Batch Operations

Process multiple items efficiently.

Pattern 1: Sequential with Rate Limiting

import time

def process_batch(items):
    results = []
    for item in items:
        result = api_call(item)
        results.append(result)
        time.sleep(0.1) # Rate limit compliance
    return results

Pattern 2: Parallel Processing

from concurrent.futures import ThreadPoolExecutor

def process_parallel(items, max_workers=10):
    with ThreadPoolExecutor(max_workers=max_workers) as executor:
        results = list(executor.map(api_call, items))
    return results