JSON Schema Validator

hipersoft/json-schema-validator

Validate JSON documents or every row of a dataset against a JSON Schema and get every failing path with a clear message. Enforce data contracts and QA scraped data.

Run this scraper →See the API call

Total users

Monthly users

Total runs

Per record validated

$0.001

Last rebuilt

Oct 26, 2026

Overview

Validate JSON documents against a JSON Schema in bulk — a single object or an array where each item is checked as one record — and get every failing path with a clear message. Enforce data contracts and QA scraped or imported data at scale.

JSON Schema Validator input — configure the options in the Apify Console

What it does

Validates data against a standard JSON Schema (Draft 7 / 2020-12), with format checks (email, uri, date…).
Handle a single object, an array of records, or a JSON/NDJSON file URL.
Returns per-record valid/invalid plus every error path and message.

Use cases

Data quality — QA scraped datasets against an expected schema.
API contracts — verify payloads match a schema before ingest.
ETL guards — catch malformed records before they hit your database.

Input

{
  "schemaText": "{ \"type\": \"object\", \"properties\": { \"email\": { \"type\": \"string\", \"format\": \"email\" } }, \"required\": [\"email\"] }",
  "dataText": "[{ \"email\": \"a@b.com\" }, { \"age\": 5 }]",
  "allErrors": true
}

Field	Type	Description
`schemaText`	string	The JSON Schema (as text).
`dataText`	string	JSON object or array to validate.
`dataUrl`	string	Optional JSON/NDJSON file URL instead of pasted data.
`allErrors`	boolean	Collect all errors per record (vs stop at first).

Output

JSON Schema Validator output — the results as a clean dataset

{ "index": 1, "valid": false, "errorCount": 1, "firstError": "/ must have required property 'email'", "errors": ["..."] }

Output schema

Field	Type	Description
`index`	integer	Record index in the input array.
`valid`	boolean	Whether the record passed.
`errorCount`	integer	Number of validation errors.
`firstError`	string	First error path + message.
`errors`	array	All error messages.

FAQ

Which JSON Schema drafts are supported? Modern drafts including Draft 7 and 2020-12, with common string formats.

Can I automate it? Yes — via integrations on the Apify platform and the Apify API.

Notes

Original clean-room implementation.

Input

Field	Type	Description
`schemaText` JSON Schema	string	The JSON Schema to validate against, as text.
`dataText` JSON data	string	The JSON to validate — a single object, or an array of objects (each validated as one record). Leave empty to use a data URL.
`dataUrl` Data URL	string	Optional: a link to a JSON/NDJSON file to validate instead of pasting data.
`allErrors` Report all errors	boolean	Collect every validation error per record instead of stopping at the first. Default: `true`

API

curl -X POST "https://api.apify.com/v2/acts/hipersoft~json-schema-validator/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
  "schemaText": "{\n  \"type\": \"object\",\n  \"properties\": { \"email\": { \"type\": \"string\", \"format\": \"email\" }, \"age\": { \"type\": \"integer\", \"minimum\": 0 } },\n  \"required\": [\"email\"]\n}",
  "dataText": "[\n  { \"email\": \"a@b.com\", \"age\": 30 },\n  { \"age\": -1 }\n]"
}'

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("hipersoft/json-schema-validator").call(run_input={
    "schemaText": "{\n  \"type\": \"object\",\n  \"properties\": { \"email\": { \"type\": \"string\", \"format\": \"email\" }, \"age\": { \"type\": \"integer\", \"minimum\": 0 } },\n  \"required\": [\"email\"]\n}",
    "dataText": "[\n  { \"email\": \"a@b.com\", \"age\": 30 },\n  { \"age\": -1 }\n]"
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('hipersoft/json-schema-validator').call({
  "schemaText": "{\n  \"type\": \"object\",\n  \"properties\": { \"email\": { \"type\": \"string\", \"format\": \"email\" }, \"age\": { \"type\": \"integer\", \"minimum\": 0 } },\n  \"required\": [\"email\"]\n}",
  "dataText": "[\n  { \"email\": \"a@b.com\", \"age\": 30 },\n  { \"age\": -1 }\n]"
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Pricing

Event	Price	Paid plans from
Record validated One JSON record validated against your schema	$0.001	$0.0005

You pay only for what the run returns. Set a maximum cost per run and it stops cleanly at that limit.

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