Comments (7)
To be more specific.. Can we build this directly into exp.where()
p.select().where(exp.or_(p.args['expressions'][0].eq("John"), p.args['expressions'][0].eq("Susan"))).sql()
vs
p.select().where(_sql_filters_to_expression(filters=[[('first_name', '==', 'John')], [('first_name', '==', 'Susan')]], parsed_columns = p)).sql()
vs.
p.select().where([[('first_name', '==', 'John')], [('first_name', '==', 'Susan')]]).sql()
The last option allows filters to be read in from a json or yaml config file..
filters = [[('first_name', '==', 'John')], [('first_name', '==', 'Susan')]]
p.select().where(filters).sql()
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Hey @davlee1972, this is already supported in sqlglot. Check out the normalize rule https://github.com/tobymao/sqlglot/blob/main/sqlglot/optimizer/normalize.py
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Can you verify that operators are supported? I only see DNF ANDs ORs.
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Apologies, I misread this issue earlier. Reopening this for now, but I will take a closer look tomorrow - cc @tobymao.
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i don't think so, it makes sense to me to just write this yourself
this seems like a reasonable solution
p.select().where(exp.or_(p.args['expressions'][0].eq("John"), p.args['expressions'][0].eq("Susan"))).sql()
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The original req included the ability to parameterize conditions..
If I had a json file or api call that could pass a filter that sqlglot understands..
{"filters": [[{"condition": ["first_name", "==", "John"]}}], [{"condition": ["first_name", "==", "Susan"]}]]}
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right, i believe this is a better fit in your code, not sqlglot core
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