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Component Name

AmazonReviewScraperWorkflow

Description

The AmazonReviewScraperWorkflow is a Yeager component designed to scrape Amazon product reviews and return a spreadsheet URL containing the scraped data. This component is part of a larger Yeager Workflow that performs specific data scraping and transformation tasks.

Input and Output Models

InputProduct

• product_name (str): Name of the Amazon product for which the reviews will be scraped.

OutputProductReviews

• spreadsheet_url (str): URL of the spreadsheet containing the scraped reviews.

Both input and output data are modeled using Pydantic's BaseModel to define and validate the required fields.

Parameters

• args (InputProduct): An instance of the InputProduct model containing the product_name.
• callbacks (typing.Any): Callback functions for various events within the transform method. Default value is None.

Transform Function

The transform method of the AmazonReviewScraperWorkflow component takes the args and callbacks as input and performs the following steps:

1. Invokes the transform method of the base AbstractWorkflow class using the input args and callbacks. This returns a dictionary containing the results of the data transformation tasks.
2. Retrieves the spreadsheet URL from the results_dict using the spreadsheet_created key.
3. Creates an instance of the OutputProductReviews model with the spreadsheet_url.
4. Returns the OutputProductReviews instance containing the spreadsheet URL.

External Dependencies

• dotenv: Library used to load environment variables from a .env file.
• fastapi: Library used to build the API for handling input and output.
• pydantic: Library used for data validation and serialization through data models (InputProduct and OutputProductReviews).

API Calls

The component doesn't explicitly make external API calls within the given source code. However, it is part of a larger Yeager Workflow that may require external API calls to access Amazon product reviews and create the spreadsheet containing the scraped data.

Error Handling

Errors are not explicitly handled within the provided source code of this component. However, any exceptions that occur during the execution of the transform method will propagate to the caller for handling. Usage of Pydantic's BaseModel for input and output validation ensures that invalid data will be automatically rejected.

Examples