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How to Diff Two Dicts in Python for Config Drift
Recursively compare two dictionaries and report added, removed, and changed keys with their old and new values for debugging configuration drift.
def diff_dicts(a, b, path=""):
differences = []
for key in a.keys() | b.keys():
new_path = f"{path}.{key}" if path else key
if key not in a:
differences.append((new_path, "<missing>", b[key], "added"))
elif key not in b:
differences.append((new_path, a[key], "<…How to Build a CSV Comparison Tool That Highlights Every Changed Cell in Python
Read two CSV files with DictReader, compare cell by cell, and return a list of dictionaries describing each changed cell using only the standard library.
import csv
from pathlib import Path
def csv_cell_diff(file_a: str, file_b: str) -> list[dict]:
rows_a = list(csv.DictReader(Path(file_a).open('r', newline='')))
rows_b = list(csv.DictReader(Path(file_b).open('r', newline='')))
if not rows_a or not rows_b:
return []
columns = list(rows_a[0].key…How to Compare Two Files by Content Hash Equality in Python
Compares two files by hashing their contents with SHA-256, skipping the hash if file sizes differ, and returns whether they are identical.
import hashlib
from pathlib import Path
def file_hash(path: Path, chunk_size: int = 8192) -> str:
sha256 = hashlib.sha256()
with path.open("rb") as f:
for chunk in iter(lambda: f.read(chunk_size), b""):
sha256.update(chunk)
return sha256.hexdigest()
def files_are_identical(file_a: Pat…Bridge Pattern in Python: Separate Abstraction from Implementation
Implement the Bridge design pattern in Python so that an abstraction (remote control) can operate on different device implementations independently.
class RemoteControl:
"""Abstraction: controls a device without knowing implementation details."""
def __init__(self, device):
self.device = device
def toggle_power(self):
if self.device.is_enabled():
self.device.disable()
return "Power off"
else:
…Find Best Meeting Time Across Time Zones in Python
This code calculates overlapping available hours among participants in different time zones and returns the best meeting time in UTC and each participant's local time.
from datetime import datetime, timedelta, timezone
from zoneinfo import ZoneInfo
from dataclasses import dataclass
from typing import List, Tuple, Optional
@dataclass
class Participant:
name: str
timezone: str
# weekdays availability: 0=Mon, start_hour (0-23), end_hour (0-23)
available_slots: List[Tup…Generate Holiday Calendars for Different Countries in Python
Generate a sorted list of public holidays for a given country and year using Python's calendar and datetime modules.
import calendar
from datetime import date, timedelta
def generate_holiday_calendar(country_code, year=2025):
holidays = []
if country_code == "US":
# New Year's Day
holidays.append(date(year, 1, 1))
# Independence Day
holidays.append(date(year, 7, 4))
# Thanksgivin…How to Compare Two GitHub Repositories and Highlight Differences in Python
Fetch metadata from two GitHub repositories using the GitHub API and compare key attributes like stars, forks, license, and language, printing any differences.
import requests
import json
from pathlib import Path
def fetch_repo_data(owner, repo_name):
"""Fetch repository metadata from GitHub API."""
url = f"https://api.github.com/repos/{owner}/{repo_name}"
response = requests.get(url)
response.raise_for_status()
return response.json()
def compare_repos(…Build a Python Utility That Detects Duplicate Records Across Multiple Excel Sheets
A Python utility that uses pandas to find overlapping records across different Excel sheets based on specified key columns.
import pandas as pd
from pathlib import Path
def find_duplicate_records_across_sheets(file_path: str, key_columns: list, sheet_names: list) -> dict:
"""
Detect duplicate records across multiple Excel sheets based on specified key columns.
Args:
file_path: Path to the Excel file
key_co…Profile Memory Usage with tracemalloc Snapshot Diff in Python
Use tracemalloc to take two memory snapshots, compute a diff, and print the top changes (size and count) by line number.
import tracemalloc
def profile_memory():
tracemalloc.start()
# Allocate some objects to track
data = [i * 2 for i in range(10000)]
text = "x" * 5000
nested = {"key": [1, 2, 3], "value": (4, 5)}
# Take first snapshot
snapshot1 = tracemalloc.take_snapshot()
# Free some mem…How to Flag Unexpected Diff Changes in Python
Compares two snapshot lists, detects unexpected differences, and returns a flag indicating whether the snapshot should be updated.
import difflib
def snapshot_diff(before, after, intentional_changes=None):
"""Compare snapshots and flag only unexpected differences."""
intentional_changes = intentional_changes or set()
diff = list(difflib.unified_diff(before, after, lineterm=""))
has_unexpected = False
for line in diff:
…Implement Bulkhead Thread Pool Isolation in Python
Create isolated thread pools with a bulkhead pattern to protect different services from cascading failures.
import threading
import time
import random
from concurrent.futures import ThreadPoolExecutor
class Bulkhead:
"""Simple bulkhead isolation: separate thread pools for different tasks."""
def __init__(self, max_workers):
self.executor = ThreadPoolExecutor(max_workers=max_workers)
self.active = …Check Covariate Balance in Python
Compute standardized mean differences and KS tests to check covariate balance between treatment and control groups in Python.
import numpy as np
from scipy import stats
def balance_check(treatment, covariate):
"""Check covariate balance between treatment and control groups."""
treat_vals = covariate[treatment == 1]
control_vals = covariate[treatment == 0]
# Standardized mean difference
pooled_std = np.sqrt((np.var(t…Check Sample Ratio Mismatch in Python
Estimates the probability that a simple random sample's proportion differs from the population proportion by more than 10% using simulation.
import random
def sample_ratio_mismatch(population_size: int, sample_size: int, p: float) -> float:
"""
Estimate the probability that a simple random sample's proportion
differs from the population proportion by more than 10%.
"""
total_counts = [0, 0]
for _ in range(10000):
sample = …Delta Method for Ratio Metrics in A/B Testing with Python
Computes the confidence interval for the difference between two ratio metrics using the delta method, with mock A/B test data.
import numpy as np
from scipy.stats import norm
def delta_method_ratio_delta(control: np.ndarray, treatment: np.ndarray, confidence: float = 0.95):
"""Estimate confidence interval for ratio metric using delta method.
Args:
control: numerator/denominator pairs from control group (n x 2 array)
…How to Mock Sequential Calls in Python with unittest.mock
Use Mock.side_effect to return a different result for each sequential call and verify the call order with assert_has_calls.
import unittest
from unittest.mock import Mock
class Service:
def fetch(self, item_id):
raise NotImplementedError
def process_items(service, ids):
results = []
for item_id in ids:
result = service.fetch(item_id)
results.append(result)
return results
if __name__ == "__main__":…How to Implement Read-After-Write Consistency Mock in Python
Simulate strong versus eventual read-after-write consistency with a primary and replica store, demonstrating the difference in data visibility over time.
import time
class MockStorage:
def __init__(self, write_delay=0.1):
self.store = {}
self.replica = {}
self.write_delay = write_delay
def write(self, key, value):
# Write to primary storage immediately
self.store[key] = value
# Simulate async replication delay
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