This article provides a general overview of Data Block Request Parameters.
One of the core components of Assette is the Data Block, which serves as a building block for retrieving, transforming, and presenting data within the platform. To maximize the flexibility and reusability of Data Blocks, Assette allows the use of Request Parameters. These parameters enable users to customize data retrieval and processing dynamically, ensuring that Data Blocks can adapt to various reporting needs without the need for multiple hard-coded configurations.
What Are Data Block Request Parameters? #
Data Block Request Parameters are variables that you can define within a Data Block to make it more dynamic and customizable. They act as placeholders that can be assigned specific values when the Data Block is executed. This mechanism allows a single Data Block to serve multiple purposes by altering its behavior based on the parameters provided at runtime.
Key Features:
- Dynamic Data Retrieval: Modify queries and data retrieval logic based on parameter values.
- Reusability: Use the same Data Block in different contexts with different parameters.
- Flexibility: Adjust data transformations and outputs without changing the underlying code.
How Do Data Block Request Parameters Work? #
When you create a Data Block in Assette, you can define parameters that will be used within the Data Block’s logic. These parameters can then be supplied with values when the Data Block is invoked, either manually or through other components like Data Objects or templates.
Defining Parameters #
In the Data Block Editor, you can define parameters by specifying:
- Parameter Name: A unique identifier for the parameter.
- Data Type: The type of data the parameter accepts (e.g., string, integer, date).
- Default Value: An optional default value if no value is provided at runtime.
- Description: A brief explanation of the parameter’s purpose.
Best Practices for Using Data Block Request Parameters #
When using Data Block Request Parameters in Assette, it’s essential to follow best practices to ensure your Data Blocks are flexible, secure, and maintainable. One key practice is to use meaningful parameter names that clearly convey their purpose, making it easier for others to understand and use your Data Blocks effectively.
- Meaningful Parameter Names: Use clear and descriptive names for parameters to make it easy for others to understand their purpose.
- Default Values: Provide default values for parameters when appropriate to ensure the Data Block can execute even if no value is supplied.
- Input Validation: Implement validation logic to ensure parameter values are valid and prevent errors.
- Reusability: Design Data Blocks with parameters in mind to maximize reusability across different reports and contexts.