How can I conduct reverse DNS lookups efficiently using DNS footprinting methods

Question

I'm currently working on a project where I need to gather DNS information about an organization. Part of the task involves performing reverse DNS lookups to identify the hostnames associated with IP addresses in a given range. I’m looking for efficient methods to conduct reverse DNS lookups, especially for a large range of IPs.

I understand that tools like dig and nslookup can help with individual lookups, but how can I scale this process for larger datasets? Are there any Python libraries or DNS footprinting tools that can speed up the process and handle multiple reverse lookups at once?