serde
A generic framework for serializing and deserializing Rust data structures efficiently and safely.
Repository Health
Technical Analysis
Serde is the de facto standard serialization framework for Rust, splitting the problem into two halves: data structures that know how to serialize and deserialize themselves via the Serialize and Deserialize traits, and data formats that know how to turn structured data into bytes and back. The #[derive(Serialize, Deserialize)] macros generate trait implementations at compile time, so most projects never hand-write conversion code.
Because the trait layer is decoupled from any specific wire format, the same derived struct can be serialized to JSON, YAML, TOML, MessagePack, CBOR, Bincode, and dozens of other formats implemented by the surrounding Serde ecosystem, with zero-cost abstractions that let the compiler optimize away the indirection entirely.
What You Get
- Serialize and Deserialize traits with a derive macro (
#[derive(Serialize, Deserialize)]) for automatic, compile-time codegen on structs and enums - A data-model abstraction (29 self-describing types) that decouples your Rust types from any specific wire format
- no_std and no_alloc support via feature flags, making it usable on embedded and constrained targets
- Fine-grained field-level attributes (
#[serde(rename = "...")],skip_serializing_if,default,flatten,with) for controlling exactly how fields map to the wire format - Compatibility with dozens of independently maintained format crates (serde_json, serde_yaml, bincode, rmp-serde, toml, and more) that all plug into the same trait layer
Common Use Cases
- Parsing and emitting JSON payloads for HTTP APIs and web services
- Loading and validating application configuration from TOML or YAML files
- Encoding compact binary wire formats for RPC and network protocols
- Persisting application state or cache entries to disk in a structured format
- Converting between in-memory Rust types and external schemas (e.g. AWS Parameter Store, environment variables) via community format crates
Under The Hood
Architecture The workspace splits the public serde crate from serde_core, which holds the actual trait definitions and blanket implementations (~12,000 lines across ser/mod.rs, de/mod.rs, de/impls.rs, de/value.rs) so that serde_derive’s generated code and third-party format crates can depend on a stable core without pulling in the thin re-export layer. At runtime, a value’s Serialize::serialize call takes a format-supplied Serializer and drives it through calls like serialize_struct/serialize_map; deserialization mirrors this with a Deserializer handing data to a Visitor that builds the target type. serde_core/src/private/content.rs implements an intermediate buffered Content representation that powers advanced features such as #[serde(untagged)] enums and #[serde(flatten)], which need to peek at data before committing to a concrete deserialization path.
Tech Stack Pure Rust, edition 2021, with an MSRV of 1.56 for serde and 1.71 for serde_derive. The proc-macro derive layer depends on proc-macro2, quote, and syn 2.x (pinned at the workspace level), while the core trait crate has zero required dependencies, keeping it embeddable via no_std/no_alloc feature flags. The five-crate Cargo workspace (serde, serde_core, serde_derive, serde_derive_internals, test_suite) is built and tested through a single GitHub Actions workflow (.github/workflows/ci.yml).
Code Quality The test_suite crate contains 150 test files covering derive macro output, UI/compile-fail cases, byte handling, unstable features, and regression fixes, plus a dedicated no_std sub-crate that verifies the no-std build path compiles independently. Documentation density is unusually high for a systems library — serde_core’s ser/mod.rs and de/mod.rs alone contain over 2,700 lines of doc comments. Error handling is idiomatic throughout: Result<T, Self::Error> with an associated error type is threaded through every trait method rather than panicking, and naming stays consistent with Rust API guidelines (Serialize/Deserialize, Serializer/Deserializer, Visitor).
API Design The common case requires only serde = { version = "1", features = ["derive"] } plus a format crate and a #[derive(Serialize, Deserialize)] attribute — no boilerplate beyond that. The ~5% of cases needing custom behavior are handled through named, documented attributes (rename, default, skip_serializing_if, flatten, with) rather than requiring hand-written trait impls, and the consistent trait vocabulary is reused verbatim by every downstream format crate (serde_json, serde_yaml, bincode, etc.), so learning it once transfers across the entire ecosystem.
Used by 114 apps in this directory
Onyx
AI Agents · AI Assistants · Knowledge Management
Self-hostable AI platform with agentic RAG, 50+ connectors, deep research, code execution, and support for every major LLM provider.
open-pencil
AI Design Tools · Design Tools
An open-source design editor that reads native Figma files, ships a built-in AI assistant with 100+ design tools, and offers real-time serverless collaboration — all without giving up your files.
codex
AI Code Assistants · Developer Tools
OpenAI's open-source CLI coding agent that reads, edits, and runs code in your terminal using natural language prompts.
OpenBB
Analytics · Databases · Invoicing Finance
The AI Workspace for Finance: Connect Data, Run AI Agents, Build Analytics
OpenClaw
AI Agents · AI Assistants
An open-source AI assistant that runs on your own hardware and meets you in Discord, Slack, WhatsApp, iMessage, Telegram, and 20+ other channels, with native apps for every major platform.
openduck
Data Engineering · Databases
OpenDuck brings MotherDuck-style cloud capabilities to self-hosted DuckDB — attach remote databases, run hybrid queries across local and remote nodes, and own your data with an open gRPC and Arrow IPC protocol.
openfootmanager
Game Development
A free and open source football management simulation game built with Rust and Tauri, inspired by Football Manager.
OpenPencil
AI Design Tools
An open-source, AI-native vector design tool with concurrent agent teams, design-as-code, a built-in MCP server, and multi-model intelligence — a distinct project from the similarly-named Figma-file-reading "open-pencil" editor.
OpenShell
AI Agents · Developer Tools
The safe, private runtime that lets autonomous AI agents operate in sandboxed environments governed by declarative YAML policies — blocking data exfiltration, credential leaks, and unauthorized network activity before they happen.