Overview

In TypeScript, turning data into JSON and back is built into the language — JSON.parse and JSON.stringify are always there. Rust takes a different route: serialization lives in a single, dominant framework called Serde (a contraction of serialize/deserialize). Instead of one hard-coded JSON object, Serde splits the problem into data types (your structs and enums, which implement the Serialize/Deserialize traits) and data formats (JSON, TOML, YAML, MessagePack, …, each a separate crate) that meet through a shared data model. The payoff: you annotate a type once and get every format for free — and unlike JSON.parse, deserialization validates against a real type and returns a Result instead of an unchecked any. This section takes you from that mental model through derive macros, attributes, dynamic JSON, alternative formats, fully hand-written (de)serialization, and performance.

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What You’ll Learn

• How JSON.parse/JSON.stringify map onto Serde’s Serialize/Deserialize traits, and the data-model architecture that lets one type target every format
• How to set up serde (with features = ["derive"]) and serde_json, and round-trip values with to_string/from_str
• What #[derive(Serialize, Deserialize)] actually generates for structs and enums
• How structs map to JSON, including nested types, Vec/HashMap, Option fields, and the four enum representations (externally/internally/adjacently tagged and untagged)
• How to work with dynamic, schema-less JSON via serde_json::Value and the json! macro — and when to prefer typed structs instead
• The common Serde attributes — rename, rename_all, skip, skip_serializing_if, default, flatten, tag, with — and what each controls
• How the same derived type serializes to TOML, YAML, MessagePack, bincode, and CSV through the Serde ecosystem
• How to hand-write Serialize/Deserialize, use serialize_with/deserialize_with, and apply remote derive for types you do not own
• How to make serialization fast: borrowing (&str, #[serde(borrow)]), zero-copy parsing, streaming, avoiding Value, and reusing buffers

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Topics

Topic	Description
Serde Intro	JSON.parse/JSON.stringify → Serde; the Serialize/Deserialize traits and the data-model architecture (data types ↔ formats).
Serde Basics	Setting up serde (features = ["derive"]) and serde_json; the to_string/from_str round-trip, compile-verified.
Deriving Serialize/Deserialize	#[derive(Serialize, Deserialize)] on structs and enums, and what the macros generate.
Structs and JSON	Structs ↔ JSON: nested types, Vec/HashMap, Option fields, and the four enum representations.
Dynamic JSON	Schema-less JSON with serde_json::Value, the json! macro, indexing, and when to use Value vs typed structs.
Serde Attributes	#[serde(rename, rename_all, skip, skip_serializing_if, default, flatten, tag, with)] and the other everyday attributes.
Other Formats	The same data in other formats: TOML, YAML (serde_norway), MessagePack (rmp-serde), bincode, and CSV.
Custom Serialization	Hand-written Serialize/Deserialize, serialize_with/deserialize_with, and remote derive.
Performance	Borrowing (&str, #[serde(borrow)]), zero-copy, streaming, avoiding Value, and buffer reuse.

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Learning Objectives

By the end of this section, you will be able to:

• Explain how Serde’s data-type/data-format split differs from TypeScript’s single built-in JSON object, and why it makes types format-agnostic
• Add and configure serde and serde_json, and round-trip your own types with to_string, to_string_pretty, and from_str
• Derive Serialize/Deserialize for structs and enums and reason about the code the macros emit
• Map realistic API payloads — nested objects, collections, optional fields, and discriminated unions — to Rust types and back
• Manipulate untyped JSON with Value and the json! macro, and decide deliberately when typed structs are the better tool
• Reshape the wire format with Serde attributes without changing your idiomatic Rust field names
• Serialize the same type to TOML, YAML, MessagePack, bincode, and CSV by swapping the format crate
• Write Serialize/Deserialize by hand when the derive is not enough, including for types you do not own
• Profile and tune serialization with borrowing, zero-copy, streaming, and buffer reuse

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Prerequisites

• Section 08: Error Handling — Serde’s from_str/to_string return Result, and deserialization errors are values you handle with ?, match, or anyhow/thiserror. The error-handling vocabulary from Section 08 is assumed throughout.
• Helpful but not required: Section 09: Generics & Traits — Serialize/Deserialize are traits, and the derive vs. hand-written distinction lands better once trait basics and the orphan rule are familiar.

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Estimated Time

• Reading: 4-5 hours
• Hands-on Practice: 3 hours
• Exercises: 2 hours
• Total: 8-10 hours

Tip: Read serde-intro → serde-basics → derive-serialize → json as a single connected track — that covers the 90% case of typed JSON. Pull in json-manipulation when you need untyped JSON and attributes when the wire format and your Rust names diverge. Treat other-formats, custom-serialization, and performance as a toolbox to reach for when a specific need arises, rather than something to master up front.

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Next: Section 16: Web APIs → — building HTTP clients and servers, where Serde does the request/response (de)serialization you just learned.