# Validate an API Dataset Contract Before Deployment

**Use case:** 

Catch schema drift, invalid types, nulls, duplicate keys, missing required fields, and unexpected fields before deployment.

## Input

```json
{
  "items": [
    {
      "id": "order-001",
      "total": 28.5,
      "currency": "USD",
      "paid": true
    },
    {
      "id": "order-002",
      "total": 19,
      "currency": "USD",
      "paid": false
    },
    {
      "id": "order-002",
      "total": "unknown",
      "currency": null,
      "paid": false,
      "legacy": true
    }
  ],
  "contract": {
    "schemaVersion": "dataset-contract-v1",
    "name": "orders",
    "version": "2.0.0",
    "fields": {
      "id": {
        "type": "string",
        "required": true,
        "nullable": false
      },
      "total": {
        "type": "number",
        "required": true,
        "nullable": false
      },
      "currency": {
        "type": "string",
        "required": true,
        "nullable": false
      },
      "paid": {
        "type": "boolean",
        "required": true,
        "nullable": false
      }
    },
    "keyFields": [
      "id"
    ],
    "allowExtraFields": false
  },
  "contractName": "dataset-contract",
  "contractVersion": "1.0.0",
  "keyFields": [],
  "allowExtraFields": true,
  "requiredPresenceRatio": 1,
  "maxItems": 500,
  "maxViolationsPerItem": 50,
  "includeValueEvidence": true
}
```

## Output

```json
{
  "recordType": {
    "label": "Record",
    "format": "string"
  },
  "status": {
    "label": "Status",
    "format": "string"
  },
  "itemIndex": {
    "label": "Item index",
    "format": "integer"
  },
  "itemKey": {
    "label": "Hashed key",
    "format": "string"
  },
  "contractName": {
    "label": "Contract",
    "format": "string"
  },
  "contractVersion": {
    "label": "Version",
    "format": "string"
  },
  "violationCount": {
    "label": "Violations",
    "format": "integer"
  },
  "violations": {
    "label": "Violation evidence",
    "format": "array"
  },
  "itemsProcessed": {
    "label": "Items processed",
    "format": "integer"
  },
  "itemsPassed": {
    "label": "Passed",
    "format": "integer"
  },
  "itemsFailed": {
    "label": "Failed",
    "format": "integer"
  },
  "duplicateItems": {
    "label": "Duplicates",
    "format": "integer"
  },
  "schemaChanges": {
    "label": "Schema changes",
    "format": "array"
  },
  "limitedByBudget": {
    "label": "Budget limited",
    "format": "boolean"
  },
  "checkedAt": {
    "label": "Checked",
    "format": "string"
  }
}
```

## About this Actor

This example demonstrates how to use [Dataset Contract & Regression Tester](https://apify.com/gifted_wagon/dataset-contract-tester) with a specific input configuration. Visit the [Actor detail page](https://apify.com/gifted_wagon/dataset-contract-tester) to learn more, explore other use cases, and run it yourself.


## 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.
This Task's input is already configured above — use it as-is rather than inventing a new one.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
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For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/gifted_wagon/dataset-contract-tester.md

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).