Apify to RabbitMQ Integration ## Overview This integration processes data from an Apify dataset and delivers it to a RabbitMQ queue. It is configured via a schema that includes details about the dataset and RabbitMQ connection settings. ## Input Schema The input schema defines the configuration required to run the integration effectively. Below are the details of the schema and its properties: ### Schema Details - Title: Apify to RabbitMQ Input Schema - Type: Object - Schema Version: 1 ### Properties #### 1. Default Dataset ID - Title: Default Dataset ID - Type: String - Description: The ID of the Apify dataset to process. - Default: default - Editor: Textfield #### 2. RabbitMQ Configuration - Title: RabbitMQ Configuration - Type: Object - Description: Configuration settings for RabbitMQ connection. - Editor: JSON - Default: json { "url": "amqp://localhost", "queue": "test-queue" } - Properties: - URL: - Title: URL - Type: String - Description: RabbitMQ connection URL. - Default: amqp://localhost - Queue: - Title: Queue - Type: String - Description: RabbitMQ queue name. - Default: test-queue ### Required Properties - defaultDatasetId - rabbitConfig ## Example Configuration json { "defaultDatasetId": "my-dataset-id", "rabbitConfig": { "url": "amqp://user:password@rabbitmq-host", "queue": "my-queue" } } ## How to Use 1. Define the Input: Provide the necessary configurations in JSON format as per the schema. 2. Run the Integration: Pass the configuration to the Apify actor or script responsible for processing and delivering the dataset to RabbitMQ. 3. Monitor Outputs: Check your RabbitMQ queue for incoming messages based on the processed dataset. ## Notes - Ensure the RabbitMQ server is reachable from the environment where the integration is executed. - The configuration assumes each message is published individually. Adjustments may be necessary for high-throughput use cases. --- With this setup, your Apify actor can seamlessly deliver data from an Apify dataset to a RabbitMQ queue.