DZakh/sury

Sury 🧬

Schema for everything - faster than hand-written code.

Declare your data once, in TypeScript or ReScript. The wires it travels are schemas too, and they chain:

const signupSchema = S.schema({ id: S.bigint, email: S.email, avatar: S.blob });
type Signup = S.Infer<typeof signupSchema>;

const signupsFileSchema = S.file.with(S.to, S.jsonString).with(S.to, S.array(signupSchema));

await S.decodeAsPromiseOrReject(signupsFileSchema)(file);
// => [{ id: 7n, email: "a@b.co", avatar: Blob }], the avatar rode as base64
await S.encodeAsPromiseOrReject(signupsFileSchema)(signups);
// => a File, from the same declaration - input and return strictly typed

Wires today: S.json, S.jsonString, S.formData, S.env, S.urlSearchParams, S.queryString, S.base64, S.base64url, S.uint8Array, S.protobuf, S.file and S.blob. Coming next: S.request, S.response, S.capnp, S.rkyv, S.toon.

npm install sury

API Reference: TypeScript | ReScript | ReScript PPX

Benchmarks: Schema | JSON Encoding | JSON Schema | Protobuf

Why Sury

Describe your data model once - unions, constraints and metadata included, with a type you can actually read on hover:

import * as S from "sury"; // Tree-shakable: a schema + parse operation starts at 8.6 kB gzip

const eventSchema = S.union([
  {
    type: "user.created",
    id: S.bigint,
    tags: S.array({ name: S.string }).with(S.nonEmpty, "Add at least one tag"),
  },
  { type: "user.deleted", id: S.bigint, payload: S.json },
]).with(S.meta, { description: "User lifecycle event" });

type Event = S.Output<typeof eventSchema>;
//   ^? { type: "user.created"; id: bigint; tags: [{ name: string }, ...{ name: string }[]] }
//      | { type: "user.deleted"; id: bigint; payload: S.JSON }

The same schema parses and encodes - no second definition. Encoding is even faster than JSON.stringify - read more in Encode, Don't Stringify: How JSON.stringify Lies to You:

const parseEvent = S.decodeOrThrow(S.jsonString, eventSchema);
parseEvent('{"type":"user.created","id":"42","tags":[{"name":"vip"}]}');
// => { type: "user.created", id: 42n, tags: [{ name: "vip" }] }

S.encodeOrThrow(eventSchema, S.jsonString, { type: "user.deleted", id: 7n, payload: { reason: "spam" } });
// => '{"type":"user.deleted","id":"7","payload":{"reason":"spam"}}'

Errors tell you exactly where to look, in wire terms - the missing id is a missing string:

parseEvent('{"type":"user.deleted"}');
// => throws S.Error: Failed at id: Expected string, received undefined

parseEvent('{"type":"user.created","id":"42","tags":[]}');
// => throws S.Error: Failed at tags: Add at least one tag

All possible ways to run your schema, with a decision required where safety matters - perfect to navigate and review agentic code:

S.parseOrThrow(eventSchema, input); // => Event, or throws S.Error
S.parseAsResult(eventSchema, input); // => { success: true, value } | { success: false, error, issues }
S.parseAsPromiseOrReject(eventSchema, input); // => Promise<Event>, rejects with S.Error
S.parseAsResultPromise(eventSchema, input); // => Promise<Result<Event>>
S.parseAsPromisableResult(eventSchema, input); // => Result<Event> for a sync schema, Promise<Result<Event>> for an async one

S.parseAsResult(input, eventSchema); // Data first works too
S.parseAsResult(S.jsonString, eventSchema, input); // A pipeline of up to three schemas
const safeParseEvent = S.parseAsResult(eventSchema); // Schema alone compiles the operation beforehand
safeParseEvent(input);

Need a different wire? Wrap the same model in base64url. The pipeline knows both of its ends, so S.encodeOrThrow and S.decodeOrThrow take just the schema:

const b64Event = S.base64url.with(S.to, S.jsonString.with(S.to, eventSchema));

S.encodeOrThrow(b64Event, { type: "user.deleted", id: 7n, payload: { reason: "spam" } });
// => "eyJ0eXBlIjoidXNlci5kZWxldGVkIiwiaWQiOiI3IiwicGF5bG9hZCI6eyJyZWFzb24iOiJzcGFtIn19"

S.decodeOrThrow(b64Event, "eyJ0eXBlIjoidXNlci5kZWxldGVkIiwiaWQiOiI3IiwicGF5bG9hZCI6eyJyZWFzb24iOiJzcGFtIn19");
// => { type: "user.deleted", id: 7n, payload: { reason: "spam" } }

Thanks to Standard Schema, the schema plugs straight into tRPC, Hono, TanStack and 28+ other libraries. validate reports every issue at once, ready for a form:

eventSchema["~standard"].validate({ type: "user.created", id: 7, tags: [] }).issues;
// => [
//   { message: "Expected bigint, received 7", path: ["id"] },
//   { message: "Add at least one tag", path: ["tags"] },
// ]

Its Standard JSON Schema extension describes the wire - and a bigint has no wire until you give it one:

S.enableStandardJSONSchema(); // Opt-in, so unused JSON Schema code tree-shakes away

eventSchema["~standard"].jsonSchema.input({ target: "draft-07" });
// => throws: Failed at id: Expected JSON, received bigint

S.json.with(S.to, eventSchema)["~standard"].jsonSchema.input({ target: "draft-07" });
// => { anyOf: [...], description: "User lifecycle event", ... } - with id: { type: "string" }

You can go the other way too: feed JSON Schema in and get a typed Sury schema back. 93% of the official draft-07 test suite passes in CI:

const emailSchema = S.fromJSONSchemaOrThrow({ type: "string", format: "email" });
//? S.Schema<string, string>

S.parseOrThrow(emailSchema, "hi@sury.dev"); // => "hi@sury.dev"

Recursive schemas work out of the box:

type Node = { id: string; children: Node[] };
const nodeSchema = S.recursive<Node>("Node", (nodeSchema) =>
  S.schema({ id: S.string, children: S.array(nodeSchema) }),
);

Renaming fields between the wire and your code is one S.shape call, and the encode direction follows automatically:

const userSchema = S.schema({
  USER_ID: S.string.with(S.to, S.bigint),
  USER_NAME: S.string,
}).with(S.shape, (input) => ({
  id: input.USER_ID,
  name: input.USER_NAME,
}));

S.parseOrThrow(userSchema, { USER_ID: "0", USER_NAME: "Dmitry" });
// => { id: 0n, name: "Dmitry" }
S.encodeOrThrow(userSchema, { id: 0n, name: "Dmitry" });
// => { USER_ID: "0", USER_NAME: "Dmitry" }

The other side of the wire is yours too. A constructor checks a value you built in code - refinements included, and whether the schema can encode it - and hands back the very object it was given. For a branded schema, it's how the brand gets minted:

const makeEvent = S.makeOutputOrThrow(eventSchema);

makeEvent({ type: "user.deleted", id: 7n, payload: { reason: "spam" } });
// => the object you passed in, checked

makeEvent({ type: "user.created", id: 7n, tags: [] });
// => throws S.Error: Failed at tags: Add at least one tag

const userIdSchema = S.uuid.with(S.brand, "UserId");
const userId = S.makeOutputOrThrow(userIdSchema, "f81d4fae-7dec-11d0-a765-00a0c91e6bf6");
//? S.Brand<string, "UserId">

The same schema lets you compare your values, fast and safe:

const sessionSchema = S.schema({ kind: "session", id: S.string, startedAt: S.date });

S.isEqualOutput(
  sessionSchema,
  { kind: "session", id: "s1", startedAt: new Date("2026-01-01") },
  { kind: "session", id: "s1", startedAt: new Date("2026-01-01") },
);
// => true, two Date objects for the same instant

const isSameSession = S.isEqualOutput(sessionSchema);
//? (a, b) => a === b || (a.id === b.id && +a.startedAt === +b.startedAt)

const ascByStart = S.compareOutput(S.date);
sessions.sort((a, b) => ascByStart(a.startedAt, b.startedAt));

Every operation that looks at one side of a schema says which side in its name - S.makeOutputOrThrow and S.isInput, S.toInputJSONSchemaOrThrow for the wire and S.toOutputJSONSchemaOrThrow for your types.

Reading a File is asynchronous, so a pipeline that starts from one becomes async too:

const configSchema = S.file.with(S.to, S.jsonString.with(S.to, S.schema({ theme: S.string })));

await S.parseAsPromiseOrReject(configSchema, new File(['{"theme":"dark"}'], "config.json"));
// => { theme: "dark" }

No need for a separate library to decode your env vars:

const envSchema = S.schema({
  PORT: S.port,
  DEBUG: S.boolean,
  NAME: S.nullable(S.string),
});

S.decodeOrThrow(process.env, S.record(S.env), envSchema);
// { PORT: "8080", DEBUG: "true" } => { PORT: 8080, DEBUG: true, NAME: null }

Some data arrives in awkward layouts - like the columnar arrays that boost Postgres INSERT performance by 2x. Describe the layout instead of writing glue code, and S.compactColumns turns columns into rows and back:

const rows = S.compactColumns(S.json).with(S.to, S.array({ id: S.bigint, city: S.string }));

S.decodeOrThrow(rows, [["1", "2"], ["Tbilisi", "Batumi"]]);
// => [{ id: 1n, city: "Tbilisi" }, { id: 2n, city: "Batumi" }]
S.encodeOrThrow(rows, [{ id: 1n, city: "Tbilisi" }, { id: 2n, city: "Batumi" }]);
// => [["1", "2"], ["Tbilisi", "Batumi"]]

A form submission is strings, files and missing checkboxes. S.formData reads it as what you declared, and builds the body you post back:

const signup = S.formData.with(
  S.to,
  S.schema({
    name: S.string.with(S.nonEmpty),
    age: S.number, // "42" -> 42
    agree: true, // a checkbox that has to be ticked
    newsletter: S.optional(S.boolean), // tri-state: absent -> undefined
    role: S.union(["admin", "user"]),
    tags: S.array(S.string), // every "tags" entry
    avatar: S.file,
    prefs: S.jsonString.with(S.to, S.schema({ theme: S.string })),
  }),
);

S.decodeOrThrow(signup)(await request.formData());
// => { name: "Ann", age: 42, agree: true, newsletter: undefined, role: "user",
//      tags: ["a", "b"], avatar: File, prefs: { theme: "dark" } }

S.encodeOrThrow(signup)(value);
// => a FormData with one append per field, ready for fetch(url, { body })

Protocol Buffers need no .proto file and no code generation step. Number the fields, name S.protobuf as the other side, and the same schema still parses, infers types and converts to JSON Schema:

const userSchema = S.schema({
  id: S.int32.with(S.protobufField, 1),
  name: S.string.with(S.protobufField, 2),
  tags: S.array(S.string).with(S.protobufField, 3),
}).with(S.meta, { name: "User" });

S.encodeOrThrow(userSchema, S.protobuf, { id: 150, name: "Ada", tags: ["ml"] });
// => Uint8Array [8, 150, 1, 18, 3, 65, 100, 97, 26, 2, 109, 108]

S.decodeOrThrow(S.protobuf, userSchema, bytes);
// => { id: 150, name: "Ada", tags: ["ml"] }

S.toProtoOrThrow(userSchema, { package: "acme.v1" }); // hand the other side its .proto
// => message User {
//      int32 id = 1;
//      string name = 2;
//      repeated string tags = 3;
//    }

The code a schema turns into

Here's what parseEvent from above actually runs - a function specialized for this exact shape: the union dispatches on the discriminant, the bigint coercion is inlined as a bare BigInt() call, your nonEmpty message is a plain length check, and S.jsonString -> union -> fields fuse into one pass:

(i) => {
  let v0;
  try {
    v0 = JSON.parse(i);
  } catch (t) {
    e[0](i);
  }
  if (typeof v0 === "object" && v0 && !Array.isArray(v0)) {
    for (;;) {
      if (v0.type === "user.created") {
        let v2 = v0.id, v3 = v0.tags;
        typeof v2 === "string" || e[2](v2);
        let v1;
        try {
          v1 = BigInt(v2);
        } catch (_) {
          e[1](v2);
        }
        Array.isArray(v3) || e[6](v3);
        // ...validates each tag, tracking the error path
        v8.length > 0 || e[5](v8); // e[5] throws your nonEmpty message
        v0 = { type: v0.type, id: v1, tags: v8 };
        break;
      }
      if (v0.type === "user.deleted") {
        // ...one branch per variant, no loop over union members
      }
      e[9](v0);
    }
  } else {
    e[10](v0);
  }
  return v0;
};

The encoder gets the same treatment right below - and that's why Sury tends to outrun even hand-rolled validation (benchmarks).

Encoding vs `JSON.stringify`

The encoder builds the JSON text directly - no intermediate object, the structure baked in as literals, and JSON.stringify left only the free-form payload:

(i) => {
  if (typeof i === "object" && i && !Array.isArray(i)) {
    for (;;) {
      // ...one branch per variant
      if (i.type === "user.deleted") {
        let v6 = JSON.stringify(i.payload);
        let v7 = '{"type":"user.deleted","id":"' + i.id + '"';
        if (v6 !== void 0) {
          v7 += ',"payload":' + v6;
        }
        i = v7 + "}";
        break;
      }
    }
  }
  return i;
};

And the values JSON.stringify silently corrupts throw instead:

JSON.stringify({ price: Infinity });
// => '{"price":null}'

S.encodeOrThrow(S.schema({ price: S.number }), S.jsonString, { price: Infinity });
// => throws S.Error: Failed at price: Expected JSON, received Infinity

Encode to JSON string	Sury	`JSON.stringify`	fast-json-stringify
API response (user profile, 7 fields)	305 ns	590 ns	382 ns
Event feed (50 tagged-union events)	5.05 µs	7.82 µs	20.26 µs
`bigint` id + binary payload + `Date`	1.17 µs	1.51 µs	1.45 µs

And 3.2× lighter than fast-json-stringify - 18.0 kB against 56.9 kB, encoder included.

Comparison

Sury shines in a lot of different aspects, so each of them gets a comparison page of its own:

Schema - describe a shape, check a value against it, read the type on hover. Against Zod, TypeBox, Valibot and ArkType.
JSON Encoding - turn a value into JSON text and read it back. Against JSON.stringify and fast-json-stringify.
JSON Schema - emit JSON Schema, and read somebody else's back. Against Zod, TypeBox, ArkType and Ajv.
Protobuf - the Protocol Buffers wire, without a .proto file or a codegen step. Against protobufjs, protobuf-es and pbf.

Don't take my word for it. Sury is measured by other people too:

typescript-runtime-type-benchmarks - every library in the ecosystem on the same object, in one chart
schemabenchmarks.dev - where the time goes, step by step: download, initialization, validation, parsing, Standard Schema, codec
json-schema-compliance-suite - how much of JSON Schema a library actually gets right

Integrations

Use Sury anywhere a schema is accepted:

tRPC, TanStack Form, TanStack Router, Hono, and 28+ more via the Standard Schema spec
Anything that speaks JSON Schema, via S.toInputJSONSchemaOrThrow / S.fromJSONSchemaOrThrow
nuqs - turn a schema into a search param parser

Used by

HyperIndex - Envio's blockchain indexing framework, which uses Sury to power native high-performance external calls
rescript-rest - RPC-like client, contract, and server implementation for a pure REST API
rescript-envsafe - makes sure you don't accidentally deploy apps with missing or invalid environment variables
rescript-stripe - describe and manage Stripe billing in a declarative way with code
Internal form library at Carla

Building something with Sury? Let me know and I'll add it here.

FAQ

Is `new Function` safe to use?

Yes. It's the same technique TypeBox, Zod v4 and ArkType use, and it's where much of the speed comes from (the code a schema turns into). Cloudflare Workers allows new Function during Worker startup (the default since compatibility date 2025-06-01), so schemas and operations created at the top level work there.

There's currently no eval-free mode, so Sury won't run where dynamic code evaluation is forbidden: pages under a strict CSP without 'unsafe-eval', some browser extension contexts, and a few restricted edge runtimes. If that's your environment, Valibot is the honest recommendation today.

Why "Sury"?

It's short, it's pronounceable, and the 🧬 fits: a schema is the DNA of your data - one definition that everything else is derived from.

Resources

Standard JSON Schema vs JSON Schema (Dev.to)
Encode, Don't Stringify: How JSON.stringify Lies to You (Dev.to)
Making my TypeScript types 15.7x faster (Dev.to)
Welcome Sury - The fastest schema with next-gen DX (Dev.to)
ReScript Schema unique features (Dev.to)
Building and consuming REST API in ReScript with rescript-rest and Fastify (YouTube)

Contributing

Bug reports, ideas, and pull requests are all welcome - open an issue to get started.

License

MIT

Sury 🧬

Schema for everything - faster than hand-written code.

Declare your data once, in TypeScript or ReScript. The wires it travels are schemas too, and they chain:

const signupSchema = S.schema({ id: S.bigint, email: S.email, avatar: S.blob });
type Signup = S.Infer<typeof signupSchema>;

const signupsFileSchema = S.file.with(S.to, S.jsonString).with(S.to, S.array(signupSchema));

await S.decodeAsPromiseOrReject(signupsFileSchema)(file);
// => [{ id: 7n, email: "a@b.co", avatar: Blob }], the avatar rode as base64
await S.encodeAsPromiseOrReject(signupsFileSchema)(signups);
// => a File, from the same declaration - input and return strictly typed

npm install sury

API Reference: TypeScript | ReScript | ReScript PPX

Benchmarks: Schema | JSON Encoding | JSON Schema | Protobuf

Why Sury

Describe your data model once - unions, constraints and metadata included, with a type you can actually read on hover:

import * as S from "sury"; // Tree-shakable: a schema + parse operation starts at 8.6 kB gzip

const eventSchema = S.union([
  {
    type: "user.created",
    id: S.bigint,
    tags: S.array({ name: S.string }).with(S.nonEmpty, "Add at least one tag"),
  },
  { type: "user.deleted", id: S.bigint, payload: S.json },
]).with(S.meta, { description: "User lifecycle event" });

type Event = S.Output<typeof eventSchema>;
//   ^? { type: "user.created"; id: bigint; tags: [{ name: string }, ...{ name: string }[]] }
//      | { type: "user.deleted"; id: bigint; payload: S.JSON }

The same schema parses and encodes - no second definition. Encoding is even faster than JSON.stringify - read more in Encode, Don't Stringify: How JSON.stringify Lies to You:

const parseEvent = S.decodeOrThrow(S.jsonString, eventSchema);
parseEvent('{"type":"user.created","id":"42","tags":[{"name":"vip"}]}');
// => { type: "user.created", id: 42n, tags: [{ name: "vip" }] }

S.encodeOrThrow(eventSchema, S.jsonString, { type: "user.deleted", id: 7n, payload: { reason: "spam" } });
// => '{"type":"user.deleted","id":"7","payload":{"reason":"spam"}}'

Errors tell you exactly where to look, in wire terms - the missing id is a missing string:

parseEvent('{"type":"user.deleted"}');
// => throws S.Error: Failed at id: Expected string, received undefined

parseEvent('{"type":"user.created","id":"42","tags":[]}');
// => throws S.Error: Failed at tags: Add at least one tag

All possible ways to run your schema, with a decision required where safety matters - perfect to navigate and review agentic code:

S.parseOrThrow(eventSchema, input); // => Event, or throws S.Error
S.parseAsResult(eventSchema, input); // => { success: true, value } | { success: false, error, issues }
S.parseAsPromiseOrReject(eventSchema, input); // => Promise<Event>, rejects with S.Error
S.parseAsResultPromise(eventSchema, input); // => Promise<Result<Event>>
S.parseAsPromisableResult(eventSchema, input); // => Result<Event> for a sync schema, Promise<Result<Event>> for an async one

S.parseAsResult(input, eventSchema); // Data first works too
S.parseAsResult(S.jsonString, eventSchema, input); // A pipeline of up to three schemas
const safeParseEvent = S.parseAsResult(eventSchema); // Schema alone compiles the operation beforehand
safeParseEvent(input);

Need a different wire? Wrap the same model in base64url. The pipeline knows both of its ends, so S.encodeOrThrow and S.decodeOrThrow take just the schema:

const b64Event = S.base64url.with(S.to, S.jsonString.with(S.to, eventSchema));

S.encodeOrThrow(b64Event, { type: "user.deleted", id: 7n, payload: { reason: "spam" } });
// => "eyJ0eXBlIjoidXNlci5kZWxldGVkIiwiaWQiOiI3IiwicGF5bG9hZCI6eyJyZWFzb24iOiJzcGFtIn19"

S.decodeOrThrow(b64Event, "eyJ0eXBlIjoidXNlci5kZWxldGVkIiwiaWQiOiI3IiwicGF5bG9hZCI6eyJyZWFzb24iOiJzcGFtIn19");
// => { type: "user.deleted", id: 7n, payload: { reason: "spam" } }

Thanks to Standard Schema, the schema plugs straight into tRPC, Hono, TanStack and 28+ other libraries. validate reports every issue at once, ready for a form:

eventSchema["~standard"].validate({ type: "user.created", id: 7, tags: [] }).issues;
// => [
//   { message: "Expected bigint, received 7", path: ["id"] },
//   { message: "Add at least one tag", path: ["tags"] },
// ]

Its Standard JSON Schema extension describes the wire - and a bigint has no wire until you give it one:

S.enableStandardJSONSchema(); // Opt-in, so unused JSON Schema code tree-shakes away

eventSchema["~standard"].jsonSchema.input({ target: "draft-07" });
// => throws: Failed at id: Expected JSON, received bigint

S.json.with(S.to, eventSchema)["~standard"].jsonSchema.input({ target: "draft-07" });
// => { anyOf: [...], description: "User lifecycle event", ... } - with id: { type: "string" }

You can go the other way too: feed JSON Schema in and get a typed Sury schema back. 93% of the official draft-07 test suite passes in CI:

const emailSchema = S.fromJSONSchemaOrThrow({ type: "string", format: "email" });
//? S.Schema<string, string>

S.parseOrThrow(emailSchema, "hi@sury.dev"); // => "hi@sury.dev"

Recursive schemas work out of the box:

type Node = { id: string; children: Node[] };
const nodeSchema = S.recursive<Node>("Node", (nodeSchema) =>
  S.schema({ id: S.string, children: S.array(nodeSchema) }),
);

Renaming fields between the wire and your code is one S.shape call, and the encode direction follows automatically:

const userSchema = S.schema({
  USER_ID: S.string.with(S.to, S.bigint),
  USER_NAME: S.string,
}).with(S.shape, (input) => ({
  id: input.USER_ID,
  name: input.USER_NAME,
}));

S.parseOrThrow(userSchema, { USER_ID: "0", USER_NAME: "Dmitry" });
// => { id: 0n, name: "Dmitry" }
S.encodeOrThrow(userSchema, { id: 0n, name: "Dmitry" });
// => { USER_ID: "0", USER_NAME: "Dmitry" }

const makeEvent = S.makeOutputOrThrow(eventSchema);

makeEvent({ type: "user.deleted", id: 7n, payload: { reason: "spam" } });
// => the object you passed in, checked

makeEvent({ type: "user.created", id: 7n, tags: [] });
// => throws S.Error: Failed at tags: Add at least one tag

const userIdSchema = S.uuid.with(S.brand, "UserId");
const userId = S.makeOutputOrThrow(userIdSchema, "f81d4fae-7dec-11d0-a765-00a0c91e6bf6");
//? S.Brand<string, "UserId">

The same schema lets you compare your values, fast and safe:

const sessionSchema = S.schema({ kind: "session", id: S.string, startedAt: S.date });

S.isEqualOutput(
  sessionSchema,
  { kind: "session", id: "s1", startedAt: new Date("2026-01-01") },
  { kind: "session", id: "s1", startedAt: new Date("2026-01-01") },
);
// => true, two Date objects for the same instant

const isSameSession = S.isEqualOutput(sessionSchema);
//? (a, b) => a === b || (a.id === b.id && +a.startedAt === +b.startedAt)

const ascByStart = S.compareOutput(S.date);
sessions.sort((a, b) => ascByStart(a.startedAt, b.startedAt));

Reading a File is asynchronous, so a pipeline that starts from one becomes async too:

const configSchema = S.file.with(S.to, S.jsonString.with(S.to, S.schema({ theme: S.string })));

await S.parseAsPromiseOrReject(configSchema, new File(['{"theme":"dark"}'], "config.json"));
// => { theme: "dark" }

No need for a separate library to decode your env vars:

const envSchema = S.schema({
  PORT: S.port,
  DEBUG: S.boolean,
  NAME: S.nullable(S.string),
});

S.decodeOrThrow(process.env, S.record(S.env), envSchema);
// { PORT: "8080", DEBUG: "true" } => { PORT: 8080, DEBUG: true, NAME: null }

const rows = S.compactColumns(S.json).with(S.to, S.array({ id: S.bigint, city: S.string }));

S.decodeOrThrow(rows, [["1", "2"], ["Tbilisi", "Batumi"]]);
// => [{ id: 1n, city: "Tbilisi" }, { id: 2n, city: "Batumi" }]
S.encodeOrThrow(rows, [{ id: 1n, city: "Tbilisi" }, { id: 2n, city: "Batumi" }]);
// => [["1", "2"], ["Tbilisi", "Batumi"]]

A form submission is strings, files and missing checkboxes. S.formData reads it as what you declared, and builds the body you post back:

const signup = S.formData.with(
  S.to,
  S.schema({
    name: S.string.with(S.nonEmpty),
    age: S.number, // "42" -> 42
    agree: true, // a checkbox that has to be ticked
    newsletter: S.optional(S.boolean), // tri-state: absent -> undefined
    role: S.union(["admin", "user"]),
    tags: S.array(S.string), // every "tags" entry
    avatar: S.file,
    prefs: S.jsonString.with(S.to, S.schema({ theme: S.string })),
  }),
);

S.decodeOrThrow(signup)(await request.formData());
// => { name: "Ann", age: 42, agree: true, newsletter: undefined, role: "user",
//      tags: ["a", "b"], avatar: File, prefs: { theme: "dark" } }

S.encodeOrThrow(signup)(value);
// => a FormData with one append per field, ready for fetch(url, { body })

Protocol Buffers need no .proto file and no code generation step. Number the fields, name S.protobuf as the other side, and the same schema still parses, infers types and converts to JSON Schema:

const userSchema = S.schema({
  id: S.int32.with(S.protobufField, 1),
  name: S.string.with(S.protobufField, 2),
  tags: S.array(S.string).with(S.protobufField, 3),
}).with(S.meta, { name: "User" });

S.encodeOrThrow(userSchema, S.protobuf, { id: 150, name: "Ada", tags: ["ml"] });
// => Uint8Array [8, 150, 1, 18, 3, 65, 100, 97, 26, 2, 109, 108]

S.decodeOrThrow(S.protobuf, userSchema, bytes);
// => { id: 150, name: "Ada", tags: ["ml"] }

S.toProtoOrThrow(userSchema, { package: "acme.v1" }); // hand the other side its .proto
// => message User {
//      int32 id = 1;
//      string name = 2;
//      repeated string tags = 3;
//    }

The code a schema turns into

(i) => {
  let v0;
  try {
    v0 = JSON.parse(i);
  } catch (t) {
    e[0](i);
  }
  if (typeof v0 === "object" && v0 && !Array.isArray(v0)) {
    for (;;) {
      if (v0.type === "user.created") {
        let v2 = v0.id, v3 = v0.tags;
        typeof v2 === "string" || e[2](v2);
        let v1;
        try {
          v1 = BigInt(v2);
        } catch (_) {
          e[1](v2);
        }
        Array.isArray(v3) || e[6](v3);
        // ...validates each tag, tracking the error path
        v8.length > 0 || e[5](v8); // e[5] throws your nonEmpty message
        v0 = { type: v0.type, id: v1, tags: v8 };
        break;
      }
      if (v0.type === "user.deleted") {
        // ...one branch per variant, no loop over union members
      }
      e[9](v0);
    }
  } else {
    e[10](v0);
  }
  return v0;
};

The encoder gets the same treatment right below - and that's why Sury tends to outrun even hand-rolled validation (benchmarks).

Encoding vs `JSON.stringify`

The encoder builds the JSON text directly - no intermediate object, the structure baked in as literals, and JSON.stringify left only the free-form payload:

(i) => {
  if (typeof i === "object" && i && !Array.isArray(i)) {
    for (;;) {
      // ...one branch per variant
      if (i.type === "user.deleted") {
        let v6 = JSON.stringify(i.payload);
        let v7 = '{"type":"user.deleted","id":"' + i.id + '"';
        if (v6 !== void 0) {
          v7 += ',"payload":' + v6;
        }
        i = v7 + "}";
        break;
      }
    }
  }
  return i;
};

And the values JSON.stringify silently corrupts throw instead:

JSON.stringify({ price: Infinity });
// => '{"price":null}'

S.encodeOrThrow(S.schema({ price: S.number }), S.jsonString, { price: Infinity });
// => throws S.Error: Failed at price: Expected JSON, received Infinity

Encode to JSON string	Sury	`JSON.stringify`	fast-json-stringify
API response (user profile, 7 fields)	305 ns	590 ns	382 ns
Event feed (50 tagged-union events)	5.05 µs	7.82 µs	20.26 µs
`bigint` id + binary payload + `Date`	1.17 µs	1.51 µs	1.45 µs

And 3.2× lighter than fast-json-stringify - 18.0 kB against 56.9 kB, encoder included.

Comparison

Sury shines in a lot of different aspects, so each of them gets a comparison page of its own:

Schema - describe a shape, check a value against it, read the type on hover. Against Zod, TypeBox, Valibot and ArkType.
JSON Encoding - turn a value into JSON text and read it back. Against JSON.stringify and fast-json-stringify.
JSON Schema - emit JSON Schema, and read somebody else's back. Against Zod, TypeBox, ArkType and Ajv.
Protobuf - the Protocol Buffers wire, without a .proto file or a codegen step. Against protobufjs, protobuf-es and pbf.

Don't take my word for it. Sury is measured by other people too:

typescript-runtime-type-benchmarks - every library in the ecosystem on the same object, in one chart
schemabenchmarks.dev - where the time goes, step by step: download, initialization, validation, parsing, Standard Schema, codec
json-schema-compliance-suite - how much of JSON Schema a library actually gets right

Integrations

Use Sury anywhere a schema is accepted:

tRPC, TanStack Form, TanStack Router, Hono, and 28+ more via the Standard Schema spec
Anything that speaks JSON Schema, via S.toInputJSONSchemaOrThrow / S.fromJSONSchemaOrThrow
nuqs - turn a schema into a search param parser

Used by

HyperIndex - Envio's blockchain indexing framework, which uses Sury to power native high-performance external calls
rescript-rest - RPC-like client, contract, and server implementation for a pure REST API
rescript-envsafe - makes sure you don't accidentally deploy apps with missing or invalid environment variables
rescript-stripe - describe and manage Stripe billing in a declarative way with code
Internal form library at Carla

Building something with Sury? Let me know and I'll add it here.

FAQ

Is `new Function` safe to use?

Why "Sury"?

It's short, it's pronounceable, and the 🧬 fits: a schema is the DNA of your data - one definition that everything else is derived from.

Resources

Standard JSON Schema vs JSON Schema (Dev.to)
Encode, Don't Stringify: How JSON.stringify Lies to You (Dev.to)
Making my TypeScript types 15.7x faster (Dev.to)
Welcome Sury - The fastest schema with next-gen DX (Dev.to)
ReScript Schema unique features (Dev.to)
Building and consuming REST API in ReScript with rescript-rest and Fastify (YouTube)

Contributing

Bug reports, ideas, and pull requests are all welcome - open an issue to get started.

License

MIT

gem-hunter

DZakh/sury（新しいタブで開きます）

README

Sury 🧬

Sponsors

Why Sury

The code a schema turns into

Encoding vs `JSON.stringify`

Comparison

Integrations

Used by

FAQ

Is `new Function` safe to use?

Why "Sury"?

Resources

Contributing

License

README

Sury 🧬

Sponsors

Why Sury

The code a schema turns into

Encoding vs `JSON.stringify`

Comparison

Integrations

Used by

FAQ

Is `new Function` safe to use?

Why "Sury"?

Resources

Contributing

License

DZakh/sury（新しいタブで開きます）

README

Sury 🧬

Sponsors

Why Sury

The code a schema turns into

Encoding vs JSON.stringify

Comparison

Integrations

Used by

FAQ

Is new Function safe to use?

Why "Sury"?

Resources

Contributing

License

README

Sury 🧬

Sponsors

Why Sury

The code a schema turns into

Encoding vs JSON.stringify

Comparison

Integrations

Used by

FAQ

Is new Function safe to use?

Why "Sury"?

Resources

Contributing

License

Encoding vs `JSON.stringify`

Is `new Function` safe to use?

Encoding vs `JSON.stringify`

Is `new Function` safe to use?