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Find Duplicate Web Pages by Content Similarity in Python
Compute SHA-256 hashes of file contents to detect and report duplicate HTML pages or any files in a directory.
import hashlib
import os
from collections import defaultdict
def get_file_hash(filepath):
"""Compute SHA-256 hash of file contents."""
sha256 = hashlib.sha256()
with open(filepath, 'rb') as f:
for chunk in iter(lambda: f.read(4096), b''):
sha256.update(chunk)
return sha256.hexdiges…How to Find Duplicate Files by Size and Hash in Python
Recursively scan a directory, group files by size, then hash candidates to identify exact duplicate files.
import hashlib
from pathlib import Path
def hash_file(path, chunk_size=8192):
hasher = hashlib.md5()
with open(path, 'rb') as f:
while chunk := f.read(chunk_size):
hasher.update(chunk)
return hasher.hexdigest()
def find_duplicates(directory):
size_map = {}
for path in Path(dir…Find Missing Numbers, Duplicates, and Ranges in Python
Analyze a list to identify missing numbers, duplicate values, and contiguous ranges using sets and the Counter class.
def find_missing_duplicates_ranges(numbers):
"""Find missing numbers, duplicates, and ranges in a list."""
from collections import Counter
if not numbers:
return {"missing": [], "duplicates": [], "ranges": []}
full_range = set(range(min(numbers), max(numbers) + 1))
present = set(n…Find the Duplicate Number in Python Using Floyd's Cycle Detection
Detects the duplicate integer in an array of n+1 numbers (values 1 to n) in O(n) time and O(1) space using Floyd's cycle detection algorithm applied to a linked-list model.
def find_duplicate(nums):
slow = nums[0]
fast = nums[0]
# Phase 1: Find intersection point of the cycle
while True:
slow = nums[slow]
fast = nums[nums[fast]]
if slow == fast:
break
# Phase 2: Find the start of the cycle (the duplicate)
slow = nums[0…How to Find Four Sum Quadruplets in Python (Sorted Demo)
Find all unique quadruplets in a sorted array that sum to a target, with duplicate skipping.
def four_sum(nums, target):
nums.sort()
result = []
n = len(nums)
for i in range(n - 3):
if i > 0 and nums[i] == nums[i - 1]:
continue
for j in range(i + 1, n - 2):
if j > i + 1 and nums[j] == nums[j - 1]:
continue
left, right = j + 1…Find and Delete Duplicate Files Using Hashing in Python
Walk a directory tree, compute SHA256 hashes for every file, and delete duplicates that share the same hash.
import hashlib
import os
from pathlib import Path
def file_hash(path, block_size=65536):
"""Return SHA256 hash of file content."""
hasher = hashlib.sha256()
with open(path, 'rb') as f:
while chunk := f.read(block_size):
hasher.update(chunk)
return hasher.hexdigest()
def find_and_d…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…Deduplicate events by ID within a window in Python
Deduplicate event streams by ID within sliding time windows, keeping the newest occurrence per window using heaps and sets.
import heapq
from collections import defaultdict
def deduplicate_events(events, window_size):
"""Return events deduplicated by id, keeping newest within each sliding window."""
# Index events by (timestamp, id) for deterministic ordering
events_by_id = defaultdict(list)
for ts, eid, *payload in events…How to Validate Fact Table Grain Row Counts in Python
Validate fact table grain by checking dimension key references, unique grain combinations, duplicate rows, and dimension cardinality from a CSV file.
import csv
import hashlib
from pathlib import Path
def validate_fact_grain(fact_file: Path, expected_dim_keys: dict[str, set[str]]) -> dict:
"""
Validate fact table grain by checking each row's dimension keys exist
in expected dimension tables and row count consistency.
"""
dim_references = {}
…Inbox pattern consumer dedupe mock in Python
Implements a mock inbox consumer that deduplicates incoming messages by ID, with automatic eviction of old seen IDs to prevent unbounded memory growth.
import json
from collections import deque
from dataclasses import dataclass, field
from hashlib import sha256
from typing import Any
@dataclass
class InboxConsumer:
max_seen: int = 1000
seen_ids: set = field(default_factory=set)
seen_history: deque = field(default_factory=deque)
def _mark_seen(self,…How to Build an Idempotency-Key POST Handler in Python
Python HTTP server mock that accepts POST requests and deduplicates them using an Idempotency-Key header, returning the same response for repeated calls.
import hashlib
import json
from http.server import BaseHTTPRequestHandler, HTTPServer
from urllib.parse import urlparse
class MockAPI(BaseHTTPRequestHandler):
responses = {}
def do_POST(self):
length = int(self.headers.get("Content-Length", 0))
body = self.rfile.read(length).decode("utf-8")
…Cache Stampede Prevention with SingleFlight in Python
Implements a SingleFlight pattern in Python to deduplicate concurrent cache-miss computations and prevent cache stampede.
import threading
import time
from functools import wraps
class SingleFlight:
def __init__(self):
self._lock = threading.Lock()
self._inflight = None
def do(self, key, fn):
with self._lock:
if self._inflight is not None:
return self._inflight[1]
…At Least Once with Idempotent Consumer in Python
Implements a thread-safe idempotent consumer that processes each unique message exactly once, even when a producer sends duplicates under an at-least-once delivery model.
import threading
import time
import uuid
from collections import Counter
class IdempotentConsumer:
def __init__(self):
self.processed = set()
self._lock = threading.Lock()
def consume(self, message_id, payload):
with self._lock:
if message_id in self.processed:
…How to Implement Hedged Requests in Python
This code demonstrates a hedged request pattern using threading, which sends duplicate calls and returns the first result that arrives within a timeout.
import time
from unittest.mock import Mock
def hedged_request(call, timeout=0.05):
"""Execute two duplicate calls, return first result within timeout."""
result_container = {}
def run_and_store():
result_container['result'] = call()
result_container['done'] = True
# Simulate slow cal…Idempotent Writes for Sharded Databases in Python
Implement a mock shard with idempotent write support using request IDs to prevent duplicate writes and track the latest value per key.
import json
class ShardMock:
"""Mock distributed shard with idempotent write support."""
def __init__(self, shard_id):
self.shard_id = shard_id
self._store = {}
def write(self, key, value, request_id):
"""Write value only if request_id not yet processed; idempotent."""
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