@omgbase/oqx

@omgbase/oqx

Generic Object Query eXpression engine for JavaScript.

OQX is a small query language for querying ordinary in-memory JavaScript objects and collections — arrays of records, nested relations, recursive trees — with a readable, declarative syntax. This package is the generic collection kernel: the OQX language semantics separated from any particular data model, exposed as a JavaScript tagged template.

import { oqx } from "@omgbase/oqx";

const people = [
  { name: "Bob", id: 124, title: "Engineer",
    jobs: [{ employer: "Globocorp", start_date: "1984/05/01", end_date: "1990/01/01" },
           { employer: "Globocorp", start_date: "2001/03/01" }] },
  // …
];
const company = "Globocorp";

const employees = oqx`
  name, id, title
  from ${people}
  where jobs exists { employer == ${company} && !end_date }
`;
// → [{ name: "Bob", id: 124, title: "Engineer" }, …]  (current Globocorp employees)

Why a tagged template

Interpolations cross the host/OQX boundary as typed value bindings, never as source text — prepared-statement semantics. A ${…} in from position is the collection being queried; a ${…} in a predicate is an ordinary host value. Because values are never spliced into the query text, they cannot alter the grammar and there is no injection surface. The compiled query is cached by the template's identity and re-runs with fresh bindings each call.

Language tutorial

A query has, in spirit, the shape below — but at the top level the clauses are order-flexible, so you can lead with the projection (SQL-style) or with from, whichever reads better:

[ [select] projection ]    name, id, title: label
from <collection>          from ${people}
[ where <predicate> ]      where age >= 18 && jobs exists { !end }
[ order by <expr> … ]      order by age desc, name
[ follow <relation> … ]    follow children { depth 4 }

The examples below all use this dataset:

const people = [
  { name: "Bob",   id: 124, title: "Engineer", active: true,  age: 41, city: "NYC",
    jobs: [{ employer: "Globocorp", start: "1984", end: "1990" },
           { employer: "Globocorp", start: "2001" }] },
  { name: "Alice", id: 7,   title: "Director", active: true,  age: 52, city: "SF",
    jobs: [{ employer: "Initech",   start: "1999", end: "2005" },
           { employer: "Globocorp", start: "2010", end: "2015" }] },
  { name: "Carol", id: 55,  title: "Analyst",  active: false, age: 29, city: "NYC",
    jobs: [{ employer: "Globocorp", start: "2020" }] },
];

1. Source: from

Every query reads from a source collection. In the tagged template the source is normally an interpolated value; it may also be a named root or a navigation (see data context).

oqx`name from ${people}`;
// [{ name: "Bob" }, { name: "Alice" }, { name: "Carol" }]

2. Projection (select)

List the fields to keep. With no projection you get the raw rows unchanged.

oqx`name, id from ${people}`;
// [{ name: "Bob", id: 124 }, { name: "Alice", id: 7 }, { name: "Carol", id: 55 }]

oqx`from ${people} where active`;                 // no projection → whole objects
// [ <Bob>, <Alice> ]

A projection item can be:

• a bare field — name;
• a dotted navigation, keyed by its last segment — meta.slug produces { slug: … };
• an alias / value expression — label: name, decade: age / 10;
• a nested collection — current: jobs collect { … } (see §6).

oqx`label: name, decade: age / 10 from ${people} where name == "Bob"`;
// [{ label: "Bob", decade: 4.1 }]

An item that is not a plain navigation — a call, arithmetic, a comparison — has no natural key, so it must be aliased (n: size(jobs)), unless the projection is in values mode (next).

The select keyword is optional and works in any position — select name from … is identical to name from … (and hosts select distinct, §6).

values — scalar projection. Ordinarily every row projects to a record. Add values after a projection of exactly one item to get the value itself:

oqx`name values from ${people}`;                       // ["Bob", "Alice", "Carol"]
oqx`name.upper() values from ${people} where age < 30`; // ["CAROL"]  (no alias needed)
oqx`${people} first { name values where age > 50 }`;    // "Alice"

values is a result-shape mode, not a consumer: it works in the top-level projection and inside any collect / first / single block, and composes with distinct (select distinct employer values from ${jobs} is the distinct set of employers as strings, not { employer } records). An alias, if present, is ignored; a lift (^name:) cannot be combined with it.

$value — the current item. Every scope has a current value; $value is that exact value, whatever its type (an object row or a plain scalar). Bare names still navigate it (name ≡ $value.name), so $value matters exactly where there is nothing to navigate: collections of numbers or strings, or handing the whole row somewhere. Together with values this makes scalar collections first-class:

const scores = [10, 60, 70, 45];
oqx`$value values from ${scores} where $value > 50`;              // [60, 70]
oqx`$value values from ${scores} order by $value desc`;           // [70, 60, 45, 10]

const players = [{ name: "Ann", scores: [10, 60, 70] }, { name: "Ben", scores: [45] }];
oqx`name, big: scores collect { $value values where $value > 50 } from ${players}`;
// [{ name: "Ann", big: [60, 70] }, { name: "Ben", big: [] }]

oqx`employee: $value from ${people} where name == "Bob"`;         // [{ employee: <Bob> }]

Inside a nested block $value is the inner item; the enclosing row is ^$value (§3). At the root scope (before any row) it is absent.

entries(x) and $key — records to collections, explicitly. A plain object is not iterable: from ${obj} is one row (the object). entries(obj) converts it into a collection of entries, and inside such a scope the current item is the property's value — $value and bare names read it — while $key is the property's key:

const settings = { theme: "dark", fontSize: 14, autosave: true };
oqx`key: $key, value: $value from entries(${settings})`;
// [{ key: "theme", value: "dark" }, { key: "fontSize", value: 14 }, { key: "autosave", value: true }]
oqx`$key values from entries(${settings}) where $value != "dark"`;   // ["fontSize", "autosave"]

const flags = { beta: { on: true }, legacy: { on: false } };
oqx`$key values from entries(${flags}) where on`;                    // ["beta"]  (bare `on` reads the value)

oqx`name, on: entries(prefs) collect { $key values where $value } from ${users}`;   // as a nested receiver
oqx`name from ${users} where entries(prefs) exists { where $key == "dark" && $value }`;

entries(array) yields numeric index keys, a Map yields its entries, and absence/scalars yield nothing. $key exists only in an entry scope — an ordinary row or array element has no implicit index; entries(arr) is how you ask for one. As a plain value (not a source) entries(x) is an array of { key, value } records.

3. Predicates (where)

where filters rows. The predicate language has comparisons (== != < <= > >=), boolean operators (&& || !) with grouping ( ), membership (in), arithmetic (+ - * / %), and bare truthiness. The where keyword is optional when the leading expression is clearly a predicate.

const min = 40;
oqx`name from ${people} where age >= ${min}`;      // → Bob, Alice
oqx`name from ${people} where city in ${["SF", "LA"]}`;   // → Alice
oqx`name from ${people} where !active`;            // → Carol

Equality is typed and strict (5 == "5" is false); a comparison against an absent (null/undefined) field is simply false rather than an error.

String literals may be double- or single-quoted ("NYC" / 'NYC') and support backslash escapes: \n, \t, \r, \0, and \<any other char> for that character itself (\", \', \\). An unterminated string is a lex error. Note that inside the oqx tagged template JavaScript resolves its own escapes first (the template's cooked strings are what OQX lexes), so \\n in your source reaches OQX as \n. Usually you don't need any of this — interpolate the host value instead (where name == ${name}).

Ranges. A Ruby-style range lo..hi (inclusive) or lo...hi (exclusive high end) is a value, used most often as the right side of in. Either bound may be omitted for an open-ended range (..hi, lo..). Bounds compare with the same ordering rules as </<=, so ranges work over numbers and over ISO-8601 date/time strings alike:

oqx`name from ${people} where age in 40..50`;   // 40 ≤ age ≤ 50
oqx`name from ${people} where age in 40...50`;  // 40 ≤ age < 50 (excludes 50)
oqx`name from ${people} where age in 40..`;     // 40 and up
oqx`name from ${people} where age in ..29`;     // up to and including 29
oqx`label from ${events} where on in "2026-01-01".."2026-03-31"`;   // dates in Q1

Bounds may be interpolated (where age in ${lo}..${hi}). A range membership is not pushed into a storage backend — it is finished in-memory over the rows the backend returns — so it always evaluates by the rules above.

When a range arrives as string data rather than as a literal, range(s) coerces it: where "2026-02-14" in range(window) reads window's string ("2026-01-01..2026-01-31") as a range and tests coverage. A bare field stays a plain string (window == "…" compares text) — range(...) is the explicit opt-in, so a value that merely looks rangey is never silently reinterpreted. A non-range string yields an absent range, so x in range(bad) is just false.

Interpolations are always values, never syntax. where name == ${x} compares against the value of x; a string in x can't inject operators or identifiers.

Scoping: bare names are local, ^ reaches out. A bare identifier resolves against the current row only. If the row lacks that property the value is absent — it never falls through to an enclosing row. To correlate with an enclosing scope you say so explicitly with ^name ("exactly one scope out"; ^^name for two, and so on):

const accounts = [
  { owner: "x", budget: 100, orders: [{ amount: 50 }, { amount: 150 }] },
  { owner: "y", budget: 200, orders: [{ amount: 250 }] },
];
oqx`owner from ${accounts} where orders exists { amount > ^budget }`;
// [{ owner: "x" }, { owner: "y" }]   — `^budget` is the enclosing account's budget

oqx`owner from ${accounts} where orders exists { amount > budget }`;
// []   — a bare `budget` is the ORDER's own budget: absent, so `>` is false

Every reference is therefore decidable from the query text alone. Adding a budget field to the order rows later cannot change what ^budget means, and a typo can't silently capture an outer field. Present-but-falsy values (null, false, 0, "") are read like any other local value — there is no "absent, so look outward" rule to trip over — and ^ always reads exactly N scopes out (one past the root is absent, not the nearest match).

A .member access always navigates the value on its left. Named roots (see data context) live on the root scope, one out from a top-level row: ^people from a person row, ^^people from a row nested one level deeper. A receiver may start with ^ too, which is how a nested consumer runs over a named root or an enclosing row's relation:

execute("name, peers: ^people collect { name where city == ^city && name != ^name } from people", { people });

Correlated subqueries. Because inner and outer rows often share names, the explicit ^ is what makes correlation unambiguous — e.g. each person's siblings, where both the person and the candidates have a parent:

const family = [
  { name: "Ada", parent: "Pat" },
  { name: "Ben", parent: "Pat" },
  { name: "Cy",  parent: "Sam" },
];
oqx`
  name,
  siblings: ${family} collect { name where parent == ^parent && name != ^name }
  from ${family}
`;
// [{ name: "Ada", siblings: [{ name: "Ben" }] },
//  { name: "Ben", siblings: [{ name: "Ada" }] },
//  { name: "Cy",  siblings: [] }]

Here parent is the inner candidate's parent while ^parent is the outer person's. (^ in an expression reads one scope out; the same ^ as a select-item prefix — ^name: … in §7 — binds one scope out. Both mean "one scope out.") A value bound into a scope by a lift is read there as a bare name, like a row property.

4. Built-in functions

Methods on a value: contains, startsWith, endsWith, matches (regex), size, lower, upper. Free functions: list(x) (coerce to an array), size(x), has(x), range(s) (§3), entries(x) (§2).

oqx`name from ${people} where title.startsWith("Eng")`;      // → Bob
oqx`name from ${people} where title.lower() == "director"`;  // → Alice
oqx`name from ${people} where has(age) && !has(nickname)`;   // present vs absent
oqx`name from ${people} where tags.contains("admin")`;       // array membership

• has(x) is true when x is present — anything other than null / undefined. has(0), has(""), and has(false) are all true; use bare truthiness (where active) when you mean truthy.
• .contains(v) works on strings (substring) and arrays (an element equal to v under OQX's strict equality); on anything else it is false.
• .size() / size(x) is the length of a string or array, the key count of an object, and 0 for absent; .matches(re) compiles its argument as a JavaScript RegExp.

Anything not in these tables is an eval error (unknown function 'f(…)' / unknown method '.m(…)') — see custom functions for adding your own.

5. Consumers

A consumer shapes a result set. There are six:

Consumer	Returns
collect	an array (the default)
exists	a boolean — one or more rows
none	a boolean — zero rows (the complement of exists)
count	a number
first	one record, or null
single	one record, or null; throws if more than one matches

The bare from … form is always collect. To reduce the whole query with a different consumer, use the directive form <source> <consumer> { <body> } — note this is not SQL: count from people would project a field called count, whereas a real reduction is a directive:

oqx`${people} exists { where active }`;            // true
oqx`${people} count { where active }`;             // 2
oqx`${people} first { name where age > 50 }`;      // { name: "Alice" }

(Inside a consumer block a bare identifier projects — count { active } selects a field named active; write count { where active } to filter.)

6. Nested collections and relations

The same consumers work as postfix directives over a relation of the current row — <relation> <consumer> { <body> } — both in where and in a projection.

In where, an exists { … } tests non-emptiness and count { … } <op> N compares cardinality:

oqx`name from ${people} where jobs exists { !end }`;   // has a current job → Bob, Carol
oqx`name from ${people} where jobs count {} >= 2`;     // ≥2 jobs → Bob, Alice
oqx`name from ${people} where jobs none { where end }`; // no past job → Carol

none { … } is exactly !… exists { … }, kept as its own word because the cardinality is the point. It is also how you say "every": all members active is members none { where !active } — there is deliberately no all { … }, whose block would have to mean something different from every other consumer's.

In a projection, collect yields a nested array; first / single yield one nested record:

oqx`name, current: jobs collect { employer where !end } from ${people} where name == "Bob"`;
// [{ name: "Bob", current: [{ employer: "Globocorp" }] }]

oqx`name, firstJob: jobs first { employer } from ${people} where name == "Alice"`;
// [{ name: "Alice", firstJob: { employer: "Initech" } }]

A relation is just an expression evaluated on the row and coerced to a collection, so nested blocks compose to any depth and can navigate dotted paths (author.books collect { … }).

distinct dedups the rows a consumer sees by their projected value, so counts and collections are over distinct projections rather than raw rows. Spell it after the consumer (count distinct { … }) or inside via select distinct:

oqx`from ${jobs} select distinct employer`;            // distinct employers
oqx`n: jobs collect distinct { select employer } from ${people}`; // per person, unique employers
oqx`name from ${people} where jobs count distinct { select employer } == 1`; // worked at exactly one employer

An empty projection dedups by row identity (count distinct { } = distinct rows).

7. Lifts (^)

Sometimes you want to filter by a nested collection and keep a value from it. A ^name: item inside a collect { … } that sits directly in the top-level where does both: it filters (non-empty) and binds name into the outer projection as a per-row array.

oqx`
  name, currentEmployers
  from ${people}
  where jobs collect { ^currentEmployers: employer where !end }
`;
// [{ name: "Bob", currentEmployers: ["Globocorp"] },
//  { name: "Carol", currentEmployers: ["Globocorp"] }]

Multi-level lifts (^^, ^^^). The caret count is how many scopes the value binds out — ^ to the immediate enclosing projection, ^^ two out, and so on (the mirror image of the ^-read in §3). When a deeper lift fires repeatedly as an intermediate collection fans out, its values flatten-append into one flat list at the target scope — "every matching value from the subtree, N scopes out":

const departments = [
  { name: "Eng",   teams: [{ id: "t1", members: [{ name: "Ada" }, { name: "Ben" }] },
                           { id: "t2", members: [{ name: "Cy" }] }] },
  { name: "Sales", teams: [{ id: "t3", members: [{ name: "Dee" }] }] },
];
oqx`
  name, teamIds, allMembers
  from ${departments}
  where teams collect { ^teamIds: id where members collect { ^^allMembers: name } }
`;
// [{ name: "Eng",   teamIds: ["t1", "t2"], allMembers: ["Ada", "Ben", "Cy"] },
//  { name: "Sales", teamIds: ["t3"],       allMembers: ["Dee"] }]

^teamIds (one out) and ^^allMembers (two out) bind to the same department row at once. Because accumulation happens as each intermediate collection is iterated, the intermediate scopes must be collect/count bodies (which iterate fully), not a short-circuiting exists.

8. Ordering

order by <expr> [asc|desc], comma-separated for tie-breaks. Absent values sort last.

oqx`name from ${people} where city == "NYC" order by age desc`;
// [{ name: "Bob" }, { name: "Carol" }]

8b. Bounding: limit / offset

limit N and offset N bound the row set after where, order by, and distinct, and before the consumer reduces it — so they mean the same thing under every consumer: count { … limit 5 } is at most 5, first { … offset 1 } is the second row, exists { offset 2 } asks for a third. They work at the top level and inside any block, and N may be a literal, a ${…} binding, or an outer reference — limit ^n reads the enclosing row's n, as ^ does everywhere inside { … }; it must be a non-negative integer.

oqx`name values from ${people} order by age desc limit 2`;                 // ["Alice", "Bob"]
oqx`name values from ${people} order by age desc offset 1 limit 1`;        // ["Bob"]
oqx`name, latest: jobs collect { employer values order by start desc limit 1 } from ${people}`;
oqx`name from ${people} where jobs exists { offset 1 }`;                   // has a second job

A storage adapter that pushes the whole query may translate them to SQL LIMIT/OFFSET; the shipped SqliteTable leaves them to the residual.

9. Recursion: follow

follow <relation> turns a query into a bounded recursive traversal: the where selects the seed rows, and follow walks a relation from each reached row. It's fully duck-typed — the relation is any expression yielding successors; a row that lacks it is simply a leaf.

const tree = [{ id: "root", children: [
  { id: "a", children: [{ id: "a1", children: [] }] },
  { id: "b", children: [] },
]}];

oqx`id, depth: $depth from ${tree} follow children order by $depth, id`;
// [{ id: "root", depth: 1 }, { id: "a", depth: 2 }, { id: "b", depth: 2 }, { id: "a1", depth: 3 }]

Reached rows expose recursion intrinsics in select / order by: $depth (1-based), $leaf (no successors), $frontier (there is unfollowed graph beyond — a boundary or the depth cap), $ordinal (a deterministic 1..N rank over the walk, ordered by depth then path), and $stop ("interior" / "leaf" / "frontier" / "depth" / "cycle", precedence cycle > frontier > depth > leaf > interior — only interior rows expand). Options go in a trailing block:

oqx`id, stop: $stop from ${tree} follow children { depth 2 } order by $ordinal`;
// a1 is never reached; a and b report stop:"depth"

The intrinsics belong to the reached row's own scope like any other name: inside a nested block (kids: children collect { … }) a bare $depth is absent, and the occurrence's depth is ^$depth.

The walk is per-path: a node reached by N distinct paths yields N occurrences, and revisiting an identity already on the current path is admitted once as $stop == "cycle" and never re-expanded, so cycles terminate without runaway. follow distinct collapses occurrences to reached nodes (the minimal (depth, path) per identity).

The block accepts: where <succ> (which successors keep participating), frontier <pred> (cut a relation that could continue), depth <n> (1–8), and by <expr> (the identity used for cycle detection + distinct — default .id or the object reference). Give follow a stable identity (.id or by) when your relation returns fresh objects rather than shared references.

Cheat-sheet

name, alias: expr, nested: rel collect { … }   projection (select optional)
from ${source}                                  source collection
where a == b && rel exists { … } || !c          predicate tree + nested ops
where rel none { … }                             zero rows (≡ !rel exists { … }; "all" = none over the complement)
where x in lo..hi / lo...hi / ..hi / lo..        range membership (incl. / excl. / open-ended)
where x in range(field)                          coerce a string field to a range, then test coverage
name                                             the CURRENT row's field only (never climbs)
$value                                           the current item itself (a scalar row, or the whole object)
from entries(obj) … $key / $value                a record's properties as a collection (key + value; bare names read the value)
<expr> values                                    scalar projection: the value, not a { name: value } record
^name / ^^name                                   read an enclosing row's field (exactly N scopes out); ^$value = the enclosing row
^name: expr  /  ^^name: expr                     lift/export a value N scopes out (flatten-append)
^rel collect { … }  /  ^^root exists { … }       nested consumer over an enclosing row's relation / a named root
entries(rel) exists { … }                        a free-function call may be a receiver
order by expr desc, expr2                        ordering
limit n / offset n                               bound the row set (after where/order/distinct, before the consumer)
follow rel { where … frontier … depth n by … }  recursion ($depth/$stop/$leaf/$frontier)
${source} <collect|exists|none|count|first|single> { … }   whole-query consumer

Data context: string queries and named roots

When you don't need interpolation, execute runs a plain string query against a data context of named roots:

import { execute } from "@omgbase/oqx";

execute("name from people where age >= 18", { people });
// `from people` resolves the `people` root

parse(source) returns a reusable AST and run(query, { values, roots }) returns the full discriminated result ({ consumer, … }).

Architecture: adapting to other storage & query systems

OQX is layered so it can be the front-end for query systems far beyond in-memory objects. The parsed Query AST is the host-agnostic IR; execution is pluggable.

Query AST  ─┬─ InMemoryEngine(DataContext)     tier 1/2 — drive any data model
            └─ PlannedEngine(QueryPlanner)      tier 3   — push work into a store
                   └─ finishes the residual on the in-memory engine

Everything obeys one scalar-semantics contract (the semantics export): typed/strict equality (5 == "5" is false), absent operands make ordering comparisons false, CEL-style in, absent-last sort order. Any backend that can't reproduce a rule in its native language must leave that fragment as an in-memory residual rather than approximate it. The conformance suite verifies this.

Tier 2 — a custom DataContext (bind any data model)

The engine never touches host objects directly; it asks a DataContext to resolve named roots, read properties/relations, coerce results to rows, and compute identity. Implement it to query an ORM graph, a remote API, or lazily loaded relations — the query semantics stay in OQX. Name resolution is simple for a context: a bare field, a .field segment, and a ^field outer reference each become one get(row, key) against exactly the row of the scope they name, so a computed relation only needs get to know about it:

import { parse, run } from "@omgbase/oqx";

const graph = {
  root: (name) => name === "tree" ? [nodes.get(1)] : undefined,
  get:  (row, key) => key === "children" ? row.childIds.map(id => nodes.get(id)) : row[key],
  toRows: (v) => v == null ? [] : Array.isArray(v) ? v : [v],
  identity: (row) => row.id,                                // for follow dedup
};
run(parse("id, depth: $depth from tree follow children"), { context: graph });

Custom functions and methods

DataContext has two optional hooks, callFunction(name, args) for free functions (f(x)) and callMethod(name, recv, args) for methods (x.m()). Each returns a CallResult: { handled: true, value } to answer, or { handled: false } to decline. The engine does not consult the builtin table itself — DefaultContext is what does that. So a context that omits these hooks, or handles only its own names without deferring, loses entries(), size(), has(), range(), .contains(), and the rest: the engine throws OqxError("unknown function 'size(…)'", "eval"). (The graph context above has exactly this limitation.) Delegate whatever you don't recognize:

import { DefaultContext, parse, run } from "@omgbase/oqx";

const builtins = new DefaultContext();          // or: semantics.BUILTIN_FUNCTIONS[name]
const ctx = {
  ...graph,
  callFunction(name, args) {
    if (name === "age") return { handled: true, value: yearsSince(args[0]) };
    return builtins.callFunction(name, args);   // entries/size/has/range keep working
  },
  callMethod(name, recv, args) {
    if (name === "slug") return { handled: true, value: slugify(recv) };
    return builtins.callMethod(name, recv, args);
  },
};
run(parse("id from tree where age(born) > 18 && title.slug() == 'x'"), { context: ctx });

The simplest route is to extends DefaultContext and super.callFunction(...) in the fallthrough. Custom calls are never pushed down by the shipped planners; they always run in the residual.

Tier 3 — a QueryPlanner (pushdown + planning)

A planner translates as much of a query as it can into its store's native query and returns the produced rows plus a residual Query for the rest. The in-memory engine finishes the residual, so a planner can be as partial as it likes and stay correct. Two adapters ship:

• IndexedCollection — hash-indexes a collection and answers equality predicates from the index instead of scanning, leaving other predicates as residual.
• @omgbase/oqx/sqlite — real pushdown to a node:sqlite database: the flat query core (scan + translatable conjunctive predicates, LIMIT for unordered first/single) becomes SQL; matches(), nested consumer ops, follow, etc. fall back to the in-memory residual.

import { parse, PlannedEngine } from "@omgbase/oqx";
import { SqliteTable } from "@omgbase/oqx/sqlite";

const planner = new SqliteTable(db, "emp", { columns: ["id", "name", "dept", "level"] });
new PlannedEngine(planner).run(parse('name from emp where dept == "eng" && level >= 5'), []);
// → `dept`/`level` pushed to SQL; anything untranslatable finishes in-memory

This is the seam an omgbase adapter uses: its existing OQX→SQL compiler (docs/ blocks/nodes, the relations table, $ intrinsics, WITH RECURSIVE for follow) becomes a QueryPlanner, while oqx contributes the parser, IR, semantics contract, and residual executor.

Exports

Everything below is exported from @omgbase/oqx (src/index.ts); the SQLite adapter lives on the @omgbase/oqx/sqlite subpath.

Running queries

• oqx (default export and named) — the tagged template. Returns the consumer-shaped value: an array for collect, a boolean for exists / none, a number for count, a record or null for first / single.

• parse(source) — a query string → reusable Query AST (an OqxError with stage: "lex" | "parse" on bad input).

• execute(source, roots?) — parse and run a string against named roots ({ people }), returning the consumer-shaped value.

• run(query, opts?) — run a parsed Query, returning the full OqxResult. opts.values are the positional ${…} bindings; then exactly one of opts.engine (any Engine, e.g. a PlannedEngine), opts.context (a DataContext, run on the in-memory engine), or opts.roots (plain-object named roots → DefaultContext). Default: an empty DefaultContext.

• runQuery(query, values, roots) — the lower-level call oqx / execute use: in-memory over a DefaultContext(roots) (roots may be undefined).

• OqxResult — the discriminated result run returns:

  type OqxResult =
    | { consumer: "collect"; rows: unknown[] }
    | { consumer: "exists";  exists: boolean }
    | { consumer: "none";    none: boolean }
    | { consumer: "count";   count: number }
    | { consumer: "first";   row: unknown | null }
    | { consumer: "single";  row: unknown | null };

Errors

• OqxError — the one error class for every failure. error.stage is "lex" | "parse" | "eval" so you can branch without matching messages; error.message carries the detail (position for lex/parse errors, the offending name or count for eval errors). Eval errors include: unknown function/method, a non-integer or negative limit / offset, and single { … } matching more than one row (zero rows is null, not an error — use first when zero-or-one is expected and you don't care to assert).

Engines and contexts

• Engine — { run(query, bindings): OqxResult }; what run({ engine }) accepts.
• InMemoryEngine — new InMemoryEngine(context?); the reference engine over a DataContext (tier 1/2).
• DataContext — the tier-2 interface: root, get, toRows, identity, plus optional callFunction / callMethod (above).
• CallResult — { handled: boolean; value?: unknown }, returned by those hooks.
• DefaultContext — new DefaultContext(roots?); plain-object access, .id identity, and the builtin function/method tables.
• semantics — the scalar-contract module (equals, relate, arith, membership, truthy, compareForSort, sizeOf, toList, coerceCollection, ranges: makeRange / isRange / rangeCovers / parseRangeString, entries: makeEntry / isEntry / entriesOf, and the BUILTIN_FUNCTIONS / BUILTIN_METHODS tables). A backend reproducing a rule natively must match these.

Planning (tier 3)

• QueryPlanner — { plan(query, params): Plan | null }. Return null to decline a query entirely (full in-memory fallback).

• Plan — { rows(): Iterable; residual: Query; context?: DataContext }: the rows the store produced, the query to finish over them, and optionally a context for navigating those rows' relations.

• PlannedEngine — new PlannedEngine(planner, fallbackContext?); an Engine that runs the planner and finishes plan.residual on the in-memory engine over plan.rows() (exposed as the ROWS_ROOT root).

• Planner helpers, used together inside plan(): partitionPushable(where, canPush) splits the top-level where conjunction into pushed expressions (those your canPush accepts) and a residual where-tree; asEquality(expr) recognizes field == const (either order) as { field, value }; isConst(expr) / constValue(expr, params) tell a literal-or-binding from a row-dependent expression and evaluate it against the query bindings; and residualQuery(query, residualWhere) rebuilds the query to scan ROWS_ROOT with the pushed predicates dropped and projection / order / consumer / bounds intact. A planner typically: checks query.source names its table (and declines from / follow), partitions the where, translates pushed into its native query using constValue for parameters, then returns { rows, residual: residualQuery(query, residual) }.

• IndexedCollection — new IndexedCollection(rootName, rows, indexFields); a QueryPlanner that hash-indexes rows on indexFields and answers field == value predicates on them from the index, leaving the rest residual:

  import { parse, run, IndexedCollection, PlannedEngine } from "@omgbase/oqx";
  const planner = new IndexedCollection("people", people, ["city", "title"]);
  const engine = new PlannedEngine(planner);
  run(parse('name from people where city == "NYC" && age > 30'), { engine });
  // city probe from the index; `age > 30` finished in-memory over the candidates

• SqliteTable (from @omgbase/oqx/sqlite) — new SqliteTable(db, tableName, options) over a node:sqlite DatabaseSync. SqliteTableOptions:

  • columns: string[] — the columns that map to bare OQX fields; only these are pushable (any other identifier stays residual).
  • jsonColumns?: string[] — columns whose stored text is JSON.parsed back into the row (for nested relations kept as JSON).
  • map?: (raw) => row — a custom raw-SQL-row → query-row mapper (overrides jsonColumns).

Types

• Every AST node type from src/ast.ts is re-exported (Query, Subquery, Where, Expr, OpNode, SelectItem, OrderSpec, Follow, …) for planners that walk the IR.

Requirements

No runtime dependencies. The package is ESM-only (there is no require condition in exports; Node 22.12+ can require() an ES module natively).

• Main entry (@omgbase/oqx): compiled ES2022 ESM. engines.node says >=22.13.0, but nothing in the main entry needs it — Node 18+ works in practice.
• @omgbase/oqx/sqlite: imports node:sqlite, which is available without a flag from Node 22.13 (behind --experimental-sqlite in 22.5–22.12). This is the reason for the engines floor.
• Developing the repo: npm test runs the .ts suite directly through Node's type stripping, unflagged from Node 22.18 (and all of 24). npm run typecheck typechecks; npm run build emits dist/.

Relationship to omgbase

This is tier 1 (the in-memory object/collection interpreter) of the OQX implementation tiers. The language kernel here is host-agnostic; richer hosts (e.g. omgbase's docs/blocks/nodes with index pushdown) layer data-model vocabulary and execution capabilities on top of the same surface syntax.

License

MIT. Release history is in the CHANGELOG.