jetro

Jetro is a library for querying, transforming, and comparing JSON. It provides a compact expression language, a bytecode VM with caching.

Jetro has minimal dependencies and operates on top of serde_json.

This project is in experimental phase — significant changes may occur.

---

Quick start

use jetro::Jetro;
use serde_json::json;

let j = Jetro::new(json!({
    "store": {
        "books": [
            {"title": "Dune",       "price": 12.99},
            {"title": "Foundation", "price":  9.99}
        ]
    }
}));

let titles = j.collect("$.store.books.filter(price > 10).map(title)").unwrap();
assert_eq!(titles, json!(["Dune"]));

One-shot evaluation (tree-walker, no VM caching):

let result = jetro::query("$.store.books.len()", &doc).unwrap();

---

Rust API tour

Progressive walk through the Rust API over one rich payload — simple field access through compile-time macros. Every snippet runs against this document:

use jetro::prelude::*;

let doc = json!({
  "store": {
    "name": "Nova Books",
    "currency": "USD",
    "books": [
      {"id": "b1", "title": "Dune",        "author": "Frank Herbert",  "price": 12.99, "year": 1965, "tags": ["sci-fi","classic"],  "stock": 14, "ratings": [5,5,4,5,3]},
      {"id": "b2", "title": "Foundation",  "author": "Isaac Asimov",   "price":  9.99, "year": 1951, "tags": ["sci-fi","classic"],  "stock":  0, "ratings": [5,5,5]},
      {"id": "b3", "title": "Neuromancer", "author": "William Gibson", "price": 19.50, "year": 1984, "tags": ["cyberpunk"],         "stock":  3, "ratings": [4,5,4,5]},
      {"id": "b4", "title": "The Hobbit",  "author": "J.R.R. Tolkien", "price": 14.25, "year": 1937, "tags": ["fantasy","classic"], "stock": 22, "ratings": [5,5,5,5,4,5]},
      {"id": "b5", "title": "Hyperion",    "author": "Dan Simmons",    "price": 18.00, "year": 1989, "tags": ["sci-fi"],            "stock":  7, "ratings": [5,5,4]}
    ],
    "customers": [
      {"id": "c1", "name": "Ada Lovelace", "tier": "gold",   "credits": 250.0},
      {"id": "c2", "name": "Alan Turing",  "tier": "silver", "credits":  40.0},
      {"id": "c3", "name": "Grace Hopper", "tier": "gold",   "credits": 180.0}
    ],
    "orders": [
      {"id": "o1", "customer_id": "c1", "items": [{"book_id":"b1","qty":2},{"book_id":"b4","qty":1}], "status": "paid"},
      {"id": "o2", "customer_id": "c2", "items": [{"book_id":"b3","qty":1}],                          "status": "pending"},
      {"id": "o3", "customer_id": "c1", "items": [{"book_id":"b5","qty":3}],                          "status": "paid"}
    ]
  }
});

let j = Jetro::new(doc.clone());

Jetro holds a thread-local VM; collect() compiles each unique expression once (then reuses the bytecode + pointer cache), so rerunning the same or similar query is essentially free.

1. Field access

assert_eq!(j.collect("$.store.name")?,              json!("Nova Books"));
assert_eq!(j.collect("$.store.books[0].author")?,   json!("Frank Herbert"));
assert_eq!(j.collect("$.store.books[-1].title")?,   json!("Hyperion"));

2. Filter + map

let cheap = j.collect("$.store.books.filter(price < 15).map(title)")?;
// ["Dune", "Foundation", "The Hobbit"]

3. Aggregations

let in_stock_total = j.collect("$.store.books.filter(stock > 0).sum(price)")?;
let mean_price     = j.collect("$.store.books.map(price).avg()")?;
let well_rated     = j.collect("$.store.books.filter(ratings.avg() >= 4.5).len()")?;

4. Shaped projections

Build a new object per element:

let summary = j.collect(r#"
    $.store.books.map({
        title,
        mean_rating: ratings.avg(),
        in_stock:    stock > 0
    })
"#)?;

5. Sort, group, membership

let scifi_by_year = j.collect(r#"
    $.store.books
      .filter("sci-fi" in tags)
      .sort_by(year)
      .map({year, title})
"#)?;

let by_first_tag = j.collect("$.store.books.group_by(tags[0])")?;

6. Comprehensions

let out_of_stock = j.collect("[b.title for b in $.store.books if b.stock == 0]")?;
// ["Foundation"]

let id_to_title = j.collect("{b.id: b.title for b in $.store.books}")?;

7. Let bindings + f-strings

let headline = j.collect(r#"
    let top = $.store.books.sort_by(ratings.avg()).reverse()[0] in
      f"Top-rated: {top.title} ({top.ratings.avg():.2f})"
"#)?;
// "Top-rated: The Hobbit (4.83)"

8. Pipelines

| passes the left value through the right expression as @:

let avg   = j.collect("$.store.books.map(price) | @.avg()")?;
let shout = j.collect("$.store.books[0].title | upper")?;  // "DUNE"

9. Patch blocks

In-place updates that compose like any other expression:

let discounted = j.collect(r#"
    patch $ {
        store.books[*].price:                  @ * 0.9,
        store.books[* if stock == 0].available: false,
        store.books[* if year < 1960].vintage:  true
    }
"#)?;

Patch-field syntax: path: value when predicate?. Paths start with an identifier and may include .field, [n], [*], [* if pred], and ..field. DELETE removes the matched key.

10. Custom methods

Register Rust code as a first-class method:

use jetro::{Method, MethodRegistry};
use jetro::eval::{Env, Val};
use jetro::EvalError;

struct Percentile;
impl Method for Percentile {
    fn name(&self) -> &str { "percentile" }
    fn call(&self, subject: &Val, args: &[Val], _env: &Env) -> Result<Val, EvalError> {
        let xs = subject.as_array().ok_or_else(|| EvalError("not an array".into()))?;
        let p = args.first().and_then(|v| v.as_f64()).unwrap_or(50.0) / 100.0;
        let mut v: Vec<f64> = xs.iter().filter_map(|x| x.as_f64()).collect();
        v.sort_by(|a, b| a.partial_cmp(b).unwrap());
        let i = ((v.len() as f64 - 1.0) * p).round() as usize;
        Ok(Val::from(v[i]))
    }
}

let mut reg = MethodRegistry::new();
reg.register(std::sync::Arc::new(Percentile));
let p90 = jetro::query_with("$.store.books.map(price).percentile(90)", &doc, reg.into())?;

11. Typed Expr<T>

Expressions carry a phantom return type:

let titles: Expr<Vec<String>> = Expr::new("$.store.books.map(title)")?;
let upper:  Expr<Vec<String>> = Expr::new("@.map(upper)")?;

// `|` composes expressions end-to-end
let pipeline = titles | upper;
let shouted  = pipeline.eval(&doc)?;

12. VM caching

Every query through Jetro::collect or VM::run_str hits two caches:

• Program cache: expr string → Arc<[Opcode]>. Each unique expression is parsed + compiled exactly once.
• Pointer cache: resolved field paths keyed by (program_id, doc_hash). Structural queries short-circuit straight to the leaves on repeat calls.

Rerunning a workload over fresh documents of the same shape is effectively free after the first call. For one-shot queries use jetro::query(expr, &doc) — it skips the VM entirely.

13. Recursive descent + drill-down chains

$..field walks every descendant level. Combine with filters and projections:

let stats = j.collect(r#"
    let prices = $..price.filter(@ kind number) in
      {min: prices.min(), max: prices.max(), sum: prices.sum(), n: prices.len()}
"#)?;

let keyed = j.collect(r#"
    $..id.filter(@ kind string).map({id: @, kind: @.slice(0, 1)})
"#)?;

14. Cross-join via nested comprehensions

Two generators produce the cartesian product; the if filter keeps only matching pairs:

let receipts = j.collect(r#"
    [
      {
        order:    o.id,
        buyer:    ($.store.customers.filter(id == o.customer_id))[0].name,
        title:    ($.store.books.filter(id == li.book_id))[0].title,
        qty:      li.qty,
        subtotal: ($.store.books.filter(id == li.book_id))[0].price * li.qty
      }
      for o  in $.store.orders
      for li in o.items
      if o.status == "paid"
    ]
"#)?;

Three nested loops + three lookups folded into one compiled program. Hits the pointer cache on repeat calls.

15. Layered patch transforms

One patch block stacks path-scoped clauses. Each clause runs on the patched result of the previous one:

let restocked = j.collect(r#"
    let tagged = patch $ {
        store.books[* if stock < 5].reorder:              true,
        store.books[* if tags.includes("classic")].badge: "Vintage",
        store.books[0].title:                             @.upper()
    }
    in patch tagged {
        store.books[* if stock == 0]: DELETE
    }
"#)?;

Two filter layers: [* if pred] filters per element against the element's own fields; when pred on a field is evaluated against root $. Chain blocks with let ... in patch ... when a later mutation needs to see earlier output.

16. Engine — shared VM across threads

Jetro gives each thread its own VM. Engine is a Send + Sync handle around a Mutex<VM> so one warm cache services many workers:

use jetro::prelude::*;
use std::sync::Arc;

let engine = Engine::new();                         // Arc<Engine>
let shared = Arc::clone(&engine);

std::thread::spawn(move || {
    // Compile + pointer caches shared with the spawner.
    shared.run("$.store.books.len()", &doc).unwrap();
}).join().unwrap();

First call compiles and fills both caches; every subsequent thread hitting the same expression skips to execution.

17. Compile-time expressions — jetro!

Enable the macros feature. Expressions get a full pest parse at compile time, with errors pointing at the exact macro call-site. Returns a typed Expr<Value>:

use jetro::jetro;

let avg_price = jetro!("$.store.books.map(price).avg()");
let n_classic = jetro!(r#"$.store.books.filter("classic" in tags).len()"#);

assert_eq!(avg_price.eval_raw(&doc)?, json!(14.946));
assert_eq!(n_classic.eval_raw(&doc)?, json!(3));

Unbalanced parens, unterminated strings, unknown operators — build failures, not runtime errors.

18. #[derive(JetroSchema)] — attribute-driven schemas

Pair a type with a fixed set of named expressions. The derive emits EXPRS, exprs(), and names(). Each #[expr(...)] line is grammar-checked at compile time, so an invalid expression in a schema never ships.

use jetro::JetroSchema;

#[derive(JetroSchema)]
#[expr(titles       = "$.store.books.map(title)")]
#[expr(mean_rating  = "$.store.books.map(ratings.avg()).avg()")]
#[expr(out_of_stock = "[b.title for b in $.store.books if b.stock == 0]")]
struct StoreView;

assert_eq!(StoreView::names(), &["titles", "mean_rating", "out_of_stock"]);
for (name, src) in StoreView::exprs() {
    let val = jetro::query(src, &doc)?;
    println!("{name}: {val}");
}

---

Feature flags

Feature	Pulls in	Unlocks
macros	jetro-macros companion crate	jetro!(...) macro, #[derive(JetroSchema)]

Cargo.toml:

[dependencies]
jetro = { version = "0.3", features = ["macros"] }

---

Syntax

Root and context

Token	Meaning
$	Document root
@	Current item (lambdas, pipes, comprehensions, patch paths)

Navigation

$.field                // child field
$.a.b.c                // nested
$.user?.name           // null-safe field
$.items[0]             // array index
$.items[-1]            // last
$.items[2:5]           // slice [2, 5)
$.items[2:]            // tail
$.items[:5]            // head
$..title               // recursive descent

Literals

null  true  false
42    3.14
"hello"  'world'
f"Hello {$.user.name}!"     // f-string with interpolation
f"{$.price:.2f}"            // format spec
f"{$.name | upper}"         // pipe transform

Operators

==  !=  <  <=  >  >=         // comparison
~=                           // fuzzy match (case-insensitive substring)
+  -  *  /  %                // arithmetic
and  or  not                 // logical
$.field ?| "default"         // null coalescing

Methods

All operations are dot-called methods:

$.books.filter(price > 10)
$.books.map(title)
$.books.sum(price)
$.books.filter(price > 10).count()
$.books.sort_by(price).reverse()
$.users.group_by(tier)
$.items.map({name, total: price * qty})

Comprehensions

[book.title for book in $.books if book.price > 10]
{user.id: user.name for user in $.users if user.active}

Let bindings

let top = $.books.filter(price > 100) in
  {count: top.len(), titles: top.map(title)}

Lambdas

$.books.filter(lambda b: b.tags.includes("sci-fi"))

Kind checks

$.items.filter(price kind number and price > 0)
$.data.filter(deleted_at kind null)

Pipelines

| passes the left value through the right expression as @:

$.name | upper
$.price | (@ * 1.1)

Patch blocks

In-place updates with block-form syntax. Each clause matches a path and produces either a replacement value or DELETE:

patch $ {
    books[*].price:             @ * 1.1,
    books[* if stock == 0]:     DELETE,
    meta.updated_at:            now()
}

---

Architecture

Expression engine

Everything below is shipped by the jetro-core crate and re-exported here.

• grammar.pest + parser.rs — pest PEG grammar → ast::Expr
• eval/mod.rs — tree-walking evaluator (reference semantics)
• eval/value.rs — Val type: Arc-wrapped compound nodes, O(1) clones
• eval/func_*.rs — built-in methods grouped by domain (strings, arrays, objects, paths, aggregates, csv)
• eval/methods.rs — Method trait + MethodRegistry for user-registered methods
• vm.rs — bytecode compiler + stack machine; 10 peephole passes; compile and pointer caches
• graph.rs — multi-document query primitive (merges named nodes into a virtual root)
• analysis.rs / schema.rs / plan.rs / cfg.rs / ssa.rs — optional IRs (type/nullness/cardinality, shape inference, logical plan, CFG, SSA numbering)

See jetro-core/README.md for a full technical walkthrough: AST variants, opcode set, peephole passes, cache invariants.

Companion crates

• jetro-core — engine (this crate re-exports it)
• jetro-macros — jetro!() + #[derive(JetroSchema)] (feature = "macros")

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License

MIT. See LICENSE.