IAsyncEnumerable in C#: A Practical Guide to Streaming APIs

In today’s data-driven world, efficiently handling large datasets and real-time data streams is crucial. C#’s IAsyncEnumerable<T> provides an elegant solution for streaming data, offering a perfect balance between performance and usability. In this guide, we’ll explore how to use IAsyncEnumerable effectively, with practical examples you can try in LINQPad.

What is IAsyncEnumerable?

IAsyncEnumerable<T> is C#’s answer to streaming data efficiently. Think of it as a conveyor belt that delivers items one at a time, exactly when you need them. This approach is particularly useful when dealing with:

Large datasets that would be memory-intensive to load all at once
Real-time data from external sources like APIs or IoT devices
Infinite data streams that need to be processed continuously

Download LINQPad Today

Get started with the most powerful .NET Rapid Progress Tool (RPT) available.

Get LINQPad Premium

Powerful .NET acceleration. Code at the speed of thought.

The Garden Hose Analogy

To understand IAsyncEnumerable, imagine you’re watering plants in your garden. You have two options:

Fill buckets with water and carry them to each plant (traditional approach)
Use a garden hose to water plants directly (streaming approach)

The garden hose method (streaming) is more efficient because:

You don’t need to wait for buckets to fill
You don’t have to carry heavy buckets
Water flows continuously as needed

This is exactly how IAsyncEnumerable works in C#!

How to Use IAsyncEnumerable

The Producer Side

The producer (server) uses IAsyncEnumerable<T> and yield return to stream data:

public async IAsyncEnumerable<batch> BatchesGetStreaming()
{
    // Database connection setup
    using var conn = new SqliteConnection(connectionString);
    await conn.OpenAsync();

    using var cmd = conn.CreateCommand();
    cmd.CommandText = "SELECT b.batchId, b.batchName, bs.batchDate FROM batches_scheduler bs INNER JOIN batches b ON bs.batchId=b.batchId";

    using var reader = await cmd.ExecuteReaderAsync();

    while (await reader.ReadAsync())
    {
        // Stream each record as it becomes available
        yield return new batch(
            reader.GetInt32("batchId"),
            reader.GetString("batchName"),
            DateTime.Parse(reader.GetString("batchDate"))
        );
    }
}

The Consumer Side

The consumer (client) uses await foreach to process the streamed data:

await foreach (var result in BatchesGetStreaming())
{
    // Process each record as it arrives
    result.Dump();
}

When to Use IAsyncEnumerable

1. Large or Infinite Datasets

When dealing with large datasets, loading everything into memory at once can be problematic. IAsyncEnumerable allows you to process data in manageable chunks, reducing memory pressure and improving application responsiveness.

2. External Data Sources

Perfect for scenarios where you can’t predict when the next piece of data will be available:

API responses
IoT sensor readings
Message queue processing
Real-time data feeds

3. Memory Optimization

By processing data as it arrives, you avoid allocating large blocks of memory. This is especially important in cloud environments where memory usage directly impacts costs.

Testing with LINQPad

LINQPad makes it easy to experiment with IAsyncEnumerable. The example above can be run directly in LINQPad, allowing you to:

Test streaming implementations quickly
Visualize data flow
Debug streaming logic
Experiment with different streaming patterns

LINQPad showing IAsyncEnumerable basic example with await foreach and yield return

Best Practices

Error Handling: Always implement proper error handling in your streaming methods
Cancellation: Support cancellation tokens for long-running streams
Resource Management: Use using statements to ensure proper cleanup
Batch Processing: Consider processing items in batches for better performance

Conclusion

IAsyncEnumerable is a powerful tool in the C# developer’s toolkit, especially when working with streaming APIs. Its combination of async/await support and streaming capabilities makes it ideal for modern applications that need to handle data efficiently.

Try the examples in this post using LINQPad to see how IAsyncEnumerable can improve your application’s performance and resource usage. The streaming approach might just be the garden hose solution your application needs!

Ready to dive deeper into IAsyncEnumerable? Try these examples in LINQPad and see how it can transform your database operations!

Want to learn more about LINQPad and how it can supercharge your development workflow? Check out my comprehensive LINQPad course where I cover everything from basic queries to advanced scenarios like the ones shown here.