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The Batcher

When inserting thousands of records, individual await repo.create() calls are slow due to network latency. The Batcher queues items and flushes them in chunks, reducing network round-trips drastically. 
from fluxcrud.async_patterns import Batcher

# Usage via context manager on Repository
async with repo.batch_writer(session, batch_size=100) as writer:
    for i in range(5000):
        # Adds to buffer, auto-flushes at 100
        await writer.add({"name": f"Item {i}"})

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ParallelExecutor

Processing many independent tasks (like calling external APIs or multiple distinct DB selects) sequentially is inefficient. ParallelExecutor runs them concurrently but with a limit (Semaphore) to avoid crashing your DB or exhausting connections. 
from fluxcrud.async_patterns import ParallelExecutor

tasks = [lambda: api.fetch_data(i) for i in ids]

# Run at most 50 at once
results = await ParallelExecutor.gather_limited(limit=50, tasks=tasks)