lifegraph-json

Dependency-light JSON toolkit in Rust with owned, borrowed, tape, and compiled-schema paths.

Why

lifegraph-json is aimed at workloads where generic JSON trees leave performance on the table:

• fast parse-and-inspect flows
• low-allocation parsing
• repeated lookup on wide objects
• repeated serialization of known object shapes

It uses no external runtime dependencies.

Features

• manual JSON serializer
• owned parser
• borrowed parser
• tape parser for fast structural access
• lazy hashed object indexing
• compiled lookup keys for repeated field queries
• compiled object and row schemas for repeated-shape serialization

Example: tape parsing with compiled lookup keys

use lifegraph_json::{parse_json_tape, CompiledTapeKeys, TapeTokenKind};

let input = r#"{"name":"hello","flag":true}"#;
let tape = parse_json_tape(input)?;
let root = tape.root(input).unwrap();
let index = root.build_object_index().unwrap();
let indexed = root.with_index(&index);
let keys = CompiledTapeKeys::new(&["name", "flag"]);
let kinds = indexed
    .get_compiled_many(&keys)
    .map(|value| value.unwrap().kind())
    .collect::<Vec<_>>();

assert_eq!(kinds, vec![TapeTokenKind::String, TapeTokenKind::Bool]);
# Ok::<(), lifegraph_json::JsonParseError>(())

Example: compiled row serialization

use lifegraph_json::{CompiledRowSchema, JsonValue};

let schema = CompiledRowSchema::new(&["id", "name"]);
let row1 = [JsonValue::from(1u64), JsonValue::from("a")];
let row2 = [JsonValue::from(2u64), JsonValue::from("b")];

let json = schema.to_json_string([row1.iter(), row2.iter()])?;
assert_eq!(json, r#"[{"id":1,"name":"a"},{"id":2,"name":"b"}]"#);
# Ok::<(), lifegraph_json::JsonError>(())

Current performance direction

On local release-mode comparisons against serde_json, the strongest wins so far have been in specialized paths such as:

• tape parsing on medium/report-like payloads
• deep structural parses
• wide-object repeated lookup with indexed compiled keys

This crate is best viewed as a performance-oriented JSON toolkit for specific workloads, not a blanket replacement for serde_json.

Status

Current focus:

• correctness
• benchmarked fast parse and lookup paths
• zero/low-allocation access modes
• repeated-shape serialization