obm_confluent_blog VS Clippy

So what is actually the Schema Registry? And how does it help to make sense of binary data? In essence Schema Registry is an application with some Rest endpoints, from which schema's can be registered and retrieved. It used to only support Apache Avro. Later support for Protobuf and JSON Schema was added. Part of the same Github project, and what makes Schema Registry easy to use, is a Collection of Java classes that are used to go from bytes to typed objects and vice versa. There are several classes that support Kafka Streams and ksqlDB next to the more low level Kafka [Producer(https://kafka.apache.org/documentation/#producerapi) and Consumer clients. There are more advanced use cases, but basically you supply the url for the Schema Registry, and the library will handle the rest. For producing data this will mean optionally register a new schema too get the correct id. The consumer will use the encoded id to fetch the schema used to produce the data. It can also be used with other frameworks like Spring Cloud Stream. For example in the Kotlin Command Handler by using the SpecificAvroSerde class. You might need to set additional properties to get this working.

I couldn't find it in the API guidelines either. From what I understand, the idea is that any trait bounds, which includes generic type parameter bounds and lifetime bound on a type (struct or enum) would be repeated back in the impl block

there is a nice discussion on this issue here: https://github.com/rust-lang/rust-clippy/issues/1689

You should not blindly follow clippy lints. They are sometimes wrong. Another example https://github.com/rust-lang/rust-clippy/issues/9782 .

I often write () = f() to assert that f() is unit. Unfortunately clippy warns on such code ( https://github.com/rust-lang/rust-clippy/issues/9048 ). There are very recent pull requests for this bug, so hopefully this bug will be fixed very soon. But meanwhile I invented this workaround: [()] = [f()] :)

Apart from running clippy on many projects being essential, clippy is also an exceptionally welcoming project, no matter your prior knowledge.

clippy is a great place to get started :) though it isn't exactly new.

clippy is also pretty compiler-adjacent and unlike rust-analyzer uses rustc's internal APIs. Don't let the size of the code base scare you off! It's actually feasible for a newcomer to contribute even such a substantial change as a new lint, and we have issues labeled as "good first issue" that come with mentorship, so you don't need to go it alone.

Yes, you could use it to write a lint. Although you might find it easier to just fork Clippy and add your own lints to their existing framework.

Check out the readme for more information.

They are two of my favorite Rust tools. If you haven’t tried them yet, I highly recommend giving them a try. Clippy can detect various lints in your code and guide you towards writing more idiomatic code. To install Clippy, simply run rustup component add clippy, and to run it within your workspace, execute cargo clippy. For more details, visit Clippy’s GitHub repository.