-like numbered rule by:
1. Checking if the rule number exists in the mock policy.
2. Computing an HMAC over the request payload for integrity.
"""
# M…How to Implement Retry with Exponential Backoff for Cloud API 429 Errors in Python
Implement a retry-with-backoff loop in Python to handle 429 throttling errors from cloud APIs, using exponential delay between attempts.
import time
import random
import requests
def api_call(attempt):
"""Mock cloud API that returns 429 for the first two attempts."""
if attempt < 2:
return 429, "Too Many Requests"
return 200, {"data": "success"}
def retry_with_backoff(api_func, max_retries=3, base_delay=0.1):
for attempt in …How to Validate Data Fields and Types in Python
Validate required fields and type correctness in a Python dictionary with small helper functions, returning a list of clear error messages.
import json
from typing import Any, Dict, List
def validate_data(data: Dict[str, Any], required_fields: List[str]) -> List[str]:
"""Check required fields exist and are non-empty. Return list of errors."""
errors = []
for field in required_fields:
value = data.get(field)
if value is None o…How to Build a Chainable Filter Helper in Python
A beginner-friendly dataclass helper that chains filters, uniqueness, and slicing on any sequence, returning a plain list at the end.
from dataclasses import dataclass
from typing import Callable, Iterator, Sequence, TypeVar
T = TypeVar("T")
@dataclass
class FilterAssistant:
"""Beginner-friendly helper to filter any collection."""
data: Sequence[T]
def where(self, predicate: Callable[[T], bool]) -> "FilterAssistant":
return …Mock pip-compile to Resolve Requirements in Python
A mock function that mimics pip-compile by converting a requirements.in file into pinned, locked package versions.
import subprocess
import tempfile
from pathlib import Path
def compile_requirements_mock(requirements_in: str) -> str:
"""Mock pip-compile: resolve a simple requirements.in into a locked format."""
lines = [line.strip() for line in requirements_in.splitlines() if line.strip() and not line.startswith("#")]
…How to Test HTTPX Async Client Pool Reuse with Mocks in Python
Mock an httpx.AsyncClient to verify connection pool reuse by asserting GET calls share a single client instance across concurrent async requests.
import asyncio
import httpx
from unittest.mock import AsyncMock, patch, Mock
async def fetch_with_pool(client, url, n_reuses=3):
results = []
for i in range(n_reuses):
resp = await client.get(url)
results.append(resp.status_code)
await asyncio.sleep(0) # yield to loop to mimic real us…How to use ThreadPoolExecutor for concurrent tasks in Python
Run blocking functions in parallel with ThreadPoolExecutor and as_completed, cutting total runtime from 5 sequential sleeps to about 1 second.
import time
from concurrent.futures import ThreadPoolExecutor, as_completed
def fetch_data(item):
"""Simulate a slow operation with a fixed delay."""
time.sleep(0.2)
return item * 2
def main():
items = [1, 2, 3, 4, 5]
start = time.perf_counter()
with ThreadPoolExecutor(max_workers=3) as ex…Using a Python Generator Instead of a List to Save Memory
Compare a list approach with a generator to stream values lazily, avoiding memory-heavy storage of large sequences.
def fibonacci_generator(limit):
a, b = 0, 1
count = 0
while count < limit:
yield a
a, b = b, a + b
count += 1
def sum_first_n(generator, n):
total = 0
for i, value in enumerate(generator):
if i >= n:
break
total += value
return total
if __…How to Merge TypedDicts in Python
Merge two TypedDict dictionaries with type-aware logic using NotRequired, **kwargs unpacking, and safe key updates.
from typing import TypedDict, NotRequired, merge # hypothetical
class User(TypedDict):
name: str
email: NotRequired[str]
age: NotRequired[int]
def merge_users(base: User, **overrides: User) -> User:
"""Merge two user dicts with typing-aware logic."""
result: User = dict(base)
for key, value …How to Mock requests.get in Python
Mock requests.get with unittest.mock to test code that makes HTTP calls without hitting the network.
import requests
from unittest.mock import Mock, patch
def fetch_user_data(user_id):
response = requests.get(f"https://api.example.com/users/{user_id}")
return response.json()
def process_user(user_id):
mock_response = Mock()
mock_response.json.return_value = {"id": user_id, "name": "Alice", "age": 30…How to Sort Data in Python
Sort sequences with type-safe helpers that handle mixed data with a string fallback.
from typing import Any, TypeVar, Protocol, Sequence, Iterable
T = TypeVar("T")
Comparable = TypeVar("Comparable", bound="Comparable")
class Sortable(Protocol):
def __lt__(self, other: Any) -> bool: ...
S = TypeVar("S", bound=Sortable)
def sort_data(data: Sequence[S], *, reverse: bool = False) -> list[S]:
"…How to Write a pytest Test Function with assert Equal in Python
Define simple pytest test functions that use assert to verify result equality and run them with pytest.main.
import pytest
def add(a, b):
return a + b
def test_add_positive_numbers():
result = add(2, 3)
assert result == 5
def test_add_negative_numbers():
result = add(-2, -3)
assert result == -5
def test_add_mixed_numbers():
result = add(2, -3)
assert result == -1
if __name__ == "__main__":
…How to Write pytest Test Function Assert Equal in Python
Write three pytest test functions that assert the result of an add() function equals an expected numeric value.
import pytest
def add(a, b):
return a + b
def test_add_positive_numbers():
assert add(2, 3) == 5
def test_add_negative_numbers():
assert add(-1, -2) == -3
def test_add_mixed_numbers():
assert add(5, -3) == 2
if __name__ == "__main__":
pytest.main([__file__, "-v"])How to use unittest mock side_effect with a sequence in Python
Demonstrates using Mock.side_effect with a list to return different values per call and raise an exception at a specific call in unittest.
import unittest
from unittest.mock import Mock
class TestMockSideEffectSequence(unittest.TestCase):
def test_side_effect_sequence(self):
mock = Mock()
mock.side_effect = [1, 2, 3, Exception("boom")]
self.assertEqual(mock(), 1)
self.assertEqual(mock(), 2)
self.asser…How to Build a Weighted Random Load Balancer in Python
A Python load balancer mock that distributes requests across servers based on configurable weights using a cumulative weighted random selection algorithm.
import random
from collections import Counter
SERVERS = {
"server-a": 50,
"server-b": 30,
"server-c": 20,
}
def weighted_random_server(servers: dict[str, int]) -> str:
"""Select a server based on its weight (higher weight = more likely)."""
total_weight = sum(servers.values())
rand = random.…How to Mock the Ambassador Pattern Retry Client in Python
This code demonstrates the ambassador pattern for API clients by simulating a flaky request and retrying with exponential backoff, useful for testing resilience in system design.
import time
import random
class RetryingClient:
"""Retry wrapper simulating a flaky ambassador-style API client."""
def __init__(self, max_attempts=3, base_delay=0.1):
self.max_attempts = max_attempts
self.base_delay = base_delay
self.attempts = 0
def _flaky_request(self):
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