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Ocupaciones relacionadas SOC
Basado en la clasificación ocupacional SOC
name json-transformer description Transform, validate, convert, and restructure data between JSON, YAML, TOML, CSV, and XML formats with schema validation layer utility category data-processing triggers ["transform json","convert json","json to yaml","yaml to json","validate json","json schema","restructure data","flatten json","merge json","transform data"] inputs ["Source data (JSON, YAML, TOML, CSV, or XML)","Target format or structure","Transformation rules (field mapping, filtering, reshaping)","Validation schema (JSON Schema, Zod, or natural language)"] outputs ["Transformed data in target format","Validation results with error details","Transformation code (reusable function)","Schema definitions (JSON Schema, Zod, TypeScript types)"] linksTo ["regex-builder","api-designer","data-modeling"] linkedFrom ["shell-scripting","migration-planner"] preferredNextSkills ["testing-patterns","api-designer"] fallbackSkills ["code-explainer"] riskLevel low memoryReadPolicy selective memoryWritePolicy selective sideEffects ["May create or modify data files","May add validation library dependencies"]
JSON Transformer Skill
Purpose
Restructure, validate, and convert data between formats. Whether transforming API responses, migrating configuration formats, flattening nested structures, or generating schemas, this skill handles the full spectrum of data transformation tasks.
Key Concepts
Transformation Types
Operation Description Example Reshape Change structure without losing data Nest flat fields into objects Map Transform values Rename keys, format dates Filter Remove unwanted data Drop null fields, select specific keys Flatten Reduce nesting depth {a: {b: 1}} -> {"a.b": 1}Unflatten Increase nesting depth {"a.b": 1} -> {a: {b: 1}}Merge Combine multiple sources Deep merge config files Validate Check conformance to schema JSON Schema, Zod Convert Change format JSON <-> YAML <-> TOML <-> CSV
Data Format Quick Reference
server:
host: localhost
port: 3000
features:
- auth
- logging
[server]
host = "localhost"
port = 3000
features = ["auth"
"logging"
{
"server" : {
"host" : "localhost" ,
"port" : 3000 ,
"features" : [ "auth" , "logging" ]
}
}
Workflow
Pattern 1: Restructure / Reshape
interface APIResponse {
user_id : string ;
user_name : string ;
user_email : string ;
address_street : string ;
address_city : string ;
address_zip : string ;
}
interface UserModel {
id : string ;
name : string ;
email : string ;
address : {
street : string ;
city : string ;
zip : string ;
};
}
function transformUser (raw : APIResponse UserModel {
return {
id : raw.user_id ,
name : raw.user_name ,
email : raw.user_email ,
address : {
street : raw.address_street ,
city : raw.address_city ,
zip : raw.address_zip ,
},
};
}
Pattern 2: Flatten / Unflatten
function flatten (
obj : Record <string , unknown >,
prefix = '' ,
result : Record <string , unknown > = {}
): Record <string , unknown > {
for (const [key, value] of Object .entries (obj)) {
const fullKey = prefix ? `${prefix} .${key} ` : key;
if (value !== null && typeof value === 'object' && !Array .isArray (value)) {
flatten (value as Record <string , unknown >, fullKey, result);
} else {
result[fullKey] = value;
}
}
return result;
}
function unflatten (obj : Record <string , unknown >Record <string , unknown > {
const result : Record <string , unknown > = {};
for (const [key, value] of Object .entries (obj)) {
const keys = key.split ('.' );
let current = result;
for (let i = 0 ; i < keys.length - 1 ; i++) {
if (!(keys[i] in current)) {
current[keys[i]] = {};
}
current = current[keys[i]] as Record <string , unknown >;
}
current[keys[keys.length - 1 ]] = value;
}
return result;
}
Pattern 3: Deep Merge function deepMerge<T extends Record <string , unknown >>(target : T, ...sources : Partial <T>[]): T {
const result = { ...target };
for (const source of sources) {
for (const [key, value] of Object .entries (source)) {
if (
value !== null &&
typeof value === 'object' &&
!Array .isArray (value) &&
typeof result[key] === 'object' &&
result[key] !== null &&
!Array .isArray (result[key])
) {
(result as Record <string , unknown >)[key] = deepMerge (
result[key] as Record <string , unknown >,
value as Record <string , unknown >
);
} else {
(result as Record <string , unknown >)[key] = value;
}
}
}
return result;
}
const config = deepMerge (
defaultConfig,
envConfig,
localOverrides
);
Pattern 4: Schema Validation with Zod import { z } from 'zod' ;
const UserSchema = z.object ({
id : z.string ().uuid (),
name : z.string ().min (1 ).max (100 ),
email : z.string ().email (),
age : z.number ().int ().min (0 ).max (150 ).optional (),
role : z.enum (['admin' , 'user' , 'moderator' ]),
preferences : z.object ({
theme : z.enum (['light' , 'dark' ]).default ('light' ),
notifications : z.boolean ().default (true ),
}).optional (),
tags : z.array (z.string ()).max (10 ).default ([]),
createdAt : z.string ().datetime (),
});
type User = z.infer <typeof UserSchema >;
function validateUser (data : unknown success : true ; data : User } | { success : false ; errors : string [] } {
const result = UserSchema .safeParse (data);
if (result.success ) {
return { success : true , data : result.data };
}
return {
success : false ,
errors : result.error .issues .map (
(issue ) => `${issue.path.join('.' )} : ${issue.message} `
),
};
}
Pattern 5: JSON Schema Generation
function generateJsonSchema (description : string object {
return {
"$schema" : "http://json-schema.org/draft-07/schema#" ,
"type" : "object" ,
"properties" : {
"id" : { "type" : "string" , "format" : "uuid" },
"name" : { "type" : "string" , "minLength" : 1 , "maxLength" : 100 },
"email" : { "type" : "string" , "format" : "email" },
"age" : { "type" : "integer" , "minimum" : 0 , "maximum" : 150 },
"role" : { "type" : "string" , "enum" : ["admin" , "user" , "moderator" ] },
"tags" : {
"type" : "array" ,
"items" : { "type" : "string" },
"maxItems" : 10 ,
"default" : []
},
"createdAt" : { "type" : "string" , "format" : "date-time" }
},
"required" : ["id" , "name" , "email" , "role" , "createdAt" ],
"additionalProperties" : false
};
}
Pattern 6: Format Conversion
import yaml from 'js-yaml' ;
function jsonToYaml (jsonData : unknown string {
return yaml.dump (jsonData, {
indent : 2 ,
lineWidth : 120 ,
noRefs : true ,
sortKeys : true ,
quotingType : '"' ,
});
}
function yamlToJson (yamlString : string unknown {
return yaml.load (yamlString);
}
import TOML from '@iarna/toml' ;
function jsonToToml (jsonData : Record <string , unknown >string {
return TOML .stringify (jsonData as TOML .JsonMap );
}
function tomlToJson (tomlString : string unknown {
return TOML .parse (tomlString);
}
function csvToJson (csv : string , delimiter = ',' Record <string , string >[] {
const lines = csv.trim ().split ('\n' );
const headers = lines[0 ].split (delimiter).map (h =>trim ());
return lines.slice (1 ).map (line =>const values = line.split (delimiter).map (v =>trim ());
return Object .fromEntries (headers.map ((h, i ) => [h, values[i] ?? '' ]));
});
}
function jsonToCsv (data : Record <string , unknown >[], delimiter = ',' string {
if (data.length === 0 ) return '' ;
const headers = Object .keys (data[0 ]);
const rows = data.map (row =>map (h =>const val = String (row[h] ?? '' );
return val.includes (delimiter) || val.includes ('"' ) || val.includes ('\n' )
? `"${val.replace(/"/g, '" "')}" `
: val;
}).join(delimiter)
);
return [headers.join(delimiter), ...rows].join('\n');
}
Pattern 7: jq-Style Transformations in JavaScript
class JsonTransformer <T> {
constructor (private data : Tstatic from <T>(data : T) {
return new JsonTransformer (data);
}
select<R>(selector : (data : T R): JsonTransformer <R> {
return new JsonTransformer (selector (this .data ));
}
map<R>(fn : (item : T extends Array <infer U> ? U : never R): JsonTransformer <R[]> {
if (!Array .isArray (this .data )) throw new Error ('map requires array' );
return new JsonTransformer ((this .data as unknown []).map (fn as (item : unknown ) => R));
}
filter (fn : (item : T extends Array <infer U> ? U : never boolean ): JsonTransformer <T> {
if (!Array .isArray (this .data )) throw new Error ('filter requires array' );
return new JsonTransformer ((this .data as unknown []).filter (fn as (item : unknown ) => boolean ) as unknown as T);
}
pick (...keys : string []): JsonTransformer <Partial <T>> {
const obj = this .data as Record <string , unknown >;
const result : Record <string , unknown > = {};
for (const key of keys) {
if (key in obj) result[key] = obj[key];
}
return new JsonTransformer (result as Partial <T>);
}
value (): T {
return this .data ;
}
}
const result = JsonTransformer .from (apiResponse)
.select (d =>users )
.filter (u =>active )
.map (u =>id : u.id , name : u.name }))
.value ();
Validation Error Formatting When validation fails, present errors clearly:
Validation Errors (3):
1. $.email: Expected string with email format, received "not-an-email"
Path: root > email
Rule: format = "email"
2. $.age: Expected integer >= 0, received -5
Path: root > age
Rule: minimum = 0
3. $.tags[2]: Expected string, received 42
Path: root > tags > [2]
Rule: type = "string"
CLI Quick Reference
cat data.json | jq '.users[] | select(.active) | {name, email}'
cat data.json | jq '.items | length'
cat data.json | jq '.config.server.port'
yq '.server.port' config.yaml
yq -i '.server.port = 8080' config.yaml
yq -o=json config.yaml
yq -P config.json
cat data.csv | mlr --csv2json
