Getting Started
On this page
This is a pre-release version. Expect possible breaking changes and inconsistencies until the stable release (v1.0) is achieved.
Installation
To install the beta version:
bash
npm install @effect/schema
bash
npm install @effect/schema
Additionally, make sure to install the effect
package, as it's peer dependencies. Note that some package managers might not install peer dependencies by default, so you need to install them manually.
Once you have installed the library, you can import the necessary types and functions from the @effect/schema/Schema
module.
Example (Namespace Import)
ts
import * asSchema from "@effect/schema/Schema"
ts
import * asSchema from "@effect/schema/Schema"
Example (Named Import)
ts
import {Schema } from "@effect/schema"
ts
import {Schema } from "@effect/schema"
Defining a schema
One common way to define a Schema
is by utilizing the Struct
constructor provided by @effect/schema
. This constructor allows you to create a new Schema
that outlines an object with specific properties. Each property in the object is defined by its own Schema
, which specifies the data type and any validation rules.
For example, consider the following Schema
that describes a person object with a name
property of type string
and an age
property of type number
:
ts
import {Schema } from "@effect/schema"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .Number })
ts
import {Schema } from "@effect/schema"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .Number })
It's important to note that by default, most constructors exported by @effect/schema
return readonly
types. For instance, in the Person
schema above, the resulting type would be { readonly name: string; readonly age: number; }
.
Extracting Inferred Types
Type
Once you've defined a Schema<A, I, R>
, you can extract the inferred type A
, which represents the data described by the schema, in two ways:
- Using the
Schema.Schema.Type
utility. - Using the
Type
field defined on your schema.
For example, you can extract the inferred type of a Person
object as demonstrated below:
ts
import {Schema } from "@effect/schema"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .NumberFromString })// 1. Using the Schema.Type utilitytypePerson =Schema .Schema .Type <typeofPerson >/*Equivalent to:type Person = {readonly name: string;readonly age: number;}*/// 2. Using the `Type` fieldtypePerson2 = typeofPerson .Type
ts
import {Schema } from "@effect/schema"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .NumberFromString })// 1. Using the Schema.Type utilitytypePerson =Schema .Schema .Type <typeofPerson >/*Equivalent to:type Person = {readonly name: string;readonly age: number;}*/// 2. Using the `Type` fieldtypePerson2 = typeofPerson .Type
Alternatively, you can define the Person
type using the interface
keyword:
ts
interfacePerson extendsSchema .Schema .Type <typeofPerson > {}/*Equivalent to:interface Person {readonly name: string;readonly age: number;}*/
ts
interfacePerson extendsSchema .Schema .Type <typeofPerson > {}/*Equivalent to:interface Person {readonly name: string;readonly age: number;}*/
Both approaches yield the same result, but using an interface provides benefits such as performance advantages and improved readability.
Encoded
In cases where in a Schema<A, I>
the I
type differs from the A
type, you can also extract the inferred I
type using the Schema.Encoded
utility (or the Encoded
field defined on your schema).
ts
import {Schema } from "@effect/schema"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .NumberFromString })// 1. Using the Schema.Encoded utilitytypePersonEncoded =Schema .Schema .Encoded <typeofPerson >/*type PersonEncoded = {readonly name: string;readonly age: string;}*/// 2. Using the `Encoded` fieldtypePersonEncoded2 = typeofPerson .Encoded
ts
import {Schema } from "@effect/schema"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .NumberFromString })// 1. Using the Schema.Encoded utilitytypePersonEncoded =Schema .Schema .Encoded <typeofPerson >/*type PersonEncoded = {readonly name: string;readonly age: string;}*/// 2. Using the `Encoded` fieldtypePersonEncoded2 = typeofPerson .Encoded
Context
You can also extract the inferred type R
that represents the context described by the schema using the Schema.Context
utility:
ts
import {Schema } from "@effect/schema"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .NumberFromString })// type PersonContext = nevertypePersonContext =Schema .Schema .Context <typeofPerson >
ts
import {Schema } from "@effect/schema"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .NumberFromString })// type PersonContext = nevertypePersonContext =Schema .Schema .Context <typeofPerson >
Advanced extracting Inferred Types
To create a schema with an opaque type, you can use the following technique that re-declares the schema:
ts
import {Schema } from "@effect/schema"const_Person =Schema .Struct ({name :Schema .String ,age :Schema .Number })interfacePerson extendsSchema .Schema .Type <typeof_Person > {}// Re-declare the schema to create a schema with an opaque typeconstPerson :Schema .Schema <Person > =_Person
ts
import {Schema } from "@effect/schema"const_Person =Schema .Struct ({name :Schema .String ,age :Schema .Number })interfacePerson extendsSchema .Schema .Type <typeof_Person > {}// Re-declare the schema to create a schema with an opaque typeconstPerson :Schema .Schema <Person > =_Person
Alternatively, you can use the Class APIs (see the Class APIs section for more details).
Note that the technique shown above becomes more complex when the schema is defined such that A
is different from I
. For example:
ts
import {Schema } from "@effect/schema"const_Person =Schema .Struct ({name :Schema .String ,age :Schema .NumberFromString })interfacePerson extendsSchema .Schema .Type <typeof_Person > {}interfacePersonEncoded extendsSchema .Schema .Encoded <typeof_Person > {}// Re-declare the schema to create a schema with an opaque typeconstPerson :Schema .Schema <Person ,PersonEncoded > =_Person
ts
import {Schema } from "@effect/schema"const_Person =Schema .Struct ({name :Schema .String ,age :Schema .NumberFromString })interfacePerson extendsSchema .Schema .Type <typeof_Person > {}interfacePersonEncoded extendsSchema .Schema .Encoded <typeof_Person > {}// Re-declare the schema to create a schema with an opaque typeconstPerson :Schema .Schema <Person ,PersonEncoded > =_Person
In this case, the field "age"
is of type string
in the Encoded
type of the schema and is of type number
in the Type
type of the schema. Therefore, we need to define two interfaces (PersonEncoded
and Person
) and use both to redeclare our final schema Person
.
Decoding From Unknown Values
When working with unknown data types in TypeScript, decoding them into a known structure can be challenging. Luckily, @effect/schema
provides several functions to help with this process. Let's explore how to decode unknown values using these functions.
decodeUnknownSync
: Synchronously decodes a value and throws an error if parsing fails.decodeUnknownOption
: Decodes a value and returns an Option type.decodeUnknownEither
: Decodes a value and returns an Either type.decodeUnknownPromise
: Decodes a value and returns aPromise
.decodeUnknown
: Decodes a value and returns an Effect.
Example (Using decodeUnknownSync
)
Let's begin with an example using the decodeUnknownSync
function. This function is useful when you want to parse a value and immediately throw an error if the parsing fails.
ts
import {Schema } from "@effect/schema"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .Number })// Simulate an unknown inputconstinput : unknown = {name : "Alice",age : 30 }console .log (Schema .decodeUnknownSync (Person )(input ))// Output: { name: 'Alice', age: 30 }console .log (Schema .decodeUnknownSync (Person )(null))/*throws:ParseError: Expected { readonly name: string; readonly age: number }, actual null*/
ts
import {Schema } from "@effect/schema"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .Number })// Simulate an unknown inputconstinput : unknown = {name : "Alice",age : 30 }console .log (Schema .decodeUnknownSync (Person )(input ))// Output: { name: 'Alice', age: 30 }console .log (Schema .decodeUnknownSync (Person )(null))/*throws:ParseError: Expected { readonly name: string; readonly age: number }, actual null*/
Example (Using decodeUnknownEither
)
Now, let's see how to use the decodeUnknownEither
function, which returns an Either type representing success or failure.
ts
import {Schema } from "@effect/schema"import {Either } from "effect"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .Number })constdecode =Schema .decodeUnknownEither (Person )// Simulate an unknown inputconstinput : unknown = {name : "Alice",age : 30 }constresult1 =decode (input )if (Either .isRight (result1 )) {console .log (result1 .right )/*Output:{ name: "Alice", age: 30 }*/}constresult2 =decode (null)if (Either .isLeft (result2 )) {console .log (result2 .left )/*Output:{_id: 'ParseError',message: 'Expected { readonly name: string; readonly age: number }, actual null'}*/}
ts
import {Schema } from "@effect/schema"import {Either } from "effect"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .Number })constdecode =Schema .decodeUnknownEither (Person )// Simulate an unknown inputconstinput : unknown = {name : "Alice",age : 30 }constresult1 =decode (input )if (Either .isRight (result1 )) {console .log (result1 .right )/*Output:{ name: "Alice", age: 30 }*/}constresult2 =decode (null)if (Either .isLeft (result2 )) {console .log (result2 .left )/*Output:{_id: 'ParseError',message: 'Expected { readonly name: string; readonly age: number }, actual null'}*/}
The decode
function returns an Either<A, ParseError>
, where ParseError
is defined as follows:
ts
interface ParseError {readonly _tag: "ParseError"readonly issue: ParseIssue}
ts
interface ParseError {readonly _tag: "ParseError"readonly issue: ParseIssue}
Here, ParseIssue
represents an error that might occur during the parsing process. It is wrapped in a tagged error to make it easier to catch errors using Effect.catchTag. The result Either<A, ParseError>
contains the inferred data type described by the schema. A successful parse yields a Right
value with the parsed data A
, while a failed parse results in a Left
value containing a ParseError
.
When your schema involves asynchronous transformations, neither the decodeUnknownSync
nor the decodeUnknownEither
functions will work for you. In such cases, you must turn to the decodeUnknown
function, which returns an Effect.
ts
import {Schema } from "@effect/schema"import {Effect } from "effect"constPersonId =Schema .Number constPerson =Schema .Struct ({id :PersonId ,name :Schema .String ,age :Schema .Number })constasyncSchema =Schema .transformOrFail (PersonId ,Person , {strict : true,// Simulate an async transformationdecode : (id ) =>Effect .succeed ({id ,name : "name",age : 18 }).pipe (Effect .delay ("10 millis")),encode : (person ) =>Effect .succeed (person .id ).pipe (Effect .delay ("10 millis"))})constsyncParsePersonId =Schema .decodeUnknownEither (asyncSchema )console .log (JSON .stringify (syncParsePersonId (1), null, 2))/*Output:{"_id": "Either","_tag": "Left","left": {"_id": "ParseError","message": "(number <-> { readonly id: number; readonly name: string; readonly age: number })\n└─ cannot be be resolved synchronously, this is caused by using runSync on an effect that performs async work"}}*/constasyncParsePersonId =Schema .decodeUnknown (asyncSchema )Effect .runPromise (asyncParsePersonId (1)).then (console .log )/*Output:{ id: 1, name: 'name', age: 18 }*/
ts
import {Schema } from "@effect/schema"import {Effect } from "effect"constPersonId =Schema .Number constPerson =Schema .Struct ({id :PersonId ,name :Schema .String ,age :Schema .Number })constasyncSchema =Schema .transformOrFail (PersonId ,Person , {strict : true,// Simulate an async transformationdecode : (id ) =>Effect .succeed ({id ,name : "name",age : 18 }).pipe (Effect .delay ("10 millis")),encode : (person ) =>Effect .succeed (person .id ).pipe (Effect .delay ("10 millis"))})constsyncParsePersonId =Schema .decodeUnknownEither (asyncSchema )console .log (JSON .stringify (syncParsePersonId (1), null, 2))/*Output:{"_id": "Either","_tag": "Left","left": {"_id": "ParseError","message": "(number <-> { readonly id: number; readonly name: string; readonly age: number })\n└─ cannot be be resolved synchronously, this is caused by using runSync on an effect that performs async work"}}*/constasyncParsePersonId =Schema .decodeUnknown (asyncSchema )Effect .runPromise (asyncParsePersonId (1)).then (console .log )/*Output:{ id: 1, name: 'name', age: 18 }*/
As shown in the code above, the first approach returns a Forbidden
error, indicating that using decodeUnknownEither
with an async transformation is not allowed. However, the second approach works as expected, allowing you to handle async transformations and return the desired result.
Parse Options
Excess properties
When using a Schema
to parse a value, by default any properties that are not specified in the Schema
will be stripped out from the output. This is because the Schema
is expecting a specific shape for the parsed value, and any excess properties do not conform to that shape.
However, you can use the onExcessProperty
option (default value: "ignore"
) to trigger a parsing error. This can be particularly useful in cases where you need to detect and handle potential errors or unexpected values.
Here's an example of how you might use onExcessProperty
set to "error"
:
ts
import {Schema } from "@effect/schema"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .Number })console .log (Schema .decodeUnknownSync (Person )({name : "Bob",age : 40,}))/*Output:{ name: 'Bob', age: 40 }*/Schema .decodeUnknownSync (Person )({name : "Bob",age : 40,},{onExcessProperty : "error" })/*throwsParseError: { readonly name: string; readonly age: number }└─ ["email"]└─ is unexpected, expected: "name" | "age"*/
ts
import {Schema } from "@effect/schema"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .Number })console .log (Schema .decodeUnknownSync (Person )({name : "Bob",age : 40,}))/*Output:{ name: 'Bob', age: 40 }*/Schema .decodeUnknownSync (Person )({name : "Bob",age : 40,},{onExcessProperty : "error" })/*throwsParseError: { readonly name: string; readonly age: number }└─ ["email"]└─ is unexpected, expected: "name" | "age"*/
If you want to allow excess properties to remain, you can use onExcessProperty
set to "preserve"
:
ts
import {Schema } from "@effect/schema"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .Number })console .log (Schema .decodeUnknownSync (Person )({name : "Bob",age : 40,},{onExcessProperty : "preserve" }))/*{ email: 'bob@example.com', name: 'Bob', age: 40 }*/
ts
import {Schema } from "@effect/schema"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .Number })console .log (Schema .decodeUnknownSync (Person )({name : "Bob",age : 40,},{onExcessProperty : "preserve" }))/*{ email: 'bob@example.com', name: 'Bob', age: 40 }*/
The onExcessProperty and error options also affect encoding.
All errors
The errors
option allows you to receive all parsing errors when attempting to parse a value using a schema. By default only the first error is returned, but by setting the errors
option to "all"
, you can receive all errors that occurred during the parsing process. This can be useful for debugging or for providing more comprehensive error messages to the user.
Here's an example of how you might use errors
:
ts
import {Schema } from "@effect/schema"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .Number })Schema .decodeUnknownSync (Person )({name : "Bob",age : "abc",},{errors : "all",onExcessProperty : "error" })/*throwsParseError: { readonly name: string; readonly age: number }├─ ["email"]│ └─ is unexpected, expected: "name" | "age"└─ ["age"]└─ Expected number, actual "abc"*/
ts
import {Schema } from "@effect/schema"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .Number })Schema .decodeUnknownSync (Person )({name : "Bob",age : "abc",},{errors : "all",onExcessProperty : "error" })/*throwsParseError: { readonly name: string; readonly age: number }├─ ["email"]│ └─ is unexpected, expected: "name" | "age"└─ ["age"]└─ Expected number, actual "abc"*/
The onExcessProperty and error options also affect encoding.
Managing Property Order
The propertyOrder
option provides control over the order of object fields in the output. This feature is particularly useful when the sequence of keys is important for the consuming processes or when maintaining the input order enhances readability and usability.
By default, the propertyOrder
option is set to "none"
. This means that the internal system decides the order of keys to optimize parsing speed. The order of keys in this mode should not be considered stable, and it's recommended not to rely on key ordering as it may change in future updates without notice.
Setting propertyOrder
to "original"
ensures that the keys are ordered as they appear in the input during the decoding/encoding process.
Example (Synchronous Decoding)
ts
import {Schema } from "@effect/schema"constschema =Schema .Struct ({a :Schema .Number ,b :Schema .Literal ("b"),c :Schema .Number })// Decoding an object synchronously without specifying the property orderconsole .log (Schema .decodeUnknownSync (schema )({b : "b",c : 2,a : 1 }))// Output decided internally: { b: 'b', a: 1, c: 2 }// Decoding an object synchronously while preserving the order of properties as in the inputconsole .log (Schema .decodeUnknownSync (schema )({b : "b",c : 2,a : 1 },{propertyOrder : "original" }))// Output preserving input order: { b: 'b', c: 2, a: 1 }
ts
import {Schema } from "@effect/schema"constschema =Schema .Struct ({a :Schema .Number ,b :Schema .Literal ("b"),c :Schema .Number })// Decoding an object synchronously without specifying the property orderconsole .log (Schema .decodeUnknownSync (schema )({b : "b",c : 2,a : 1 }))// Output decided internally: { b: 'b', a: 1, c: 2 }// Decoding an object synchronously while preserving the order of properties as in the inputconsole .log (Schema .decodeUnknownSync (schema )({b : "b",c : 2,a : 1 },{propertyOrder : "original" }))// Output preserving input order: { b: 'b', c: 2, a: 1 }
Example (Asynchronous Decoding)
ts
import {ParseResult ,Schema } from "@effect/schema"import type {Duration } from "effect"import {Effect } from "effect"// Function to simulate an asynchronous process within the schemaconsteffectify = (duration :Duration .DurationInput ) =>Schema .Number .pipe (Schema .transformOrFail (Schema .Number , {strict : true,decode : (x ) =>Effect .sleep (duration ).pipe (Effect .andThen (ParseResult .succeed (x ))),encode :ParseResult .succeed }))// Define a structure with asynchronous behavior in each fieldconstschema =Schema .Struct ({a :effectify ("200 millis"),b :effectify ("300 millis"),c :effectify ("100 millis")}).annotations ({concurrency : 3 })// Decoding data asynchronously without preserving orderSchema .decode (schema )({a : 1,b : 2,c : 3 }).pipe (Effect .runPromise ).then (console .log )// Output decided internally: { c: 3, a: 1, b: 2 }// Decoding data asynchronously while preserving the original input orderSchema .decode (schema )({a : 1,b : 2,c : 3 }, {propertyOrder : "original" }).pipe (Effect .runPromise ).then (console .log )// Output preserving input order: { a: 1, b: 2, c: 3 }
ts
import {ParseResult ,Schema } from "@effect/schema"import type {Duration } from "effect"import {Effect } from "effect"// Function to simulate an asynchronous process within the schemaconsteffectify = (duration :Duration .DurationInput ) =>Schema .Number .pipe (Schema .transformOrFail (Schema .Number , {strict : true,decode : (x ) =>Effect .sleep (duration ).pipe (Effect .andThen (ParseResult .succeed (x ))),encode :ParseResult .succeed }))// Define a structure with asynchronous behavior in each fieldconstschema =Schema .Struct ({a :effectify ("200 millis"),b :effectify ("300 millis"),c :effectify ("100 millis")}).annotations ({concurrency : 3 })// Decoding data asynchronously without preserving orderSchema .decode (schema )({a : 1,b : 2,c : 3 }).pipe (Effect .runPromise ).then (console .log )// Output decided internally: { c: 3, a: 1, b: 2 }// Decoding data asynchronously while preserving the original input orderSchema .decode (schema )({a : 1,b : 2,c : 3 }, {propertyOrder : "original" }).pipe (Effect .runPromise ).then (console .log )// Output preserving input order: { a: 1, b: 2, c: 3 }
Customizing Parsing Behavior at the Schema Level
You can tailor parse options for each schema using the parseOptions
annotation. These options allow for specific parsing behavior at various levels of the schema hierarchy, overriding any parent settings and cascading down to nested schemas.
ts
import {Schema } from "@effect/schema"import {Either } from "effect"constschema =Schema .Struct ({a :Schema .Struct ({b :Schema .String ,c :Schema .String }).annotations ({title : "first error only",parseOptions : {errors : "first" } // Only the first error in this sub-schema is reported}),d :Schema .String }).annotations ({title : "all errors",parseOptions : {errors : "all" } // All errors in the main schema are reported})constresult =Schema .decodeUnknownEither (schema )({a : {} },{errors : "first" })if (Either .isLeft (result )) {console .log (result .left .message )}/*all errors├─ ["d"]│ └─ is missing└─ ["a"]└─ first error only└─ ["b"]└─ is missing*/
ts
import {Schema } from "@effect/schema"import {Either } from "effect"constschema =Schema .Struct ({a :Schema .Struct ({b :Schema .String ,c :Schema .String }).annotations ({title : "first error only",parseOptions : {errors : "first" } // Only the first error in this sub-schema is reported}),d :Schema .String }).annotations ({title : "all errors",parseOptions : {errors : "all" } // All errors in the main schema are reported})constresult =Schema .decodeUnknownEither (schema )({a : {} },{errors : "first" })if (Either .isLeft (result )) {console .log (result .left .message )}/*all errors├─ ["d"]│ └─ is missing└─ ["a"]└─ first error only└─ ["b"]└─ is missing*/
Detailed Output Explanation:
In this example:
- The main schema is configured to display all errors. Hence, you will see errors related to both the
d
field (since it's missing) and any errors from thea
subschema. - The subschema (
a
) is set to display only the first error. Although bothb
andc
fields are missing, only the first missing field (b
) is reported.
Managing Missing Properties
When using the @effect/schema
library to handle data structures, it's important to understand how missing properties are processed. By default, if a property is not present in the input, it is treated as if it were present with an undefined
value.
ts
import {Schema } from "@effect/schema"constschema =Schema .Struct ({a :Schema .Unknown })constinput = {}console .log (Schema .decodeUnknownSync (schema )(input )) // Output: { a: undefined }
ts
import {Schema } from "@effect/schema"constschema =Schema .Struct ({a :Schema .Unknown })constinput = {}console .log (Schema .decodeUnknownSync (schema )(input )) // Output: { a: undefined }
In this example, although the key "a"
is not present in the input, it is treated as { a: undefined }
by default.
If your validation logic needs to distinguish between truly missing properties and those that are explicitly undefined, you can enable the exact
option:
ts
import {Schema } from "@effect/schema"constschema =Schema .Struct ({a :Schema .Unknown })constinput = {}console .log (Schema .decodeUnknownSync (schema )(input , {exact : true }))/*throwsParseError: { readonly a: unknown }└─ ["a"]└─ is missing*/
ts
import {Schema } from "@effect/schema"constschema =Schema .Struct ({a :Schema .Unknown })constinput = {}console .log (Schema .decodeUnknownSync (schema )(input , {exact : true }))/*throwsParseError: { readonly a: unknown }└─ ["a"]└─ is missing*/
For the APIs Schema.is
and Schema.asserts
, however, the default behavior is to treat missing properties strictly, where the default for exact
is true
:
ts
import type {AST } from "@effect/schema"import {Schema } from "@effect/schema"constschema =Schema .Struct ({a :Schema .Unknown })constinput = {}console .log (Schema .is (schema )(input )) // Output: falseconsole .log (Schema .is (schema )(input , {exact : false })) // Output: trueconstasserts : (u : unknown,overrideOptions ?:AST .ParseOptions ) => assertsu is {readonlya : unknown} =Schema .asserts (schema )try {asserts (input )console .log ("asserts passed")} catch (e : any) {console .error ("asserts failed")console .error (e .message )}/*Output:asserts failed{ readonly a: unknown }└─ ["a"]└─ is missing*/try {asserts (input , {exact : false })console .log ("asserts passed")} catch (e : any) {console .error ("asserts failed")console .error (e .message )}// Output: asserts passed
ts
import type {AST } from "@effect/schema"import {Schema } from "@effect/schema"constschema =Schema .Struct ({a :Schema .Unknown })constinput = {}console .log (Schema .is (schema )(input )) // Output: falseconsole .log (Schema .is (schema )(input , {exact : false })) // Output: trueconstasserts : (u : unknown,overrideOptions ?:AST .ParseOptions ) => assertsu is {readonlya : unknown} =Schema .asserts (schema )try {asserts (input )console .log ("asserts passed")} catch (e : any) {console .error ("asserts failed")console .error (e .message )}/*Output:asserts failed{ readonly a: unknown }└─ ["a"]└─ is missing*/try {asserts (input , {exact : false })console .log ("asserts passed")} catch (e : any) {console .error ("asserts failed")console .error (e .message )}// Output: asserts passed
Encoding
The @effect/schema/Schema
module provides several encode*
functions to encode data according to a schema:
encodeSync
: Synchronously encodes data and throws an error if encoding fails.encodeOption
: Encodes data and returns an Option type.encodeEither
: Encodes data and returns an Either type representing success or failure.encodePromise
: Encodes data and returns aPromise
.encode
: Encodes data and returns an Effect.
Let's consider an example where we have a schema for a Person
object with a name
property of type string
and an age
property of type number
.
ts
import {Schema } from "@effect/schema"// Age is a schema that can decode a string to a number and encode a number to a stringconstAge =Schema .NumberFromString constPerson =Schema .Struct ({name :Schema .NonEmptyString ,age :Age })console .log (Schema .encodeSync (Person )({name : "Alice",age : 30 }))// Output: { name: 'Alice', age: '30' }console .log (Schema .encodeSync (Person )({name : "",age : 30 }))/*throws:ParseError: { readonly name: NonEmpty; readonly age: NumberFromString }└─ ["name"]└─ NonEmpty└─ Predicate refinement failure└─ Expected NonEmpty (a non empty string), actual ""*/
ts
import {Schema } from "@effect/schema"// Age is a schema that can decode a string to a number and encode a number to a stringconstAge =Schema .NumberFromString constPerson =Schema .Struct ({name :Schema .NonEmptyString ,age :Age })console .log (Schema .encodeSync (Person )({name : "Alice",age : 30 }))// Output: { name: 'Alice', age: '30' }console .log (Schema .encodeSync (Person )({name : "",age : 30 }))/*throws:ParseError: { readonly name: NonEmpty; readonly age: NumberFromString }└─ ["name"]└─ NonEmpty└─ Predicate refinement failure└─ Expected NonEmpty (a non empty string), actual ""*/
Note that during encoding, the number value 30
was converted to a string "30"
.
The onExcessProperty and error options also affect encoding.
Handling Unsupported Encoding
Although it is generally recommended to define schemas that support both decoding and encoding, there are situations where encoding support might be impossible. In such cases, the Forbidden
error can be used to handle unsupported encoding.
Here is an example of a transformation that never fails during decoding. It returns an Either containing either the decoded value or the original input. For encoding, it is reasonable to not support it and use Forbidden
as the result.
ts
import {ParseResult ,Schema } from "@effect/schema"import {Either } from "effect"// Define a schema that safely decodes to Either typeexport constSafeDecode = <A ,I >(self :Schema .Schema <A ,I , never>) => {constdecodeUnknownEither =Schema .decodeUnknownEither (self )returnSchema .transformOrFail (Schema .Unknown ,Schema .EitherFromSelf ({left :Schema .Unknown ,right :Schema .typeSchema (self )}),{strict : true,decode : (input ) =>ParseResult .succeed (Either .mapLeft (decodeUnknownEither (input ), () =>input )),encode : (actual ,_ ,ast ) =>Either .match (actual , {onLeft : () =>ParseResult .fail (newParseResult .Forbidden (ast ,actual , "cannot encode a Left")),onRight :ParseResult .succeed })})}
ts
import {ParseResult ,Schema } from "@effect/schema"import {Either } from "effect"// Define a schema that safely decodes to Either typeexport constSafeDecode = <A ,I >(self :Schema .Schema <A ,I , never>) => {constdecodeUnknownEither =Schema .decodeUnknownEither (self )returnSchema .transformOrFail (Schema .Unknown ,Schema .EitherFromSelf ({left :Schema .Unknown ,right :Schema .typeSchema (self )}),{strict : true,decode : (input ) =>ParseResult .succeed (Either .mapLeft (decodeUnknownEither (input ), () =>input )),encode : (actual ,_ ,ast ) =>Either .match (actual , {onLeft : () =>ParseResult .fail (newParseResult .Forbidden (ast ,actual , "cannot encode a Left")),onRight :ParseResult .succeed })})}
Explanation
- Decoding: The
SafeDecode
function ensures that decoding never fails. It wraps the decoded value in an Either, where a successful decoding results in aRight
and a failed decoding results in aLeft
containing the original input. - Encoding: The encoding process uses the
Forbidden
error to indicate that encoding aLeft
value is not supported. OnlyRight
values are successfully encoded.
Naming Conventions
The naming conventions in @effect/schema
are designed to be straightforward and logical, focusing primarily on compatibility with JSON serialization. This approach simplifies the understanding and use of schemas, especially for developers who are integrating web technologies where JSON is a standard data interchange format.
Overview of Naming Strategies
JSON-Compatible Types
Schemas that naturally serialize to JSON-compatible formats are named directly after their data types.
For instance:
Schema.Date
: serializes JavaScript Date objects to ISO-formatted strings, a typical method for representing dates in JSON.Schema.Number
: used directly as it maps precisely to the JSON number type, requiring no special transformation to remain JSON-compatible.
Non-JSON-Compatible Types
When dealing with types that do not have a direct representation in JSON, the naming strategy incorporates additional details to indicate the necessary transformation. This helps in setting clear expectations about the schema's behavior:
For instance:
Schema.DateFromSelf
: indicates that the schema handlesDate
objects, which are not natively JSON-serializable.Schema.NumberFromString
: this naming suggests that the schema processes numbers that are initially represented as strings, emphasizing the transformation from string to number when decoding.
Practical Application
The primary goal of these schemas is to ensure that domain objects can be easily serialized ("encoded") and deserialized ("decoded") for transmission over network connections, thus facilitating their transfer between different parts of an application or across different applications.
Here is an example demonstrating how straightforward naming conventions can be applied:
ts
import {Schema } from "@effect/schema"constschema =Schema .Struct ({sym :Schema .Symbol ,optional :Schema .Option (Schema .Date ),chunk :Schema .Chunk (Schema .BigInt ),createdAt :Schema .Date ,updatedAt :Schema .Date })// This approach is preferred over more complex naming conventions like:/*const schema = Schema.Struct({sym: Schema.SymbolFromString,optional: Schema.OptionFromJson(Schema.DateFromString),chunk: Schema.ChunkFromJson(Schema.BigIntFromString),createdAt: Schema.DateFromString,updatedAt: Schema.DateFromString})*/
ts
import {Schema } from "@effect/schema"constschema =Schema .Struct ({sym :Schema .Symbol ,optional :Schema .Option (Schema .Date ),chunk :Schema .Chunk (Schema .BigInt ),createdAt :Schema .Date ,updatedAt :Schema .Date })// This approach is preferred over more complex naming conventions like:/*const schema = Schema.Struct({sym: Schema.SymbolFromString,optional: Schema.OptionFromJson(Schema.DateFromString),chunk: Schema.ChunkFromJson(Schema.BigIntFromString),createdAt: Schema.DateFromString,updatedAt: Schema.DateFromString})*/
Rationale
While JSON's ubiquity justifies its primary consideration in naming, the conventions also accommodate serialization for other types of transport. For instance, converting a Date
to a string is a universally useful method for various communication protocols, not just JSON. Thus, the selected naming conventions serve as sensible defaults that prioritize clarity and ease of use, facilitating the serialization and deserialization processes across diverse technological environments.
Type Guards
The Schema.is
function provided by the @effect/schema/Schema
module represents a way of verifying that a value conforms to a given schema.
It functions as a type guard, taking a value of type unknown
and determining if it matches the structure and type constraints defined in the schema.
Here's how the Schema.is
function works
-
Schema Definition: Define a schema to describe the structure and constraints of the data type you expect. For instance,
Schema<A, I, R>
whereA
is the desired type. -
Type Guard Creation: Convert the schema into a user-defined type guard
(u: unknown) => u is A
. This allows you to assert at runtime whether a value meets the specified schema.
The type I
, typically used in schema transformations, does not influence the generation of the type guard. The primary focus is on ensuring that the input conforms to the desired type A
.
Example Usage:
ts
import {Schema } from "@effect/schema"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .Number })/*const isPerson: (a: unknown, options?: number | ParseOptions) => a is {readonly name: string;readonly age: number;}*/constisPerson =Schema .is (Person )console .log (isPerson ({name : "Alice",age : 30 })) // trueconsole .log (isPerson (null)) // falseconsole .log (isPerson ({})) // false
ts
import {Schema } from "@effect/schema"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .Number })/*const isPerson: (a: unknown, options?: number | ParseOptions) => a is {readonly name: string;readonly age: number;}*/constisPerson =Schema .is (Person )console .log (isPerson ({name : "Alice",age : 30 })) // trueconsole .log (isPerson (null)) // falseconsole .log (isPerson ({})) // false
Assertions
While type guards verify and inform about type conformity, the Schema.asserts
function takes it a step further by asserting that an input matches the schema A
type (from Schema<A, I, R>
). If the input does not match, it throws a detailed error.
Example Usage:
ts
import {Schema } from "@effect/schema"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .Number })// equivalent to: (input: unknown, options?: ParseOptions) => asserts input is { readonly name: string; readonly age: number; }constassertsPerson :Schema .Schema .ToAsserts <typeofPerson > =Schema .asserts (Person )try {assertsPerson ({name : "Alice",age : "30" })} catch (e ) {console .error ("The input does not match the schema:")console .error (e )}/*The input does not match the schema:{_id: 'ParseError',message: '{ readonly name: string; readonly age: number }\n' +'└─ ["age"]\n' +' └─ Expected number, actual "30"'}*/// this will not throw an errorassertsPerson ({name : "Alice",age : 30 })
ts
import {Schema } from "@effect/schema"constPerson =Schema .Struct ({name :Schema .String ,age :Schema .Number })// equivalent to: (input: unknown, options?: ParseOptions) => asserts input is { readonly name: string; readonly age: number; }constassertsPerson :Schema .Schema .ToAsserts <typeofPerson > =Schema .asserts (Person )try {assertsPerson ({name : "Alice",age : "30" })} catch (e ) {console .error ("The input does not match the schema:")console .error (e )}/*The input does not match the schema:{_id: 'ParseError',message: '{ readonly name: string; readonly age: number }\n' +'└─ ["age"]\n' +' └─ Expected number, actual "30"'}*/// this will not throw an errorassertsPerson ({name : "Alice",age : 30 })