# Google Dataset Items Translator (`web.harvester/google-dataset-items-translator`) Actor

Translate any dataset field(s) to any of the supported languages using the Google Translate website, it goes through all the items in the dataset and translates all of the selected fields

- **URL**: https://apify.com/web.harvester/google-dataset-items-translator.md
- **Developed by:** [Web Harvester](https://apify.com/web.harvester) (community)
- **Categories:** Automation
- **Stats:** 20 total users, 1 monthly users, 100.0% runs succeeded, 3 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **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).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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

## What does Google Dataset Items Translator do?

Translate any dataset field(s) to any of the supported languages using the [Google Translate](https://translate.google.com) website, it goes through all the items in the dataset and translate the selected fields, with it you can:

- Translate single or multiple fields in a dataset.
- Can replace the original field with the translated field, or add a new field with the translated text inside a new object `translation`.
  Here's an input example in JSON:

```json
{
    "sourceLanguage": "en",
    "targetLanguage": "es",
    "datasetId": "mTzNzHg9dL0YioVR0",
    "pathsToFields": ["description"],
    "includeItemsTranslationInfo": false,
    "replaceFiledValues": false
}
```

For the full list of optional parameters, their default values, and how to set the values of your own, see the [Input Schema tab](https://apify.com/hamza.alwan/google-dataset-items-translator/input-schema).

### Google Translator data output

The output for the translation is stored in the dataset. After the run is finished, you can download the dataset in various data formats (JSON, CSV, XML, RSS, HTML Table).

#### Output example

```json
{
    // sourceItemFields...
    "description": "Ranch condo with two bedroom and two bathrooms on the main level.",
    "translation": {
        "description": "Condo rancho con dos habitaciones y dos baños en el nivel principal."
    }
}
```

### Limitations

- Each field text must have a maximum length of 5000 characters.

### Integrations and Google Dataset Items Translator

Last but not least, Google Dataset Items Translator can be connected with almost any cloud service or web app thanks to <a href="https://apify.com/integrations"  target="_blank"> integrations on the Apify platform</a>. You can integrate with Make, Zapier, Slack, Airbyte, GitHub, Google Sheets, Google Drive, <a href="https://docs.apify.com/integrations" target="_blank"> and more</a>. Or you can use <a href="https://docs.apify.com/integrations/webhooks"  target="_blank"> webhooks</a> to carry out an action whenever an event occurs, e.g. get a notification whenever Google Dataset Items Translator successfully finishes a run.

### Using Google Dataset Items Translator with the Apify API

The Apify API gives you programmatic access to the Apify platform. The API is organized around RESTful HTTP endpoints that enable you to manage, schedule, and run Apify actors. The API also lets you access any datasets, monitor actor performance, fetch results, create and update versions, and more.

To access the API using Node.js, use the apify-client NPM package. To access the API using Python, use the apify-client PyPI package.

Check out the <a href="https://docs.apify.com/api/v2"  target="_blank"> Apify API reference</a> docs for full details or click on the <a href="https://apify.com/hamza.alwan/google-dataset-items-translator/api"  target="_blank"> API tab</a> for code examples.

# Actor input Schema

## `datasetId` (type: `string`):

Dataset ID of the dataset to be translated

## `pathsToFields` (type: `array`):

Path to the fields to be translated

## `sourceLanguage` (type: `string`):

Language of the text to be translated, default is Auto Detect

## `targetLanguage` (type: `string`):

The language into which the text should be translated

## `replaceFiledValues` (type: `boolean`):

If true, the field values will be replaced with the translated values. Will ignore translation info.

## `includeItemsTranslationInfo` (type: `boolean`):

If true, the translation info will be included in the translation output for each filed in each dataset item.

## Actor input object example

```json
{
  "sourceLanguage": "auto",
  "targetLanguage": "es",
  "replaceFiledValues": false,
  "includeItemsTranslationInfo": false
}
```

# 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 = {
    "sourceLanguage": "auto",
    "targetLanguage": "es"
};

// Run the Actor and wait for it to finish
const run = await client.actor("web.harvester/google-dataset-items-translator").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 = {
    "sourceLanguage": "auto",
    "targetLanguage": "es",
}

# Run the Actor and wait for it to finish
run = client.actor("web.harvester/google-dataset-items-translator").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 '{
  "sourceLanguage": "auto",
  "targetLanguage": "es"
}' |
apify call web.harvester/google-dataset-items-translator --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=web.harvester/google-dataset-items-translator",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/2BBm9lkxSpPhHdYvE/builds/oZ7NLoBFgbLiTZQWW/openapi.json