README.md

Async Batcher

This project provides a Python library to batch the asynchronous requests and handle them in batches.

How to use

To use the library, you need to install the package in your environment. You can install the package using pip:

pip install async-batcher

Then, you can create a new AsyncBatcher class by implementing the process_batch method:

from async_batcher.batcher import AsyncBatcher

class MyAsyncBatcher(AsyncBatcher):
    async def process_batch(self, batch):
        # Process the batch
        print(batch)

# Create a new instance of the `MyAsyncBatcher` class
async_batcher = MyAsyncBatcher(max_batch_size=20)
async_batcher.start()

Benchmark

The benchmark is available in the BENCHMARK.md file.

Use cases

The AsyncBatcher library can be used in any application that needs to handle asynchronous requests in batches, such as:

• Serving machine learning models that optimize the batch processing (e.g. TensorFlow, PyTorch, Scikit-learn, etc.)
• Storing multiple records in a database in a single query to optimize the I/O operations (or to reduce the cost of the database operations, e.g. AWS DynamoDB)
• Sending multiple messages in a single request to optimize the network operations (or to reduce the cost of the network operations, e.g. Kafka, RabbitMQ, AWS SQS, AWS SNS, etc.)