The Detroit Post
Saturday, 16 October, 2021

Rust Json

author
David Lawrence
• Wednesday, 21 October, 2020
• 7 min read

Accepted types are: FN, mod, struct, ENIM, trait, type, macro, and coast. JSON has become one of the most common data exchange formats on the web, so it’s critical that server-side languages have good support for it.

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(Source: stackoverflow.com)

Contents

The large ecosystem built around serve makes it the top choice for web servers written in Rust. That’s all you need to do to make Person serializable and serializable into any data format with a crate that supports serve.

In more complete examples it would be inferred from things like function argument types when passing around person. Serialization can fail in a number of ways, so serve_ Jason ::from_str returns a Result to let us handle those failures.

Errors from serve_ Jason are quite rich and give us enough information to pin down exactly what went wrong. For example, running the same code as above with the age field removed triggers the following error message.

Instead of using unwrap, you can extract the same information seen above by using the methods provided by serve_ Jason ::Error and handle the error gracefully whenever possible. The places where you use JSON are almost always at system boundaries where you can receive all kinds of unexpected inputs.

Having first-class, consistent support for error handling makes dealing with these system boundaries much more enjoyable and reliable. To show them in action, we’ll create a server that calculates the perimeter and area of various shapes.

(Source: siciarz.net)

By default, the variants of Calculation will be converted to the JSON strings Perimeter and Area. By default, this is represented by an externally tagged JSON object and adds nesting that we don’t want.

As you might have noticed, this type adds another layer of nesting that doesn’t match our desired JSON format. I encourage you to play around with the input JSON to see how robust the type validation is and how helpful the errors are.

Since we’re enforcing invariants in the type system, our logic becomes simple and easy to reason about. In this case, it is a pure function that takes a Request and returns a Response, making it testable and completely decoupled from any web framework.

One nice thing about serve is that it doesn’t force you to couple your logic and types to it since the derive macros don’t modify existing things; they purely add trait implementations. Lots of crates contain code that is generic over types that implement the Serialize or Deserialize traits.

Our handler already has a type signature that resembles an HTTP request-response cycle, so we will be able to plug it into any web framework that integrates with serve. Don’t worry too much about what’s going on here; the important part is the closure inside of map.

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(Source: developpaper.com)

At this point, we can try sending POST requests with a JSON body to localhost:5000 to test whether everything, including error messages, now works over our HTTP API. One key takeaway from this example is that you can use Rust types that don’t have the exact structure of the JSON you interact with.

When using more advanced features of Rust ’s type system that more naturally fit the problem than a simple key-value object, we are free to use them without worrying about additional boilerplate. Although it is usually best to use your own types and derive the Serialize and Deserialize traits with serve_ Jason, sometimes you either can’t or don’t want to.

This essentially allows you to write JSON directly in Rust source code. If you have a Value representing an object or array, you can access the fields using Value::get, similar to DEC::get and Yashmak::get.

Since things like web frameworks are generic over the Serialize and Deserialize traits, which serve_ Jason ::Value implements, you can use these Value s without any additional friction. Is extremely flexible, so you should be able to handle any JSON data with ergonomic, minimal boilerplate Rust.

To put it simply, JSON support shouldn’t be a concern for any Rust developer. Instead of guessing why problems happen, you can aggregate and report on what state your application was in when an issue occurred.

(Source: tech.aptpod.co.jp)

Serve is a framework for serializing and DE serializing Rust data structures efficiently and generically. JSON is a ubiquitous open-standard format that uses human-readable text to transmit data objects consisting of key-value pairs.

There are three common ways that you might find yourself needing to work with JSON data in Rust. An unprocessed string of JSON data that you receive on an HTTP endpoint, read from a file, or prepare to send to a remote server.

Maybe you want to check that some JSON data is valid before passing it on, but without knowing the structure of what it contains. When you expect all or most of your data to conform to a particular structure and want to get real work done without JSON's loosey-goosey nature tripping you up.

Serve JSON provides efficient, flexible, safe ways of converting data between each of these representations. The Value representation is sufficient for very basic tasks but can be tedious to work with for anything more significant.

Error handling is verbose to implement correctly, for example imagine trying to detect the presence of unrecognized fields in the input data. The compiler is powerless to help you when you make a mistake, for example imagine typing v as v in one of the dozens of places it is used in your code.

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(Source: jaxenter.de)

This includes built-in Rust standard library types like DEC and Yashmak, as well as any structs or ends annotated with #. The IDE can autocomplete field names to prevent typos, which was impossible in the serve_ Jason ::Value representation.

Macro is that variables and expressions can be interpolated directly into the JSON value as you are building it. Serve will check at compile time that the value you are interpolating is able to be represented as JSON.

This is amazingly convenient, but we have the problem we had before with Value which is that the IDE and Rust compiler cannot help us if we get it wrong. This includes built-in Rust standard library types like DEC and Yashmak, as well as any structs or ends annotated with #.

Serve is one of the most widely used Rust libraries so any place that Crustaceans congregate will be able to help you out. It's acceptable to file a support issue in this repo, but they tend not to get as many eyes as any of the above and may get closed without a response after some time.

As long as there is a memory allocator, it is possible to use serve_ Jason without the rest of the Rust standard library. The example below shows how to serialize a simple Rust primitive data type i32 into a JSON string, and then deserialize it back.

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(Source: www.dakkadakka.com)

You can pass this JSON string to other Rust programs or Internet applications written in other languages. Here are more examples showing the serialization and serialization of Rust primitive data types.

Like XML, it allows encoding structured data in a text format that can be easily read by humans. Its simple syntax and native compatibility with JavaScript have made it a widely used format.

A simple JSON document encoding a person, their age, address and phone numbers could look like Rust provides a mechanism for low boilerplate encoding & decoding of values to and from JSON via the serialization API.

The Rust compiler provides an annotation to automatically generate the code for these traits: # You can also use the Jason ::Encoder object, which implements the Encoder trait.

The examples below use the Towson trait to generate the JSON string, which is required for custom mappings. While this library is the standard way of working with JSON in Rust, there is a next-generation library called Serve that's in the works (it's faster, overcomes some design limitations of rustc-serialize and has more features).

actix rust rest postgresql api part tutorial rs main
(Source: turreta.com)

You might consider using it when starting a new project or evaluating Rust JSON performance. Encoder A structure for implementing serialization to JSON.

PrettyJsonStack A Stack represents the current position of the parser in the logical structure of the JSON stream. DecoderErrorEncoderErrorErrorCode The errors that can arise while parsing a JSON stream.

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