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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))Convert All Markdown Files in a Folder to HTML in Python
Batch convert every .md file in a folder to .html using the `markdown` library with the 'extra' extensions.
import os
import markdown
from pathlib import Path
def convert_md_folder_to_html(input_folder="markdown_files", output_folder="html_pages"):
input_path = Path(input_folder)
output_path = Path(output_folder)
output_path.mkdir(exist_ok=True)
for md_file in input_path.glob("*.md"):
with open…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
…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"},
…Chunk an Iterable into Batches with a Generator in Python
Yield fixed-size batches from any iterable lazily using itertools.islice inside a generator function.
from itertools import islice
def chunked(iterable, size):
iterator = iter(iterable)
while True:
batch = list(islice(iterator, size))
if not batch:
break
yield batch
if __name__ == "__main__":
data = range(10)
for batch in chunked(data, 3):
print(batch)How to Batch Embed a List of Strings in Python
Batch embed a list of strings into deterministic pseudo-random vectors using a mock encoder class.
class MockEncoder:
def __init__(self, dim=8, seed=42):
self.dim = dim
self.seed = seed
def embed(self, text):
# Deterministic pseudo-random embedding based on text content
hash_val = hash(text)
import random
rng = random.Random(hash_val + self.seed)
retu…Batch Rename Hundreds of Files in Python
Rename all files with a given extension inside a folder using a sequential counter and a custom prefix.
import os
from pathlib import Path
def batch_rename_files(directory: str, prefix: str, extension: str = ".txt") -> None:
"""Rename all files with given extension in directory to prefix_{counter}.ext."""
path = Path(directory)
if not path.is_dir():
print(f"Directory '{directory}' does not exist.")
…Convert Markdown to HTML in Python (Batch)
Convert every Markdown file in a directory to HTML with the Python markdown library, saving each result with an .html extension.
import markdown
from pathlib import Path
def convert_md_to_html(source_dir: str, dest_dir: str) -> list[str]:
src = Path(source_dir)
dst = Path(dest_dir)
dst.mkdir(parents=True, exist_ok=True)
converted_files = []
for md_file in src.glob("*.md"):
html_content = markdown.markdown(md_file.…Create ICS Calendar Invites in Python
This script generates a batch of calendar invites in the ICS format using the ics library.
import ics
from datetime import datetime, timedelta
def create_invites(batch):
calendar = ics.Calendar()
for event_data in batch:
event = ics.Event()
event.name = event_data["name"]
event.begin = event_data["start"]
event.end = event_data["end"]
event.description = even…How to Batch Resize Images in Python with pathlib and Pillow
Batch resize all JPG images from a source folder and save to a destination folder using pathlib and Pillow.
from pathlib import Path
from PIL import Image
def batch_resize_images(src_dir: str, dest_dir: str, size: tuple[int, int] = (800, 600)) -> None:
src_path = Path(src_dir)
dest_path = Path(dest_dir)
dest_path.mkdir(parents=True, exist_ok=True)
for img_path in src_path.glob("*.jpg"):
if not …How to Resize Hundreds of Images in Batch with Python
Resize every image in a folder to a target size using Pillow, creating a new subfolder for processed files.
import os
from PIL import Image
def resize_images_in_batch(directory, output_size=(800, 600)):
if not os.path.exists(directory):
print(f"Directory {directory} does not exist.")
return
output_dir = os.path.join(directory, "resized")
os.makedirs(output_dir, exist_ok=True)
for filename in…How to Track Checkpoint Offset After Batch Commit in Python
A batch processor that tracks the last successfully committed offset after processing records in batches, advancing the checkpoint only when each batch commits successfully.
import json
from typing import Any
class BatchProcessor:
"""Tracks checkpoint offset after committing batches."""
def __init__(self, batch_size: int = 3):
self.batch_size = batch_size
self.offset = 0 # last successfully committed offset (exclusive)
self.total_committed = 0
def …How to route late-arriving data to a side output in Python
Separate late-arriving events from a streaming data batch into a dead-letter side output list using a timestamp threshold.
from collections import defaultdict
def late_arriving_side_output(events, late_threshold_ts):
"""
Mock a streaming pipeline that separates late-arriving data events
into a side output list (e.g., for dead-letter analysis).
events: list of (timestamp, data) tuples, timestamps as ints.
late_thresho…How to Simulate a Micro-Batch Interval Trigger in Python
A dataclass-based mock that emits batch numbers at fixed intervals, mimicking a micro-batch streaming scheduler for testing and development.
import time
from dataclasses import dataclass, field
from typing import List, Callable
@dataclass
class MicroBatchTriggerMock:
batch_interval_seconds: float = 0.5
max_batches: int = 5
_batches_emitted: int = 0
_next_emit_time: float = field(init=False, default=0)
def start(self, on_batch: Callab…How to use Redis MGET MSET pipeline in Python
Store multiple keys atomically and read them efficiently with Redis MSET/MGET, then batch commands with a pipeline to cut round trips.
import redis # v4.x+ required
r = redis.Redis(host="localhost", port=6379, db=0, decode_responses=True)
# Sample data to store
r.flushdb()
data = {"name": "Alice", "age": "30", "city": "Berlin"}
# MSET: store multiple key-value pairs in one command
r.mset(data)
# MGET: fetch multiple keys in one round trip
keys =…How to Ship Logs to an Aggregator Endpoint in Python
Ship batched log entries to a mock HTTP aggregator endpoint with proper error handling and response status.
import json
import requests
from datetime import datetime, timezone
LOG_ENTRIES = [
{"timestamp": "2024-01-15T10:00:00Z", "level": "INFO", "message": "Server started"},
{"timestamp": "2024-01-15T10:00:05Z", "level": "WARN", "message": "High memory usage"},
{"timestamp": "2024-01-15T10:00:10Z", "level": "E…How to Mock a Feature Store Online Lookup in Python
This code simulates an online feature store with single and batch retrieval methods, using a dict-backed cache and timestamps.
import random
import time
class OnlineFeatureStore:
def __init__(self):
self.features = {}
def put(self, entity_id: str, feature_name: str, value):
key = (entity_id, feature_name)
self.features[key] = (value, time.time())
def get(self, entity_id: str, feature_name: str):
…How to Run Batch Predictions with a Mock Model in Python
Build a lightweight mock model class and run predictions across a batch of samples, returning results as a plain Python list.
import numpy as np
class MockModel:
def __init__(self, weights):
self.weights = np.array(weights)
def predict(self, X):
return X @ self.weights
def predict_batch(model, batch):
"""Run predictions for a batch of samples and return results as a list."""
return model.predict(np.array(ba…How to Batch Load JSON Data in Python for Database Optimization
This code parses JSON data into records and loads them in batches to simulate efficient database insertion, reducing load and improving performance.
import json
import time
def parse_and_load(data, batch_size=100):
"""
Parse JSON data and batch-load into a list of dicts.
Demonstrates batching for database efficiency.
"""
records = json.loads(data)
batches = []
for i in range(0, len(records), batch_size):
batch = records[i:i + …How to Create a Database Helper Class for Beginners in Python
Build a beginner-friendly SQLite helper class with indexing and batch inserts to optimize database queries in Python.
import sqlite3
class DatabaseHelper:
def __init__(self, db_path):
self.connection = sqlite3.connect(db_path)
self.cursor = self.connection.cursor()
def create_table_with_index(self, table_name, columns, indexed_column):
columns_sql = ", ".join(f"{name} {dtype}" for name, dtype in col…How to Revoke Tokens with a Blacklist Set in Python
A minimal TokenBlacklist class using a Python set to revoke, batch-revoke, check, and remove expired tokens for simple token invalidation.
import time
class TokenBlacklist:
def __init__(self):
self.blacklisted_tokens = set()
def revoke(self, token):
self.blacklisted_tokens.add(token)
print(f"Token {token} revoked. Blacklist size: {len(self.blacklisted_tokens)}")
def revoke_batch(self, tokens):
before = len(s…Browse by section
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