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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
Separate Evens and Odds into Two Lists in Python
Split a list of numbers into two lists containing even and odd numbers using a simple loop and the modulo operator.
def separate_evens_odds(numbers):
evens = []
odds = []
for num in numbers:
if num % 2 == 0:
evens.append(num)
else:
odds.append(num)
return evens, odds
if __name__ == "__main__":
nums = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
evens, odds = separate_evens_odds(nu…How to partition a list into n nearly equal parts in Python
Divide a list into n contiguous chunks of nearly equal size using an average-length calculation that distributes the remainder evenly.
def partition(lst, n):
"""Partition a list into n nearly equal contiguous parts."""
if n <= 0:
raise ValueError("n must be positive")
if not lst:
return [[] for _ in range(n)]
parts = []
avg = len(lst) / n
last_idx = 0.0
while last_idx < len(lst):
end_idx =…How to Partition Output Files by Date Key in Python
Group output files into a dictionary partitioned by a YYYYMMDD date key extracted from the filename prefix.
from pathlib import Path
from collections import defaultdict
def partition_files_by_date(directory: str) -> dict:
"""Partition output files by date key extracted from filename (YYYYMMDD prefix)."""
path = Path(directory)
partitions = defaultdict(list)
for file in path.iterdir():
if file.i…Map Partition Over Chunks in Python with Multiprocessing and Mock
Process data in chunks across multiple CPU cores using multiprocessing Pool.map, and mock the chunk function to test partitioning behavior without heavy computation.
from multiprocessing import Pool
from unittest.mock import patch, Mock
def process_chunk(chunk):
return [x * x for x in chunk]
def map_partition_over_chunks(data, chunk_size, process_func=process_chunk):
chunks = [data[i:i + chunk_size] for i in range(0, len(data), chunk_size)]
with Pool() as pool:
…How to Partition and Order Kafka-Style Messages by Key in Python
Group messages with the same key into ordered buckets using hashing and a defaultdict, mimicking Kafka partition ordering.
from dataclasses import dataclass
from collections import defaultdict
@dataclass
class Message:
key: str
content: str
def partition_and_order(messages, num_partitions=3):
partitions = defaultdict(list)
for msg in messages:
partition_id = hash(msg.key) % num_partitions
partitions[parti…How to Implement row_number Window Function in Python
This code implements a SQL-style ROW_NUMBER() window function in pure Python, partitioning rows by a set of columns and ranking them within each partition by an ordered set of columns.
from collections import defaultdict
import itertools
def row_number(rows, partition_by, order_by):
partitions = defaultdict(list)
for index, row in enumerate(rows):
key = tuple(row[col] for col in partition_by)
partitions[key].append((index, row))
result = []
for key in partitions:
…Partition Data by Hash Key Mod N in Python
Returns a partition index for a string key by hashing it with MD5 and taking modulo N, then groups sample keys into partitions.
import hashlib
def partition_key(key: str, num_partitions: int) -> int:
"""Return partition index for key using MD5 hash mod N."""
digest = hashlib.md5(key.encode()).hexdigest()
return int(digest, 16) % num_partitions
if __name__ == "__main__":
keys = ["alice", "bob", "carol", "dave", "eve"]
nu…How to Build a Shard Map Mock Dict in Python
Implement a dictionary-like class that distributes keys across multiple shards using Python's hash() for realistic data partitioning.
class ShardMap:
def __init__(self, shard_count):
self.shards = {i: {} for i in range(shard_count)}
self.shard_count = shard_count
def _shard_for(self, key):
return hash(key) % self.shard_count
def __getitem__(self, key):
return self.shards[self._shard_for(key)][key]
d…How to mock directory-based sharding in Python
Simulates distributing files into logical shards using a deterministic hash of each filename, mocking how a database might shard rows across nodes.
import os
import hashlib
from collections import defaultdict
from pathlib import Path
def get_shard_for_key(key: str, num_shards: int) -> int:
"""Return a deterministic shard index (0..num_shards-1) for a key."""
digest = hashlib.md5(key.encode('utf-8')).hexdigest()
return int(digest, 16) % num_shards
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