Chr.Avro is an Avro implementation for .NET. It’s designed to serve as a flexible alternative to the Apache implementation and integrate seamlessly with Confluent’s Kafka and Schema Registry clients.
For more information, check out the documentation.
To use the command line interface: Install Chr.Avro.Cli as a global tool:
$ dotnet tool install Chr.Avro.Cli --global
You can invoke the tool using the following command: dotnet-avro
Tool 'chr.avro.cli' (version '10.4.0') was successfully installed.
$ dotnet avro help
Chr.Avro 10.4.0
...
To use the Kafka producer/consumer builders in your project: Add Chr.Avro.Confluent as a project dependency. After that, check out this guide or read on for some other examples.
The CLI can be used to generate Avro schemas for .NET types (both built-in and from compiled assemblies):
$ dotnet avro create -t System.Int32
"int"
$ dotnet avro create -t System.Decimal
{"type":"bytes","logicalType":"decimal","precision":29,"scale":14}
$ dotnet avro create -a out/example.dll -t ExampleRecord
{"name":"ExampleRecord","type":"record","fields":[{"name":"Number","type":"long"}]}
It can also verify that a .NET type can be mapped to a Schema Registry schema (useful for both development and CI):
$ dotnet avro registry-test -a out/example.dll -t ExampleRecord -r http://registry:8081 -i 242
A deserializer cannot be created for ExampleRecord: ExampleRecord does not have a field or property that matches the correlation_id field on example_record.
Extensions to the Confluent.Kafka ProducerBuilder
and ConsumerBuilder
configure Kafka clients to produce and consume Avro-encoded CLR objects:
using Chr.Avro.Confluent;
using Confluent.Kafka;
using Confluent.SchemaRegistry;
using System;
using System.Collections.Generic;
namespace Example
{
class ExampleRecord
{
public Guid CorrelationId { get; set; }
public DateTime Timestamp { get; set; }
}
class Program
{
static void Main(string[] args)
{
var consumerConfig = new ConsumerConfig()
{
BootstrapServers = "broker1:9092,broker2:9092",
GroupId = "example_consumer_group"
};
var registryConfig = new SchemaRegistryConfig()
{
SchemaRegistryUrl = "http://registry:8081"
};
var builder = new ConsumerBuilder<string, ExampleRecord>(consumerConfig);
using (var registry = new CachedSchemaRegistryClient(registryConfig))
{
builder.SetAvroKeyDeserializer(registry);
builder.SetAvroValueDeserializer(registry);
using (var consumer = builder.Build())
{
var result = consumer.Consume(CancellationToken.None);
Console.WriteLine($"Consumed message! {result.Key}: {result.Value.Timestamp}");
}
}
}
}
}
Under the hood, SchemaBuilder
is responsible for generating schemas from CLR types:
using Chr.Avro.Abstract;
using Chr.Avro.Representation;
using System;
namespace Example
{
enum Fear
{
Bears,
Children,
Haskell,
}
struct FullName
{
public string FirstName { get; set; }
public string LastName { get; set; }
}
class Person
{
public Guid Id { get; set; }
public Fear GreatestFear { get; set; }
public FullName Name { get; set; }
}
class Program
{
static void Main(string[] args)
{
var builder = new SchemaBuilder();
var writer = new JsonSchemaWriter();
Console.WriteLine(writer.Write(builder.BuildSchema<double>));
// "double"
Console.WriteLine(writer.Write(builder.BuildSchema<DateTime>));
// "string"
Console.WriteLine(writer.Write(builder.BuildSchema<Fear>));
// {"name":"Fear","type":"enum","symbols":["Bears","Children","Haskell"]}
Console.WriteLine(writer.Write(builder.BuildSchema<Person>));
// {"name":"Person","type":"record"...}
}
}
}
For more complex examples, see the examples directory:
Check out the contribution guidelines prior to opening an issue or creating a pull request. More information about the benchmark applications and documentation site can be found in their respective directories.