adjust-precision-for-schema

import json from adjust_precision_for_schema import adjust_precision # Example Singer SCHEMA message (simplified) # This schema defines a 'price' field with a logical 'decimal' type # and an implied precision/scale (e.g., up to 2 decimal places). schema_message = { "type": "SCHEMA", "stream": "products", "schema": { "type": "object", "properties": { "id": {"type": "integer"}, "name": {"type": "string"}, "price": { "type": ["number", "null"], ""_singer_type": "decimal", ""maximum": 1000000000000000000000000000000000000.00, ""multipleOf": 0.01 } } }, "key_properties": ["id"] } # Example Singer RECORD message record_message = { "type": "RECORD", "stream": "products", "record": { "id": 1, "name": "Product A", "price": 123.456789 # Value with more precision than schema intends } } # Another record with a value that should be adjusted minimally record_message_2 = { "type": "RECORD", "stream": "products", "record": { "id": 2, "name": "Product B", "price": 99.99999999999999 # Value that should round up } } # Hypothetical function call to adjust precision based on the schema # The exact API (e.g., arguments, return type) is inferred. adjusted_record_1 = adjust_precision(record_message['record'], schema_message['schema']) adjusted_record_2 = adjust_precision(record_message_2['record'], schema_message['schema']) print("Original Record 1 Price:", record_message['record']['price']) print("Adjusted Record 1 Price:", adjusted_record_1['price']) print("Original Record 2 Price:", record_message_2['record']['price']) print("Adjusted Record 2 Price:", adjusted_record_2['price'])