# JSON Schema Batch Validator (`junipr/json-schema-batch-validator`) Actor Validate JSON/JSONL batches against JSON Schema and return row-level validation errors and summaries. - **URL**: https://apify.com/junipr/json-schema-batch-validator.md - **Developed by:** [junipr](https://apify.com/junipr) (community) - **Categories:** SEO tools, Developer tools, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.90 / 1,000 record processeds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## JSON Schema Batch Validator ### Store Positioning **Store title:** JSON Schema Batch Validator **Short description:** Validate JSON/JSONL batches against JSON Schema and return row-level validation errors and summaries. **SEO title:** JSON Schema Batch Validator — data QA, validation, and cleanup utility **SEO description:** Validate JSON/JSONL batches against JSON Schema and return row-level validation errors and summaries. Use it to validate rows, schemas, duplicates, field quality, and delivery-readiness before handing data to clients or automations. **Categories:** SEO_TOOLS, DEVELOPER_TOOLS, ECOMMERCE **Keywords:** json, schema, batch, validator, data/schema qa utility ### Pricing This actor uses pay-per-event pricing. Event prices include Apify platform usage; users are not expected to pay a separate platform-usage pass-through charge for the configured pricing model. - Tier: U2 — Data/schema QA utility - Primary event: `schema-validated` at $0.00390 base - Default max charge: $5.00 - Store discounts: FREE/BRONZE base, SILVER discounted, GOLD deepest approved discount Event set: - `actor-start`: base $0.00500, GOLD $0.00400. JSON Schema Batch Validator: charged when actor start is completed. The price includes Apify platform usage; no separate usage pass-through is intended. - `schema-validated`: base $0.00390, GOLD $0.00312. JSON Schema Batch Validator: charged when schema validated is completed. The price includes Apify platform usage; no separate usage pass-through is intended. - `issue-detected`: base $0.00372, GOLD $0.00298. JSON Schema Batch Validator: charged when issue detected is completed. The price includes Apify platform usage; no separate usage pass-through is intended. - `qa-report-generated`: base $0.05000, GOLD $0.04000. JSON Schema Batch Validator: charged when qa report generated is completed. The price includes Apify platform usage; no separate usage pass-through is intended. ### Public Task Concepts - Validate JSON Schema Batch records from bounded input - Find invalid JSON Schema Batch values before delivery - Check JSON Schema Batch coverage against expected rules - Review JSON Schema Batch failures with error paths - Export JSON Schema Batch pass-fail rows with evidence ### What It Does Validate JSON/JSONL batches against JSON Schema and return row-level validation errors and summaries. Use it to identify missing required fields and type mismatches in a bounded set of JSON records before ingestion or API delivery. ### What It Does Not Do - It does not repair invalid records or mutate the supplied schema. - It does not call external endpoints or upload records to third-party services. - It currently checks required properties and declared primitive property types. - It does not replace a full application-level semantic validation suite. ### Input Fields Provide `schemaJson` and `recordsJson`, then set bounded item and charge limits. ### Output Fields - `rowIndex` - `isValid` - `errorCount` - `errorPath` - `errorKeyword` - `errorMessage` - `schemaPath` - `warnings` ### Public Task Examples #### Validate JSON records against a JSON Schema - Input: A JSON Schema and a bounded array of records. - Output: Row-level validity, error counts, paths, keywords, messages, and an optional report. - Use case: Catch contract violations before sending a batch downstream. #### Find missing required fields in a batch import - Input: Records where selected required fields are intentionally absent. - Output: Failed rows with required-field error paths and messages. - Use case: Stop incomplete imports before they reach production tables. #### Report type mismatches in JSON payload samples - Input: Payload samples containing strings, numbers, and booleans in incorrect fields. - Output: Type mismatch paths, expected type keywords, and row-level validity. - Use case: Identify coercion problems before integrating a feed. #### Create validation rows for API example records - Input: API documentation examples and the corresponding object schema. - Output: One normalized validation row per example record. - Use case: Verify that published examples satisfy the stated contract. #### Audit customer JSON before ingestion - Input: A capped customer JSON export and its expected schema. - Output: Valid and invalid row evidence with an optional summary. - Use case: Triage customer import defects before ingestion. ### Tests - Actor-specific tests live in `test/json-schema-batch-validator.test.ts`. - The suite validates output artifacts, invalid/no-result cases, report billing, and max-charge stops. ### FAQ #### Does the actor modify invalid records? No. It reports validation evidence and leaves the supplied records unchanged. #### Are all JSON Schema keywords supported? The current bounded validator covers required properties and declared primitive property types. Use a full schema engine when advanced keywords are required. # Actor input Schema ## `schemaJson` (type: `object`): Object schema used to validate each supplied record. ## `recordsJson` (type: `array`): JSON records to check against the schema. ## `maxRecords` (type: `integer`): Hard cap for emitted validation rows. ## `includeValidRows` (type: `boolean`): Include passing records as well as failed records. ## `failFast` (type: `boolean`): Return only the first invalid record. ## `includeReport` (type: `boolean`): Create charged Markdown and JSON report artifacts. ## `maxChargeUsd` (type: `number`): Stop before an event would exceed this run budget. ## Actor input object example ```json { "schemaJson": { "type": "object", "properties": { "productId": { "type": "integer", "title": "Product Id", "description": "Product Id input value." }, "productName": { "type": "string", "title": "Product Name", "description": "Product Name input value." }, "price": { "type": "number", "title": "Price", "description": "Price input value." }, "tags": { "type": "array", "title": "Tags", "description": "Tags input value." } }, "required": [ "productId", "productName", "price" ] }, "recordsJson": [ { "productId": 1, "productName": "A green door", "price": 12.5, "tags": [ "home", "green" ] } ], "maxRecords": 1, "includeValidRows": true, "failFast": false, "includeReport": true, "maxChargeUsd": 1 } ```` # Actor output Schema ## `dataset` (type: `string`): Structured rows emitted by the actor. ## `report` (type: `string`): Run summary report stored in the default key-value store. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("junipr/json-schema-batch-validator").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("junipr/json-schema-batch-validator").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call junipr/json-schema-batch-validator --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=junipr/json-schema-batch-validator", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "JSON Schema Batch Validator", "description": "Validate JSON/JSONL batches against JSON Schema and return row-level validation errors and summaries.", "version": "1.0", "x-build-id": "yyVfs2a3YjcOTYlRM" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/junipr~json-schema-batch-validator/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-junipr-json-schema-batch-validator", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/junipr~json-schema-batch-validator/runs": { "post": { "operationId": "runs-sync-junipr-json-schema-batch-validator", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/junipr~json-schema-batch-validator/run-sync": { "post": { "operationId": "run-sync-junipr-json-schema-batch-validator", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "schemaJson": { "title": "JSON Schema", "type": "object", "description": "Object schema used to validate each supplied record.", "default": { "type": "object", "properties": { "productId": { "type": "integer", "title": "Product Id", "description": "Product Id input value." }, "productName": { "type": "string", "title": "Product Name", "description": "Product Name input value." }, "price": { "type": "number", "title": "Price", "description": "Price input value." }, "tags": { "type": "array", "title": "Tags", "description": "Tags input value." } }, "required": [ "productId", "productName", "price" ] } }, "recordsJson": { "title": "Records", "type": "array", "description": "JSON records to check against the schema.", "items": { "type": "object" }, "default": [ { "productId": 1, "productName": "A green door", "price": 12.5, "tags": [ "home", "green" ] } ] }, "maxRecords": { "title": "Maximum records", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Hard cap for emitted validation rows.", "default": 1 }, "includeValidRows": { "title": "Include valid rows", "type": "boolean", "description": "Include passing records as well as failed records.", "default": true }, "failFast": { "title": "Stop after first failure", "type": "boolean", "description": "Return only the first invalid record.", "default": false }, "includeReport": { "title": "Include report", "type": "boolean", "description": "Create charged Markdown and JSON report artifacts.", "default": true }, "maxChargeUsd": { "title": "Maximum charge USD", "minimum": 0, "maximum": 100, "type": "number", "description": "Stop before an event would exceed this run budget.", "default": 1 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```