For the record, I don't use Logica myself so I'm not familiar with every design decision or feature -- I'm not a Python programmer. I'm speaking about Datalog i

For the record, I don't use Logica myself so I'm not familiar with every design decision or feature -- I'm not a Python programmer. I'm speaking about Datalog in general. > making variables implicit at the call site What example are you looking at? The NewsData example for instance seems pretty understandable to me. It seems like for any given predicate you can either take the implicit name of the column or you can map it onto a different name e.g. `date: date_num` for the underlying column on gdelt-bq.gdeltv2.gkg. Really it just seems like a way to make the grammar less complicated; the `name: foo` syntax is their way of expressing 'AS' clauses and `name:` is just a shorthand for `name: name` > In light of that quote it's also weird that they mention that they are able to run the SQL they compiled to "in interactive time" on a rather large dataset, which they supposedly already could with SQL. The query in question is run on BigQuery (which IIRC was the original and only target database for Logica), and in that setup you might do a query over 4TB of data but get a response in milliseconds due to partitioning, column compression, parallel aggregation, etc. This is actually really common for many queries. So, in that kind of setup the translation layer needs to be fast so it doesn't spoil the benefit for the end user. I think the statement makes complete sense, tbh. (This also probably explains why they wrote it in Python, so you could use it in Jupyter notebooks hooked up to BigQuery.)