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How to Stream Large CSV Files in Python
Process a large CSV file in memory-efficient chunks using Python's csv module, yielding batches of rows instead of loading everything at once.
import csv
from pathlib import Path
def process_csv_in_chunks(file_path, chunk_size=1000):
"""Yield rows from a large CSV file in chunks without loading all into memory."""
with open(file_path, 'r', newline='') as f:
reader = csv.DictReader(f)
chunk = []
for row in reader:
…How to Implement a Batch Requests Flush Interval in Python
A simple async batcher that accumulates items and flushes them either when a max batch size is reached or after a time-based flush interval.
import asyncio
from collections import deque
class Batcher:
def __init__(self, flush_interval=0.5, max_batch=5):
self.flush_interval = flush_interval
self.max_batch = max_batch
self.queue = deque()
self.lock = asyncio.Lock()
async def add(self, item):
async with self.l…Limit Concurrency with asyncio.Semaphore in Python
Use asyncio.Semaphore to cap how many async tasks run at once, throttling a batch of coroutines to a set concurrency limit.
import asyncio
import random
async def fetch_data(i: int, semaphore: asyncio.Semaphore) -> str:
async with semaphore:
print(f"Task {i} starts")
await asyncio.sleep(random.uniform(0.1, 0.5))
print(f"Task {i} finishes")
return f"Result {i}"
async def main() -> None:
semaphore …How to Build a Batch Operations Multi-Status 207 Mock Server in Python
Build a mock HTTP server that accepts a batch of operations and returns HTTP 207 Multi-Status with per-operation status codes in JSON.
from http.server import BaseHTTPRequestHandler, HTTPServer
import json
class BatchHandler(BaseHTTPRequestHandler):
def do_POST(self):
if self.path != "/batch":
self.send_response(404)
self.end_headers()
return
content_length = int(self.headers.get("Content-Leng…Batch Consume Process Commit Pattern in Python
A mock batch processor that accumulates items in a queue, processes full batches, commits successful or failed results, and flushes remaining items.
import random
import threading
import time
from collections import deque
class MockBatchProcessor:
def __init__(self, process_func, commit_func, batch_size=5):
self.queue = deque()
self.batch_size = batch_size
self.process_func = process_func
self.commit_func = commit_func
de…How to Mock a Kafka Producer Batch Send in Python
Simulate a Kafka producer in Python that sends batched JSON events with mock partitions and latency for testing streaming pipelines without a real broker.
import json
import random
import time
from datetime import datetime
class MockKafkaProducer:
def __init__(self, topic):
self.topic = topic
self.sent_messages = []
def send(self, value, key=None):
message = {
"topic": self.topic,
"key": key,
"value"…Kafka Consumer Poll Loop Mock in Python
Simulate a Kafka consumer poll loop with a mock class, process messages in batches, and commit offsets to understand streaming consumption patterns.
import time
class MockKafkaConsumer:
def __init__(self, topic, messages):
self.topic = topic
self.messages = list(messages)
self.position = 0
def poll(self, timeout_ms=100):
if self.position >= len(self.messages):
time.sleep(timeout_ms / 1000)
return []…How to Mock Redis Pipeline Batch Commands in Python
Create a lightweight MockRedis class that simulates Redis pipeline batching with SET, GET, and DELETE operations for testing without a live server.
import redis
import time
class MockRedis:
def __init__(self):
self.data = {}
def pipeline(self):
return MockPipeline(self)
def execute(self, commands):
results = []
for cmd in commands:
op, args = cmd[0], cmd[1:]
if op == "SET":
se…How to implement a write-behind cache with async queue in Python
Build an async write-behind cache that queues writes in memory and flushes them in batches to persistent storage.
import asyncio
from collections import deque
from dataclasses import dataclass
@dataclass
class CacheEntry:
key: str
value: str
class WriteBehindCache:
def __init__(self, flush_interval=1.0):
self.cache = {}
self.queue = deque()
self.flush_interval = flush_interval
self._f…How to Mock Spark Streaming Micro-Batches in Python
Simulate Spark's micro-batch streaming with a simple deque-based class that collects events over time and processes them in timed batches.
import time
from collections import deque
from datetime import datetime
class MicroBatchStream:
def __init__(self, batch_interval_sec=2):
self.batch_interval = batch_interval_sec
self.source = deque()
self.processed = []
def add_events(self, events):
self.source.extend(events…How to use foreachBatch with a mock sink in PySpark
Demonstrates using Spark Structured Streaming's foreachBatch sink to capture and verify streaming batches by writing them into a custom mock sink object.
from pyspark.sql import SparkSession
from pyspark.sql.functions import col, lit
class MockSink:
def __init__(self):
self.batches = []
def write_batch(self, batch_df, batch_id):
# Collect batch data as list of dicts for verification
records = batch_df.collect()
self.batches…Database Helper in Python with SQLite Scaling Optimization
Build a beginner-friendly SQLite database helper class with WAL, indexed queries, and efficient batch inserts for scaling.
import sqlite3
from contextlib import contextmanager
class DatabaseHelper:
"""Beginner-friendly helper for SQLite database operations with scaling tips."""
def __init__(self, db_path):
self.db_path = db_path
@contextmanager
def connection(self):
"""Context manager for automatic comm…How to Mock SQLite executemany When Batch Inserting in Python
Batch insert many rows into SQLite with executemany and mock the cursor for isolated tests.
import sqlite3
from unittest.mock import Mock, patch
def insert_users(conn, users):
"""Insert multiple user records using executemany."""
cursor = conn.cursor()
cursor.executemany(
"INSERT INTO users (name, age) VALUES (?, ?)",
users
)
conn.commit()
return cursor.rowcount
if _…How to mock batch commit of transactions in Python
Simulate a transaction batch writer with commit, rollback, and summary logic to test database write patterns without a real database.
import json
from datetime import datetime, timezone
class TransactionBatch:
def __init__(self):
self.pending = []
self.committed = []
self._log = []
def add(self, operation):
self.pending.append(operation)
def commit(self):
if not self.pending:
return …Browse by section
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