Python Code
Samples
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How to Add a Correlation ID to Logging Records in Python
Attach a unique correlation ID to every log record using a custom logging.Filter, making distributed request tracking traceable.
import logging
import uuid
from dataclasses import dataclass, field
@dataclass
class CorrelationIdFilter(logging.Filter):
correlation_id: str = field(default_factory=lambda: str(uuid.uuid4()))
def filter(self, record: logging.LogRecord) -> bool:
record.correlation_id = self.correlation_id
re…Find All Triplets with Sum Zero in Python
This code finds all unique triplets in an array that sum to zero using a sorted array and two-pointer technique.
def find_triplets(nums):
nums.sort()
n = len(nums)
triplets = []
for i in range(n - 2):
if i > 0 and nums[i] == nums[i - 1]:
continue
left, right = i + 1, n - 1
while left < right:
total = nums[i] + nums[left] + nums[right]
if total == 0:
…Find two unique numbers in an array with Python
Returns the two numbers that appear exactly once in a list where every other number appears twice, using XOR bit manipulation.
def find_two_odd(arr):
"""Return the two numbers that appear exactly once, while all others appear twice."""
xor_all = 0
for num in arr:
xor_all ^= num
# xor_all now equals the XOR of the two unique numbers.
# Find a set bit (any bit where they differ).
diff_bit = xor_all & (-xor_all)
…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…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 = {}
…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:
…HyperLogLog Cardinality Estimation in Python
A small HyperLogLog implementation using MD5 hashing and 256 registers to estimate the number of unique items in a large stream with fixed memory.
import hashlib
import math
class HyperLogLog:
def __init__(self, b=8):
self.b = b
self.m = 1 << b
self.registers = [0] * self.m
self.alpha = 0.7213 / (1 + 1.079 / self.m)
def add(self, item):
h = int(hashlib.md5(str(item).encode()).hexdigest(), 16)
idx = h & (s…Snowflake ID Generator with Cluster Index Mock in Python
A thread-safe Snowflake ID generator mock that creates unique 64-bit IDs across simulated cluster nodes and maintains a sorted in-memory index for range queries.
import time
import threading
class SnowflakeIDGenerator:
def __init__(self, machine_id, datacenter_id):
self.machine_id = machine_id
self.datacenter_id = datacenter_id
self.sequence = 0
self.last_timestamp = -1
self.machine_bits = 5
self.datacenter_bits = 5
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