# Record Normalizer & Deduplicator (`axelhu/record-normalizer`) Actor

Normalize JSON or Apify Dataset records with key conversion, flattening, deterministic SHA-256 fingerprints, and duplicate removal.

- **URL**: https://apify.com/axelhu/record-normalizer.md
- **Developed by:** [Axel Hu](https://apify.com/axelhu) (community)
- **Categories:** Developer tools, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.05 / 1,000 record normalizeds

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Record Normalizer

Normalize arbitrary JSON records or an existing Apify Dataset with deterministic pure code.

Features:

- preserve, snake_case, or camelCase keys
- optional nested-object flattening
- empty-value removal
- deterministic SHA-256 fingerprints
- duplicate suppression
- inline JSON or an existing Apify Dataset as input

### Monetization unit

Each emitted record is billed as one `record-normalized` event at **$0.00005 per record** ($0.05 per 1,000 records).

The transformation uses no external web service or paid API.

Every run also uses Apify's standard `apify-actor-start` event at **$0.00005 per start**. This enables Apify's startup-cost reduction and is separate from per-record billing.

### Example

Input:

```json
{
  "inlineItems": [
    {"firstName": "Ada", "Postal Code": "12345"},
    {"firstName": "Grace", "Postal Code": "22201"}
  ],
  "keyStyle": "snake",
  "deduplicate": true,
  "includeFingerprint": true
}
```

Output records include normalized keys and a deterministic `_fingerprint`.

### Support

Use the **Issues** tab on this Actor's Apify page for bug reports or questions. Include the Actor run ID, expected behavior, and a non-sensitive minimal input when possible. Please do not post API tokens, cookies, or private datasets.

# Actor input Schema

## `inlineItems` (type: `array`):

Optional array of JSON objects to normalize directly.

## `sourceDatasetId` (type: `string`):

Optional existing Dataset to read records from.

## `maxItems` (type: `integer`):

Maximum combined number of records to process.

## `keyStyle` (type: `string`):

How object keys should be normalized.

## `flatten` (type: `boolean`):

Flatten nested objects using dot-separated paths. Arrays remain arrays.

## `maxDepth` (type: `integer`):

Stop recursive key normalization or flattening after this depth.

## `dropEmptyValues` (type: `boolean`):

Remove null, undefined, and empty-string values while keeping false and zero.

## `deduplicate` (type: `boolean`):

Emit only the first record for each deterministic fingerprint.

## `includeFingerprint` (type: `boolean`):

Add \_fingerprint containing a deterministic SHA-256 hash.

## Actor input object example

```json
{
  "inlineItems": [
    {
      "firstName": "Ada",
      "Postal Code": "12345",
      "active": true
    },
    {
      "firstName": "Grace",
      "Postal Code": "22201",
      "active": true
    }
  ],
  "maxItems": 10000,
  "keyStyle": "snake",
  "flatten": false,
  "maxDepth": 12,
  "dropEmptyValues": true,
  "deduplicate": true,
  "includeFingerprint": true
}
```

# Actor output Schema

## `dataset` (type: `string`):

No description

## `summary` (type: `string`):

No description

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "inlineItems": [
        {
            "firstName": "Ada",
            "Postal Code": "12345",
            "active": true
        },
        {
            "firstName": "Grace",
            "Postal Code": "22201",
            "active": true
        }
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("axelhu/record-normalizer").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "inlineItems": [
        {
            "firstName": "Ada",
            "Postal Code": "12345",
            "active": True,
        },
        {
            "firstName": "Grace",
            "Postal Code": "22201",
            "active": True,
        },
    ] }

# Run the Actor and wait for it to finish
run = client.actor("axelhu/record-normalizer").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "inlineItems": [
    {
      "firstName": "Ada",
      "Postal Code": "12345",
      "active": true
    },
    {
      "firstName": "Grace",
      "Postal Code": "22201",
      "active": true
    }
  ]
}' |
apify call axelhu/record-normalizer --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,axelhu/record-normalizer"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/neT2s8vIf2lu44cMZ/builds/un0a4vmueC7dHpYIK/openapi.json