Product Catalog Dataset Manager

Build a dataset management system for an e-commerce product catalog that supports dynamic schema updates.

Requirements

Create a system that:

1. Initializes a product catalog dataset with columns for product ID, name, and description
2. Adds a price column with appropriate numeric type after initial creation
3. Renames the "description" column to "product_details" to match company naming standards
4. Removes the "name" column (consolidated into description field)

Capabilities

Dataset Initialization

• Creates a new dataset with columns: id (text), name (text), and description (text) @test
• The dataset is created at the path "./product_catalog" @test

Adding Columns

• Adds a "price" column of type float32 to the existing dataset @test

Renaming Columns

• Renames the "description" column to "product_details" @test

Removing Columns

• Removes the "name" column from the dataset @test

Implementation

@generates

API

def initialize_catalog(path: str) -> None:
    """
    Initialize a new product catalog dataset with base columns.

    Args:
        path: Path where the dataset should be created
    """
    pass

def add_price_column(path: str) -> None:
    """
    Add a price column with float32 type to an existing catalog.

    Args:
        path: Path to the existing dataset
    """
    pass

def rename_description_column(path: str) -> None:
    """
    Rename the 'description' column to 'product_details'.

    Args:
        path: Path to the existing dataset
    """
    pass

def remove_name_column(path: str) -> None:
    """
    Remove the name column from the dataset.

    Args:
        path: Path to the existing dataset
    """
    pass

Dependencies { .dependencies }

deeplake { .dependency }

Provides database capabilities for AI with storage format optimized for deep-learning applications.

@satisfied-by