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How to Split a List into Chunks in Python
Split a list into fixed-size sublists using a simple list comprehension with slicing.
def chunk_list(lst, size):
"""Split a list into sublists of given size."""
return [lst[i:i + size] for i in range(0, len(lst), size)]
if __name__ == "__main__":
sample = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
print(chunk_list(sample, 3))How to Group a List into Chunks in Python
Split a list into smaller groups of a fixed size using a reusable function with a default parameter.
def make_groups(numbers, group_size=2):
"""Splits a list into smaller groups of a given size."""
groups = []
for i in range(0, len(numbers), group_size):
groups.append(numbers[i:i + group_size])
return groups
if __name__ == "__main__":
data = [1, 2, 3, 4, 5, 6, 7]
print("Default size…How to Compute File SHA256 Hash with hashlib in Python
Compute the SHA256 hash of a file by reading it in chunks with hashlib and Path.open.
import hashlib
from pathlib import Path
def sha256_file(file_path: Path) -> str:
sha256_hash = hashlib.sha256()
with file_path.open("rb") as f:
for chunk in iter(lambda: f.read(4096), b""):
sha256_hash.update(chunk)
return sha256_hash.hexdigest()
if __name__ == "__main__":
demo_fi…Split CSV Files into Smaller Chunks in Python
Splits a large CSV file into multiple smaller chunk files, preserving the header row in each chunk.
import csv
import os
def split_csv(input_file, chunk_size=1000, output_prefix="chunk"):
"""Split a large CSV file into smaller chunks."""
with open(input_file, 'r', newline='') as infile:
reader = csv.reader(infile)
header = next(reader)
file_count = 1
row_count = 0
…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 =…Batch Rows in Chunks with a Generator in Python
Group a list of row dicts into fixed-size chunks using a generator that yields one slice per call.
from typing import Iterator, List
def batch_rows(rows: List[dict], batch_size: int) -> Iterator[List[dict]]:
for i in range(0, len(rows), batch_size):
yield rows[i:i + batch_size]
if __name__ == "__main__":
sample_rows = [
{"id": 1, "name": "Alice"},
{"id": 2, "name": "Bob"},
…How to Split Data into Chunks and Use Generators in Python
Split a list into fixed-size chunks with a list comprehension and square even numbers lazily with a generator expression.
def split_numbers(data, chunk_size):
return [data[i:i + chunk_size] for i in range(0, len(data), chunk_size)]
def square_even_numbers(numbers):
return (n ** 2 for n in numbers if n % 2 == 0)
if __name__ == "__main__":
sample_data = list(range(1, 21))
chunks = split_numbers(sample_data, 5)
print…Cosine Similarity to Retrieve Top K Chunks in Python
Compute cosine similarity between a query vector and a list of chunk vectors, then return the indices and scores of the top k most similar chunks.
import numpy as np
from numpy.linalg import norm
def cosine_similarity(vec1, vec2):
return np.dot(vec1, vec2) / (norm(vec1) * norm(vec2))
def retrieve_top_k(query_vec, chunk_vectors, k=3):
similarities = [cosine_similarity(query_vec, vec) for vec in chunk_vectors]
top_indices = sorted(range(len(similarit…How to Chunk a Long Document for RAG Retrieval in Python
Split text into overlapping chunks at sentence boundaries using a custom Python function suitable for RAG retrieval pipelines.
import re
from pathlib import Path
def chunk_document(text, chunk_size=500, overlap=100):
"""Split text into overlapping chunks suitable for RAG retrieval."""
# Normalize whitespace
text = re.sub(r'\s+', ' ', text).strip()
chunks = []
start = 0
while start < len(text):
end = min(s…Benchmark Disk Write Speed in Python with tempfile
Benchmark raw disk write performance by writing a temporary file in 1MB chunks and measuring throughput in MB/s.
import os
import tempfile
import time
def benchmark_write(size_mb=50):
size_bytes = size_mb * 1024 * 1024
chunk = b'x' * 1024 * 1024 # 1 MB chunk
with tempfile.NamedTemporaryFile(delete=True) as tmp:
start = time.perf_counter()
written = 0
while written < size_bytes:
…How to Reduce Aggregate Counts from Mapped Chunks in Python
Combine a list of mapped chunk dictionaries into a single aggregated count dictionary using functools.reduce.
from functools import reduce
from collections import defaultdict
def aggregate_chunks(mapped_chunks):
"""Combine mapped chunk counts into a single aggregate dict."""
return reduce(
lambda acc, chunk: {
**acc,
**{k: acc.get(k, 0) + v for k, v in chunk.items()}
},
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