Comprehensive and Detailed Explanation From Exact Extract of Databricks Data Engineer Documents:
Lakeflow Declarative Pipelines provide the expect_all method for programmatically applying multiple data quality expectations at once. The documentation explains that @dlt.expect_all accepts a dictionary of expectation names mapped to SQL constraints, allowing rules to be dynamically loaded from metadata such as JSON files. This ensures that pipelines remain maintainable and scalable without needing to hardcode individual @dlt.expect decorators. The event logs will track each expectation's pass and fail counts individually, making it auditable. Other options are incorrect: invoking an external API introduces unnecessary complexity, individual decorators require hardcoding, and SQL constraints cannot dynamically reference external JSON.