# Preview JSONL Exports to Cloudflare R2

**Use case:** 

Preview an Apify dataset export to Cloudflare R2 without cloud credentials. This task generates sample JSONL output and an export manifest in dry-run mode, allowing developers to validate their export workflow before configuring a real storage bucket. Ideal for ETL testing, data pipeline development, and cloud storage integrations.

## Input

```json
{
  "provider": "r2",
  "region": "us-east-1",
  "sampleItems": [
    {
      "company": "OptiRefine",
      "sales": 500
    }
  ],
  "format": "jsonl",
  "keyPrefix": "apify-exports",
  "maxItems": 1,
  "maxRowsPerPart": 1000,
  "maxBytesPerPart": 5242880,
  "compressGzip": false,
  "forcePathStyle": true,
  "incremental": false,
  "cursorStoreName": "multicloud-exporter-cursor",
  "dryRun": true
}
```

## Output

```json
{
  "objectKey": {
    "label": "Object key",
    "format": "string"
  },
  "bucket": {
    "label": "Bucket",
    "format": "string"
  },
  "rows": {
    "label": "Rows",
    "format": "integer"
  },
  "bytes": {
    "label": "Stored bytes",
    "format": "integer"
  },
  "dryRun": {
    "label": "Preview only",
    "format": "boolean"
  },
  "sha256": {
    "label": "SHA-256 checksum",
    "format": "string"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Multi-Cloud Dataset Exporter — S3, R2, B2 & Wasabi Actor is ready to run with the inputs already set for "Preview JSONL Exports to Cloudflare R2". [Sign up or log in](https://console.apify.com/create-task-from-example/7FijXtzc73d8RFdiK) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Preview JSONL Exports to Cloudflare R2" task

The Multi-Cloud Dataset Exporter — S3, R2, B2 & Wasabi Actor will start running based on the input automatically. You can also change all the input fields, like cloud storage provider, cloud region, and more, to match your specific use case.

### 3. Receive the "Preview JSONL Exports to Cloudflare R2" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as object key, bucket, rows, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Preview JSONL Exports to Cloudflare R2" task via API](https://apify.com/optirefine/multicloud-dataset-exporter.md).

## About this Actor

This example demonstrates how to use [Multi-Cloud Dataset Exporter — S3, R2, B2 & Wasabi](https://apify.com/optirefine/multicloud-dataset-exporter.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/optirefine/multicloud-dataset-exporter.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

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

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 full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/optirefine/multicloud-dataset-exporter.md

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`).