# 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:
```bash
pip install async-batcher
```
Then, you can create a new `AsyncBatcher` class by implementing the `process_batch` method:
```python
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](https://github.com/hussein-awala/async-batcher/blob/main/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.)
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