Integrating External Address & CEP Validation APIs into KNIME Data Workflows

Hi KNIME Community,

We are currently building an automated data cleaning and geolocation workflow in KNIME to process Brazilian customer address datasets.

As part of the ETL pipeline, we need to validate raw postal codes (8-digit CEP format) and enrich the rows with standardized street names (logradouro), neighborhood, and city details.

For auditing and testing response formats (such as IBGE municipality codes and address schema structures), we have been cross-referencing lookups via tools like https://cep-br.com during initial dataset pre-processing.

When executing high-volume GET requests using the 'GET Request' node or Python Integration nodes, we are looking for the most efficient way to handle rate limiting and JSON parsing without slowing down the workflow execution.

Has anyone implemented a similar postal validation node pipeline? Are there recommended caching strategies within KNIME to optimize repeated lookup requests?

Thanks for any tips or node workflow suggestions!