Dummy Run

Overview

Dummy Run is an open-source Apify actor that creates a placeholder run on the Apify platform. Its primary purpose is to generate a run context, which allows you to programmatically obtain references to platform resources like the request queue or dataset associated with that run. You can then use these resources in your own external scripts or applications.

Key Features

• Creates a Run Context: Initiates a run solely to gain access to the Apify environment and its storage.
• Access Platform Storage: Enables you to fetch the run's associated default or named request queues and datasets.
• Lightweight and Simple: Performs no actual scraping or processing, making it fast and efficient for this specific utility purpose.
• Open Source: The code is publicly available for inspection and modification.

How to Use

Using the actor is straightforward. You don't need to configure any specific input. Simply call the actor via the Apify API, Apify SDK, or directly from the Apify Console to start a run.

Example using the Apify API (curl):

curl "https://api.apify.com/v2/acts/your-username~dummy-run/runs?token=YOUR_API_TOKEN" -X POST

Once the run is started, you can use the returned runId to access its context and storage from your external code.

Example using the Apify SDK (JavaScript) to get the run's default dataset:

const { ApifyClient } = require('apify-client');
const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

// Assuming you have the runId from starting Dummy Run
const runId = 'your_run_id_here';

// Get the run object
const run = await client.run(runId).get();
// Access the default dataset ID for this run
const defaultDatasetId = run.defaultDatasetId;

// Now you can use this datasetId with the client to push or pull data
const datasetClient = client.dataset(defaultDatasetId);

Input/Output

Input:
The actor does not require any specific input configuration. Standard run settings (like memory, timeout) can be adjusted if needed but are not necessary for its core function.

Output:
The actor itself does not produce a dataset or specific output. Its "output" is the run instance itself. The value is in the metadata and environment of this run, which provides:
* A runId for identification.
* Access to the run's default datasetId and requestQueueId.
* The ability to open named storage resources (datasets, request queues) within the context of this run.

You use the Apify API or SDK to query for this run and then utilize its associated storage resources in your external processes.