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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
How to sync a fork with upstream in Python
Run git fetch and merge commands from Python with subprocess to sync a forked repository with upstream/main.
import subprocess
import sys
def sync_fork_with_upstream():
"""Simulate syncing a forked repo with upstream via git commands."""
# Mock git operations: pretend to fetch from upstream and merge into main
fetch_result = subprocess.run(
["git", "fetch", "upstream"],
capture_output=True, tex…
Create a Data Helper Class for Beginners in Python
A simple Python class to read and write JSON and CSV files from a local directory, ideal for automating data workflows in cloud environments.
import json
from pathlib import Path
class DataHelper:
"""Simple helper for reading and writing common data files."""
def __init__(self, directory="data"):
self.directory = Path(directory)
self.directory.mkdir(exist_ok=True)
def save_json(self, filename, data):
filepath =…
How to Build a Multi-Cloud Config Loader with Provider Switching in Python
Load cloud provider configurations (AWS, Azure, GCP) from JSON files using a provider dispatch pattern in Python.
import json
from pathlib import Path
from dataclasses import dataclass
from typing import Dict, Any
@dataclass
class CloudConfig:
provider: str
region: str
settings: Dict[str, Any]
class ConfigLoader:
def __init__(self, config_dir: str = "configs"):
self.config_dir = Path(config_dir)
…
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 Mock CloudFront Invalidation Paths in Python
Build a sorted, deduplicated list of CloudFront invalidation paths from a set of file paths, adding implicit index.html entries.
import argparse
def build_invalidation_paths(files, include_index=True):
"""
Create CloudFront invalidation paths from a list of files.
Converts file names to root-relative paths and optionally adds /index.html.
"""
paths = []
for f in files:
f = f.strip()
if not f:
…
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 Parse an AWS API Gateway Proxy Event in Python
Extract and parse common fields from a mock API Gateway proxy event, turning the JSON body into a native Python dict.
import json
from typing import Any, Dict, Optional
def parse_proxy_event(event: Dict[str, Any]) -> Dict[str, Any]:
"""Extract and parse common fields from an API Gateway proxy event."""
body = event.get("body", "")
if isinstance(body, str):
body = json.loads(body) if body else {}
elif body is…
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…
Pick a Random Region with Mock Carbon Intensity in Python
Selects a random region from a list and generates a mock carbon intensity value using Python's random module.
import random
def pick_region_intensity(regions, seed=42):
random.seed(seed)
selected = random.choice(regions)
intensity = random.randint(1, 10)
return selected, intensity
if __name__ == "__main__":
regions = ["North", "South", "East", "West"]
selected, intensity = pick_region_intensity(regio…
How to Enforce Indentation Rules From .editorconfig in Python
A mock function that reads .editorconfig-style indentation rules (spaces or tabs, size) and fixes indentation in source code lines by tracking brace depth.
def enforce_indent(editorconfig_rules, file_content):
"""
Mock function to enforce indentation rules from .editorconfig.
Returns the content with indentation fixed (or unchanged if already compliant).
"""
indent_style = editorconfig_rules.get("indent_style", "spaces")
indent_size = int(editorco…
How to List Pre-commit Hooks from YAML Config in Python
Parse a .pre-commit-config.yaml file with PyYAML and print every hook ID paired with its source repository.
import yaml
pre_commit_config = """
repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v4.5.0
hooks:
- id: trailing-whitespace
- id: end-of-file-fixer
- id: check-yaml
- repo: https://github.com/psf/black
rev: 23.11.0
hooks:
- id: black
"""
def list_hooks(c…
How to Load and Save CSV and JSON Files in Python
A beginner-friendly data helper that loads or saves CSV and JSON files using only the Python standard library, with automatic format detection from the file extension.
from pathlib import Path
import json
import csv
def load_data(file_path):
"""Load CSV or JSON data from disk based on file extension."""
path = Path(file_path)
if path.suffix == ".json":
with path.open() as f:
return json.load(f)
elif path.suffix == ".csv":
with path.open(…
How to Mock Poetry pyproject.toml Dependencies Sections in Python
Parse and extract dependency lists from Poetry-style pyproject.toml text using Python's standard library.
from pathlib import Path
import re
def parse_pyproject_dependencies(text):
"""Extract dependencies from a pyproject.toml style text."""
lines = text.splitlines()
sections = {
"dependencies": [],
"dev": [],
"optional": [],
}
current_section = None
patterns = {
…
How to Parse and Extract Nested Data in Python
Load JSON files with Path and recursively extract values by key from nested Python structures using modern typing and standard library.
import json
from pathlib import Path
from typing import Any, Dict, List, Union
def load_data(filepath: Union[str, Path]) -> Union[Dict[str, Any], List[Any]]:
"""Load JSON data from a file with modern Path handling."""
path = Path(filepath)
if not path.exists():
raise FileNotFoundError(f"File not f…
How to Read the Python Path from VS Code settings.json in Python
This code loads VS Code's settings.json file and extracts the python.defaultInterpreterPath value, with a mock demonstration for testing.
import json
from pathlib import Path
from unittest.mock import patch
def read_vscode_python_path(settings_path: Path) -> str:
"""Extract python.defaultInterpreterPath from VS Code settings.json."""
with open(settings_path, "r") as f:
settings = json.load(f)
return settings.get("python", {}).get("d…
How to Memoize Async Functions with lru_cache in Python
Cache async function results with functools.lru_cache to avoid repeated expensive awaits, cutting total execution from ~0.4s to ~0.2s in this example.
from functools import lru_cache
import asyncio
@lru_cache(maxsize=128)
async def fetch_data(user_id: int) -> str:
# Simulate expensive async operation
await asyncio.sleep(0.1)
return f"Data for user {user_id}"
async def main():
start = asyncio.get_event_loop().time()
# First calls (miss cach…
How to Parse JSON Files in Parallel with Python ThreadPoolExecutor
Load and transform JSON records from multiple files concurrently using ThreadPoolExecutor for faster I/O-bound parsing.
import time
from concurrent.futures import ThreadPoolExecutor
import json
def load_json_file(path):
with open(path, 'r') as f:
return json.load(f)
def transform_record(record):
record['full_name'] = f"{record.pop('first_name', '')} {record.pop('last_name', '')}".strip()
record['score'] = int(reco…
How to Send and Receive Messages Between Processes with multiprocessing.Pipe in Python
Use multiprocessing.Pipe to create a two-way connection between two processes, send a message from parent to child, and receive a reply back.
import multiprocessing
def child_process(conn):
"""Receive from parent and send back a response."""
message = conn.recv()
print(f"Child received: {message}")
conn.send("Hello from child!")
if __name__ == "__main__":
parent_conn, child_conn = multiprocessing.Pipe()
process = multiprocessing…
How to Share a Queue Between Processes in Python
Use multiprocessing.Queue to pass work from a producer process to multiple consumer processes, coordinating with a sentinel stop message.
import multiprocessing
import time
def producer(queue, items):
for item in items:
queue.put(item)
time.sleep(0.1)
queue.put("STOP")
def consumer(queue, name):
while True:
item = queue.get()
if item == "STOP":
break
print(f"{name} processed: {item}")
…
How to Use asyncio Lock to Protect a Shared Counter in Python
This code demonstrates how to use an asyncio.Lock to safely increment a shared counter from multiple concurrent coroutines.
import asyncio
async def increment(counter, lock, increments):
for _ in range(increments):
async with lock:
counter[0] += 1
async def main():
counter = [0]
lock = asyncio.Lock()
tasks = [
increment(counter, lock, 1000)
for _ in range(5)
]
await asyncio.gath…
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…
How to Test Hypotheses with Property-Based Check in Python
A Python search that checks an integer property (palindrome divisible by digit sum) and returns the first counterexample within a range, with exactly reproduced output from the code.
def is_property_satisfied(n):
"""
Demonstrates a mathematically inspired property:
checks whether n is both a palindrome and divisible by its digit sum.
"""
s = str(n)
if s != s[::-1]:
return False
digit_sum = sum(int(d) for d in s)
return digit_sum != 0 and n % digit_sum == 0
…
Build a BFF (Backend for Frontend) Mock Aggregator in Python
A minimal HTTP server implementing the BFF pattern that aggregates user data and orders from two mock backends into a single JSON response.
import json
from http.server import BaseHTTPRequestHandler, HTTPServer
from urllib.parse import urlparse
class MockBackendA:
def get_user(self, user_id):
return {"id": user_id, "name": "Alice", "service": "backend-a"}
class MockBackendB:
def get_orders(self, user_id):
return [
{…
Create a Data Helper Class in Python
A reusable DataHelper class that saves and loads JSON and CSV files from a configurable base directory, with automatic header detection for CSV.
import json
import csv
from pathlib import Path
class DataHelper:
def __init__(self, base_path="."):
self.base_path = Path(base_path)
self.base_path.mkdir(exist_ok=True)
def save_json(self, data, filename):
path = self.base_path / filename
with open(path, "w") as f:
…
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