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As you can see, name, gender, email, country, address, zip code and phones are all coeherent. That's because JR, under the hood, keep track of everything and reuse data previously generated in the template. So, if you generate a work_email, the function will reuse name, surname and company. Zip code is a reverse regex pattern which is valid for the city, mobile phone is valid for the country, and so on. At the moment some JR localisations are in progress, so pls contribute if you want to help us!
In the first part of this series, we have seen how to use JR in simple use cases to stream random data from predefined templates to standard out and Apache Kafka on Confluent Cloud.
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